Revision as of 16:19, 21 October 2010

Interworking: Engineering & Biology

Schematical overview of the connection between biology and computer science. Wet laboratory provided mathematical modeling and information processing with experimental data and knowledge, while mathematical modeling supported the other two with parameter evaluation. Information processing provided wet laboratory with experimental validation of the biological implementation and used the combined mathematical model as test bench.

E. lemming is a special project, because the final product has biological and engineering aspects in equal parts. For this reason, it was decided to connect the wet laboratory and the modeling subteam closely from the very beginning to make the best decisions for the whole project. This process is called interworking: multiple parts interact with each other to create a comprehensive result.

Wet Laboratory: Experimental data

Bacterial movement

Besides its theoretical importance of closing the modeling loop of our system, the Movement Model also brings together biological and theoretical results, by the in - silico reproduction of the in - vivo observed data.

All the parameters of our model are based on statistical estimates of the biologically observed Chemotaxis behavior. Furthermore, by fixing the parameters for which the biological evidence supports independence, the model is accurately estimating the remaining set of parameters, providing us with reliable biological feedback & novel insights.

In this way, the wetlab team received the modeler's input on the predicted final behavior of our E.lemming, which served as a further input in tuning the design of the wetlab experiments.

Cell detection

<<< how did experimental data (E. coli) help to create cell detection? write about this here. >>>

Mathematical Modeling: Parameter evaluation

Objective function for parameter evaluation. Evaluation to achieve modeling insights relies on optimization of the relative amplitude of the regulating protein for the tumbling / directed movement ratio.

Modeling insights for wet laboratory

Mathematical modeling of biological pathways should never be an end in itself. Instead, mathematical models should be build to give insights into the pathway of interest, which are otherwise hard to obtain, or to speed up experimental work. In this project, a molecular setup for implementation by the wet laboratory was evaluated and resulted in an effort alleviating priority list of BioBrick candidates. Experimental Design: Insights for wet laboratory provide more information about this topic.

**Table 1: Evaluation results for wet laboratory**
Che	LSP1	LSP2	[Asp]	[AP]	[anchor]
CheY	PIF3	PhyB	10^-6 uM	40 uM	50 uM

Modeling insights for information processing

Furthermore, the combined model was used to estimate the reaction time of the network on the red and far-red light pulses and the optimal configuration of the light pulse setup, crucial for the controller design. See Experimental Design: Insights for information processing for more details.

**Table 2: Evaluation results for information processing**
model	tc RL	tc FRL
Spiro et al.	0.2200s	0.3485s
Mello & Tu	0.1380s	0.3205s

@@ Line 23: / Line 23: @@
 === Modeling insights for wet laboratory ===
-Mathematical modeling of biological pathways should never be an end in itself. Instead, mathematical models should be build to give insights into the pathway of interest, which are otherwise hard to obtain, or to speed up experimental work. In this project, a molecular setup for implementation by the wet laboratory was evaluated and resulted in an effort alleviating priority list of BioBrick candidates. [[Team:ETHZ_Basel/Modeling/Evaluation#Insights_for_wet_laboratory|'''Parameter Evaluation: Insights for wet laboratory''']] provide more information about this topic.
+Mathematical modeling of biological pathways should never be an end in itself. Instead, mathematical models should be build to give insights into the pathway of interest, which are otherwise hard to obtain, or to speed up experimental work. In this project, a molecular setup for implementation by the wet laboratory was evaluated and resulted in an effort alleviating priority list of BioBrick candidates. [[Team:ETHZ_Basel/Modeling/Experimental_Design#Insights_for_wet_laboratory|'''Experimental Design: Insights for wet laboratory''']] provide more information about this topic.
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@@ Line 33: / Line 33: @@
 === Modeling insights for information processing ===
-Furthermore, the combined model was used to estimate the reaction time of the network on the red and far-red light pulses and the optimal configuration of the light pulse setup, crucial for the controller design. See [[Team:ETHZ_Basel/Modeling/Evaluation#Insights_for_information processing|'''Parameter Evaluation: Insights for information processing''']] for more details.
+Furthermore, the combined model was used to estimate the reaction time of the network on the red and far-red light pulses and the optimal configuration of the light pulse setup, crucial for the controller design. See [[Team:ETHZ_Basel/Modeling/Experimental_Design#Insights_for_information processing|'''Experimental Design: Insights for information processing''']] for more details.
 {| border="1" align="center"

Team:ETHZ Basel/Achievements/Systems Design

From 2010.igem.org