{"title":"Case study: visualizing sets of evolutionary trees","authors":"N. Amenta, J. Klingner","doi":"10.1109/INFVIS.2002.1173150","DOIUrl":null,"url":null,"abstract":"We describe a visualization tool which allows a biologist to explore a large set of hypothetical evolutionary trees. Interacting with such a dataset allows the biologist to identify distinct hypotheses about how different species or organisms evolved, which would not have been clear from traditional analyses. Our system integrates a point-set visualization of the distribution of hypothetical trees with detail views of an individual tree, or of a consensus tree summarizing a subset of trees. Efficient algorithms were required for the key tasks of computing distances between trees, finding consensus trees, and laying out the point-set visualization.","PeriodicalId":293232,"journal":{"name":"IEEE Symposium on Information Visualization, 2002. INFOVIS 2002.","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"97","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Symposium on Information Visualization, 2002. INFOVIS 2002.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFVIS.2002.1173150","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 97
Abstract
We describe a visualization tool which allows a biologist to explore a large set of hypothetical evolutionary trees. Interacting with such a dataset allows the biologist to identify distinct hypotheses about how different species or organisms evolved, which would not have been clear from traditional analyses. Our system integrates a point-set visualization of the distribution of hypothetical trees with detail views of an individual tree, or of a consensus tree summarizing a subset of trees. Efficient algorithms were required for the key tasks of computing distances between trees, finding consensus trees, and laying out the point-set visualization.