INRIA Paris-Rocquencourt, Le Chesnay, France.
Bioinformatics. 2010 Sep 15;26(18):i603-10. doi: 10.1093/bioinformatics/btq387.
Investigating the relation between the structure and behavior of complex biological networks often involves posing the question if the hypothesized structure of a regulatory network is consistent with the observed behavior, or if a proposed structure can generate a desired behavior.
The above questions can be cast into a parameter search problem for qualitative models of regulatory networks. We develop a method based on symbolic model checking that avoids enumerating all possible parametrizations, and show that this method performs well on real biological problems, using the IRMA synthetic network and benchmark datasets. We test the consistency between IRMA and time-series expression profiles, and search for parameter modifications that would make the external control of the system behavior more robust.
GNA and the IRMA model are available at http://ibis.inrialpes.fr/.
研究复杂生物网络的结构和行为之间的关系，通常需要提出以下问题：假设的调控网络结构是否与观察到的行为一致，或者提出的结构是否可以产生所需的行为。
上述问题可以转化为调控网络定性模型的参数搜索问题。我们开发了一种基于符号模型检查的方法，该方法避免了枚举所有可能的参数化，并使用 IRMA 合成网络和基准数据集表明，该方法在真实的生物学问题上表现良好。我们测试了 IRMA 与时间序列表达谱之间的一致性，并搜索了使系统行为的外部控制更稳健的参数修改。
GNA 和 IRMA 模型可在 http://ibis.inrialpes.fr/ 获得。
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