Computational approach for the prediction of ERF and DREB proteins in indica rice using support vector machine

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dc.contributor.authorHemalatha, N.
dc.contributor.authorRajesh, M.K.
dc.contributor.authorNarayanan, N.K.
dc.date.accessioned2014-06-05T08:58:26Z
dc.date.available2014-06-05T08:58:26Z
dc.date.issued2012
dc.description.abstractDrought and salt stress are considered to be major impediments in rice production systems. To understand the genetics of tolerance to these abiotic stresses and develop drought/salt tolerant cultivars, genomic regions influencing yield and its response to water deficit have to be identified. A method for predicting two drought tolerant proteins viz. dehydration-responsive element binding proteins (DREB) and ethylene responsive factor (ERF) in the genome of indica rice has been described. The proposed method, ERFDREBSVMPRED, was developed using support vector machine and a prediction accuracy of 89% for DREB and 81% for ERF was achieved. The developed tool could predict DREB protein with 100% specificity at a 71% sensitivity rate and ERF protein with 100% specificity at a 60% sensitivity rate.en_US
dc.identifier.citationOryza Vol. 49. No. 4, 2012 (239-245)en_US
dc.identifier.urihttp://hdl.handle.net/123456789/2422
dc.language.isoenen_US
dc.subjectriceen_US
dc.subjectERFen_US
dc.subjectDREBen_US
dc.subjectproteinen_US
dc.subjectsupport vector machineen_US
dc.titleComputational approach for the prediction of ERF and DREB proteins in indica rice using support vector machineen_US
dc.typeArticleen_US

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