Identifying responsive modules by mathematical programming: an application to budding yeast cell cycle.
Identifying responsive modules by mathematical programming: an application to budding yeast cell cycle.
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通过数学编程识别响应模块：在出芽酵母细胞周期中的应用
DOI：
10.1371/journal.pone.0041854
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Chen L
中科院分区：
文献类型：
--
作者：
Wen Z;Liu ZP;Yan Y;Piao G;Liu Z;Wu J;Chen L
高通量生物数据为充分描述生物过程提供了前所未有的机会。然而，如何从这些数据集中提取有意义的生物信息是一个重大的挑战。最近，基于通路的分析在识别某些表型的生物标记物方面取得了很大进展。然而，这些所谓的基于途径的方法主要是基于单个基因或基于分子复合体的分析。在本文中，我们提出了一种新的基于模块的方法，通过整合基因表达数据和蛋白质-蛋白质相互作用网络来揭示网络模块与生物表型之间的因果关系或依赖关系。具体地说，我们首先通过利用表型差异将生物表型背后的反应模块的识别问题描述为一个数学规划模型，这也可以看作是一个多分类问题。然后，我们将其应用于基于生物学实验的微阵列数据研究发芽酵母的细胞周期过程，并针对细胞周期过程的不同阶段确定了重要的基于表型和过渡的响应模块。由此产生的响应模块从网络的角度为细胞周期过程的调控机制提供了新的见解。此外，过渡模的识别为在功能模块水平上研究动态过程提供了一种新的途径。特别是，我们发现一个著名的模块和两个新的模块的功能障碍可能直接导致细胞周期停滞在S期。除了我们的生物学实验，识别出的响应模块也被两个独立的芽期酵母细胞周期数据集所验证。
High-throughput biological data offer an unprecedented opportunity to fully characterize biological processes. However, how to extract meaningful biological information from these datasets is a significant challenge. Recently, pathway-based analysis has gained much progress in identifying biomarkers for some phenotypes. Nevertheless, these so-called pathway-based methods are mainly individual-gene-based or molecule-complex-based analyses. In this paper, we developed a novel module-based method to reveal causal or dependent relations between network modules and biological phenotypes by integrating both gene expression data and protein-protein interaction network. Specifically, we first formulated the identification problem of the responsive modules underlying biological phenotypes as a mathematical programming model by exploiting phenotype difference, which can also be viewed as a multi-classification problem. Then, we applied it to study cell-cycle process of budding yeast from microarray data based on our biological experiments, and identified important phenotype- and transition-based responsive modules for different stages of cell-cycle process. The resulting responsive modules provide new insight into the regulation mechanisms of cell-cycle process from a network viewpoint. Moreover, the identification of transition modules provides a new way to study dynamical processes at a functional module level. In particular, we found that the dysfunction of a well-known module and two new modules may directly result in cell cycle arresting at S phase. In addition to our biological experiments, the identified responsive modules were also validated by two independent datasets on budding yeast cell cycle.
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影响因子：
14.9
作者：
Güldener U;Münsterkötter M;Oesterheld M;Pagel P;Ruepp A;Mewes HW;Stümpflen V
通讯作者：
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作者：
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通讯作者：
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影响因子：
64.8
作者：
Alizadeh, AA;Eisen, MB;Staudt, LM
通讯作者：
Staudt, LM