GcatWiki - User contributions [en]

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:42:40Z

Stmeador: /* Detecting Windows */

==Requirements==
*iRobot Create
*Command Module
*Virtual walls
*PC with Windows OS
*RoboRealm
*MATLAB
*webcam
*flashlight
*reflective tape

==Guide==
===Navigation===

Our general navigation algorithm is as follows:

*Find checkpoint
*Move along the wall a preset distance
*Now the robot is at a door. Face the door.
*Drive at maximum speed to clear threshold. Once threshold is clear, resume normal speed
*If door is open, then enter room, wait until image processing is done, turn around and leave
*Find the next checkpoint... etc.

Checkpoints can be a virtual wall, or the real wall immediately next to the room the robot has just left. The first checkpoint is just the robot's starting point. The robot follows the wall whenever it is measuring distance because the wall keeps the robot going straight ahead, which helps precision.

*Script:
**[[Media:Command Module Script.c.zip]]

===Detecting Windows===
*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Matlab script:
**[[Media:RoboRealmControl.m.txt]]
*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

*Sticker for windows
**bottom of sticker should be reflective
**reflective part only visible when window open
**sticker mockup
***[[Media:WindowSticker.jpg]]

===Communicating between navigation and detection===
*created motion sensing filter
*MATLAB starts window detection filter when motion sensor determines that robot has stopped moving

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:37:58Z

Stmeador: /* Navigation */

==Requirements==
*iRobot Create
*Command Module
*Virtual walls
*PC with Windows OS
*RoboRealm
*MATLAB
*webcam
*flashlight
*reflective tape

==Guide==
===Navigation===

Our general navigation algorithm is as follows:

*Find checkpoint
*Move along the wall a preset distance
*Now the robot is at a door. Face the door.
*Drive at maximum speed to clear threshold. Once threshold is clear, resume normal speed
*If door is open, then enter room, wait until image processing is done, turn around and leave
*Find the next checkpoint... etc.

Checkpoints can be a virtual wall, or the real wall immediately next to the room the robot has just left. The first checkpoint is just the robot's starting point. The robot follows the wall whenever it is measuring distance because the wall keeps the robot going straight ahead, which helps precision.

*Script:
**[[Media:Command Module Script.c.zip]]

===Detecting Windows===
*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Matlab script:
**[[Media:RoboRealmControl.m.txt]]
*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

===Communicating between navigation and detection===
*created motion sensing filter
*MATLAB starts window detection filter when motion sensor determines that robot has stopped moving

File:Command Module Script.c.zip

2012-05-16T16:36:52Z

Stmeador:

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:33:01Z

Stmeador: /* Detecting Windows */

==Requirements==
*iRobot Create
*Command Module
*Virtual walls
*PC with Windows OS
*RoboRealm
*MATLAB
*webcam
*flashlight
*reflective tape

==Guide==
===Navigation===

Our general navigation algorithm is as follows:

*Find checkpoint
*Move along the wall a preset distance
*Now the robot is at a door. Face the door.
*Drive at maximum speed to clear threshold. Once threshold is clear, resume normal speed
*If door is open, then enter room, wait until image processing is done, turn around and leave
*Find the next checkpoint... etc.

Checkpoints can be a virtual wall, or the real wall immediately next to the room the robot has just left. The first checkpoint is just the robot's starting point. The robot follows the wall whenever it is measuring distance because the wall keeps the robot going straight ahead, which helps precision.

===Detecting Windows===
*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Matlab script:
**[[Media:RoboRealmControl.m.txt]]
*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

===Communicating between navigation and detection===
*created motion sensing filter
*MATLAB starts window detection filter when motion sensor determines that robot has stopped moving

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:31:56Z

Stmeador: /* Guide */

==Requirements==
*iRobot Create
*Command Module
*Virtual walls
*PC with Windows OS
*RoboRealm
*MATLAB
*webcam
*flashlight
*reflective tape

==Guide==
===Navigation===

Our general navigation algorithm is as follows:

*Find checkpoint
*Move along the wall a preset distance
*Now the robot is at a door. Face the door.
*Drive at maximum speed to clear threshold. Once threshold is clear, resume normal speed
*If door is open, then enter room, wait until image processing is done, turn around and leave
*Find the next checkpoint... etc.

Checkpoints can be a virtual wall, or the real wall immediately next to the room the robot has just left. The first checkpoint is just the robot's starting point. The robot follows the wall whenever it is measuring distance because the wall keeps the robot going straight ahead, which helps precision.

===Detecting Windows===
*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

===Communicating between navigation and detection===
*created motion sensing filter
*MATLAB starts window detection filter when motion sensor determines that robot has stopped moving

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:28:48Z

Stmeador: /* Guide */

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:26:47Z

Stmeador: /* Guide */

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:24:53Z

Stmeador: /* Requirements */

==Requirements==
*iRobot Create
*Command Module
*Virtual walls
*PC with Windows OS
*RoboRealm
*MATLAB
*webcam
*flashlight
*reflective tape

==Guide==

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:21:53Z

Stmeador: /* Requirements */

==Requirements==
*iRobot Create
*Command Module
*Virtual walls
*PC with Windows OS
*RoboRealm
*MATLAB

==Guide==

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:21:24Z

Stmeador: /* Requirements */

==Requirements==
**iRobot Create
**Command Module
**Virtual walls
**PC with Windows OS
**RoboRealm
**MATLAB

==Guide==

Team Commando Tutorial/Explanation of Methods

2012-05-16T16:19:49Z

Stmeador: Created page with '==Requirements== ==Guide=='

==Requirements==

==Guide==

Team Commando

2012-05-09T07:49:44Z

Stmeador: /* Communication Between Detection and Navigation */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**Matlab create toolbox
***http://www.usna.edu/Users/weapsys/esposito/roomba.matlab/
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**Communication between command module and matlab
***serial port
***microphone
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What "Works"==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:
**[[Media:RoboRealmControl.m.txt]]
*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

===Communication Between Detection and Navigation===
*initialize serial port connection:
**[[Media:InitializeComMod.m.txt]]
*read input:
**[[Media:ReadCommand.m.txt]]
*motion detection script

==Contacting our iRobot create==
*send your fan mail to davidsonirobot@gmail.com

Team Commando

2012-05-09T06:48:31Z

Stmeador:

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**Matlab create toolbox
***http://www.usna.edu/Users/weapsys/esposito/roomba.matlab/
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**Communication between command module and matlab
***serial port
***microphone
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What "Works"==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:
**[[Media:RoboRealmControl.m.txt]]
*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

===Communication Between Detection and Navigation===
*initialize serial port connection:
**[[Media:InitializeComMod.m.txt]]
*read input:
**[[Media:ReadCommand.m.txt]]

==Contacting our iRobot create==
*send your fan mail to davidsonirobot@gmail.com

Team Commando

2012-05-09T05:13:07Z

Stmeador: /* What Works */

Team Commando

2012-05-09T05:11:52Z

Stmeador: /* Detecting Windows */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**Matlab create toolbox
***http://www.usna.edu/Users/weapsys/esposito/roomba.matlab/
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**Communication between command module and matlab
***serial port
***microphone
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:
**[[Media:RoboRealmControl.m.txt]]
*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

===Communication Between Detection and Navigation===
*initialize serial port connection:
**[[Media:InitializeComMod.m.txt]]
*read input:
**[[Media:ReadCommand.m.txt]]

File:RoboRealmControl.m.txt

2012-05-09T05:11:16Z

Stmeador: remove .txt extension to run matlab script

remove .txt extension to run matlab script

Team Commando

2012-05-09T04:59:27Z

Stmeador: /* Communication Between Detection and Navigation */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**Matlab create toolbox
***http://www.usna.edu/Users/weapsys/esposito/roomba.matlab/
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**Communication between command module and matlab
***serial port
***microphone
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:

*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

===Communication Between Detection and Navigation===
*initialize serial port connection:
**[[Media:InitializeComMod.m.txt]]
*read input:
**[[Media:ReadCommand.m.txt]]

File:ReadCommand.m.txt

2012-05-09T04:57:58Z

Stmeador: remove .txt extension to use matlab file

remove .txt extension to use matlab file

Team Commando

2012-05-09T04:56:32Z

Stmeador: /* Detecting Windows */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**Matlab create toolbox
***http://www.usna.edu/Users/weapsys/esposito/roomba.matlab/
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**Communication between command module and matlab
***serial port
***microphone
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:

*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

===Communication Between Detection and Navigation===
*initialize serial port connection:
**[[Media:InitializeComMod.m.txt]]

File:InitializeComMod.m.txt

2012-05-09T04:55:31Z

Stmeador: remove .txt extension to use matlab script

remove .txt extension to use matlab script

Team Commando

2012-05-09T04:53:09Z

Stmeador: /* What Works */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**Matlab create toolbox
***http://www.usna.edu/Users/weapsys/esposito/roomba.matlab/
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**Communication between command module and matlab
***serial port
***microphone
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:

*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

===Communication Between Detection and Navigation
*initialize serial port connection:
**

Team Commando

2012-05-09T03:49:33Z

Stmeador: /* Image Processing */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**Matlab create toolbox
***http://www.usna.edu/Users/weapsys/esposito/roomba.matlab/
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**Communication between command module and matlab
***serial port
***microphone
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:

*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

Team Commando

2012-05-09T03:47:34Z

Stmeador: /* To-Do: */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**Communication between command module and matlab
***serial port
***microphone
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:

*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

Team Commando

2012-05-09T03:40:59Z

Stmeador: /* Detecting Windows */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**Evan's going to get an LED
**Tomorrow we are going to find the best color for detection (Wal-Mart might have good tapes)
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**We'll also talk to the nav guys and figure out serial port communication
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:

*RoboRealm filters:
**for at night with lights on
**for at night with lights off and flashlight

Team Commando

2012-05-09T03:40:47Z

Stmeador: /* Detecting Windows */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**Evan's going to get an LED
**Tomorrow we are going to find the best color for detection (Wal-Mart might have good tapes)
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**We'll also talk to the nav guys and figure out serial port communication
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:

*RoboRealm filters:
**for at night with lights on

**for at night with lights off and flashlight

Team Commando

2012-05-09T03:39:52Z

Stmeador: /* What Works */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**Evan's going to get an LED
**Tomorrow we are going to find the best color for detection (Wal-Mart might have good tapes)
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**We'll also talk to the nav guys and figure out serial port communication
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==
===Navigation===
*Command module script:

===Detecting Windows===
*Matlab script:

*RoboRealm filters:

Team Commando

2012-05-09T03:37:47Z

Stmeador:

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**Evan's going to get an LED
**Tomorrow we are going to find the best color for detection (Wal-Mart might have good tapes)
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**We'll also talk to the nav guys and figure out serial port communication
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

==What Works==

Team Commando

2012-05-09T03:20:57Z

Stmeador: /* Image Processing */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**Evan's going to get an LED
**Tomorrow we are going to find the best color for detection (Wal-Mart might have good tapes)
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**We'll also talk to the nav guys and figure out serial port communication
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

Team Commando

2012-05-09T03:20:45Z

Stmeador: /* Image Processing */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open
[

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info
**sticker mockup
***[Media:WindowSticker.jpg]]

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**Evan's going to get an LED
**Tomorrow we are going to find the best color for detection (Wal-Mart might have good tapes)
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**We'll also talk to the nav guys and figure out serial port communication
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

Team Commando

2012-05-09T03:20:11Z

Stmeador: /* Image Processing */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open
[[Media:WindowSticker.jpg]]

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**Evan's going to get an LED
**Tomorrow we are going to find the best color for detection (Wal-Mart might have good tapes)
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**We'll also talk to the nav guys and figure out serial port communication
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

Team Commando

2012-05-09T03:18:55Z

Stmeador: /* Image Processing */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open
[[File:WindowSticker.jpg]]

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**Evan's going to get an LED
**Tomorrow we are going to find the best color for detection (Wal-Mart might have good tapes)
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**We'll also talk to the nav guys and figure out serial port communication
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

File:WindowSticker.jpg

2012-05-09T03:17:53Z

Stmeador: potential sticker to be placed on each window.

potential sticker to be placed on each window.

Team Commando

2012-05-08T19:07:16Z

Stmeador: /* Image Processing */

==Navigation==

==Image Processing==
*Camera
**Logitech Orbit (on a stick)

*Software
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*Method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room via command module serial ports => matlab
**webcam pans and roborealm scans for magenta
***matlab checks to see if roborealm has found magenta at every degree of the pan
****if found, places a one in the vector entry corresponding to that room

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*What We Have So Far:
**RoboRealm module string to find magenta blobs and control Orbit
**MatLab script that opens RoboRealm and controls camera/gets magenta detection info

==To-Do:==
**Get magenta tape
**test Orbit in different light conditions
**look into more filter options
***sunglasses seemed like an option
***Rob McSwain has been emailed about video filters
**Figure out exact frequency of magenta and how that corresponds to hue/intensity in RoboRealm so that extraneous magenta objects are not picked up
**Add something to MatLab script to interpret the vector once the Roomba has been everywhere
**Test/figure out the serial port pings to MatLab
*roborealm over rtacks while panning; needs a second to get oriented
**change matlab script to only check for blobs once camera has paused for a second.

*The Most Current To-DO:
**Evan's going to get an LED
**Tomorrow we are going to find the best color for detection (Wal-Mart might have good tapes)
**We'll also fine-tune the script so the center of gravity doesn't appear when it isn't supposed to
**We'll also talk to the nav guys and figure out serial port communication
**Jonah is going to add pause-checks to the MatLab script so it doesn't mis-classify
**A beautiful sticker will be designed with the specs we currently have
**And the world shall rejoice in itself and its conservation of energy

Team Commando

2012-05-02T00:57:10Z

Stmeador: /* To Do */

==To Do==
*command module navigation (Daniel and Matt)
*image processing (Steph, Evan, Jonah)
*decide on a camera
*abstract
**https://docs.google.com/document/d/1YrS9Ua821oJdYNquYGewYql7AsK0MqUhzOm-0q8JxM8/edit
*poster
**[[File:TeamCommando.ppt]]

==Navigation==

==Image Processing==
*camera

**simple webcam!

*software
**matlab toolbox
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room
**use laptop to take image
**process image to determine whether or not a window is open

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*to-do:

-figure out physical orientation of computer/camera

-build training set: every possible window configuration

-figure out how to get the images... opencv documentation: http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html, http://opencv.willowgarage.com/wiki/CameraCapture

-decide on preprocessing method: threshhold, line detection, contrast upping, pulling out the windows, or doing none of that and trusting the neural net.

-figure out how to get the command module to tell comp when to take a picture

-get the neural net trained and tested

*Active Thoughts:

-RoboRealm seems sweeeeell.
::interface with MATLAB: http://www.mathworks.com/matlabcentral/fileexchange/22882
-current plan-ish:
::roborealm does processing and recieve signals from command module via serial port, then sends processed images ot matlab for NN classification. BOOM.

File:TeamCommando.ppt

2012-05-02T00:56:20Z

Stmeador: Poster used to present work at Davidson College's Spring 2012 Math and Science poster session.

Poster used to present work at Davidson College's Spring 2012 Math and Science poster session.

Team Commando

2012-05-02T00:54:18Z

Stmeador: /* To Do */

==To Do==
*command module navigation (Daniel and Matt)
*image processing (Steph, Evan, Jonah)
*decide on a camera
*abstract
**https://docs.google.com/document/d/1YrS9Ua821oJdYNquYGewYql7AsK0MqUhzOm-0q8JxM8/edit
*poster

==Navigation==

==Image Processing==
*camera

**simple webcam!

*software
**matlab toolbox
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room
**use laptop to take image
**process image to determine whether or not a window is open

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*to-do:

-figure out physical orientation of computer/camera

-build training set: every possible window configuration

-figure out how to get the images... opencv documentation: http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html, http://opencv.willowgarage.com/wiki/CameraCapture

-decide on preprocessing method: threshhold, line detection, contrast upping, pulling out the windows, or doing none of that and trusting the neural net.

-figure out how to get the command module to tell comp when to take a picture

-get the neural net trained and tested

*Active Thoughts:

-RoboRealm seems sweeeeell.
::interface with MATLAB: http://www.mathworks.com/matlabcentral/fileexchange/22882
-current plan-ish:
::roborealm does processing and recieve signals from command module via serial port, then sends processed images ot matlab for NN classification. BOOM.

Team Commando

2012-05-01T18:13:03Z

Stmeador: /* Image Processing */

==To Do==
*command module navigation (Daniel and Matt)
*image processing (Steph, Evan, Jonah)
*decide on a camera
*abstract
**https://docs.google.com/document/d/1YrS9Ua821oJdYNquYGewYql7AsK0MqUhzOm-0q8JxM8/edit

==Navigation==

==Image Processing==
*camera

**simple webcam!

*software
**matlab toolbox
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room
**use laptop to take image
**process image to determine whether or not a window is open

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*RoboRealm
**Color to detect: magenta?
**attach color to bottom of window so can only be detected when open

*to-do:

-figure out physical orientation of computer/camera

-build training set: every possible window configuration

-figure out how to get the images... opencv documentation: http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html, http://opencv.willowgarage.com/wiki/CameraCapture

-decide on preprocessing method: threshhold, line detection, contrast upping, pulling out the windows, or doing none of that and trusting the neural net.

-figure out how to get the command module to tell comp when to take a picture

-get the neural net trained and tested

*Active Thoughts:

-RoboRealm seems sweeeeell.
::interface with MATLAB: http://www.mathworks.com/matlabcentral/fileexchange/22882
-current plan-ish:
::roborealm does processing and recieve signals from command module via serial port, then sends processed images ot matlab for NN classification. BOOM.

Team Commando

2012-05-01T17:47:31Z

Stmeador: /* Image Processing */

==To Do==
*command module navigation (Daniel and Matt)
*image processing (Steph, Evan, Jonah)
*decide on a camera
*abstract
**https://docs.google.com/document/d/1YrS9Ua821oJdYNquYGewYql7AsK0MqUhzOm-0q8JxM8/edit

==Navigation==

==Image Processing==
*camera

**simple webcam!

*software
**matlab toolbox
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room
**use laptop to take image
**process image to determine whether or not a window is open

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*to-do:

-figure out physical orientation of computer/camera

-build training set: every possible window configuration

-figure out how to get the images... opencv documentation: http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html, http://opencv.willowgarage.com/wiki/CameraCapture

-decide on preprocessing method: threshhold, line detection, contrast upping, pulling out the windows, or doing none of that and trusting the neural net.

-figure out how to get the command module to tell comp when to take a picture

-get the neural net trained and tested

*Active Thoughts:

-RoboRealm seems sweeeeell.
::interface with MATLAB: http://www.mathworks.com/matlabcentral/fileexchange/22882
-current plan-ish:
::roborealm does processing and recieve signals from command module via serial port, then sends processed images ot matlab for NN classification. BOOM.

Team Commando

2012-05-01T17:47:01Z

Stmeador: /* Image Processing */

==To Do==
*command module navigation (Daniel and Matt)
*image processing (Steph, Evan, Jonah)
*decide on a camera
*abstract
**https://docs.google.com/document/d/1YrS9Ua821oJdYNquYGewYql7AsK0MqUhzOm-0q8JxM8/edit

==Navigation==

==Image Processing==
*possible cameras


*software
**matlab toolbox
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room
**use laptop to take image
**process image to determine whether or not a window is open

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*to-do:

-figure out physical orientation of computer/camera

-build training set: every possible window configuration

-figure out how to get the images... opencv documentation: http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html, http://opencv.willowgarage.com/wiki/CameraCapture

-decide on preprocessing method: threshhold, line detection, contrast upping, pulling out the windows, or doing none of that and trusting the neural net.

-figure out how to get the command module to tell comp when to take a picture

-get the neural net trained and tested

*Active Thoughts:

-RoboRealm seems sweeeeell.
::interface with MATLAB: http://www.mathworks.com/matlabcentral/fileexchange/22882
-current plan-ish:
::roborealm does processing and recieve signals from command module via serial port, then sends processed images ot matlab for NN classification. BOOM.

Team Commando

2012-05-01T17:46:47Z

Stmeador: /* Image Processing */

==To Do==
*command module navigation (Daniel and Matt)
*image processing (Steph, Evan, Jonah)
*decide on a camera
*abstract
**https://docs.google.com/document/d/1YrS9Ua821oJdYNquYGewYql7AsK0MqUhzOm-0q8JxM8/edit

==Navigation==

==Image Processing==
*possible cameras
<--!**http://www.logitech.com/en-us/webcam-communications/webcams/devices/6333
**http://us.playstation.com/ps3/accessories/playstation-eye-camera-ps3.html
**http://www.westernunion.com/wushop/category/product/304009645/search/Microsoft-LifeCam-VX-5000-Webcam---Red---Bulk/
**http://www.zagrosrobotics.com/shop/item.aspx?itemid=759-->

*software
**matlab toolbox
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room
**use laptop to take image
**process image to determine whether or not a window is open

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*to-do:

-figure out physical orientation of computer/camera

-build training set: every possible window configuration

-figure out how to get the images... opencv documentation: http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html, http://opencv.willowgarage.com/wiki/CameraCapture

-decide on preprocessing method: threshhold, line detection, contrast upping, pulling out the windows, or doing none of that and trusting the neural net.

-figure out how to get the command module to tell comp when to take a picture

-get the neural net trained and tested

*Active Thoughts:

-RoboRealm seems sweeeeell.
::interface with MATLAB: http://www.mathworks.com/matlabcentral/fileexchange/22882
-current plan-ish:
::roborealm does processing and recieve signals from command module via serial port, then sends processed images ot matlab for NN classification. BOOM.

Team Commando

2012-05-01T01:12:44Z

Stmeador: /* Image Processing */

==To Do==
*command module navigation (Daniel and Matt)
*image processing (Steph, Evan, Jonah)
*decide on a camera
*abstract
**https://docs.google.com/document/d/1YrS9Ua821oJdYNquYGewYql7AsK0MqUhzOm-0q8JxM8/edit

==Navigation==

==Image Processing==
*possible cameras
**http://www.logitech.com/en-us/webcam-communications/webcams/devices/6333
**http://us.playstation.com/ps3/accessories/playstation-eye-camera-ps3.html
**http://www.westernunion.com/wushop/category/product/304009645/search/Microsoft-LifeCam-VX-5000-Webcam---Red---Bulk/
**http://www.zagrosrobotics.com/shop/item.aspx?itemid=759

*software
**matlab toolbox
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room
**use laptop to take image
**process image to determine whether or not a window is open

*Current dataset
**26 closed windows
**26 open windows
**https://www.dropbox.com/sh/hx5rwp9ilakwg5c/8Yf4twUjV1

*to-do:

-figure out physical orientation of computer/camera

-build training set: every possible window configuration

-figure out how to get the images... opencv documentation: http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html, http://opencv.willowgarage.com/wiki/CameraCapture

-decide on preprocessing method: threshhold, line detection, contrast upping, pulling out the windows, or doing none of that and trusting the neural net.

-figure out how to get the command module to tell comp when to take a picture

-get the neural net trained and tested

*Active Thoughts:

-RoboRealm seems sweeeeell.
::interface with MATLAB: http://www.mathworks.com/matlabcentral/fileexchange/22882
-current plan-ish:
::roborealm does processing and recieve signals from command module via serial port, then sends processed images ot matlab for NN classification. BOOM.

Team Commando

2012-04-26T18:43:54Z

Stmeador: /* Image Processing */

==To Do==
*command module navigation (Daniel and Matt)
*image processing (Steph, Evan, Jonah)
*decide on a camera
*abstract
**https://docs.google.com/document/d/1YrS9Ua821oJdYNquYGewYql7AsK0MqUhzOm-0q8JxM8/edit

==Navigation==

==Image Processing==
*possible cameras
**http://www.logitech.com/en-us/webcam-communications/webcams/devices/6333
**http://us.playstation.com/ps3/accessories/playstation-eye-camera-ps3.html
**http://www.westernunion.com/wushop/category/product/304009645/search/Microsoft-LifeCam-VX-5000-Webcam---Red---Bulk/
**http://www.zagrosrobotics.com/shop/item.aspx?itemid=759

*software
**matlab toolbox
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf
**Roborealm
***useful demo: http://www.roborealm.com/tutorial/Fun_with_Roomba/slide070.php

*method
**attach laptop to iRobot
**receive signal from robot when it has arrived in room
**use laptop to take image
**process image to determine whether or not a window is open

*to-do:

-figure out physical orientation of computer/camera

-build training set: every possible window configuration

-figure out how to get the images... opencv documentation: http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html, http://opencv.willowgarage.com/wiki/CameraCapture

-decide on preprocessing method: threshhold, line detection, contrast upping, pulling out the windows, or doing none of that and trusting the neural net.

-figure out how to get the command module to tell comp when to take a picture

-get the neural net trained and tested

*Active Thoughts:

-RoboRealm seems sweeeeell.
::interface with MATLAB: http://www.mathworks.com/matlabcentral/fileexchange/22882

Team Commando

2012-04-23T04:29:32Z

Stmeador: /* Image Processing */

Team Commando

2012-04-23T04:20:51Z

Stmeador: /* Image Processing */

Team Commando

2012-04-23T04:12:57Z

Stmeador: /* To Do */

Team Commando

2012-04-23T04:11:49Z

Stmeador: Created page with '==To Do== *command module navigation (Daniel and Matt) *image processing (Steph, Evan, Jonah) *decide on a camera *abstract ==Navigation== ==Image Processing== *possible camera…'

==To Do==
*command module navigation (Daniel and Matt)
*image processing (Steph, Evan, Jonah)
*decide on a camera
*abstract

==Navigation==

==Image Processing==
*possible cameras
**http://www.logitech.com/en-us/webcam-communications/webcams/devices/6333
**http://us.playstation.com/ps3/accessories/playstation-eye-camera-ps3.html
**http://www.westernunion.com/wushop/category/product/304009645/search/Microsoft-LifeCam-VX-5000-Webcam---Red---Bulk/

*software
**matlab toolbox
**http://homepages.inf.ed.ac.uk/rbf/BOOKS/PHILLIPS/cips2ed.pdf

IGEM 2010 Project

2010-07-01T13:22:56Z

Stmeador: /* Math Sub-Projects */

* [http://gcat.davidson.edu/GcatWiki/index.php/Davidson_Missouri_W/Davidson_Protocols Davidson Lab Protocols] 
* [http://gcat.davidson.edu/GcatWiki/index.php/Davidson_Missouri_W/MWSU_protocols MWSU Lab Protocols] 
* [http://gcat.davidson.edu/GCATalog GCAT-alog Freezer Stocks] 

== We need to start capturing what we are doing, and why. ==
Please use this page as a starting place.

We need an overall description of our project at the overview level as well as the subsections and phases of implementation.

== Math Sub-Projects ==

'''Counting Permutations'''

'''Improving Oligo Assembler'''
We adapted the lancelator (http://gcat.davidson.edu/IGEM06/oligo.html), a program created by Lance Harden as a part of the 2006 iGem team, so that it would execute faster and can handle longer sequences. The old program could only handle sequences of 300 bp or shorter. Also, the more oligos the program broke the sequence into, the longer it took to run, and for 8 or more the run time was simply unreasonable. However, for the sequences it could handle it always finds the optimal oligos to use.
Our program allows the user to enter a sequence of any length, and the length does not significantly effect runtime. In addition, we added extra features such as checking for and removing BioBrick restriction sites and adding BioBrick primers. While our program does not always find the optimal oligos, it still does very well which is an acceptable compromise because the runtime is improved so dramatically.

http://gcat.davidson.edu/iGem10/index.html

'''Paris IGEM 2007 Results'''
{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
|'''T'''
|'''r'''
|-

|19.5 ||40.16
|-

|20.5 ||39.61
|-

|25.5 ||36.76
|-

|30.5 ||33.78
|-

|35.5 ||30.66
|-

|40.5 ||27.39
|-

|45.5 ||23.97
|-

|50.5 ||20.39
|-

|55.5 ||16.64
|-

|}

This is a chart of the experimental group in the Paris IGEM 2007 project. I used the formula r=1-10^(.004*T)/2 where r is the recombination rate (how many times Cre makes a cut and a Scar site is formed) and T is the generation time in minutes (How long it takes the cell to divide).

'''Paris IGEM 2007 Results'''
{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
|'''r'''
|'''G'''
|-

|.05 ||103.3
|-

|.10 ||50.3
|-

|.15 ||32.6
|-

|.20 ||23.7
|-

|.25 ||18.4
|-

|.30 ||14.9
|-

|.35 ||12.3
|-

|.40 ||10.4
|-

|.45 ||8.9
|-

|.50 ||7.6
|-

|.55 ||6.6
|-

|.60 ||5.8
|-

|.65 ||5.0
|-

|.70 ||4.4
|-

|.75 ||3.8
|-

|.80 ||3.3
|-

|.85 ||2.8
|-

|.90 ||2.3
|-

|.95 ||1.8
|-

|}

This is a chart of the experimental group in the Paris IGEM 2007 project. I used the formula G=log(1/200)/log(1-r) where r is the recombination rate (how many times Cre makes a cut and a Scar site is formed) and G is the number of generations (or the number of times the cell will need to divide). I am making an assumption here that the initial prey population (the plasmids in the cell) is 200.

== Biology Sub-Projects==

'''Codon Optimization''' 

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Segment
|'''Number of Base Pairs'''
|'''Wild Type Sequence'''
|'''Optimized Sequence'''
|'''Deoptimized Sequence'''
|-

| 1 || 141 || Atgaaatctaacaatgcgctcatcgtcatcctcggcaccgtcaccctggatgctgtaggcataggcttggttatgccggtactgccgggcctcttgcgggatatcgtccattccgacagcatcgccagtcactatggcgtg || ATGAAATCTAACAACGCGCTGATCGTTATCCTGGGTACCGTTACCCTGGACGCGGTTGGTATCGGTCTGGTTATGCCGGTTCTGCCGGGTCTGCTGCGTGACATCGTTCACTCTGACTCTATCGCGTCTCACTACGGTGTT || ATGAAGAGTAATAATGCCCTAATAGTCATACTAGGAACAGTCACACTAGATGCCGTCGGAATAGGACTCGTCATGCCCGTCCTACCCGGACTACTAAGGGATATAGTCCATAGTGATAGTATAGCCAGTCATTATGGAGTC
|-

| 2 || 138 || ctatatgcgttgatgcaatttctatgcgcacccgttctcggagcactgtccgaccgctttggccgccgcccagtcctgctcgcttcgctacttggagccactatcgactacgcgatcatggcgaccacacccgtcctg || CTGTACGCGCTGATGCAGTTCCTGTGCGCGCCGGTTCTGGGTGCGCTGTCTGACCGTTTCGGTCGTCGTCCGGTTCTGCTGGCGTCTCTGCTGGGTGCGACCATCGACTACGCGATCATGGCGACCACCCCGGTTCTG || CTATATGCCCTAATGCAATTTCTATGTGCCCCCGTCCTAGGAGCCCTAAGTGATAGGTTTGGAAGGAGGCCCGTCCTACTAGCCAGTCTACTAGGAGCCACAATAGATTATGCCATAATGGCCACAACACCCGTCCTA
|-

| 3 || 177 || tacgccggacgcatcgtggccggcatcaccggcgccacaggtgcggttgctggcgcctatatcgccgacatcaccgatggggaagatcgggctcgccacttcgggctcatgagcgcttgtttcggcgtgggtatggtggcaggccccgtggccgggggactgttgggcgccatctcc || TACGCGGGTCGTATCGTTGCGGGTATCACCGGTGCGACCGGTGCGGTTGCGGGTGCGTACATCGCGGACATCACCGACGGTGAAGACCGTGCGCGTCACTTCGGTCTGATGTCTGCGTGCTTCGGTGTTGGTATGGTTGCGGGTCCGGTTGCGGGTGGTCTGCTGGGTGCGATCTCT || TATGCCGGAAGGATAGTCGCCGGAATAACAGGAGCCACAGGAGCCGTCGCCGGAGCCTATATAGCCGATATAACAGATGGAGAGGATAGGGCCAGGCATTTTGGACTAATGAGTGCCTGTTTTGGAGTCGGAATGGTCGCCGGACCCGTCGCCGGAGGACTACTAGGAGCCATAAGT
|-

| 4 || 81 || ccattccttgcggcggcggtgctcaacggcctcaacctactactgggctgcttcctaatgcaggagtcgcataagggagag || CCGTTCCTGGCGGCGGCGGTTCTGAACGGTCTGAACCTGCTGCTGGGTTGCTTCCTGATGCAGGAATCTCACAAAGGTGAA || CCCTTTCTAGCCGCCGCCGTCCTAAATGGACTAAATCTACTACTAGGATGTTTTCTAATGCAAGAGAGTCATAAGGGAGAG
|-

|}

Note: All above segments have been optimized and deoptimized using the online [http://genomes.urv.es/OPTIMIZER/ Optimizer] program.

To create the optimized and deoptimized segments of the Tet A gene we used the sequence that the Optimizer program gave us and put it into the [http://gcat.davidson.edu/IGEM06/oligo.html Lancelator] a program created by Lance Harden as part of the 2006 iGEM team. After getting the recommended Oligo sequences from the Lancelator, we added necessary "sticky ends" that were compatible with the naturally occurring restriction enzyme sites that we discovered (see Restriction Enzymes below). At this time we have ordered Oligo parts for segments 1 and 2 of the Tet A gene. The Oligos that were ordered can be seen below.

'''Segment 1 Oligos'''

'''Optimized'''

top 1 5' AATTCGCGGCCGCTTCTAGATGAAATCTAACAACGCGCTGATCGTTATCCTGGGTACCG 3’

top 2 5' TTACCCTGGACGCGGTTGGTATCGGTCTGGTTATGCCGGTTCTGCCGGGTCTGCTGCGTGAC 3’

top 3 5' ATCGTTCACTCTGACTCTATCGCGTCTCACTACGGTGTTCTG 3’

bottom 2 5' CATAACCAGACCGATACCAACCGCGTCCAGGGTAACGGTAC
CCAGGATAACGATCAGCGCGTTGTTAGATTTCATCTAGAAGCGGCCGCG 3’

bottom 1 5' CTAGCAGAACACCGTAGTGAGACGCGATAGAGTCAGAGTGAACGATGTCACGCAGCAGACCCGGCAGAACCGG 3’

'''Deoptimized'''

top 1 5' AATTCGCGGCCGCTTCTAGATGAAGAGTAATAATGCCCTAATAGTCATACTAGGAACAG 3’

top 2 5' TCACACTAGATGCCGTCGGAATAGGACTCGTCATGCCCGTCCTACCCGGACTACTAAGGGA 3’

top 3 5' TATAGTCCATAGTGATAGTATAGCCAGTCATTATGGAGTCCTG 3’

bottom 2 5' GAGTCCTATTCCGACGGCATCTAGTGTGACTGTTCCTAGTATG
ACTATTAGGGCATTATTACTCTTCATCTAGAAGCGGCCGCG 3’

bottom 1 5' CTAGCAGGACTCCATAATGACTGGCTATACTATCACTATGGACTATATCCCTTAGTAGTCCGGGTAGGACGGGCATGAC 3’

'''Segment 2 Oligos'''

'''Optimized'''

top 1 5' CTAGCCTGTACGCGCTGATGCAGTTCCTGTGCGCGCCGGTTCTGGGTGCGCTGTCTGAC 3’

top 2 5' CGTTTCGGTCGTCGTCCGGTTCTGCTGGCGTCTCTGCTGGGTGCGACCATCGACTAC 3’

top 3 5' GCGATCATGGCGACCACCCCGGTTCTGTG 3’

bottom 1 5' GCGCACAGGAACTGCATCAGCGCGTACAGG 3’

bottom 2 5' CCAGCAGAACCGGACGACGACCGAAACGGTCAGACAGCGCACCCAGAACCGGC 3’

bottom 3 5' GATCCACAGAACCGGGGTGGTCGCCATGATCGCGTAGTCGATGGTCGCACCCAGCAGAGACG 3’

'''Deoptimized'''

top 1 5' CTAGCGCTATATGCCCTAATGCAATTTCTATGTGCCCCCGTCCTAGGAGCCCTAAGTG 3'

top 2 5' ATAGGTTTGGAAGGAGGCCCGTCCTACTAGCCAGTCTACTAGGAGCCACAATAGAT 3'

top 3 5' TATGCCATAATGGCCACAACACCCGTCCTATG 3'

bottom 1 5' GGCACATAGAAATTGCATTAGGGCATATAGCG 3' 

bottom 2 5' TAGGACGGGCCTCCTTCCAAACCTATCACTTAGGGCTCCTAGGACGGG 3' 

bottom 3 5' GATCCATAGGACGGGTGTTGTGGCCATTATGGCATAATCTATTGTGGCTCCTAGTAGACTGGCTAG 3'

[[Image:wiki3.jpg]]

'''Restriction Enzymes'''

To insert the annealed Oligo segments that were created we had to digest the Tet A gene using naturally occurring enzyme restriction sites that did not exist in the rest of the gene or in the plasmid (pSBIA2).

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Segment
|'''First Restriction Enzyme'''
|'''Second Restriction Enzyme'''
|-

| 1 || EcoRI || NheI
|-

| 2 || NheI || BamHI
|-

| 3 || BamHI || SphI
|-

| 4 || SphI || SalI
|-

|}

'''Parts Used (to be used)'''
{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Part
|'''Registry Link'''
|'''Construct Including Part'''
|-

| Tet A (tetracycline resistance gene) J31007 || [http://partsregistry.org/Part:BBa_J31007 Tet A (forward)] || promoter-RBS-RFP-RBS-TetA on pSBIA2
|-

| pLac-RBS-RFP I715039 || [http://partsregistry.org/Part:BBa_I715039 pLac-RBS-RFP ]|| Possibly: pLac-RBS-RFP-RBS-TetA on pSBIA2
|-

| pLac-RBS-RFP-RBS-TetA-TT on pSBIAK3 S04435 || [http://partsregistry.org/Part:BBa_S04435 pLac-RBS-RFP-RBS-TetA-TT]|| Possibly: pLac-RBS-RFP-RBS-TetA-TT on pSBIA2
|-

| Part Name and Registry Number || [http://partsregistry.org/Main_Page Registry Link]|| Construct
|-

| Part Name and Registry Number || [http://partsregistry.org/Main_Page Registry Link]|| Construct
|-
|}

'''Promoters'''

This chart shows flourescene levels of different promoter constructs with varying levels of IPTG added (error bars with standard error can be seen on the graph). Note: This experiment is still in progress. More data will be posted when available.

[[Image:wiki4.jpg]]

'''Tet-trations''' 

[[Image:cellturbidity.jpg]]

'''Making and Testing lox_ Sites'''
<center>
 '''Green''' Part has been cloned and sequence verified; '''Red''' Part is under construction

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Final Construct
!width="30"|Current Status
!Registry Number and Link
!width="30"|Primary Team Member
|-
| '''''lox5171'' Forward in pSB1A2''' || I got colonies on my second attempt. Once I isolate the plasmid, it will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] ''lox5171'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Nitya
|-

| '''''lox5171'' Reverse in pSB1A2''' || This plasmid will also be sent off for sequencing soon. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] ''lox5171'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Nitya
|-

| '''loxm2 Forward in pSB1A2''' || I ligated loxm2 F with the plasmid and have prepared the DNA for sequencing to confirm what is there. || [http://partsregistry.org/Part:BBa_K315004] ''loxm2'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Tom
|-

| '''loxm2 Reverse in pSB1A2''' || I ligated loxm2 F with the plasmid and have prepared the DNA for sequencing to confirm what is there. || [http://partsregistry.org/Part:BBa_K315005] ''loxm2'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Tom
|-

| '''loxBri forward in pSB1A2''' || 4 colonies grew with the correct sized insert from colony PCR verification and will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] loxBri does not exist in the registry. We ordered this oligos with 3 mutations and transformed in lab. || Bri
|-

| '''loxBri reverse in pSB1A2''' || I had 3 successful colonies from this oligos ligation that were also confirmed by colony PCR that will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] loxBri does not exist in the registry. This oligos was also transformed in the lab. || Bri
|-

| '''loxP reverse in pSB1A2''' || I had 5 successful colonies from this oligos ligation that were also confirmed by colony PCR. They will be sent off for sequencing. || [http://partsregistry.org/Part:BBa_K206013 loxP reverse] loxP reverse exists in the registry. We ordered this oligos and ligated it into pSB1A2 in the lab. || Bri
|-

| '''loxN Forward in pSB1A2''' || I had 5 successful colonies from this oligos ligation that were also confirmed by colony PCR. They are sent off for sequencing and four of them were confirmed to be correct. || [http://partsregistry.org/Part:BBa_K315007] loxN forward does not exist in the registry. We ordered the oligos and built it in the lab. || Anvi
|-

| '''loxN Reverse in pSB1A2''' || I had 3 successful colonies from this oligos ligation that were also confirmed by colony PCR. They are sent off for sequencing and two of them were confirmed to be correct. || [http://partsregistry.org/Part:BBa_K315011] loxN reverse does not exist in the registry. We ordered the oligos and built it in the lab. || Anvi
|-

|}
 
</center>

'''Testing Cre Activity''' 
<center>

 '''Green''' Part has been cloned and sequence verified; '''Red''' Part is under construction

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Final Construct
!width="30"|Current Status
!Registry Number and Link
!width="30"|Primary Team Member
|-
| '''I718008 (pBAD+RBS+cre) in pSB4K5''' || At this point, I have isolated both the insert and the plasmid, but my two attempts at ligation have not produced any colonies. || [http://partsregistry.org/Part:BBa_I718008 I718008] [http://partsregistry.org/wiki/index.php?title=Part:pSB4K5 pSB4K5] || Nitya
|-

| '''I718008 (pBAD+RBS+cre) in pSB3K3''' || At this point, I have ligated and transformed the cells but I am having trouble growing it in the LB + kan media. || [http://partsregistry.org/Part:BBa_I718008 I718008][http://partsregistry.org/wiki/index.php?title=Part:pSB3K5] describe intermediate || Anvi
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-
|}
</center>
 

'''pSBIA7 & pSBIA2'''

Data showing the varying levels of expression between pSBIA7 and pSBIA2

[[Image:curtiss3.jpg]]

IGEM 2010 Project

2010-07-01T13:20:09Z

Stmeador: /* Math Sub-Projects */

* [http://gcat.davidson.edu/GcatWiki/index.php/Davidson_Missouri_W/Davidson_Protocols Davidson Lab Protocols] 
* [http://gcat.davidson.edu/GcatWiki/index.php/Davidson_Missouri_W/MWSU_protocols MWSU Lab Protocols] 
* [http://gcat.davidson.edu/GCATalog GCAT-alog Freezer Stocks] 

== We need to start capturing what we are doing, and why. ==
Please use this page as a starting place.

We need an overall description of our project at the overview level as well as the subsections and phases of implementation.

== Math Sub-Projects ==

'''Counting Permutations'''

'''Improving Oligo Assembler'''
We adapted the lancelator (http://gcat.davidson.edu/IGEM06/oligo.html), a program created by Lance Harden as a part of the 2006 iGem team, so that it would execute faster and can handle longer sequences. The old program could only handle sequences of 300 bp or shorter. Also, the more oligos the program broke the sequence into, the longer it took to run, and for 8 or more the run time was simply unreasonable. However, for the sequences it could handle it always finds the optimal oligos to use.
Our program allows the user to enter a sequence of any length, and the length does not significantly effect runtime. In addition, we added extra features such as checking for and removing BioBrick restriction sites and adding BioBrick primers. While our program does not always find the optimal oligos, it still does very well which is an acceptable compromise because the runtime is improved so dramatically.

http://gcat.davidson.edu/iGem10/index.html

'''Paris IGEM 2007 Results'''
{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
|'''T'''
|'''r'''
|-

|19.5 ||40.16
|-

|20.5 ||39.61
|-

|25.5 ||36.76
|-

|30.5 ||33.78
|-

|35.5 ||30.66
|-

|40.5 ||27.39
|-

|45.5 ||23.97
|-

|50.5 ||20.39
|-

|55.5 ||16.64
|-

|}

This is a chart of the experimental group in the Paris IGEM 2007 project. I used the formula r=1-10^(.004*T)/2 where r is the recombination rate (how many times Cre makes a cut and a Scar site is formed) and T is the generation time in minutes (How long it takes the cell to divide).

'''Paris IGEM 2007 Results'''
{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
|'''r'''
|'''G'''
|-

|.05 ||103.3
|-

|.10 ||50.3
|-

|.15 ||32.6
|-

|.20 ||23.7
|-

|.25 ||18.4
|-

|.30 ||14.9
|-

|.35 ||12.3
|-

|.40 ||10.4
|-

|.45 ||8.9
|-

|.50 ||7.6
|-

|.55 ||6.6
|-

|.60 ||5.8
|-

|.65 ||5.0
|-

|.70 ||4.4
|-

|.75 ||3.8
|-

|.80 ||3.3
|-

|.85 ||2.8
|-

|.90 ||2.3
|-

|.95 ||1.8
|-

|}

== Biology Sub-Projects==

'''Codon Optimization''' 

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Segment
|'''Number of Base Pairs'''
|'''Wild Type Sequence'''
|'''Optimized Sequence'''
|'''Deoptimized Sequence'''
|-

| 1 || 141 || Atgaaatctaacaatgcgctcatcgtcatcctcggcaccgtcaccctggatgctgtaggcataggcttggttatgccggtactgccgggcctcttgcgggatatcgtccattccgacagcatcgccagtcactatggcgtg || ATGAAATCTAACAACGCGCTGATCGTTATCCTGGGTACCGTTACCCTGGACGCGGTTGGTATCGGTCTGGTTATGCCGGTTCTGCCGGGTCTGCTGCGTGACATCGTTCACTCTGACTCTATCGCGTCTCACTACGGTGTT || ATGAAGAGTAATAATGCCCTAATAGTCATACTAGGAACAGTCACACTAGATGCCGTCGGAATAGGACTCGTCATGCCCGTCCTACCCGGACTACTAAGGGATATAGTCCATAGTGATAGTATAGCCAGTCATTATGGAGTC
|-

| 2 || 138 || ctatatgcgttgatgcaatttctatgcgcacccgttctcggagcactgtccgaccgctttggccgccgcccagtcctgctcgcttcgctacttggagccactatcgactacgcgatcatggcgaccacacccgtcctg || CTGTACGCGCTGATGCAGTTCCTGTGCGCGCCGGTTCTGGGTGCGCTGTCTGACCGTTTCGGTCGTCGTCCGGTTCTGCTGGCGTCTCTGCTGGGTGCGACCATCGACTACGCGATCATGGCGACCACCCCGGTTCTG || CTATATGCCCTAATGCAATTTCTATGTGCCCCCGTCCTAGGAGCCCTAAGTGATAGGTTTGGAAGGAGGCCCGTCCTACTAGCCAGTCTACTAGGAGCCACAATAGATTATGCCATAATGGCCACAACACCCGTCCTA
|-

| 3 || 177 || tacgccggacgcatcgtggccggcatcaccggcgccacaggtgcggttgctggcgcctatatcgccgacatcaccgatggggaagatcgggctcgccacttcgggctcatgagcgcttgtttcggcgtgggtatggtggcaggccccgtggccgggggactgttgggcgccatctcc || TACGCGGGTCGTATCGTTGCGGGTATCACCGGTGCGACCGGTGCGGTTGCGGGTGCGTACATCGCGGACATCACCGACGGTGAAGACCGTGCGCGTCACTTCGGTCTGATGTCTGCGTGCTTCGGTGTTGGTATGGTTGCGGGTCCGGTTGCGGGTGGTCTGCTGGGTGCGATCTCT || TATGCCGGAAGGATAGTCGCCGGAATAACAGGAGCCACAGGAGCCGTCGCCGGAGCCTATATAGCCGATATAACAGATGGAGAGGATAGGGCCAGGCATTTTGGACTAATGAGTGCCTGTTTTGGAGTCGGAATGGTCGCCGGACCCGTCGCCGGAGGACTACTAGGAGCCATAAGT
|-

| 4 || 81 || ccattccttgcggcggcggtgctcaacggcctcaacctactactgggctgcttcctaatgcaggagtcgcataagggagag || CCGTTCCTGGCGGCGGCGGTTCTGAACGGTCTGAACCTGCTGCTGGGTTGCTTCCTGATGCAGGAATCTCACAAAGGTGAA || CCCTTTCTAGCCGCCGCCGTCCTAAATGGACTAAATCTACTACTAGGATGTTTTCTAATGCAAGAGAGTCATAAGGGAGAG
|-

|}

Note: All above segments have been optimized and deoptimized using the online [http://genomes.urv.es/OPTIMIZER/ Optimizer] program.

To create the optimized and deoptimized segments of the Tet A gene we used the sequence that the Optimizer program gave us and put it into the [http://gcat.davidson.edu/IGEM06/oligo.html Lancelator] a program created by Lance Harden as part of the 2006 iGEM team. After getting the recommended Oligo sequences from the Lancelator, we added necessary "sticky ends" that were compatible with the naturally occurring restriction enzyme sites that we discovered (see Restriction Enzymes below). At this time we have ordered Oligo parts for segments 1 and 2 of the Tet A gene. The Oligos that were ordered can be seen below.

'''Segment 1 Oligos'''

'''Optimized'''

top 1 5' AATTCGCGGCCGCTTCTAGATGAAATCTAACAACGCGCTGATCGTTATCCTGGGTACCG 3’

top 2 5' TTACCCTGGACGCGGTTGGTATCGGTCTGGTTATGCCGGTTCTGCCGGGTCTGCTGCGTGAC 3’

top 3 5' ATCGTTCACTCTGACTCTATCGCGTCTCACTACGGTGTTCTG 3’

bottom 2 5' CATAACCAGACCGATACCAACCGCGTCCAGGGTAACGGTAC
CCAGGATAACGATCAGCGCGTTGTTAGATTTCATCTAGAAGCGGCCGCG 3’

bottom 1 5' CTAGCAGAACACCGTAGTGAGACGCGATAGAGTCAGAGTGAACGATGTCACGCAGCAGACCCGGCAGAACCGG 3’

'''Deoptimized'''

top 1 5' AATTCGCGGCCGCTTCTAGATGAAGAGTAATAATGCCCTAATAGTCATACTAGGAACAG 3’

top 2 5' TCACACTAGATGCCGTCGGAATAGGACTCGTCATGCCCGTCCTACCCGGACTACTAAGGGA 3’

top 3 5' TATAGTCCATAGTGATAGTATAGCCAGTCATTATGGAGTCCTG 3’

bottom 2 5' GAGTCCTATTCCGACGGCATCTAGTGTGACTGTTCCTAGTATG
ACTATTAGGGCATTATTACTCTTCATCTAGAAGCGGCCGCG 3’

bottom 1 5' CTAGCAGGACTCCATAATGACTGGCTATACTATCACTATGGACTATATCCCTTAGTAGTCCGGGTAGGACGGGCATGAC 3’

'''Segment 2 Oligos'''

'''Optimized'''

top 1 5' CTAGCCTGTACGCGCTGATGCAGTTCCTGTGCGCGCCGGTTCTGGGTGCGCTGTCTGAC 3’

top 2 5' CGTTTCGGTCGTCGTCCGGTTCTGCTGGCGTCTCTGCTGGGTGCGACCATCGACTAC 3’

top 3 5' GCGATCATGGCGACCACCCCGGTTCTGTG 3’

bottom 1 5' GCGCACAGGAACTGCATCAGCGCGTACAGG 3’

bottom 2 5' CCAGCAGAACCGGACGACGACCGAAACGGTCAGACAGCGCACCCAGAACCGGC 3’

bottom 3 5' GATCCACAGAACCGGGGTGGTCGCCATGATCGCGTAGTCGATGGTCGCACCCAGCAGAGACG 3’

'''Deoptimized'''

top 1 5' CTAGCGCTATATGCCCTAATGCAATTTCTATGTGCCCCCGTCCTAGGAGCCCTAAGTG 3'

top 2 5' ATAGGTTTGGAAGGAGGCCCGTCCTACTAGCCAGTCTACTAGGAGCCACAATAGAT 3'

top 3 5' TATGCCATAATGGCCACAACACCCGTCCTATG 3'

bottom 1 5' GGCACATAGAAATTGCATTAGGGCATATAGCG 3' 

bottom 2 5' TAGGACGGGCCTCCTTCCAAACCTATCACTTAGGGCTCCTAGGACGGG 3' 

bottom 3 5' GATCCATAGGACGGGTGTTGTGGCCATTATGGCATAATCTATTGTGGCTCCTAGTAGACTGGCTAG 3'

[[Image:wiki3.jpg]]

'''Restriction Enzymes'''

To insert the annealed Oligo segments that were created we had to digest the Tet A gene using naturally occurring enzyme restriction sites that did not exist in the rest of the gene or in the plasmid (pSBIA2).

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Segment
|'''First Restriction Enzyme'''
|'''Second Restriction Enzyme'''
|-

| 1 || EcoRI || NheI
|-

| 2 || NheI || BamHI
|-

| 3 || BamHI || SphI
|-

| 4 || SphI || SalI
|-

|}

'''Parts Used (to be used)'''
{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Part
|'''Registry Link'''
|'''Construct Including Part'''
|-

| Tet A (tetracycline resistance gene) J31007 || [http://partsregistry.org/Part:BBa_J31007 Tet A (forward)] || promoter-RBS-RFP-RBS-TetA on pSBIA2
|-

| pLac-RBS-RFP I715039 || [http://partsregistry.org/Part:BBa_I715039 pLac-RBS-RFP ]|| Possibly: pLac-RBS-RFP-RBS-TetA on pSBIA2
|-

| pLac-RBS-RFP-RBS-TetA-TT on pSBIAK3 S04435 || [http://partsregistry.org/Part:BBa_S04435 pLac-RBS-RFP-RBS-TetA-TT]|| Possibly: pLac-RBS-RFP-RBS-TetA-TT on pSBIA2
|-

| Part Name and Registry Number || [http://partsregistry.org/Main_Page Registry Link]|| Construct
|-

| Part Name and Registry Number || [http://partsregistry.org/Main_Page Registry Link]|| Construct
|-
|}

'''Promoters'''

This chart shows flourescene levels of different promoter constructs with varying levels of IPTG added (error bars with standard error can be seen on the graph). Note: This experiment is still in progress. More data will be posted when available.

[[Image:wiki4.jpg]]

'''Tet-trations''' 

[[Image:cellturbidity.jpg]]

'''Making and Testing lox_ Sites'''
<center>
 '''Green''' Part has been cloned and sequence verified; '''Red''' Part is under construction

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Final Construct
!width="30"|Current Status
!Registry Number and Link
!width="30"|Primary Team Member
|-
| '''''lox5171'' Forward in pSB1A2''' || I got colonies on my second attempt. Once I isolate the plasmid, it will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] ''lox5171'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Nitya
|-

| '''''lox5171'' Reverse in pSB1A2''' || This plasmid will also be sent off for sequencing soon. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] ''lox5171'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Nitya
|-

| '''loxm2 Forward in pSB1A2''' || I ligated loxm2 F with the plasmid and have prepared the DNA for sequencing to confirm what is there. || [http://partsregistry.org/Part:BBa_K315004] ''loxm2'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Tom
|-

| '''loxm2 Reverse in pSB1A2''' || I ligated loxm2 F with the plasmid and have prepared the DNA for sequencing to confirm what is there. || [http://partsregistry.org/Part:BBa_K315005] ''loxm2'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Tom
|-

| '''loxBri forward in pSB1A2''' || 4 colonies grew with the correct sized insert from colony PCR verification and will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] loxBri does not exist in the registry. We ordered this oligos with 3 mutations and transformed in lab. || Bri
|-

| '''loxBri reverse in pSB1A2''' || I had 3 successful colonies from this oligos ligation that were also confirmed by colony PCR that will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] loxBri does not exist in the registry. This oligos was also transformed in the lab. || Bri
|-

| '''loxP reverse in pSB1A2''' || I had 5 successful colonies from this oligos ligation that were also confirmed by colony PCR. They will be sent off for sequencing. || [http://partsregistry.org/Part:BBa_K206013 loxP reverse] loxP reverse exists in the registry. We ordered this oligos and ligated it into pSB1A2 in the lab. || Bri
|-

| '''loxN Forward in pSB1A2''' || I had 5 successful colonies from this oligos ligation that were also confirmed by colony PCR. They are sent off for sequencing and four of them were confirmed to be correct. || [http://partsregistry.org/Part:BBa_K315007] loxN forward does not exist in the registry. We ordered the oligos and built it in the lab. || Anvi
|-

| '''loxN Reverse in pSB1A2''' || I had 3 successful colonies from this oligos ligation that were also confirmed by colony PCR. They are sent off for sequencing and two of them were confirmed to be correct. || [http://partsregistry.org/Part:BBa_K315011] loxN reverse does not exist in the registry. We ordered the oligos and built it in the lab. || Anvi
|-

|}
 
</center>

'''Testing Cre Activity''' 
<center>

 '''Green''' Part has been cloned and sequence verified; '''Red''' Part is under construction

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Final Construct
!width="30"|Current Status
!Registry Number and Link
!width="30"|Primary Team Member
|-
| '''I718008 (pBAD+RBS+cre) in pSB4K5''' || At this point, I have isolated both the insert and the plasmid, but my two attempts at ligation have not produced any colonies. || [http://partsregistry.org/Part:BBa_I718008 I718008] [http://partsregistry.org/wiki/index.php?title=Part:pSB4K5 pSB4K5] || Nitya
|-

| '''I718008 (pBAD+RBS+cre) in pSB3K3''' || At this point, I have ligated and transformed the cells but I am having trouble growing it in the LB + kan media. || [http://partsregistry.org/Part:BBa_I718008 I718008][http://partsregistry.org/wiki/index.php?title=Part:pSB3K5] describe intermediate || Anvi
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-
|}
</center>
 

'''pSBIA7 & pSBIA2'''

Data showing the varying levels of expression between pSBIA7 and pSBIA2

[[Image:curtiss3.jpg]]

IGEM 2010 Project

2010-06-28T20:47:26Z

Stmeador: /* Math Sub-Projects */

* [http://gcat.davidson.edu/GcatWiki/index.php/Davidson_Missouri_W/Davidson_Protocols Davidson Lab Protocols] 
* [http://gcat.davidson.edu/GcatWiki/index.php/Davidson_Missouri_W/MWSU_protocols MWSU Lab Protocols] 
* [http://gcat.davidson.edu/GCATalog GCAT-alog Freezer Stocks] 

== We need to start capturing what we are doing, and why. ==
Please use this page as a starting place.

We need an overall description of our project at the overview level as well as the subsections and phases of implementation.

== Math Sub-Projects ==

'''Counting Permutations'''

'''Improving Oligo Assembler'''
We adapted the lancelator (http://gcat.davidson.edu/IGEM06/oligo.html), a program created by Lance Harden as a part of the 2006 iGem team, so that it would execute faster and can handle longer sequences. The old program could only handle sequences of 300 bp or shorter. Also, the more oligos the program broke the sequence into, the longer it took to run, and for 8 or more the run time was simply unreasonable. However, for the sequences it could handle it always finds the optimal oligos to use.
Our program allows the user to enter a sequence of any length, and the length does not significantly effect runtime. In addition, we added extra features such as checking for and removing BioBrick restriction sites and adding BioBrick primers. While our program does not always find the optimal oligos, it still does very well which is an acceptable compromise because the runtime is improved so dramatically.

http://gcat.davidson.edu/iGem10/index.html

'''Paris IGEM 2007 Results'''
{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
|'''T'''
|'''r'''
|-

|19.5 ||40.16
|-

|20.5 ||39.61
|-

|25.5 ||36.76
|-

|30.5 ||33.78
|-

|35.5 ||30.66
|-

|40.5 ||27.39
|-

|45.5 ||23.97
|-

|50.5 ||20.39
|-

|55.5 ||16.64
|-

|}

This is a chart of the experimental group in the Paris IGEM 2007 project. I used the formula r=1-10^(.004*T)/2 where r is the recombination rate (how many times Cre makes a cut and a Scar site is formed) and T is the generation time in minutes (How long it takes the cell to divide).

== Biology Sub-Projects==

'''Codon Optimization''' 

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Segment
|'''Number of Base Pairs'''
|'''Wild Type Sequence'''
|'''Optimized Sequence'''
|'''Deoptimized Sequence'''
|-

| 1 || 141 || Atgaaatctaacaatgcgctcatcgtcatcctcggcaccgtcaccctggatgctgtaggcataggcttggttatgccggtactgccgggcctcttgcgggatatcgtccattccgacagcatcgccagtcactatggcgtg || ATGAAATCTAACAACGCGCTGATCGTTATCCTGGGTACCGTTACCCTGGACGCGGTTGGTATCGGTCTGGTTATGCCGGTTCTGCCGGGTCTGCTGCGTGACATCGTTCACTCTGACTCTATCGCGTCTCACTACGGTGTT || ATGAAGAGTAATAATGCCCTAATAGTCATACTAGGAACAGTCACACTAGATGCCGTCGGAATAGGACTCGTCATGCCCGTCCTACCCGGACTACTAAGGGATATAGTCCATAGTGATAGTATAGCCAGTCATTATGGAGTC
|-

| 2 || 138 || ctatatgcgttgatgcaatttctatgcgcacccgttctcggagcactgtccgaccgctttggccgccgcccagtcctgctcgcttcgctacttggagccactatcgactacgcgatcatggcgaccacacccgtcctg || CTGTACGCGCTGATGCAGTTCCTGTGCGCGCCGGTTCTGGGTGCGCTGTCTGACCGTTTCGGTCGTCGTCCGGTTCTGCTGGCGTCTCTGCTGGGTGCGACCATCGACTACGCGATCATGGCGACCACCCCGGTTCTG || CTATATGCCCTAATGCAATTTCTATGTGCCCCCGTCCTAGGAGCCCTAAGTGATAGGTTTGGAAGGAGGCCCGTCCTACTAGCCAGTCTACTAGGAGCCACAATAGATTATGCCATAATGGCCACAACACCCGTCCTA
|-

| 3 || 177 || tacgccggacgcatcgtggccggcatcaccggcgccacaggtgcggttgctggcgcctatatcgccgacatcaccgatggggaagatcgggctcgccacttcgggctcatgagcgcttgtttcggcgtgggtatggtggcaggccccgtggccgggggactgttgggcgccatctcc || TACGCGGGTCGTATCGTTGCGGGTATCACCGGTGCGACCGGTGCGGTTGCGGGTGCGTACATCGCGGACATCACCGACGGTGAAGACCGTGCGCGTCACTTCGGTCTGATGTCTGCGTGCTTCGGTGTTGGTATGGTTGCGGGTCCGGTTGCGGGTGGTCTGCTGGGTGCGATCTCT || TATGCCGGAAGGATAGTCGCCGGAATAACAGGAGCCACAGGAGCCGTCGCCGGAGCCTATATAGCCGATATAACAGATGGAGAGGATAGGGCCAGGCATTTTGGACTAATGAGTGCCTGTTTTGGAGTCGGAATGGTCGCCGGACCCGTCGCCGGAGGACTACTAGGAGCCATAAGT
|-

| 4 || 81 || ccattccttgcggcggcggtgctcaacggcctcaacctactactgggctgcttcctaatgcaggagtcgcataagggagag || CCGTTCCTGGCGGCGGCGGTTCTGAACGGTCTGAACCTGCTGCTGGGTTGCTTCCTGATGCAGGAATCTCACAAAGGTGAA || CCCTTTCTAGCCGCCGCCGTCCTAAATGGACTAAATCTACTACTAGGATGTTTTCTAATGCAAGAGAGTCATAAGGGAGAG
|-

|}

Note: All above segments have been optimized and deoptimized using the online [http://genomes.urv.es/OPTIMIZER/ Optimizer] program.

To create the optimized and deoptimized segments of the Tet A gene we used the sequence that the Optimizer program gave us and put it into the [http://gcat.davidson.edu/IGEM06/oligo.html Lancelator] a program created by Lance Harden as part of the 2006 iGEM team. After getting the recommended Oligo sequences from the Lancelator, we added necessary "sticky ends" that were compatible with the naturally occurring restriction enzyme sites that we discovered (see Restriction Enzymes below). At this time we have ordered Oligo parts for segments 1 and 2 of the Tet A gene. The Oligos that were ordered can be seen below.

'''Segment 1 Oligos'''

'''Optimized'''

top 1 5' AATTCGCGGCCGCTTCTAGATGAAATCTAACAACGCGCTGATCGTTATCCTGGGTACCG 3’

top 2 5' TTACCCTGGACGCGGTTGGTATCGGTCTGGTTATGCCGGTTCTGCCGGGTCTGCTGCGTGAC 3’

top 3 5' ATCGTTCACTCTGACTCTATCGCGTCTCACTACGGTGTTCTG 3’

bottom 2 5' CATAACCAGACCGATACCAACCGCGTCCAGGGTAACGGTAC
CCAGGATAACGATCAGCGCGTTGTTAGATTTCATCTAGAAGCGGCCGCG 3’

bottom 1 5' CTAGCAGAACACCGTAGTGAGACGCGATAGAGTCAGAGTGAACGATGTCACGCAGCAGACCCGGCAGAACCGG 3’

'''Deoptimized'''

top 1 5' AATTCGCGGCCGCTTCTAGATGAAGAGTAATAATGCCCTAATAGTCATACTAGGAACAG 3’

top 2 5' TCACACTAGATGCCGTCGGAATAGGACTCGTCATGCCCGTCCTACCCGGACTACTAAGGGA 3’

top 3 5' TATAGTCCATAGTGATAGTATAGCCAGTCATTATGGAGTCCTG 3’

bottom 2 5' GAGTCCTATTCCGACGGCATCTAGTGTGACTGTTCCTAGTATG
ACTATTAGGGCATTATTACTCTTCATCTAGAAGCGGCCGCG 3’

bottom 1 5' CTAGCAGGACTCCATAATGACTGGCTATACTATCACTATGGACTATATCCCTTAGTAGTCCGGGTAGGACGGGCATGAC 3’

'''Segment 2 Oligos'''

'''Optimized'''

top 1 5' CTAGCCTGTACGCGCTGATGCAGTTCCTGTGCGCGCCGGTTCTGGGTGCGCTGTCTGAC 3’

top 2 5' CGTTTCGGTCGTCGTCCGGTTCTGCTGGCGTCTCTGCTGGGTGCGACCATCGACTAC 3’

top 3 5' GCGATCATGGCGACCACCCCGGTTCTGTG 3’

bottom 1 5' GCGCACAGGAACTGCATCAGCGCGTACAGG 3’

bottom 2 5' CCAGCAGAACCGGACGACGACCGAAACGGTCAGACAGCGCACCCAGAACCGGC 3’

bottom 3 5' GATCCACAGAACCGGGGTGGTCGCCATGATCGCGTAGTCGATGGTCGCACCCAGCAGAGACG 3’

'''Deoptimized'''

top 1 5' CTAGCGCTATATGCCCTAATGCAATTTCTATGTGCCCCCGTCCTAGGAGCCCTAAGTG 3'

top 2 5' ATAGGTTTGGAAGGAGGCCCGTCCTACTAGCCAGTCTACTAGGAGCCACAATAGAT 3'

top 3 5' TATGCCATAATGGCCACAACACCCGTCCTATG 3'

bottom 1 5' GGCACATAGAAATTGCATTAGGGCATATAGCG 3' 

bottom 2 5' TAGGACGGGCCTCCTTCCAAACCTATCACTTAGGGCTCCTAGGACGGG 3' 

bottom 3 5' GATCCATAGGACGGGTGTTGTGGCCATTATGGCATAATCTATTGTGGCTCCTAGTAGACTGGCTAG 3'

[[Image:wiki3.jpg]]

'''Restriction Enzymes'''

To insert the annealed Oligo segments that were created we had to digest the Tet A gene using naturally occurring enzyme restriction sites that did not exist in the rest of the gene or in the plasmid (pSBIA2).

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Segment
|'''First Restriction Enzyme'''
|'''Second Restriction Enzyme'''
|-

| 1 || EcoRI || NheI
|-

| 2 || NheI || BamHI
|-

| 3 || BamHI || SphI
|-

| 4 || SphI || SalI
|-

|}

'''Parts Used (to be used)'''
{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Part
|'''Registry Link'''
|'''Construct Including Part'''
|-

| Tet A (tetracycline resistance gene) J31007 || [http://partsregistry.org/Part:BBa_J31007 Tet A (forward)] || promoter-RBS-RFP-RBS-TetA on pSBIA2
|-

| pLac-RBS-RFP I715039 || [http://partsregistry.org/Part:BBa_I715039 pLac-RBS-RFP ]|| Possibly: pLac-RBS-RFP-RBS-TetA on pSBIA2
|-

| pLac-RBS-RFP-RBS-TetA-TT on pSBIAK3 S04435 || [http://partsregistry.org/Part:BBa_S04435 pLac-RBS-RFP-RBS-TetA-TT]|| Possibly: pLac-RBS-RFP-RBS-TetA-TT on pSBIA2
|-

| Part Name and Registry Number || [http://partsregistry.org/Main_Page Registry Link]|| Construct
|-

| Part Name and Registry Number || [http://partsregistry.org/Main_Page Registry Link]|| Construct
|-
|}

'''Promoters'''

This chart shows flourescene levels of different promoter constructs with varying levels of IPTG added (error bars with standard error can be seen on the graph). Note: This experiment is still in progress. More data will be posted when available.

[[Image:wiki4.jpg]]

'''Tet-trations''' 

'''Making and Testing lox_ Sites'''
<center>
 '''Green''' Part has been cloned and sequence verified; '''Red''' Part is under construction

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Final Construct
!width="30"|Current Status
!Registry Number and Link
!width="30"|Primary Team Member
|-
| '''''lox5171'' Forward in pSB1A2''' || I got colonies on my second attempt. Once I isolate the plasmid, it will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] ''lox5171'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Nitya
|-

| '''''lox5171'' Reverse in pSB1A2''' || This plasmid will also be sent off for sequencing soon. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] ''lox5171'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Nitya
|-

| '''loxm2 Forward in pSB1A2''' || I ligated loxm2 F with the plasmid and have prepared the DNA for sequencing to confirm what is there. || [http://partsregistry.org/Part:BBa_K315004] ''loxm2'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Tom
|-

| '''loxm2 Reverse in pSB1A2''' || I ligated loxm2 F with the plasmid and have prepared the DNA for sequencing to confirm what is there. || [http://partsregistry.org/Part:BBa_K315005] ''loxm2'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Tom
|-

| '''loxBri forward in pSB1A2''' || 4 colonies grew with the correct sized insert from colony PCR verification and will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] loxBri does not exist in the registry. We ordered this oligos with 3 mutations and transformed in lab. || Bri
|-

| '''loxBri reverse in pSB1A2''' || I had 3 successful colonies from this oligos ligation that were also confirmed by colony PCR that will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] loxBri does not exist in the registry. This oligos was also transformed in the lab. || Bri
|-

| '''loxP reverse in pSB1A2''' || I had 5 successful colonies from this oligos ligation that were also confirmed by colony PCR. They will be sent off for sequencing. || [http://partsregistry.org/Part:BBa_K206013 loxP reverse] loxP reverse exists in the registry. We ordered this oligos and ligated it into pSB1A2 in the lab. || Bri
|-

| '''loxN Forward in pSB1A2''' || I had 5 successful colonies from this oligos ligation that were also confirmed by colony PCR. They are sent off for sequencing and four of them were confirmed to be correct. || [http://partsregistry.org/Part:BBa_K315007] loxN forward does not exist in the registry. We ordered the oligos and built it in the lab. || Anvi
|-

| '''loxN Reverse in pSB1A2''' || I had 3 successful colonies from this oligos ligation that were also confirmed by colony PCR. They are sent off for sequencing and two of them were confirmed to be correct. || [http://partsregistry.org/Part:BBa_K315011] loxN reverse does not exist in the registry. We ordered the oligos and built it in the lab. || Anvi
|-

|}
 
</center>

'''Testing Cre Activity''' 
<center>

 '''Green''' Part has been cloned and sequence verified; '''Red''' Part is under construction

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Final Construct
!width="30"|Current Status
!Registry Number and Link
!width="30"|Primary Team Member
|-
| '''I718008 (pBAD+RBS+cre) in pSB4K5''' || At this point, I have isolated both the insert and the plasmid, but my two attempts at ligation have not produced any colonies. || [http://partsregistry.org/Part:BBa_I718008 I718008] [http://partsregistry.org/wiki/index.php?title=Part:pSB4K5 pSB4K5] || Nitya
|-

| '''I718008 (pBAD+RBS+cre) in pSB3K3''' || At this point, I have ligated and transformed the cells but I am having trouble growing it in the LB + kan media. || [http://partsregistry.org/Part:BBa_I718008 I718008][http://partsregistry.org/wiki/index.php?title=Part:pSB3K5] describe intermediate || Anvi
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-
|}
</center>
 

'''pSBIA7 & pSBIA2'''

Data showing the varying levels of expression between pSBIA7 and pSBIA2

[[Image:curtiss3.jpg]]

IGEM 2010 Project

2010-06-28T19:18:29Z

Stmeador: /* Math Sub-Projects */

* [http://gcat.davidson.edu/GcatWiki/index.php/Davidson_Missouri_W/Davidson_Protocols Davidson Lab Protocols] 
* [http://gcat.davidson.edu/GcatWiki/index.php/Davidson_Missouri_W/MWSU_protocols MWSU Lab Protocols] 
* [http://gcat.davidson.edu/GCATalog GCAT-alog Freezer Stocks] 

== We need to start capturing what we are doing, and why. ==
Please use this page as a starting place.

We need an overall description of our project at the overview level as well as the subsections and phases of implementation.

== Math Sub-Projects ==

'''Counting Permutations'''

'''Improving Oligo Assembler'''
We adapted the lancelator (http://gcat.davidson.edu/IGEM06/oligo.html), a program created by Lance Harden as a part of the 2006 iGem team, so that it would execute faster and can handle longer sequences. The old program could only handle sequences of 300 bp or shorter. Also, the more oligos the program broke the sequence into, the longer it took to run, and for 8 or more the run time was simply unreasonable. However, for the sequences it could handle it always finds the optimal oligos to use.
Our program allows the user to enter a sequence of any length, and the length does not significantly effect runtime. In addition, we added extra features such as checking for and removing BioBrick restriction sites and adding BioBrick primers. While our program does not always find the optimal oligos, it still does very well which is an acceptable compromise because the runtime is improved so dramatically.

http://gcat.davidson.edu/iGem10/index.html

'''Paris IGEM 2007 Results'''

T r

19.5 40.16

20.5 39.61

25.5 36.76

30.5 33.78

35.5 30.66

40.5 27.39

45.5 23.97

50.5 20.39

55.5 16.64

This is a chart of the experimental group in the Paris IGEM 2007 project. I used the formula r=1-10^(.004*T)/2 where r is the recombination rate (how many times Cre makes a cut and a Scar site is formed) and T is the generation time in minutes (How long it takes the cell to divide).

== Biology Sub-Projects==

'''Codon Optimization''' 

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Segment
|'''Number of Base Pairs'''
|'''Wild Type Sequence'''
|'''Optimized Sequence'''
|'''Deoptimized Sequence'''
|-

| 1 || 141 || Atgaaatctaacaatgcgctcatcgtcatcctcggcaccgtcaccctggatgctgtaggcataggcttggttatgccggtactgccgggcctcttgcgggatatcgtccattccgacagcatcgccagtcactatggcgtg || ATGAAATCTAACAACGCGCTGATCGTTATCCTGGGTACCGTTACCCTGGACGCGGTTGGTATCGGTCTGGTTATGCCGGTTCTGCCGGGTCTGCTGCGTGACATCGTTCACTCTGACTCTATCGCGTCTCACTACGGTGTT || ATGAAGAGTAATAATGCCCTAATAGTCATACTAGGAACAGTCACACTAGATGCCGTCGGAATAGGACTCGTCATGCCCGTCCTACCCGGACTACTAAGGGATATAGTCCATAGTGATAGTATAGCCAGTCATTATGGAGTC
|-

| 2 || 138 || ctatatgcgttgatgcaatttctatgcgcacccgttctcggagcactgtccgaccgctttggccgccgcccagtcctgctcgcttcgctacttggagccactatcgactacgcgatcatggcgaccacacccgtcctg || CTGTACGCGCTGATGCAGTTCCTGTGCGCGCCGGTTCTGGGTGCGCTGTCTGACCGTTTCGGTCGTCGTCCGGTTCTGCTGGCGTCTCTGCTGGGTGCGACCATCGACTACGCGATCATGGCGACCACCCCGGTTCTG || CTATATGCCCTAATGCAATTTCTATGTGCCCCCGTCCTAGGAGCCCTAAGTGATAGGTTTGGAAGGAGGCCCGTCCTACTAGCCAGTCTACTAGGAGCCACAATAGATTATGCCATAATGGCCACAACACCCGTCCTA
|-

| 3 || 177 || tacgccggacgcatcgtggccggcatcaccggcgccacaggtgcggttgctggcgcctatatcgccgacatcaccgatggggaagatcgggctcgccacttcgggctcatgagcgcttgtttcggcgtgggtatggtggcaggccccgtggccgggggactgttgggcgccatctcc || TACGCGGGTCGTATCGTTGCGGGTATCACCGGTGCGACCGGTGCGGTTGCGGGTGCGTACATCGCGGACATCACCGACGGTGAAGACCGTGCGCGTCACTTCGGTCTGATGTCTGCGTGCTTCGGTGTTGGTATGGTTGCGGGTCCGGTTGCGGGTGGTCTGCTGGGTGCGATCTCT || TATGCCGGAAGGATAGTCGCCGGAATAACAGGAGCCACAGGAGCCGTCGCCGGAGCCTATATAGCCGATATAACAGATGGAGAGGATAGGGCCAGGCATTTTGGACTAATGAGTGCCTGTTTTGGAGTCGGAATGGTCGCCGGACCCGTCGCCGGAGGACTACTAGGAGCCATAAGT
|-

| 4 || 81 || ccattccttgcggcggcggtgctcaacggcctcaacctactactgggctgcttcctaatgcaggagtcgcataagggagag || CCGTTCCTGGCGGCGGCGGTTCTGAACGGTCTGAACCTGCTGCTGGGTTGCTTCCTGATGCAGGAATCTCACAAAGGTGAA || CCCTTTCTAGCCGCCGCCGTCCTAAATGGACTAAATCTACTACTAGGATGTTTTCTAATGCAAGAGAGTCATAAGGGAGAG
|-

|}

Note: All above segments have been optimized and deoptimized using the online [http://genomes.urv.es/OPTIMIZER/ Optimizer] program.

To create the optimized and deoptimized segments of the Tet A gene we used the sequence that the Optimizer program gave us and put it into the [http://gcat.davidson.edu/IGEM06/oligo.html Lancelator] a program created by Lance Harden as part of the 2006 iGEM team. After getting the recommended Oligo sequences from the Lancelator, we added necessary "sticky ends" that were compatible with the naturally occurring restriction enzyme sites that we discovered (see Restriction Enzymes below). At this time we have ordered Oligo parts for segments 1 and 2 of the Tet A gene. The Oligos that were ordered can be seen below.

'''Segment 1 Oligos'''

'''Optimized'''

top 1 5' AATTCGCGGCCGCTTCTAGATGAAATCTAACAACGCGCTGATCGTTATCCTGGGTACCG 3’

top 2 5' TTACCCTGGACGCGGTTGGTATCGGTCTGGTTATGCCGGTTCTGCCGGGTCTGCTGCGTGAC 3’

top 3 5' ATCGTTCACTCTGACTCTATCGCGTCTCACTACGGTGTTCTG 3’

bottom 2 5' CATAACCAGACCGATACCAACCGCGTCCAGGGTAACGGTAC
CCAGGATAACGATCAGCGCGTTGTTAGATTTCATCTAGAAGCGGCCGCG 3’

bottom 1 5' CTAGCAGAACACCGTAGTGAGACGCGATAGAGTCAGAGTGAACGATGTCACGCAGCAGACCCGGCAGAACCGG 3’

'''Deoptimized'''

top 1 5' AATTCGCGGCCGCTTCTAGATGAAGAGTAATAATGCCCTAATAGTCATACTAGGAACAG 3’

top 2 5' TCACACTAGATGCCGTCGGAATAGGACTCGTCATGCCCGTCCTACCCGGACTACTAAGGGA 3’

top 3 5' TATAGTCCATAGTGATAGTATAGCCAGTCATTATGGAGTCCTG 3’

bottom 2 5' GAGTCCTATTCCGACGGCATCTAGTGTGACTGTTCCTAGTATG
ACTATTAGGGCATTATTACTCTTCATCTAGAAGCGGCCGCG 3’

bottom 1 5' CTAGCAGGACTCCATAATGACTGGCTATACTATCACTATGGACTATATCCCTTAGTAGTCCGGGTAGGACGGGCATGAC 3’

'''Segment 2 Oligos'''

'''Optimized'''

top 1 5' CTAGCCTGTACGCGCTGATGCAGTTCCTGTGCGCGCCGGTTCTGGGTGCGCTGTCTGAC 3’

top 2 5' CGTTTCGGTCGTCGTCCGGTTCTGCTGGCGTCTCTGCTGGGTGCGACCATCGACTAC 3’

top 3 5' GCGATCATGGCGACCACCCCGGTTCTGTG 3’

bottom 1 5' GCGCACAGGAACTGCATCAGCGCGTACAGG 3’

bottom 2 5' CCAGCAGAACCGGACGACGACCGAAACGGTCAGACAGCGCACCCAGAACCGGC 3’

bottom 3 5' GATCCACAGAACCGGGGTGGTCGCCATGATCGCGTAGTCGATGGTCGCACCCAGCAGAGACG 3’

'''Deoptimized'''

top 1 5' CTAGCGCTATATGCCCTAATGCAATTTCTATGTGCCCCCGTCCTAGGAGCCCTAAGTG 3'

top 2 5' ATAGGTTTGGAAGGAGGCCCGTCCTACTAGCCAGTCTACTAGGAGCCACAATAGAT 3'

top 3 5' TATGCCATAATGGCCACAACACCCGTCCTATG 3'

bottom 1 5' GGCACATAGAAATTGCATTAGGGCATATAGCG 3' 

bottom 2 5' TAGGACGGGCCTCCTTCCAAACCTATCACTTAGGGCTCCTAGGACGGG 3' 

bottom 3 5' GATCCATAGGACGGGTGTTGTGGCCATTATGGCATAATCTATTGTGGCTCCTAGTAGACTGGCTAG 3'

[[Image:wiki3.jpg]]

'''Restriction Enzymes'''

To insert the annealed Oligo segments that were created we had to digest the Tet A gene using naturally occurring enzyme restriction sites that did not exist in the rest of the gene or in the plasmid (pSBIA2).

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Segment
|'''First Restriction Enzyme'''
|'''Second Restriction Enzyme'''
|-

| 1 || EcoRI || NheI
|-

| 2 || NheI || BamHI
|-

| 3 || BamHI || SphI
|-

| 4 || SphI || SalI
|-

|}

'''Parts Used (to be used)'''
{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Part
|'''Registry Link'''
|'''Construct Including Part'''
|-

| Tet A (tetracycline resistance gene) J31007 || [http://partsregistry.org/Part:BBa_J31007 Tet A (forward)] || promoter-RBS-RFP-RBS-TetA on pSBIA2
|-

| pLac-RBS-RFP I715039 || [http://partsregistry.org/Part:BBa_I715039 pLac-RBS-RFP ]|| Possibly: pLac-RBS-RFP-RBS-TetA on pSBIA2
|-

| pLac-RBS-RFP-RBS-TetA-TT on pSBIAK3 S04435 || [http://partsregistry.org/Part:BBa_S04435 pLac-RBS-RFP-RBS-TetA-TT]|| Possibly: pLac-RBS-RFP-RBS-TetA-TT on pSBIA2
|-

| Part Name and Registry Number || [http://partsregistry.org/Main_Page Registry Link]|| Construct
|-

| Part Name and Registry Number || [http://partsregistry.org/Main_Page Registry Link]|| Construct
|-
|}

'''Promoters'''

This chart shows flourescene levels of different promoter constructs with varying levels of IPTG added (error bars with standard error can be seen on the graph). Note: This experiment is still in progress. More data will be posted when available.

[[Image:wiki4.jpg]]

'''Tet-trations''' 

'''Making and Testing lox_ Sites'''
<center>
 '''Green''' Part has been cloned and sequence verified; '''Red''' Part is under construction

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Final Construct
!width="30"|Current Status
!Registry Number and Link
!width="30"|Primary Team Member
|-
| '''''lox5171'' Forward in pSB1A2''' || I got colonies on my second attempt. Once I isolate the plasmid, it will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] ''lox5171'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Nitya
|-

| '''''lox5171'' Reverse in pSB1A2''' || This plasmid will also be sent off for sequencing soon. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] ''lox5171'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Nitya
|-

| '''loxm2 Forward in pSB1A2''' || I ligated loxm2 F with the plasmid and have prepared the DNA for sequencing to confirm what is there. || [http://partsregistry.org/Part:BBa_K315004] ''loxm2'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Tom
|-

| '''loxm2 Reverse in pSB1A2''' || I ligated loxm2 F with the plasmid and have prepared the DNA for sequencing to confirm what is there. || [http://partsregistry.org/Part:BBa_K315005] ''loxm2'' does not exist in the registry. We ordered oligos and constructed the site in the lab. || Tom
|-

| '''loxBri forward in pSB1A2''' || 4 colonies grew with the correct sized insert from colony PCR verification and will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] loxBri does not exist in the registry. We ordered this oligos with 3 mutations and transformed in lab. || Bri
|-

| '''loxBri reverse in pSB1A2''' || I had 3 successful colonies from this oligos ligation that were also confirmed by colony PCR that will be sent off for sequencing. || [http://partsregistry.org/Part:pSB1A2 pSB1A2] loxBri does not exist in the registry. This oligos was also transformed in the lab. || Bri
|-

| '''loxP reverse in pSB1A2''' || I had 5 successful colonies from this oligos ligation that were also confirmed by colony PCR. They will be sent off for sequencing. || [http://partsregistry.org/Part:BBa_K206013 loxP reverse] loxP reverse exists in the registry. We ordered this oligos and ligated it into pSB1A2 in the lab. || Bri
|-

| '''loxN Forward in pSB1A2''' || I had 5 successful colonies from this oligos ligation that were also confirmed by colony PCR. They are sent off for sequencing and four of them were confirmed to be correct. || [http://partsregistry.org/Part:BBa_K315007] loxN forward does not exist in the registry. We ordered the oligos and built it in the lab. || Anvi
|-

| '''loxN Reverse in pSB1A2''' || I had 3 successful colonies from this oligos ligation that were also confirmed by colony PCR. They are sent off for sequencing and two of them were confirmed to be correct. || [http://partsregistry.org/Part:BBa_K315011] loxN reverse does not exist in the registry. We ordered the oligos and built it in the lab. || Anvi
|-

|}
 
</center>

'''Testing Cre Activity''' 
<center>

 '''Green''' Part has been cloned and sequence verified; '''Red''' Part is under construction

{| class="wikitable" style="text-align:center" border="1" cellpadding="2"
!Final Construct
!width="30"|Current Status
!Registry Number and Link
!width="30"|Primary Team Member
|-
| '''I718008 (pBAD+RBS+cre) in pSB4K5''' || At this point, I have isolated both the insert and the plasmid, but my two attempts at ligation have not produced any colonies. || [http://partsregistry.org/Part:BBa_I718008 I718008] [http://partsregistry.org/wiki/index.php?title=Part:pSB4K5 pSB4K5] || Nitya
|-

| '''I718008 (pBAD+RBS+cre) in pSB3K3''' || At this point, I have ligated and transformed the cells but I am having trouble growing it in the LB + kan media. || [http://partsregistry.org/Part:BBa_I718008 I718008][http://partsregistry.org/wiki/index.php?title=Part:pSB3K5] describe intermediate || Anvi
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-

| '''Insert Info Here''' || what is built so far? || [http://partsregistry.org/Part:BBa_K199000 change to correct link] describe intermediate || your name here
|-
|}
</center>
 

'''pSBIA7 & pSBIA2'''

Data showing the varying levels of expression between pSBIA7 and pSBIA2

[[Image:curtiss3.jpg]]