Global networks of functional coupling in eukaryotes from comprehensive data integration
Global networks of functional coupling in eukaryotes from comprehensive data integration
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DOI：
10.1101/gr.087528.108
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发表时间：
2009-06-01
期刊：
影响因子：
7
通讯作者：
Sonnhammer, Erik L. L.
中科院分区：
文献类型：
--
作者：
Alexeyenko, Andrey;Sonnhammer, Erik L. L.
没有一种单一的实验方法可以发现相互作用组中的所有联系。计算方法可以通过整合来自多个通常不相关的蛋白质组学和基因组学管道的数据来提供帮助。重建全球功能耦合网络（FC）面临着规模和异构性的挑战，即如何有效地整合来自多个生物的大量不同数据，同时保证高精度。我们开发了一个优化的贝叶斯框架FunCoup来解决这些问题。由于相互作用组包含多种类型的功能耦合，FunCoup用置信度评分标注网络边缘，以支持不同类型的相互作用：物理相互作用、蛋白质复合体成员、代谢或信号链接。这种能力提高了整体的准确性。总体而言，对构建的框架进行了全面测试，以优化整体置信度，确保无缝、自动化地纳入异构类型的新数据集。利用7种生物的50多个数据集，并在同源物之间广泛传递信息，FunCoup预测了8种真核生物的全球网络。对于Ciona ninteinalis网络，只使用了同源信息，它恢复了大量的实验事实。在独立的癌症突变数据上验证了FunCoup预测。我们展示了如何使用FunCoup来发现帕金森和阿尔茨海默病途径的候选成员。跨物种途径保护分析进一步支持了这些观察结果。
No single experimental method can discover all connections in the interactome. A computational approach can help by integrating data from multiple, often unrelated, proteomics and genomics pipelines. Reconstructing global networks of functional coupling (FC) faces the challenges of scale and heterogeneity-how to efficiently integrate huge amounts of diverse data from multiple organisms, yet ensuring high accuracy. We developed FunCoup, an optimized Bayesian framework, to resolve these issues. Because interactomes comprise functional coupling of many types, FunCoup annotates network edges with confidence scores in support of different kinds of interactions: physical interaction, protein complex member, metabolic, or signaling link. This capability boosted overall accuracy. On the whole, the constructed framework was comprehensively tested to optimize the overall confidence and ensure seamless, automated incorporation of new data sets of heterogeneous types. Using over 50 data sets in seven organisms and extensively transferring information between orthologs, FunCoup predicted global networks in eight eukaryotes. For the Ciona intestinalis network, only orthologous information was used, and it recovered a significant number of experimental facts. FunCoup predictions were validated on independent cancer mutation data. We show how FunCoup can be used for discovering candidate members of the Parkinson and Alzheimer pathways. Cross-species pathway conservation analysis provided further support to these observations.