Team:ETHZ Basel/InformationProcessing

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Although the synthetic network we implemented makes the tumbling frequency of an E. coli cells dependent on red and far-red light, the biological part alone is not sufficient to control the swimming direction of the E. lemming. Thus, it is complemented by an 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. The interface between the two sub-networks, the genetic 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). 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.
Although the synthetic network we implemented makes the tumbling frequency of an E. coli cells dependent on red and far-red light, the biological part alone is not sufficient to control the swimming direction of the E. lemming. Thus, it is complemented by an 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. The interface between the two sub-networks, the genetic 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). 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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In this section we will describe in detail the in-silico part of the network. For the in-vivo part, we refer to [[Team:ETHZ_Basel/Biology]]
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In this section we will describe in detail the in-silico part of the network. For the in-vivo part, we refer to the [[Team:ETHZ_Basel/Biology | Biology & Wet Laboratory]] section.

Revision as of 18:16, 14 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. This means that E. coli tumbling is induced or suppressed simply by pressing a light switch! This synthetic network enables control of single E. coli cells.
Although the synthetic network we implemented makes the tumbling frequency of an E. coli cells dependent on red and far-red light, the biological part alone is not sufficient to control the swimming direction of the E. lemming. Thus, it is complemented by an 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. The interface between the two sub-networks, the genetic 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). 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.

In this section we will describe in detail the in-silico part of the network. For the in-vivo part, we refer to the Biology & Wet Laboratory section.

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