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Team:USTC-Software
From 2011.igem.org
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<span lang="EN-US" xml:lang="EN-US">Our project this year is named Lachesis, which consists of the following</span> | <span lang="EN-US" xml:lang="EN-US">Our project this year is named Lachesis, which consists of the following</span> | ||
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| - | + | 1.Automatic generation of biological reaction network simply from biobrick assemblys.<br/> | |
| - | + | 2.Data exchange,Reaction network visualization.<br/> | |
| - | + | 3.Automatic parameter fitting of a mathematical model for a desired behavior, according to experiment data or hand drawn curves using evolution algorithm.<br/> | |
| - | + | 4.Evaluation of the workablility or robustness of a biological reaction network using pca and entropy.<br/> | |
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Latest revision as of 12:42, 27 October 2011
USTC-Software
Lachesis
Team
Our team is formed of a group of diligent students coming from various departments of USTC. In the School of Life Sciences, we devoted our perspirations to this project for nearly a year.
Models
Biological reaction networks, even small ones, contain a lot of species and reactions and, thus, are hard to build by hand. Our rule-based modeling approach aims at freeing human from such labor.
Human practice
We conducted a survey, during the National Science Week, to discover USTC students' opinion on Synthetic Biology.
Project
Our project this year is named Lachesis, which consists of the following
1.Automatic generation of biological reaction network simply from biobrick assemblys.
2.Data exchange,Reaction network visualization.
3.Automatic parameter fitting of a mathematical model for a desired behavior, according to experiment data or hand drawn curves using evolution algorithm.
4.Evaluation of the workablility or robustness of a biological reaction network using pca and entropy.
2.Data exchange,Reaction network visualization.
3.Automatic parameter fitting of a mathematical model for a desired behavior, according to experiment data or hand drawn curves using evolution algorithm.
4.Evaluation of the workablility or robustness of a biological reaction network using pca and entropy.
Sponsers
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Vistor
