Algorithms for discriminating between biochemical reaction network models: Towards systematic experimental design

We develop a methodology for distinguishing between biochemical reaction network models for biological systems modeled by nonlinear ordinary differential equations. We show how to choose the 'best' initial condition direction (the dependent variables, the state) so as to maximize the discr...

詳細記述

書誌詳細
主要な著者: Papachristodoulou, A, El-Samad, H, IEEE
フォーマット: Conference item
出版事項: 2007
その他の書誌記述
要約:We develop a methodology for distinguishing between biochemical reaction network models for biological systems modeled by nonlinear ordinary differential equations. We show how to choose the 'best' initial condition direction (the dependent variables, the state) so as to maximize the discrepancy between the outputs of possible network models. This information could then be used to design new experiments with the hope that some of the networks would be invalidated from experimental data. The methodology is applied to discriminate between models of the network underlying chemoattractant-induced movement of Dictyostelium cells. © 2007 IEEE.