Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0025-5564(03)00096-8
DC FieldValue
dc.titleProtein function classification via support vector machine approach
dc.contributor.authorCai, C.Z.
dc.contributor.authorWang, W.L.
dc.contributor.authorSun, L.Z.
dc.contributor.authorChen, Y.Z.
dc.date.accessioned2014-05-19T02:57:28Z
dc.date.available2014-05-19T02:57:28Z
dc.date.issued2003-10
dc.identifier.citationCai, C.Z., Wang, W.L., Sun, L.Z., Chen, Y.Z. (2003-10). Protein function classification via support vector machine approach. Mathematical Biosciences 185 (2) : 111-122. ScholarBank@NUS Repository. https://doi.org/10.1016/S0025-5564(03)00096-8
dc.identifier.issn00255564
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/53353
dc.description.abstractSupport vector machine (SVM) is introduced as a method for the classification of proteins into functionally distinguished classes. Studies are conducted on a number of protein classes including RNA-binding proteins; protein homodimers, proteins responsible for drug absorption, proteins involved in drug distribution and excretion, and drug metabolizing enzymes. Testing accuracy for the classification of these protein classes is found to be in the range of 84-96%. This suggests the usefulness of SVM in the classification of protein functional classes and its potential application in protein function prediction. © 2003 Elsevier Inc. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S0025-5564(03)00096-8
dc.sourceScopus
dc.subjectClassification
dc.subjectDrug absorption protein
dc.subjectDrug distribution protein
dc.subjectDrug excretion protein
dc.subjectDrug metabolizing enzyme
dc.subjectProtein homodimer
dc.subjectRNA-binding protein
dc.subjectSupport vector machine
dc.typeReview
dc.contributor.departmentCOMPUTATIONAL SCIENCE
dc.contributor.departmentBIOPROCESSING TECHNOLOGY CENTRE
dc.description.doi10.1016/S0025-5564(03)00096-8
dc.description.sourcetitleMathematical Biosciences
dc.description.volume185
dc.description.issue2
dc.description.page111-122
dc.description.codenMABIA
dc.identifier.isiut000185342000001
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