{"title":"Use of clustering to improve the layout of gene network for visualization","authors":"N. Noman, Kouichi Okada, N. Hosoyama, H. Iba","doi":"10.1109/CEC.2004.1331151","DOIUrl":null,"url":null,"abstract":"A very effective means to study the gene networks is visualization. With rapid increase of the size of gene networks, it has become more realistic to identify the collaborating genes in the network, which will facilitate the behavioral study of the groups and the network as a whole. In our previous paper, we presented a layered approach for visualizing gene regulatory networks. In this paper, we present a 3D layout model for visualizing gene networks, which clusters the correlated genes depending on their causal relationships. To demonstrate the effectiveness of the approach, we visualize real gene networks of different sizes. The experimental results show the superiority and usefulness of the new model when compared with previous results.","PeriodicalId":152088,"journal":{"name":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2004.1331151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A very effective means to study the gene networks is visualization. With rapid increase of the size of gene networks, it has become more realistic to identify the collaborating genes in the network, which will facilitate the behavioral study of the groups and the network as a whole. In our previous paper, we presented a layered approach for visualizing gene regulatory networks. In this paper, we present a 3D layout model for visualizing gene networks, which clusters the correlated genes depending on their causal relationships. To demonstrate the effectiveness of the approach, we visualize real gene networks of different sizes. The experimental results show the superiority and usefulness of the new model when compared with previous results.