{"title":"An Information Theoretic Framework for Ontology-based Bioinformatics","authors":"G. Alterovitz, M. Xiang, M. Ramoni","doi":"10.1109/ITA.2007.4357555","DOIUrl":null,"url":null,"abstract":"With myriad information being generated from high-throughput experiments such as microarrays and sequencing technologies, an ever-increasing amount of data is being recorded and analyzed with the help of hierarchical ontologies, such as the gene ontology (GO). We have developed a novel framework- based on the well established foundations of information theory- that allows for the evaluation of new types of hypotheses. The framework, encapsulated in open biomedical ontology-based exploration and search (OBOES), has already been applied in the investigation of different kinds of questions. The resulting framework enables the new field of information theoretic ontology-based analysis. We have applied this framework to create methods to re-engineer ontologies, explore fundamental questions on the evolution of biological complexity, determine optimal ontology terms for bioinformatics analysis, and quantify the usefulness of biofluids as proxies for tissues/diseases. In each case, we found that our methods provide novel, significant findings. An open source Java implementation of OBOES is available at: http://oboes.sourceforge.net.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 Information Theory and Applications Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITA.2007.4357555","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
With myriad information being generated from high-throughput experiments such as microarrays and sequencing technologies, an ever-increasing amount of data is being recorded and analyzed with the help of hierarchical ontologies, such as the gene ontology (GO). We have developed a novel framework- based on the well established foundations of information theory- that allows for the evaluation of new types of hypotheses. The framework, encapsulated in open biomedical ontology-based exploration and search (OBOES), has already been applied in the investigation of different kinds of questions. The resulting framework enables the new field of information theoretic ontology-based analysis. We have applied this framework to create methods to re-engineer ontologies, explore fundamental questions on the evolution of biological complexity, determine optimal ontology terms for bioinformatics analysis, and quantify the usefulness of biofluids as proxies for tissues/diseases. In each case, we found that our methods provide novel, significant findings. An open source Java implementation of OBOES is available at: http://oboes.sourceforge.net.