Team:ETHZ Basel/InformationProcessing

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= Information Processing Overview =
= Information Processing Overview =
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<iframe title="YouTube video player" class="youtube-player" type="text/html" width="425" height="349" src="http://www.youtube.com/embed/1qQBmMcMZDI?hd=1" frameborder="0"></iframe>
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<iframe title="YouTube video player" class="youtube-player" type="text/html" width="400" height="325" src="http://www.youtube.com/embed/DmglULaxNrY?hd=1" frameborder="0"></iframe>
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<div class="thumbcaption"><div class="magnify"><a href="http://www.youtube.com/watch?v=1qQBmMcMZDI?hd=1" class="external" title="Enlarge"><img src="/wiki/skins/common/images/magnify-clip.png" width="15" height="11" alt="" /></a></div><b>Information processing principle of E. lemming.</b> Tumbling / directed movement rates are monitored by image processing algorithms, which are linked to the light-pulse generator. This means that <i>E. coli</i> tumbling is induced or suppressed simply by pressing a light switch! This synthetic network enables control of single <i>E. coli</i> cells.</div></div></div>
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<div class="thumbcaption"><div class="magnify"><a href="http://www.youtube.com/watch?v=DmglULaxNrY?hd=1" class="external" title="Enlarge"><img src="/wiki/skins/common/images/magnify-clip.png" width="15" height="11" alt="" /></a></div><b>Information processing principle of E. lemming.</b> Tumbling / directed movement rates are monitored by image processing algorithms, which are linked to the light-pulse generator. Therefore, <i>E. coli</i> tumbling is induced or suppressed simply by pressing a light switch. This synthetic network enables control of single E. lemming cells.</div></div></div>
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Although the synthetic network we implemented makes the tumbling frequency of ''E. coli'' cells dependent on red and far-red light, the biological part alone is not sufficient to control the swimming direction of E.lemming. Thus, it is complemented by a complex ''in-silico'' network realizing a controller which automatically sends the light signals and, by thus time-dependently changing the tumbling frequency, forces the cell to swim in a desired direction.
 
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The interface between the two sub-networks, the ''in-vivo'' network and the ''in-silico'' network, is defined as the current microscope image (''in-vivo'' -> ''in-silico'') and the red and far-red light signals (''in-silico'' -> ''in-vivo'').  
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Although the synthetic network we implemented makes the tumbling frequency of ''E. coli'' cells dependent on red and far-red light, the [[Team:ETHZ_Basel/Biology | '''biological part''']] alone is not sufficient to control the swimming direction of E. lemming. Thus, it is complemented by a complex ''in silico'' setup centered around a controller which guides the cell towards the desired destination.
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By interconnecting both sub-networks, we thus can close the loop and obtain the overall network, which allows us to increase the information processing capabilities significantly compared to traditional synthetic networks completely realized ''in-vivo''.
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E. Lemming cells are imaged using [[Team:ETHZ_Basel/InformationProcessing/Microscope|'''microscopy techniques''']]. The resulting images are processed by fast [[Team:ETHZ_Basel/InformationProcessing/CellDetection|'''cell detection and cell tracking algorithms''']], that determine the current movement direction & trajectory of the chosen bacterium. The desired reference direction which is clearly [[Team:ETHZ_Basel/InformationProcessing/Visualization|'''visualized''']] is set by the input of the user, which is translated by the [[Team:ETHZ_Basel/InformationProcessing/Controller|'''the controller algorithm''']] into series of light pulses (red light and far-red light) that would lead E. lemming towards the right destination. Therefore, by the changing the tumbling frequency, the cell is forced to swim in a desired direction in real time.
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This section is meant to describe in detail the ''in-silico'' part of the overall network. For the ''in-vivo'' part, please refer to the [[Team:ETHZ_Basel/Biology | Biology & Wet Laboratory]] section.<br clear="all" />
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To demonstrate parts of the information processing pipeline, the sidekick <br>[[Team:ETHZ_Basel/InformationProcessing/Game|'''E. lemming 2D Game''']] was created, which is built using the capabilities of our very own [[Team:ETHZ_Basel/Achievements/Matlab_Toolbox|'''Matlab Toolbox (Lemming Toolbox)''']].
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== [https://2010.igem.org/Team:ETHZ_Basel/InformationProcessing/Microscope| Imaging] ==
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The cells are placed in a 50 &mu;m (?) high flow channel restricting their movement to the x/y-plane, thus preventing them from swimming out of focus. They are imaged in bright field by an automatized microscope with 40x magnification approximately every 0.3s. The image is send via a local network or the Internet to the controller workstation, which forwards them to Matlab/Simulink.
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== [https://2010.igem.org/Team:ETHZ_Basel/InformationProcessing/CellDetection| Cell detection and Cell tracking] ==
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In the controller workstation, the images are pre-processed by the Lemming Toolbox and the cells are detected and tracked in real-time, by means of fast image processing algorithms developed by our team. From the change of position between the microscope frames, the current direction of E.lemming is estimated. 
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== User experience  ==
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The Toolbox is connected to either a joystick or a keyboard with which the user can choose the cell he/she wants to control and interactively define the reference direction for the E.lemming in real time.
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== [https://2010.igem.org/Team:ETHZ_Basel/InformationProcessing/Controller| Controller] ==
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For controlling E. lemming, our modeling group implemented five different control algorithms, based on the same template. The actual direction of E.lemming, together with the desired direction set by the user and the time-point of the simulation form the inputs of the algorithms, while boolean values for red light and far-red light represent the outputs.
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Based on original combinations of error minimization, hysteresis, noise suppression and predictions, our algorithms decide when to send red or far-red light. This decision is then send back through the network to the microscope computer, which activates or deactivates the respective diodes, thus closing the loop between the in-silico and in-vivo part of the network.
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Furthermore the controller detects if a cell is swimming out of the field of vision of the microscope and automatically adjusts the position of the x/y-stage.
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== [https://2010.igem.org/Team:ETHZ_Basel/InformationProcessing/Visualization| Visualization] ==
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Finally, the microscope image is post-processed to show the position of all cells, the selected cell and its current and reference direction, and visualized on the computer screen or with a beamer.
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Latest revision as of 22:45, 27 October 2010

Information Processing Overview

Information processing principle of E. lemming. Tumbling / directed movement rates are monitored by image processing algorithms, which are linked to the light-pulse generator. Therefore, E. coli tumbling is induced or suppressed simply by pressing a light switch. This synthetic network enables control of single E. lemming cells.

Although the synthetic network we implemented makes the tumbling frequency of E. coli cells dependent on red and far-red light, the biological part alone is not sufficient to control the swimming direction of E. lemming. Thus, it is complemented by a complex in silico setup centered around a controller which guides the cell towards the desired destination.

E. Lemming cells are imaged using microscopy techniques. The resulting images are processed by fast cell detection and cell tracking algorithms, that determine the current movement direction & trajectory of the chosen bacterium. The desired reference direction which is clearly visualized is set by the input of the user, which is translated by the the controller algorithm into series of light pulses (red light and far-red light) that would lead E. lemming towards the right destination. Therefore, by the changing the tumbling frequency, the cell is forced to swim in a desired direction in real time.

To demonstrate parts of the information processing pipeline, the sidekick
E. lemming 2D Game was created, which is built using the capabilities of our very own Matlab Toolbox (Lemming Toolbox).