lect5.ppt.Convertorˇ

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1、MultipleSequenceAlignment多序列比对OutlineIntroductionMethodToolsExample1.WhyneedMSA?Comparingapairofsequencesisnotsufficientformanyresearchpurposes,mainlyforevolutionaryreconstructionsandstudyfunctionalsimilaritieschite---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKDwheat--DPNKPKRAPSAFFVFMGEFREEF

2、KQKNPKNKSVAAVGKAAGERWKSLSEtrybrKKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGPmouse-----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP***.:::.:...:..*.*:*chiteAATAKQNYIRALQEYERNGG-wheatANKLKGEYNKAIAAYNKGESAtrybrAEKDKERYKREM---------mouseAKDDRIRYDNEMKSWEEQMAE*:.*.:PotentialUsesofAMultipleSequ

3、enceAlignment?ExtrapolationMotifs/PatternsPhylogenyProfilesStruc.PredictionMultipleAlignmentsAreCENTRALtoMOSTBioinformaticsTechniques.proteinsequencesthatare>30%identicaloftenhavethesamestructureandfunctionProfiles谱andmotifs模体一个序列模体是一段局部保守的区域或由一组序列共有的短的序列模式（pattern）Asequencemotifisalocallyconser

4、vedregionofasequenceorashortsequencepatternsharedbyasetofsequences.模体指用于预测分子功能、结构特征或家族关系的模式Thetermmotifreferstoanysequencepatternthatispredictiveofamolecule’sfunction,astructuralfeature,orafamilymembership.Motifscanbedetectedinproteins,DNAandRNAsequences,buttheymostcommonlyrefertoproteinmotifs.模

5、体可以表示为不同的形式因不同计算目的MotifscanberepresentedforcomputationalpurposesasFlexiblepatterns[K,R]-R-P-C-x(11)-C-V-S(qualitative,unweighted;seethePrositedatabaseatwww.expasy.org)Position-specificscoringmatrices(PSSM,seenextpage)ProfilehiddenMarkovmodels(HMM).Thesearerigorousprobabilisticformulationofaseque

6、nceprofile.TheycontainthesameprobabilityinformationasPSSMsbutcanalsoaccountforgaps.Discoveryofnovelrelatedsequencesisefficientlydoneusingmultiplesequencealignments.Thisprofile-ormotif-basedanalysisusesknowldedgederivedfromalignmentstoconstructandsearchforsequencepatterns.Profiles谱andmotifs模体Prof

7、ile–Theconservedregionsofamultiplesequencealignmentrepresentedasamatrix.Aprofilecanallowforgapsinthesequencealignments.Thecolumnsofthematrixcontainsubstitutionscoresfortheaminoacids.Therowscontainscoresformatchingcolumnsofth