{"title":"挖掘人类蛋白质相互作用组中最大的准团","authors":"M. Bhattacharyya, S. Bandyopadhyay","doi":"10.1109/ICAIS.2009.39","DOIUrl":null,"url":null,"abstract":"A clique is a complete subgraph of a graph. Often, a clique is interpreted as a dense module of vertices within a graph. However, in many real-world situations, the classical problem of finding a clique is required to be relaxed. This motivates the problem of finding quasicliques that are almost complete subgraphs of a graph. In sparse and very large scale-free networks, the problem of finding the largest quasi-clique becomes hard to manage with the existing approaches. Here, we propose a heuristic algorithm in this paper for locating the largest quasi-clique from the human protein-protein interaction networks. The results show promise in computational biology research by the exploration of significant protein modules.","PeriodicalId":161840,"journal":{"name":"2009 International Conference on Adaptive and Intelligent Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Mining the Largest Quasi-clique in Human Protein Interactome\",\"authors\":\"M. Bhattacharyya, S. Bandyopadhyay\",\"doi\":\"10.1109/ICAIS.2009.39\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A clique is a complete subgraph of a graph. Often, a clique is interpreted as a dense module of vertices within a graph. However, in many real-world situations, the classical problem of finding a clique is required to be relaxed. This motivates the problem of finding quasicliques that are almost complete subgraphs of a graph. In sparse and very large scale-free networks, the problem of finding the largest quasi-clique becomes hard to manage with the existing approaches. Here, we propose a heuristic algorithm in this paper for locating the largest quasi-clique from the human protein-protein interaction networks. The results show promise in computational biology research by the exploration of significant protein modules.\",\"PeriodicalId\":161840,\"journal\":{\"name\":\"2009 International Conference on Adaptive and Intelligent Systems\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Adaptive and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIS.2009.39\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Adaptive and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIS.2009.39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mining the Largest Quasi-clique in Human Protein Interactome
A clique is a complete subgraph of a graph. Often, a clique is interpreted as a dense module of vertices within a graph. However, in many real-world situations, the classical problem of finding a clique is required to be relaxed. This motivates the problem of finding quasicliques that are almost complete subgraphs of a graph. In sparse and very large scale-free networks, the problem of finding the largest quasi-clique becomes hard to manage with the existing approaches. Here, we propose a heuristic algorithm in this paper for locating the largest quasi-clique from the human protein-protein interaction networks. The results show promise in computational biology research by the exploration of significant protein modules.