{"title":"基于模糊图的聚类亲和性搜索技术在基因表达数据聚类中的应用","authors":"Koyel Mandal, R. Sarmah, B. Borah","doi":"10.1109/ICSMB.2016.7915092","DOIUrl":null,"url":null,"abstract":"Cluster analysis is a widely used data mining technique for extracting biological knowledge from gene expression data. In this paper, we modified one of the graph-theoretic approach CAST by using fuzzy graph concept. Our algorithm FGBCAST (Fuzzy Graph Based Cluster Affinity Search Technique) is tested over three real life datasets Yeast Cell Cycle, Yeast Sporulation and Escheria Coli. The performance of the proposed algorithm gives better results than CAST in terms of z-score, p-value and Q-value.","PeriodicalId":231556,"journal":{"name":"2016 International Conference on Systems in Medicine and Biology (ICSMB)","volume":"6 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Fuzzy Graph Based Cluster Affinity Search Technique for clustering of gene expression data\",\"authors\":\"Koyel Mandal, R. Sarmah, B. Borah\",\"doi\":\"10.1109/ICSMB.2016.7915092\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cluster analysis is a widely used data mining technique for extracting biological knowledge from gene expression data. In this paper, we modified one of the graph-theoretic approach CAST by using fuzzy graph concept. Our algorithm FGBCAST (Fuzzy Graph Based Cluster Affinity Search Technique) is tested over three real life datasets Yeast Cell Cycle, Yeast Sporulation and Escheria Coli. The performance of the proposed algorithm gives better results than CAST in terms of z-score, p-value and Q-value.\",\"PeriodicalId\":231556,\"journal\":{\"name\":\"2016 International Conference on Systems in Medicine and Biology (ICSMB)\",\"volume\":\"6 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Systems in Medicine and Biology (ICSMB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSMB.2016.7915092\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Systems in Medicine and Biology (ICSMB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSMB.2016.7915092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Fuzzy Graph Based Cluster Affinity Search Technique for clustering of gene expression data
Cluster analysis is a widely used data mining technique for extracting biological knowledge from gene expression data. In this paper, we modified one of the graph-theoretic approach CAST by using fuzzy graph concept. Our algorithm FGBCAST (Fuzzy Graph Based Cluster Affinity Search Technique) is tested over three real life datasets Yeast Cell Cycle, Yeast Sporulation and Escheria Coli. The performance of the proposed algorithm gives better results than CAST in terms of z-score, p-value and Q-value.