Mohammad Bozlul Karim, Nobutaka Wakamatsu, M. Altaf-Ul-Amin
{"title":"[Dedicated to Prof. T. Okada and Prof. T. Nishioka: data science in chemistry]DPClusOST: A Software Tool for General Purpose Graph Clustering","authors":"Mohammad Bozlul Karim, Nobutaka Wakamatsu, M. Altaf-Ul-Amin","doi":"10.2751/JCAC.18.76","DOIUrl":null,"url":null,"abstract":"Modern world is incorporating highly connected heterogeneous data due to information sharing through computer and communication technology. These data lead to a complex relation where drilling down and mining are needed for understanding the actual meaning of data. Today any modern computational technique uses graph clustering as a sophisticated technology for data analysis. In this paper we implement a generalized graph clustering algorithm DPClusO with easy operating procedure and clear visualization techniques. DPClusO is enhanced version of DPClus algorithm where overlapping property of clusters is taken into consideration along with density and periphery tracking. User can select different parameters and visualization attributes to render cluster set, single cluster, hierarchical graph etc. and save these data in image and text formats. This paper discusses step by step operation of the proposed software tool using an example network of metabolites collected from KNApSAcK database. This tool successfully generated cohesive groups of structurally similar metabolites. The tool can be used for analysis of network data of any field of studies.","PeriodicalId":41457,"journal":{"name":"Journal of Computer Aided Chemistry","volume":"18 1","pages":"76-93"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2751/JCAC.18.76","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Aided Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2751/JCAC.18.76","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Modern world is incorporating highly connected heterogeneous data due to information sharing through computer and communication technology. These data lead to a complex relation where drilling down and mining are needed for understanding the actual meaning of data. Today any modern computational technique uses graph clustering as a sophisticated technology for data analysis. In this paper we implement a generalized graph clustering algorithm DPClusO with easy operating procedure and clear visualization techniques. DPClusO is enhanced version of DPClus algorithm where overlapping property of clusters is taken into consideration along with density and periphery tracking. User can select different parameters and visualization attributes to render cluster set, single cluster, hierarchical graph etc. and save these data in image and text formats. This paper discusses step by step operation of the proposed software tool using an example network of metabolites collected from KNApSAcK database. This tool successfully generated cohesive groups of structurally similar metabolites. The tool can be used for analysis of network data of any field of studies.