A Machine Learning Approach for Prediction of Gibberellic Acid Metabolic Enzymes in Monocotyledonous Plants

dc.contributor.authorSreepriya, P.
dc.contributor.authorNaganeeswaran, S.
dc.contributor.authorHemalatha, N.
dc.contributor.authorSreejisha, P.
dc.contributor.authorRajesh, M.K.
dc.date.accessioned2014-10-15T10:47:24Z
dc.date.available2014-10-15T10:47:24Z
dc.date.issued2014-08
dc.description.abstractGibberellins (GA) are one of the most important phytohormones that control different aspects of plant growth and influence various developments such as seed germination, stem elongation and floral induction. More than 130 GAs have been identified; however, only a small number of them are biologically active. In this study, five enzymes in GA metabolic pathway in monocots have been thoroughly researched namely, ent-copalyl-diphosphate synthase (CPS), ent-kaurene synthase (KS), ent-kaurene oxidase (KO), GA 20-oxidase (GA20ox), and GA 2-oxidase (GA2ox). We have designed and implemented a high performance prediction tool for these enzymes using machine learning algorithms. ‘GAPred’ is a web-based system to provide a comprehensive collection of enzymes in GA metabolic pathway and a systematic framework for the analysis of these enzymes for monocots. WEKA-based classifiers (Naïve-Bayes) and Support Vector Machine (SVM) based-modules were developed using dipeptide composition and high accuracies were obtained. In addition, BLAST and Hidden Markov Model (HMMER-based model) were also developed for searching sequence databases for homolog’s of enzymes of GA metabolic pathway, and for making protein sequence alignments.en_US
dc.identifier.citationTransactions on Machine Learning and Artificial Intelligence Volume 2, Issue 4, August 2014, pp.35-47en_US
dc.identifier.urihttp://hdl.handle.net/123456789/6016
dc.language.isoenen_US
dc.subjectGAen_US
dc.subjectSVMen_US
dc.subjectWEKAen_US
dc.subjectBLASTen_US
dc.subjectHMMERen_US
dc.titleA Machine Learning Approach for Prediction of Gibberellic Acid Metabolic Enzymes in Monocotyledonous Plantsen_US
dc.typeArticleen_US

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