简介:TheBIONISnetworkwassetupinspring2002byProf.GeorgeJeronimidis,Prof.JulianVincentandPhilSheppard.Membershipisnowover300,withmembersfromacademiaandindustryinmorethan40countries.ThemissionofthenetworkistopromotetheapplicationofBiomimeticsinproductsandservicesanditsuseineducationandtraining.ItiscurrentlysupportedbySwedishBiomimetics3000?andhostedbytheUniversityofReading.
简介:Anewmethodwasdescribedforusingarecurrentneuralnetworkwithbiasunitstopredictcontactmapsinproteins.Themaininputstotheneuralnetworkincluderesiduespairwise,residueclassificationaccordingtohydrophobicity,polar,acidic,basicandsecondarystructureinformationandresidueseparationbetweentworesidues.Inourwork,adatasetwasusedwhichwascomposedof53globulinproteinsofknown3Dstructure.Anaveragepredictiveaccuracyof0.29wasobtained.Ourresultsdemonstratetheviabilityoftheapproachforpredictingcontactmaps.
简介:Inthepost-genomicbiologyera,thereconstructionofgeneregulatorynetworksfrommicroarraygeneexpressiondataisveryimportanttounderstandtheunderlyingbiologicalsystem,andithasbeenachallengingtaskinbioinformatics.TheBayesiannetworkmodelhasbeenusedinreconstructingthegeneregulatorynetworkforitsadvantages,buthowtodeterminethenetworkstructureandparametersisstillimportanttobeexplored.Thispaperproposesatwo-stagestructurelearningalgorithmwhichintegratesimmuneevolutionalgorithmtobuildaBayesiannetwork.Thenewalgorithmisevaluatedwiththeuseofbothsimulatedandyeastcellcycledata.Theexperimentalresultsindicatethattheproposedalgorithmcanfindmanyoftheknownrealregulatoryrelationshipsfromliteratureandpredicttheothersunknownwithhighvalidityandaccuracy.