数据挖掘在蛋白质二级结构预测中的应用

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1、AbstractAbstractThemainofembodimentoforganismfunctionisprotein.Theresearchofproteinfunctionisimportantcontentofbioinformatics.Theprotein’three-dimensionalstructureisavailabletorevealingitsstructure.Traditionalexperimentcanbeusedtoresolveprotein’sstructure,butitrequiresfirst-classt

2、estinstallationsandtechnology,andhaslong-termandlow-efficiency.Soit’simportantforustopredictprotein’sstructurebyusingtheinformationintheproteindatabase.Wefindthatit’shardtopredictprotein’stertiarystructureandfromtheprimarystructure,andthesecondarystructurecanbeabridgeintheprocess.

3、Alongwiththeexpansionoftheresearchrangeandtheunceasingincreaseofthedata,thetraditionaldataprocessmethodcannotkeeppacewiththebioinformaticsdevelopment.Theapplicationofdataminingindatasearches,Statistic,comparisonandanalysiscandiscoverytheeffectiveinformation.Thisapplicationisaninte

4、rdisciplinaryandprosperouseffort.ThemainissueresearchedinthispaperistopredictthesecondarystructurebyusingAssociationanalysisofdatamining.Weattempttoanalyzeprotein’saminoacidsequencesandtheirsecondarystructuresfromthedataprovidedbyproteindatabase,andtofindassociationrulebyusingimpr

5、ovedApriorialgorithm.Thenweattempttoforecastprotein’ssecondarystructurebyusingminedaggregateofassociationrule.Eventually,weestablishedaprotein’ssecondarystructurepredictionsystembasedontheresearch.Ourexperimenthasprovedthismethodisaccurateandeffective.Keywords:bioinformatics,prote

6、insecondarystructureprediction,associationrule,datamining.IIAbstractAbstractNowadays,biologydevelopsrapidly.Regardlessoffromquantityorthequality,thebiologyresourcesaregettingmoreandmore.Computerandthenetworktechnologyseepthrougheachfieldsofbio-sciencegradually.Abrand-new,owningthe

7、enormouspotentialDiscipline-bioinformaticshasappearedanditbecomes21centuriesforwardpositionscience.Proteinisakindofbigmoleculeoflivingthings.Ithasagreatvariety.Itwidelyandmassivelyexistsinthebiosphere.Themainofembodimentoforganismfunctionisprotein.Itdecidesbiological’speciescharac

8、teranditsmetabolismtype.Sotherese