Mohammadi Shahin, Kollias Giorgos, Grama Ananth
Department of Computer Science, Purdue University, West Lafayette, IN 47906, USA.
Pac Symp Biocomput. 2012:43-54.
Synthetic genetic interactions reveal buffering mechanisms in the cell against genetic perturbations. These interactions have been widely used by researchers to predict functional similarity of gene pairs. In this paper, we perform a comprehensive evaluation of various methods for predicting co-pathway membership of genes based on their neighborhood similarity in the genetic network. We clearly delineate the scope of these methods and use it to motivate a rigorous statistical framework for quantifying the contribution of each pathway to the functional similarity of gene pairs. We then use our model to infer interdependencies among KEGG pathways. The resulting KEGG crosstalk map yields significant insights into the high-level organization of the genetic network and is used to explain the effective scope of genetic interactions for predicting co-pathway membership of gene pairs. A direct byproduct of this effort is that we are able to identify subsets of genes in each pathway that act as 'ports' for interaction across pathways.
合成遗传相互作用揭示了细胞中针对遗传扰动的缓冲机制。这些相互作用已被研究人员广泛用于预测基因对的功能相似性。在本文中,我们基于基因在遗传网络中的邻域相似性,对各种预测基因共通路成员关系的方法进行了全面评估。我们明确划定了这些方法的适用范围,并以此推动建立一个严格的统计框架,用于量化每条通路对基因对功能相似性的贡献。然后,我们使用我们的模型来推断KEGG通路之间的相互依赖性。由此产生的KEGG串扰图为遗传网络的高级组织提供了重要见解,并用于解释遗传相互作用在预测基因对共通路成员关系方面的有效范围。这项工作的一个直接副产品是,我们能够识别每条通路中作为跨通路相互作用“端口”的基因子集。