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简介：Anewmethodwasdescribedforusingarecurrentneuralnetworkwithbiasunitstopredictcontactmapsinproteins.Themaininputstotheneuralnetworkincluderesiduespairwise,residueclassificationaccordingtohydrophobicity,polar,acidic,basicandsecondarystructureinformationandresidueseparationbetweentworesidues.Inourwork,adatasetwasusedwhichwascomposedof53globulinproteinsofknown3Dstructure.Anaveragepredictiveaccuracyof0.29wasobtained.Ourresultsdemonstratetheviabilityoftheapproachforpredictingcontactmaps.

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简介：TheBIONISnetworkwassetupinspring2002byProf.GeorgeJeronimidis,Prof.JulianVincentandPhilSheppard.Membershipisnowover300,withmembersfromacademiaandindustryinmorethan40countries.ThemissionofthenetworkistopromotetheapplicationofBiomimeticsinproductsandservicesanditsuseineducationandtraining.ItiscurrentlysupportedbySwedishBiomimetics3000?andhostedbytheUniversityofReading.

简介：Wehaveawinner!Newprizetodevelopbiomimeticsresearchawarded.

简介：Simulatingbiologicalolfactoryneuralsystem,KⅢnetwork,whichisahigh-dimensionalchaoticneuralnetwork,isdesignedinthispaper.Differentfromconventionalartificialneuralnetwork,theKⅢnetworkworksinitschaotictrajectory.ItcansimulatenotonlytheoutputEEGwaveformobservedinelectrophysiologicalexperiments,butalsothebiologicalintelligenceforpatternclassification.Thesimulationanalysisandapplicationtotherecognitionofhandwritingnmeralsarepresentedhere.TheclassificationperformanceoftheKⅢnetworkatdifferentnoiselevelswasalsoinvestigated.

简介：Anactivestereovisionsystembasedonamodelofneuralpathwaysofhumanbinocularmotorsystemisproposed.Withthismodel,itisguaranteedthatthetwocamerasoftheactivestereovisionsystemcankeeptheirlinesofsightfixedonthesametargetobjectduringsmoothpursuit.Thisfeatureisveryimportantforactivestereovisionsystems,sincenotonly3Drecon-structionneedsthetwocamerashaveanoverlappingfieldofvision,butalsoitcanfacilitatethe3Dreconstructionalgorithm.Toevaluatetheeffectivenessoftheproposedmethod,somesoftwaresimulationsaredonetodemonstratethesametargettrackingcharacteristicinavirtualenvironmentapttomistrackingeasily.Here,mistrackingmeanstwoeyestracktwodifferentobjectsseparately.Thentheproposedmethodisimplementedinouractivestereovisionsystemtoperformrealtrackingtaskinalaboratoryscenewhereseveralpersonswalkself-determining.Beforetheproposedmodelisimplementedinthesystem,mis-trackingoccurredfrequently.Afteritisenabled,mistrackingneveroccurred.Theresultshowsthatthevisionsystembasedonneuralpathwaysofhumanbinocularmotorsystemcanreliablyavoidmistracking.

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

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