Sequence Comparison.pdf

More documents

Recommendations

Info

Index O-notation, 18 P-value, 139 affine gap penalty, 8, 46, 163 algorithm, 17, 18 Huffman’s, 20 mergesort, 22 Needleman-Wunsch, 9, 60 Smith-Waterman, 10, 61, 71 alignment, 2, 37 gapped, 3, 72 global, 9, 38, 39, 41, 42, 50 graph, 3, 38, 86 local, 10, 42, 52 multiple, 11, 73, 81, 196 number of, 5 optimal, 9, 38, 41 pairwise, 11, 35, 195 score, 8, 37, 83, 121 ungapped, 3, 69 amino acid, 174 background frequency, 121, 123, 134 backtracking procedure, 24, 41, 45 band alignment, 54, 68 binary search, 28 BLAST, 69, 91, 130, 132, 139, 141 BLASTN, 92 BLASTP, 115, 142 BLASTX, 141 BLASTZ, 62, 79, 112 BLAT, 74 block, 153 BLOSUM45, 141, 158, 171 BLOSUM62, 135, 138, 141, 158, 170 BLOSUM80, 141, 158, 172 central dogma of molecular biology, 175 Chebyshev’s inequality, 185 Chen-Stein method, 135 ClustalW, 87 consecutive seed, 92, 94, 95, 100–104, 112 consensus alignment, 87 constant gap penalty, 48 deletion, 3 distribution background frequency, 121, 123 Bernoulli, 179 binomial, 180 divergence, 187 exponential, 163, 182 extreme value, 120, 121, 134–136 location and scale parameters, 120 mean and variance, 120 function, 179 geometric, 180 geometric-like, 128, 137, 180 normal, 183 optimal local alignment scores, 121, 134 λ, K, 121 λ, K estimation, 136 gapped, 134 ungapped, 121, 132, 138 Poisson, 180 relative entropy, 187 uniform, 182 divide-and-conquer, 21 DNA, 173 dot matrix, 37 dynamic programming, 23 E-value or Expect value, 128, 139, 141, 144 edge effect, 130, 133 207
208 Index effective size of search space, 140, 141 event, 177 certain, 177 complementary, 177 disjoint, 177 impossible, 177 independent, 178 intersection, 177 rare, 120, 181 recurrent, 191 union, 177 evolutionary model Markov chain, 150, 161 exact word match problem, 64 extreme value distribution, 120, 121, 134–136 location and scale parameters, 120 mean and variance, 120 FASTA, 68 Fibonacci number, 25 first hit probability, 94 function density, 179 distribution, 179 moment-generating, 186 probability generating, 181 gap, 8 extension, 72 generalized, 163 penalty, 136 effect, 134 logarithmic region, 135 penalty model, 8, 46 affine, 163 constant, 48 Gapped BLAST, 72 GenBank, 36, 63 gene, 175 generalized gap, 163 genome, 175 global alignment, 9, 38, 39, 41, 42, 50 greedy method, 18 greedy-choice property, 19 hash table, 64 Hedera, 110, 113 hidden Markov model, 62 Hirschberg’s linear space approach, 50, 55, 59 hit, 70, 74 non-overlapping, 72, 100, 103 overlapping, 76 probability, 94 homology, 1 search, 10, 63, 195 HSP, 70, 75, 78 Huffman coding, 19 insertion, 3 Karlin-Altschul sum statistic, 131, 138, 140 length adjustment, 140, 142, 143 linear space, 50, 55 local alignment, 10, 42, 52 longest common subsequence, 9, 30 longest increasing subsequence, 27 Mandala, 111, 113 Markov chain absorbing state, 189 aperiodic, irreducible, 189 evolutionary model, 150, 161 high-order, 191 memoryless, time homogeneity, 188 stationary distribution, 189 matrix BLOSUM, 153 BLOSUM45, 141, 158, 171 BLOSUM62, 135, 138, 141, 158, 170 BLOSUM80, 141, 158, 172 PAM, 150 PAM120, 158, 169 PAM250, 138, 158, 166 PAM30, 141, 158, 167 PAM70, 141, 158, 168 scoring, 7, 37 valid, 156 substitution, 8 maximal word match, 67 maximal-scoring segment, 123, 130 pair, MSP, 70, 71, 132 maximum segment score, 123, 128, 132 maximum-sum segment, 26, 70 mergesort, 22 model gap penalty, 8, 46 Markov chain, 188 absorbing state, 189 aperiodic, irreducible, 189 high-order, 191 memoryless, time homogeneity, 188 stationary distribution, 189 sequence Bernoulli, 12 Markov chain, 12 MSP, 70, 71, 132 multiple alignment, 11, 73, 81, 196
Page 2 and 3:
Computational Biology Editors-in-Ch
Page 4 and 5:
Kun-Mao Chao·Louxin Zhang Sequence
Page 6 and 7:
KMC: To Daddy, Mommy, Pei-Pei and L
Page 8 and 9:
viii Foreword I invite you to study
Page 10 and 11:
x Preface Chapters 2 to 5 form the
Page 12 and 13:
Acknowledgments We are extremely gr
Page 14 and 15:
Contents Foreword .................
Page 16 and 17:
Contents xix Part II. Theory ......
Page 18 and 19:
Chapter 1 Introduction 1.1 Biologic
Page 20 and 21:
1.2 Alignment: A Model for Sequence
Page 22 and 23:
1.2 Alignment: A Model for Sequence
Page 24 and 25:
1.3 Scoring Alignment 7 ( ) k m a k
Page 26 and 27:
1.4 Computing Sequence Alignment 9
Page 28 and 29:
1.5 Multiple Alignment 11 1.5 Multi
Page 30 and 31:
1.8 Bibliographic Notes and Further
Page 32 and 33:
PART I. ALGORITHMS AND TECHNIQUES 1
Page 34 and 35:
18 2 Basic Algorithmic Techniques 2
Page 36 and 37:
20 2 Basic Algorithmic Techniques F
Page 38 and 39:
22 2 Basic Algorithmic Techniques s
Page 40 and 41:
Page 42 and 43:
Page 44 and 45:
28 2 Basic Algorithmic Techniques P
Page 46 and 47:
30 2 Basic Algorithmic Techniques a
Page 48 and 49:
32 2 Basic Algorithmic Techniques O
Page 50 and 51:
Chapter 3 Pairwise Sequence Alignme
Page 52 and 53:
3.3 Global Alignment 37 3.2 Dot Mat
Page 54 and 55:
3.3 Global Alignment 39 ⎧ ⎨ S[i
Page 56 and 57:
3.3 Global Alignment 41 ( ai b j )
Page 58 and 59:
3.4 Local Alignment 43 ⎧ 0, ⎪
Page 60 and 61:
3.4 Local Alignment 45 Algorithm LO
Page 62 and 63:
3.5 Various Scoring Schemes 47 Fig.
Page 64 and 65:
3.6 Space-Saving Strategies 49 Fig.
Page 66 and 67:
3.6 Space-Saving Strategies 51 Algo
Page 68 and 69:
3.6 Space-Saving Strategies 53 scor
Page 70 and 71:
3.7 Other Advanced Topics 55 ning,
Page 72 and 73:
3.7 Other Advanced Topics 57 (0,0).
Page 74 and 75:
3.7 Other Advanced Topics 59 3.7.4
Page 76 and 77:
Page 78 and 79:
Chapter 4 Homology Search Tools The
Page 80 and 81:
4.1 Finding Exact Word Matches 65 F
Page 82 and 83:
4.1 Finding Exact Word Matches 67 F
Page 84 and 85:
4.3 BLAST 69 SALSDLHAHKLRVDPVNFKLLS
Page 86 and 87:
4.3 BLAST 71 length w, whereas for
Page 88 and 89:
4.3 BLAST 73 Fig. 4.9 A scenario of
Page 90 and 91:
4.5 PatternHunter 75 BLAT identifie
Page 92 and 93:
4.5 PatternHunter 77 can develop an
Page 94 and 95:
Page 96 and 97:
82 5 Multiple Sequence Alignment S
Page 98 and 99:
84 5 Multiple Sequence Alignment S
Page 100 and 101:
86 5 Multiple Sequence Alignment Fi
Page 102 and 103:
88 5 Multiple Sequence Alignment al
Page 104 and 105:
Chapter 6 Anatomy of Spaced Seeds B
Page 106 and 107:
6.2 Basic Formulas on Hit Probabili
Page 108 and 109:
Page 110 and 111:
Page 112 and 113:
6.3 Distance between Non-Overlappin
Page 114 and 115:
Page 116 and 117:
Page 118 and 119:
6.4 Asymptotic Analysis of Hit Prob
Page 120 and 121:
Page 122 and 123:
Page 124 and 125:
6.5 Spaced Seed Selection 111 Count
Page 126 and 127:
6.6 Generalizations of Spaced Seeds
Page 128 and 129:
Page 130 and 131:
Page 132 and 133:
120 7 Local Alignment Statistics tr
Page 134 and 135:
122 7 Local Alignment Statistics Fi
Page 136 and 137:
124 7 Local Alignment Statistics Le
Page 138 and 139:
126 7 Local Alignment Statistics Be
Page 140 and 141:
128 7 Local Alignment Statistics we
Page 142 and 143:
130 7 Local Alignment Statistics A
Page 144 and 145:
132 7 Local Alignment Statistics pr
Page 146 and 147:
134 7 Local Alignment Statistics wh
Page 148 and 149:
136 7 Local Alignment Statistics Ta
Page 150 and 151:
138 7 Local Alignment Statistics Be
Page 152 and 153:
140 7 Local Alignment Statistics 7.
Page 154 and 155:
Page 156 and 157:
144 7 Local Alignment Statistics al
Page 158 and 159:
Page 160 and 161:
Chapter 8 Scoring Matrices With the
Page 162 and 163:
8.1 The PAM Scoring Matrices 151 AB
Page 164 and 165:
8.2 The BLOSUM Scoring Matrices 153
Page 166 and 167: 8.3 General Form of the Scoring Mat
Page 168 and 169: 8.4 How to Select a Scoring Matrix?
Page 170 and 171: 8.5 Compositional Adjustment of Sco
Page 172 and 173: 8.6 DNA Scoring Matrices 161 This i
Page 174 and 175: 8.7 Gap Cost in Gapped Alignments 1
Page 176 and 177: 8.8 Bibliographic Notes and Further
Page 184 and 185: Appendix A Basic Concepts in Molecu
Page 186 and 187: A.4 The Genomes 175 ondary structur
Page 188 and 189: Appendix B Elementary Probability T
Page 190 and 191: B.3 Major Discrete Distributions 17
Page 192 and 193: B.3 Major Discrete Distributions 18
Page 194 and 195: B.5 Mean, Variance, and Moments 183
Page 196 and 197: B.5 Mean, Variance, and Moments 185
Page 198 and 199: B.6 Relative Entropy of Probability
Page 200 and 201: B.7 Discrete-time Finite Markov Cha
Page 202 and 203: B.8 Recurrent Events and the Renewa
Page 204 and 205: B.8 Recurrent Events and the Renewa
Page 206 and 207: 196 C Software Packages for Sequenc
Page 208 and 209: 198 References 19. Bafna, V. and Pe
Page 210 and 211: 200 References 71. Fitch, W.M. and
Page 212 and 213: 202 References 122. Letunic, I., Co
Page 214 and 215: 204 References 173. Robinson, A.B.
Page 218: Index 209 heuristic, 85 progressive
show all

Sequence Comparison.pdf

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?