III:Small: Overlapping Clustering Analysis of Biological Networks

本项目组成了一个跨学科的研究团队，汇集了计算机科学家和生物医学科学家的专业知识，以解决分析蛋白质相互作用数据中的挑战性问题。具体来说，该项目开发了一种新的方法来检测新出现的大量蛋白质-蛋白质相互作用数据中的重叠簇，并验证了酵母中的计算方法。大量的蛋白质-蛋白质相互作用数据为我们提供了一个很好的机会来系统地分析一个大型生命系统的结构，也使我们能够理解基本原理，如本质、遗传相互作用、功能、功能模块、蛋白质复合物和细胞途径。鉴定蛋白质相互作用网络中的功能模块是非常有趣的，因为它们经常揭示蛋白质之间未知的功能联系，从而预测未知蛋白质的功能。蛋白质可能包含在一个或多个官能团中。因此，需要在蛋白质相互作用数据中识别重叠簇。本项目开发了一种独特的方法，将领域知识与蛋白质相互作用数据相结合，使数据更加可靠。它还开发了一种独特的方法来支持蛋白质相互作用数据的重叠模块化分析，智能地将生物信息集成到模块化分析过程中。这个项目的另一个独特的方面是计算方法与生物验证的紧密结合。通过将每个功能模块中的未知蛋白质与已知蛋白质相关联，我们可以建议这些蛋白质积极地为分配给模块的相应功能工作。该项目还可以在其他具有模块化网络属性的数据处理领域中找到广泛的应用，例如web网络、社交网络和技术网络。欲了解更多信息，请参阅项目网页：http://www.cse.buffalo.edu/DBGROUP/PPI-networks/index.html

This project forms an interdisciplinary research team with integrated expertise of computer scientists and biomedical scientists to tacklethe challenging issues in analyzing protein interaction data. Specifically,the project develops a novel approach to detecting overlapping clusters onemerging large volume of protein-protein interaction data and validatesthe computational approaches in yeast. The vast amount of protein-proteininteraction data provides us with a good opportunity to systematicallyanalyze the structure of a large living system and also allows us tounderstand essential principles like essentiality, genetic interactions,functions, functional modules, protein complexes, and cellular pathways.The identification of functional modules in protein interaction networks isof great interest because they often reveal unknown functional ties betweenproteins and hence predict functions for unknown proteins. A protein maybe included in one or more functional groups. Therefore, overlapping clustersneed to be identified in protein interaction data. This project develops a unique method to integrate domain knowledge with the protein interactiondata so that the data will be more reliable. It also developsa unique method to support overlapping modularity analysis forprotein interaction data that intelligently integrates biologicalinformation into the modularity analysis process. Another uniqueaspect of this project is the tight integration of computational methods with biological verification. By associating unknown proteins with the known proteins within each functional module, we can suggest that those proteins positively work for the corresponding functions that are assigned to the modules. This project can also find broad applications in other areas which handle data with the modular network property, such as web network, social networks, and technological networks.For further information see the project web page:http://www.cse.buffalo.edu/DBGROUP/PPI-networks/index.html