Predicting protein complex membership using probabilistic network reliability
Predicting protein complex membership using probabilistic network reliability
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DOI：
10.1101/gr.2203804
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发表时间：
2004-06-01
期刊：
影响因子：
7
通讯作者：
Roth, FP
中科院分区：
文献类型：
--
作者：
Asthana, S;King, OD;Roth, FP
越来越多的小规模和大规模研究提供了特定蛋白质-蛋白质相互作用的证据，并且可以被视为一个网络。以前已经注意到，在大规模研究中，错误是频繁的，错误频率取决于所使用的大规模方法。尽管知道交互证据的易错性，但该网络中的边缘（连接）通常被视为存在或不存在。然而，使用考虑支持证据的数量和质量的概率网络应该改善来自蛋白质网络的推断。在这里，我们展示了推理的成员在一个部分已知的蛋白质复合物，通过使用概率网络模型和以前用于评估通信网络的可靠性的算法。
Evidence for specific protein-protein interactions is increasingly available from both small- and large-scale studies, and can be viewed as a network. It has previously been noted that errors are frequent among large-scale studies, and that error frequency depends on the large-scale method used. Despite knowledge of the error-prone nature of interaction evidence, edges (connections) in this network are typically viewed as either present or absent. However, use of a probabilistic network that considers quantity and quality of supporting evidence should improve inference derived from protein networks. Here we demonstrate inference of membership in a partially known protein complex by using a probabilistic network model and an algorithm previously used to evaluate reliability in communication networks.