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dc.contributor.authorChiu, HCen_US
dc.contributor.authorChang, CAen_US
dc.contributor.authorHu, YJen_US
dc.date.accessioned2014-12-08T15:18:53Z-
dc.date.available2014-12-08T15:18:53Z-
dc.date.issued2005-06-01en_US
dc.identifier.issn0169-2607en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.cmpb.2005.03.002en_US
dc.identifier.urihttp://hdl.handle.net/11536/13594-
dc.description.abstractMaking accurate functional predictions plays an important role in the era of proteomics. Reliable functional information can be extracted from orthologs in other species when annotating an unknown gene. Here a site-based approach called PORFIS is proposed to predict orthologous relationship. When applied to the bacterial. transcription factor PurR/Lacl family and the protein kinase AGC family, our method was able to identify, with few false positives, the important sites that agree with those verified by biological experiments. We also tested it on the alpha-proteasome family, the glycoprotein hormone family and the growth hormone family to demonstrate its ability to predict orthologous relationship. Compared with other prediction methods based on phylogenetic analysis or hidden Markov models, PORFIS not only has competitive prediction accuracy, but also provides valuable biological information of functionally important sites associated with orthologs which can be further studied in biological experiments. (c) 2005 Elsevier Ireland Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectorthologsen_US
dc.subjectparalogsen_US
dc.subjectprotein functionsen_US
dc.subjectimportant sitesen_US
dc.titlePrediction of orthologous relationship by functionally important sitesen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.cmpb.2005.03.002en_US
dc.identifier.journalCOMPUTER METHODS AND PROGRAMS IN BIOMEDICINEen_US
dc.citation.volume78en_US
dc.citation.issue3en_US
dc.citation.spage209en_US
dc.citation.epage222en_US
dc.contributor.department生物科技學系zh_TW
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000229655600003-
dc.citation.woscount3-
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