Mitra et al. Integrative approaches for finding modular structure in biological networks. Nat Rev Genet 2013, 14:719-732.
http://www.nature.com/nrg/journal/v14/n10/abs/nrg3552.html

Abstract: A central goal of systems biology is to elucidate the structural and functional architecture of the cell. To this end, large and complex networks of molecular interactions are being rapidly generated for humans and model organisms. A recent focus of bioinformatics research has been to integrate these networks with each other and with diverse molecular profiles to identify sets of molecules and interactions that participate in a common biological function — that is, 'modules'. Here, we classify such integrative approaches into four broad categories, describe their bioinformatic principles and review their applications.

文中将模块识别的研究分成了：活跃子网（通过定义活跃度分数或通过聚类分析）、在进化中保守子网（主要通过网络比对）和差异网络（即在不同条件下动态相互作用发生变化的边）三类。文中也提到了我们自主开发的基于聚类的活跃子网识别算法ClustEx（正在开发基于密度聚类的2.0版本）。

众多的功能学和数据分析表明，生物网络呈现明显的模块性，即一组基因协同调控某一生物表型，现在的基于模块的研究主要用于理解生物过程/疾病的分子机理。陈洛南研究小组关于critical transition states和dynamic network biomarkers的研究也表明当复杂系统处于状态转换的过程中，会出现一组强烈相互关联且强烈变化的基因子网。

“模块”的思想在研究生物网络的分子机理方面取得了一些成果，但尚少见利用类似思想探讨生物网络的状态调控。相信基于模块思想的多靶点干预策略即将得到更多的关注和重视。