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This article is part of the supplement: BioSysBio 2007: Systems Biology, Bioinformatics, Synthetic Biology

Open Access Poster presentation

Modeling the arsenic biosensor system

Yizhi Cai1*, Bryony Davidson2, Hongwu Ma3 and Chris French4

Author Affiliations

1 Virginia Bioinformatics Institute, Virginia Tech, the University of Edinburgh, UK

2 School of Engineering, the University of Edinburgh, UK

3 School of Informatics, the University of Edinburgh, UK

4 School of Biology, the University of Edinburgh, UK

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BMC Systems Biology 2007, 1(Suppl 1):P83  doi:10.1186/1752-0509-1-S1-P83

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1752-0509/1/S1/P83


Published:8 May 2007

© 2007 Cai et al; licensee BioMed Central Ltd.

Poster presentation

This paper reports the modeling part of an arsenic biosensor system, which was the iGEM project accomplished in the University of Edinburgh 2006. The arsenic biosensor system sought to address the fatal water pollution problem occurring in many poor countries/areas like Bangladesh by producing calibratable pH changes in response to a range of arsenic concentrations. An ODE based computational model which contains 3 operons, 19 reactions and 17 species has been constructed in order to shed light on the wet-lab experimental design. The model showed good induction of urease and repression of lacZ in the absence of arsenate, and repression of urease and induction of lacZ at high arsenate levels. By analyzing the sensitivity of each parameter/species, we identified their relative importance in the system which gives the theoretical guide when measuring the variable in wet-lab.