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原文連結
論文資訊
- 類型：已發表論文
- 日期：2013-05-28
摘要
Predictive dynamical models are critical for the analysis of complex 生物 systems. However, methods to systematically develop and discriminate among systems biology models are still lacking. We describe a 計算 method that incorporates all hypothetical mechanisms about the architecture of a 生物 system into a single model and automatically generates a set of simpler models compatible with observational data. As a proof of principle, we analyzed the dynamic control of the transcription factor Msn2 in Saccharomyces cerevisiae, specifically the short-term mechanisms mediating the cells' recovery after release from starvation stress. Our method determined that 12 of 192 possible models were compatible with available Msn2 localization data. Iterations between model predictions and rationally designed
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