Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan.
BMC Bioinformatics. 2011 Jul 12;12:281. doi: 10.1186/1471-2105-12-281.
Identifying key components in biological processes and their associations is critical for deciphering cellular functions. Recently, numerous gene expression and molecular interaction experiments have been reported in Saccharomyces cerevisiae, and these have enabled systematic studies. Although a number of approaches have been used to predict gene functions and interactions, tools that analyze the essential coordination of functional components in cellular processes still need to be developed.
In this work, we present a new approach to study the cooperation of functional modules (sets of functionally related genes) in a specific cellular process. A cooperative module pair is defined as two modules that significantly cooperate with certain functional genes in a cellular process. This method identifies cooperative module pairs that significantly influence a cellular process and the correlated genes and interactions that are essential to that process. Using the yeast cell cycle as an example, we identified 101 cooperative module associations among 82 modules, and importantly, we established a cell cycle-specific cooperative module network. Most of the identified module pairs cover cooperative pathways and components essential to the cell cycle. We found that 14, 36, 18, 15, and 20 cooperative module pairs significantly cooperate with genes regulated in early G1, late G1, S, G2, and M phase, respectively. Fifty-nine module pairs that correlate with Cdc28 and other essential regulators were also identified. These results are consistent with previous studies and demonstrate that our methodology is effective for studying cooperative mechanisms in the cell cycle.
In this work, we propose a new approach to identifying condition-related cooperative interactions, and importantly, we establish a cell cycle-specific cooperation module network. These results provide a global view of the cell cycle and the method can be used to discover the dynamic coordination properties of functional components in other cellular processes.
识别生物过程中的关键组件及其相互关系对于破译细胞功能至关重要。最近，在酿酒酵母中报告了大量的基因表达和分子相互作用实验，这些实验使系统研究成为可能。尽管已经使用了许多方法来预测基因功能和相互作用，但仍需要开发分析细胞过程中功能组件基本协调的工具。
在这项工作中，我们提出了一种新的方法来研究特定细胞过程中功能模块（功能相关基因集）的协作。协同模块对定义为在细胞过程中与某些功能基因显著协作的两个模块。该方法可识别显著影响细胞过程以及该过程所必需的相关基因和相互作用的协同模块对。以酵母细胞周期为例，我们在 82 个模块中鉴定出 101 对协同模块关联，重要的是，我们建立了一个细胞周期特异性协同模块网络。大多数鉴定出的模块对涵盖了对细胞周期至关重要的协同途径和组件。我们发现，14、36、18、15 和 20 对协同模块对分别与早期 G1、晚期 G1、S、G2 和 M 期调节的基因显著协作。还鉴定出了 59 对与 Cdc28 和其他必需调节剂相关的模块对。这些结果与之前的研究一致，表明我们的方法对于研究细胞周期中的协作机制是有效的。
在这项工作中，我们提出了一种识别与条件相关的协同相互作用的新方法，重要的是，我们建立了一个细胞周期特异性的协同模块网络。这些结果提供了细胞周期的全局视图，并且该方法可用于发现其他细胞过程中功能组件的动态协调特性。
