Reconstruction of Gene Regulatory Networks Based on Two-Stage Bayesian Network Structure Learning Algorithm-中国期刊网

摘要 Inthepost-genomicbiologyera,thereconstructionofgeneregulatorynetworksfrommicroarraygeneexpressiondataisveryimportanttounderstandtheunderlyingbiologicalsystem,andithasbeenachallengingtaskinbioinformatics.TheBayesiannetworkmodelhasbeenusedinreconstructingthegeneregulatorynetworkforitsadvantages,buthowtodeterminethenetworkstructureandparametersisstillimportanttobeexplored.Thispaperproposesatwo-stagestructurelearningalgorithmwhichintegratesimmuneevolutionalgorithmtobuildaBayesiannetwork.Thenewalgorithmisevaluatedwiththeuseofbothsimulatedandyeastcellcycledata.Theexperimentalresultsindicatethattheproposedalgorithmcanfindmanyoftheknownrealregulatoryrelationshipsfromliteratureandpredicttheothersunknownwithhighvalidityandaccuracy.

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Reconstruction of Gene Regulatory Networks Based on Two-Stage Bayesian Network Structure Learning Algorithm

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Reconstruction of Gene Regulatory Networks Based on Two-Stage Bayesian Network Structure Learning Algorithm

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