第四章生物信息学方法

Part1Part14.14.1——NCBIEBI——GCGBLASTCLUSTAL——PHYLIPPALM——GROMACSNAMD——4.1.14.1.1——————EXCELSPSSSASMATLAB——————————LinuxC/C++PERL1234.1.24.1.21(Database&searching)——————EntrezSRSBLAST——2(Software&application)——GCGBLASTCLUSTAL——PHYLIPPALM……——ScanArrayArray-Pro……——GROMACSNAMD……3(Probabilitytheory)——————“Mostoftheproblemsincomputationalsequenceanalysisareessentiallystatistical.”——“Biologicalsequenceanalysis”4(Statisticalmethods)——……——————SPSSSAS5(Compositionanalysis&weightmatrixmethod)——————k-tuples/k-mers——WeightMatrixDecipheringasecretmessage……TheGold-BugAparchmentwrittenbypirateCaptainKidd:53##+305))6*;4826)4#.)4#):806*;48+8$60))85;53##+305))6*;4826)4#.)4#):806*;48+8$60))85;1#(;:#*8+83(88)5*+;46(88*96*?;8)*#(;485);5*1#(;:#*8+83(88)5*+;46(88*96*?;8)*#(;485);5*+2:*#(;4956*2(5*+2:*#(;4956*2(5*----4)8$8*;4069285);)6+8)4##;4)8$8*;4069285);)6+8)4##;1(#9;48081;8:8#1;48#85;4)485+528806*81(#9;1(#9;48081;8:8#1;48#85;4)485+528806*81(#9;48;(48;(88;4(#?34;48)4#161;:188;#?;48;(48;(88;4(#?34;48)4#161;:188;#?;53##+305))6*53##+305))6*THETHE26)26)HH#.)#.)HH#):#):EE06*06*THTHEE++EE$60))$60))EE55TT1#(1#(TT:#*:#*EE++EE3(3(EEEE)5*+)5*+THTH6(6(EEEE*96*?*96*?TETE)*#()*#(THTHEE5)5)TT5*+2:*#(5*+2:*#(THTH956*2(5*956*2(5*----HH))EE$$EE**THTH06920692EE5)5)TT)6+)6+EE))HH####TT1(#91(#9THETHE00EE11TETE::EE#1#1THTHEE##EE55THTH))HHEE5+525+52EEEE06*06*EE1(#91(#9THTHETET((HETHET((EEEE;;HH(#?3(#?3HTHEHTHE))HH#161#161TT:1:1EETEET#?#?TT“Agoodglassinthebishop'shostelinthedevil'sseatforty-onedegreesandthirteenminutesnortheastandbynorthmainbranchseventhlimbeastsideshootfromthelefteyeofthedeath's-headabeelinefromthetreethroughtheshotfiftyfeetout.”——k-merssequencepattern——S(x,w)k=1weightmatrixk1weightarray/R=AorGY=CorUN=A,G,CorUdonorsitek=1acceptorsitek=1-3-2-1123456A34.060.49.20.00.052.671.37.116.0C36.312.93.30.00.02.87.65.516.5G18.312.580.31000.041.911.881.420.9U11.414.27.30.01002.59.35.946.2-14-13-12-11-10-9-8-7-6-5-4-3-2-11A9.08.47.56.87.68.09.79.27.67.823.74.21000.023.9C31.031.030.729.332.633.037.338.541.035.230.970.80.00.013.8G12.511.510.610.411.011.311.38.56.66.421.20.30.010052.0U42.344.047.049.449.446.340.842.944.550.424.024.60.00.010.4k=2,3,…12)'()|()()|()()|()|(nonsitePnonsitePsitePsitePsitePsitePsitePvolumesassociatedatproperties)()|(logsitePsitePBayesianThelikelihoodthatapropertyvaluev(ofanewstructure)isdrawnfromthesplicingsiteis:Scorefortheoveralllikelihoodofthequerysequencebeingasiteis:P(S|splicesite)P(S|background)SaywehaveasequenceS=S1S2…Sn.ThenoneneedtocalculateSotolookforadonorsiteinthesequence,wemightcalculate6(Informationmethod)——Shannon1948logiiiHpp——ACGT————H{pi}SequencelogoSchneider,1990E.coliP.aby7EM(ExpectationMaximization)——EMEExpectationstepMMaximizationstepEM——HMM——MotifMEMEHMMBaum-Welch8(DynamicProgramming)——————DNAMarkovC+C+GG++CCGGCCGGCC––GG––C+C+CC––GG++GG––BBEE0.130.130.120.120.0340.0340.0100.0100.0120.0120.0030.0030.00320.00320.00020.0002HMM9(Iteration)——————10(Regression,fitting,correlation&association)————Regression:therelationbetweenselectedvaluesofxandobservedvaluesofy(fromwhichthemostprobablevalueofycanbepredictedforanyvalueofx)——11(Discriminantanalysis)——————12(Clusteringmethod)——————(“)——————DNAX(1)X(2)X(3)X(4)X(5)GibbonSymphalangusHumanGorillaChimpanzee13Markov(Markovmodel)——Markovnnn——Markov——Markov0.50.3750.1250.1250.250.6250.3750.250.3750.50.250.250.3750.1250.3750.1250.6250.37512ACGTMarkov1ACGT2AA,AC,…asttAtCtGtTsA0.1800.2740.4260.120sC0.1700.3680.2740.188sG0.1610.3390.3750.125sT0.0790.3550.3840.182CpG1Markov(s→t)14Markov(HMMmethod)——DNAMarkovMarkovC+C+GG++CCGGCCGGCC––GG––C+C+CC––GG++GG––BBEE0.130.130.120.120.0340.0340.0100.0100.0120.0120.0030.0030.00320.00320.00020.0002HMMDNAHMMMarkov(HMM)(Speechrecognition)(Speechrecognition)(Opticalcharacter(Opticalcharacterrecognition)recognition)(Biologicalsequenceanalysis)(Biologicalsequenceanalysis)12DNA……3……(Biometrics)(Biometrics)15(Perceptron&ANNmethod)——Acollectionofmathematicalmodelsthatemulatesomeoftheobservedpropertiesofbiologicalnervoussystemsanddrawontheanalogiesofadaptivebiologicallearning.——Thekeyelementoftheartificialneuralnetwork(ANN)modelisthestructureoftheinformationprocessingsystem.Itiscomposedofmanyhighlyinterconnectedprocessingelementsthatareanalogoustoneuronsandaretiedtogetherwithweightedconnectionsthatareanalogoustosynapses.————ANNANN————16(Decisiontree&SVMmethod)——————DNA17(Numericalmethods)——————18Allinone!——————————4.24.2TGACCATGAGCATGAAATTGCCTGGTTCACTGAGCGCTTGACCATGAGCATGAAATTGCCTGGTTCACTGAGCGCTTGACCATGAGCATGAAATTGCCTGGTTCACTGAGCGCTCTGATAAGAGCTACGAGCACCAGACACCCTTCGAAATTCTGATAAGAGCTACGAGCACCAGACACCCTTCGAAATTCTGATAAGAGCTACGAGCACCAGACACCCTTCGAAATTAAGAGTGCCAAGAAATTTGACACTTTCAAAGGGGAATGAAGAGTGCCAAGAAATTTGACACTTTCAAAGGGGAATGAAGAGTGCCAAGAAATTTGACACTTTCAAAGGGGAATGCCCAAAGTTTGTGTTTCCTCTTAACTCAAAAGTCAAAGTCCCAAAGTTTGTGTTTCCTCTTAACTCAAAAGTCAAAGTCCCAAAGTTTGTGTTTCCTCTTAACTCAAAAGTCAAAGTCATTCAACCACGTGTTGAAAAGAAAAAGACTGAGGGTTCATTCAACCACGTGTTGAAAAGAAAAAGACTGAGGGTTCATTCAACCACGTGTTGAAAAGAAAAAGACTGAGGGTTTCATGGGGCGTATACGCTCTGTGTACCCTGTTGCATCTCTCAT