Ranking Genes by Their Co-expression to Subsets of Pathway Members
Ranking Genes by Their Co-expression to Subsets of Pathway Members
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DOI：
10.1111/j.1749-6632.2008.03747.x
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发表时间：
2009-01-01
期刊：
影响因子：
--
通讯作者：
Vilo, Jaak
中科院分区：
文献类型：
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作者：
Adler, Priit;Peterson, Hedi;Vilo, Jaak
细胞过程经常进行。基因和蛋白质相互作用的复杂系统。其中一些系统在通路数据库中得到了很好的研究和描述，而大多数基因的作用和功能却知之甚少。一个大型的公共微阵列数据纲要是可用的，涵盖了各种条件，样品和组织，并提供了丰富的基因组规模的信息来源。我们的研究重点是在各种生物条件下基因共表达的背景下分析35种策划的生物途径。通过为每个基因和通路定义一个全局共表达相似性排名，我们使用相应通路的其他成员作为参考，进行穷举留一法计算来描述现有通路成员。我们证明，虽然成功地恢复生物基础过程，如其代谢和翻译，全球相关性措施未能检测到基因成员的信号转导通路中的共表达是不太明显。我们的研究结果还表明，通路成员检测是更有效的，当只使用一个子集的相应的通路成员作为参考，支持存在更紧密的共表达的基因子集内的途径。我们的研究评估了全球基因表达相关性措施在重建各种功能和特异性的生物系统中的预测能力。所开发的计算网络在检测可疑通路成员和预测新成员候选人方面具有直接的应用。
Cellular processes are often carried out. by intricate systems of interacting genes and proteins. Some of these systems are rather well studied and described in pathway databases, while the roles and functions of the majority of genes are poorly understood. A large compendium of public microarray data is available that covers it variety of conditions, sample, and tissues and provides a rich source for genome-scale information. We focus our study oil the analysis of 35 curated biological pathways in the context of gene co-expression over a large variety of biological conditions. By defining a global co-expression similarity rank for each gene and pathway, we perform exhaustive leave-one-out computations to describe existing pathway memberships using other members of the corresponding pathway as reference. We demonstrate that while successful in recovering biological base processes such its metabolism and translation, the global correlation measure fails to detect gene memberships in signaling pathways where co-expression is less evident. Our results also show that pathway membership detection is more effective when using only a subset of corresponding pathway members as reference, supporting the existence of more tightly co-expressed subsets of genes within pathways. Our study assesses the predictive power of global gene expression correlation measures in reconstructing biological systems of various functions and specificity. The developed computational network has immediate applications in detecting dubious pathway members and predicting novel member candidates.