The role of indirect connections in gene networks in predicting function
The role of indirect connections in gene networks in predicting function
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DOI：
10.1093/bioinformatics/btr288
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发表时间：
2011-07-01
期刊：
影响因子：
5.8
通讯作者：
Pavlidis, Paul
中科院分区：
文献类型：
--
作者：
Gillis, Jesse;Pavlidis, Paul
动机：基因网络已被广泛用于基因功能预测算法，许多基于复杂的扩展的“内疚协会”的原则。我们试图提供一个统一的解释基因功能预测算法的性能，在利用网络结构，从而简化未来的analysis.Results：我们使用共表达网络表明，大多数利用网络结构简单地重建原始的相关矩阵，从中获得的共表达网络。我们表明，同样的原理在蛋白质相互作用网络中预测基因功能，这些方法执行更复杂的基因功能预测算法。
Motivation: Gene networks have been used widely in gene function prediction algorithms, many based on complex extensions of the 'guilt by association' principle. We sought to provide a unified explanation for the performance of gene function prediction algorithms in exploiting network structure and thereby simplify future analysis.Results: We use co-expression networks to show that most exploited network structure simply reconstructs the original correlation matrices from which the co-expression network was obtained. We show the same principle works in predicting gene function in protein interaction networks and that these methods perform comparably to much more sophisticated gene function prediction algorithms.