Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/90487
DC FieldValue
dc.titleVPMCD: Variable interaction modeling approach for class discrimination in biological systems
dc.contributor.authorRaghuraj, R.
dc.contributor.authorLakshminarayanan, S.
dc.date.accessioned2014-10-09T07:05:50Z
dc.date.available2014-10-09T07:05:50Z
dc.date.issued2007-03-06
dc.identifier.citationRaghuraj, R., Lakshminarayanan, S. (2007-03-06). VPMCD: Variable interaction modeling approach for class discrimination in biological systems. FEBS Letters 581 (5) : 826-830. ScholarBank@NUS Repository.
dc.identifier.issn00145793
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/90487
dc.description.abstractData classification algorithms applied for class prediction in computational biology literature are data specific and have shown varying degrees of performance. Different classes cannot be distinguished solely based on interclass distances or decision boundaries. We propose that inter-relations among the features be exploited for separating observations into specific classes. A new variable predictive model based class discrimination (VPMCD) method is described here. Three well established and proven data sets of varying statistical and biological significance are utilized as benchmark. The performance of the new method is compared with advanced classification algorithms. The new method performs better during different tests and shows higher stability and robustness. The VPMCD is observed to be a potentially strong classification approach and can be effectively extended to other data mining applications involving biological systems. © 2007 Federation of European Biochemical Societies.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.febslet.2007.01.052
dc.sourceScopus
dc.subjectComputational biology
dc.subjectData classification
dc.subjectDiscriminant analysis
dc.subjectMachine learning
dc.subjectMultivariate statistics
dc.subjectVariable predictive models
dc.typeArticle
dc.contributor.departmentCHEMICAL & BIOMOLECULAR ENGINEERING
dc.description.sourcetitleFEBS Letters
dc.description.volume581
dc.description.issue5
dc.description.page826-830
dc.description.codenFEBLA
dc.identifier.isiut000244941100007
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

33
checked on Mar 6, 2018

WEB OF SCIENCETM
Citations

12
checked on Dec 31, 2018

Page view(s)

49
checked on Sep 7, 2019

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.