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Team:USTC-Software
From 2013.igem.org
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Description：
Synthetic biology has been working on transforming target organisms, which usually means integrating new genes with an available network to achieve a high expression level of certain compounds. Nevertheless, the new-integrated genes are always not the original parts of the target metabolic network, so it is hard to predict how the new genes will affect the network.
Our application aims to simulate genetic networks. The application analyzes the stability of genetic networks after introduction of exogenous genes. Meanwhile, given the original network and specific purposes, the application traces the regulative process back and gives possible regulative patterns.
[NAME]
[BASIC FUNCTION]
Our application aims to simulate genetic networks. The application analyzes the stability of genetic networks after introduction of exogenous genes. Meanwhile, given the specific purposes of the original network, the application traces the regulative process back and gives possible regulative patterns of new gene.
[APPROACH & METHODOLOGY]
The software is comprised of several modules as shown below: Introduction of modules:
(Hill’s Equation)
The simulation runs until the network is stable, which means the concentration of material in the network is basically constant. In order to compare the stability between the original network and the new one, the simulation of the original network will be done as well. More random numbers will be adopted as repeating the simulation.
Based on the data from simulation above, a stability score of each combination of coefficients will be calculated. Those scores are based on the cost of stable time and the difference of two network. After the topological analysis of those scores, an overall score will be given.
[PURPOSE & BACKGROUND]
Synthetic biology has been working on transforming target organisms, which usually means integrating new genes with an available network to achieve a high expression level of certain compounds. Nevertheless, the new-integrated genes are always not the original parts of the target metabolic network, so it is hard to predict how the new genes will affect the network. In some cases, new genes may even lead the network to a breakdown unexpected by wet lab experimenter. On the other hand, some wet lab experimenters also expect that target organisms could increase some original gene’s expression. As a reference to those experiment, our software put a virtual gene into the network and figure out its best regulation. To achieve wet lab’s purpose, experimenter could find a specific gene based on our prediction regulation. Lots of simulations of metabolic networks have been done with various methods. Most of them concentrate on the network itself and some of them analyze those network’s stability, robustness and Flux Balance Analysis (FBA).
[SIGNIFICANCE & INNOVATION]
The software provides a great model as a reference before wet lab experiments. It provides suggestions on both specific practicality and input of exogenous gene. Meanwhile, the software is comprised of separate modules, which can be customized for different database and optimized as the amount of users grows. Previously, we could not find any specific work on the simulation and analysis of the newly introduced genes’ impact on regulation networks, and also those softwares were unavailable, which makes our software an innovation in the field. Algorithmically, the software aims to complete the simulation based on a small amount of lab data as possible.
Console
Console is where you manage heavy computing and complex tasks. With different buttons controlling each parameter, you can optimize the behaviors of the software. We applied evolution algorithm and machine learning techniques in the network inferences to provide the best simulation of your data.
Sand Box
SandBox displays the Genetic Regulatory Networks in a clean and interactive way, with clear connection and 3-D interaction, you will get better understanding of how genes and proteins regulating each other.
