Lander E.S., Waterman M.S. (eds.) — Calculating the Secrets of Life: Applications of the Mathematical Sciences to Molecular Biology :: Электронная библиотека попечительского совета мехмата МГУ

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Lander E.S., Waterman M.S. (eds.) — Calculating the Secrets of Life: Applications of the Mathematical Sciences to Molecular Biology

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Название: Calculating the Secrets of Life: Applications of the Mathematical Sciences to Molecular Biology

Авторы: Lander E.S., Waterman M.S. (eds.)

Аннотация:

In this first-ever survey of the partnership between mathematics and biology, leading experts look at how mathematical research and methods have made possible important discoveries in biology. Explores how differential geometry, topology, and differential mechanics have allowed researchers to "wind" and "unwind" DNA's double helix to understand the phenomenon of supercoiling. Explains how mathematical tools are revealing the workings of enzymes and proteins. Describes how mathematicians are detecting echoes from the origin of life by applying the stochastic and statictical theory to the study of DNA sequences.

Язык:

Рубрика: Биология/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 1995

Количество страниц: 285

Добавлена в каталог: 30.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID

Предметный указатель

$\alpha$ -Helix      242—248 254
$\beta$ -sheet      242—248 254
4-plat knots      215—216 220 222
Adenine (A)      8 9 99
Algorithms      35—36 84—86 87
Algorithms, approximate pattern matching      78—79
Algorithms, difference measures      72—73
Algorithms, dynamic programming      60—64 78 82 84 85 86 109
Algorithms, gap cost penalties      70—72
Algorithms, global alignment      58—64 94—99
Algorithms, heuristic      82—84
Algorithms, in evolutionary analysis      106 110—112
Algorithms, in genetic mapping      35—36
Algorithms, in physical mapping      46—51
Algorithms, K-best alignments      76—78
Algorithms, local alignment      65—70 99—106
Algorithms, multiple alignments      73—76
Alleles      6
Amino acids      4 57 “Protein “Sequence
Amplification      see “Polymerase chain reaction”
Ancestry      see “Evolutionary analysis”
ANREP systems      87
Antidiagonals      62 79—80
APC gene      34 37—38
Approximate pattern matching      78—79 86
Approximate repeats      87
ARIADNE systems      87
Assay techniques      2—3
Autosomes      26
Base pairs      8 26 48 153 154 163 179 185 188 189 191 194 204 249 “Thymine” “Cystosine” “Guanine” “Uracil”)
Bayesian statistics      35
Bernoulli random variables      102 125
Biochemistry      2—5
Biosequences      see “Databases of DNA sequences” “Sequence “Sequencing
BLASTA algorithm      82—84
Booth — Leuker algorithm      50—51
BRCAl (breast cancer) gene      33
Cancer      33 34 37—42 58 91 183 196
Catenanes      205 212
Cauchy’s formula      136
Cellular structures      9
Chaperonins      238—239
Chen — Stein method      102 106 110
Chimeras      51
Chirality      213—215
Chromosomal walking      17 18 42 43
Clones and cloning      13 14 26 42—43 209
Closed circular DNA      153—154 155 156 157 181 204
Coalescent      117 119—121
Coalescent, combinatorial structures      119 136—148
Coalescent, Ewens sampling formula      119 122—124 136—139
Coalescent, K-allele model      130—132
Coalescent, likelihood methods      146—148
Coalescent, tree construction and movement      124—127 (see also “Finitely-many-sites model” “Infinitely-manysites
Codons      12 115 239
Colon cancer      34 37—42
Combinatorics      119 136—148 185
Computing time and memory capacity, algorithmic efficiencies      35—36 84—86 87
Computing time and memory capacity, approximate pattern matching      79 87
Computing time and memory capacity, dynamic programming, algorithms      62—63 64 68 83 84
Computing time and memory capacity, gap cost functions      72
Computing time and memory capacity, heuristic algorithms      83—84
Computing time and memory capacity, K-best paths      77
Computing time and memory capacity, multiple alignments      75
Computing time and memory capacity, parallel processing      79—81 84
Computing time and memory capacity, sublinear similarity searches      84—85
Consecutive ones property      50
Consensus scores      76
Contigs      47—50
Crick and Watson model      153 204—205
Crossovers      27—29
Cruciforms      154
Crystallography      202 203 240
Cystic fibrosis (CF)      16—18 20—21 26
Cytosine (C)      8 9 99
Databases of DNA sequences      13 17 56 81 87
Databases of DNA sequences, similarity searches in      78—79 82—86 87 91—92 94 BLASTA”)
Dayhoff matrix      66 67 83
Diagnostics      see “Genetic diagnostics”
Difference measures      72—73
Diffusion processes      37—42 148
Dimers      212
DNA (deoxyribonucleic acid)      8—9 92
DNA (deoxyribonucleic acid), primers      13 15 16
DNA (deoxyribonucleic acid), protein binding      166—167 168 170—171 181
DNA (deoxyribonucleic acid), transcription      9—12 154 179 196—198 204—205 “Protein “Sequence “Sequencing “Strand “Supercoiling”)
DNA polymerases      8 16 154
DNA polymorphisms and mutations      8—9 16—17 26 30 34 57 106
DNA polymorphisms and mutations, as markers      31 34
DNA polymorphisms and mutations, in evolutionary analysis      114—135
DNA polymorphisms and mutations, in mitochondria      115—116 117 118 148—149
DNA polymorphisms and mutations, minimal cost alignments      72—73
DNA polymorphisms and mutations, rates of      66 67 116 117 124—125
Dot plots      68 70
Duplex unwinding elements (DUEs)      183 194 195
Dynamic programming algorithm      60—64 78 82 84 85 86 109 251
Edit graphs      59—61 68—70 75
Effective population size      117
Efficient algorithms      35—36 84—86 87
Electron microscopy      202 211 227
Electrostatic interactions      251
Energetics      154 180 182 186—195
Enzymes      3 7 180 238
Eve hypothesis      116
Evolutionary analysis      57—58 90—94
Evolutionary analysis, coalescent structures      117 119—135 148—149
Evolutionary analysis, common origins      57 248
Evolutionary analysis, extremal statistical methods      106—112
Evolutionary analysis, minimal cost alignments      72—73
Evolutionary analysis, multiple alignments      73 76
Evolutionary analysis, random combinatorial structures      136—148
Evolutionary analysis, trees      73 76 87 124 129 132 266
Evolutionary analysis, use of mitochondrial DNA      57—58 90—94 115—116 117 148—149
Ewens sampling formula (ESF)      119 122—124 136—139
Extremal statistical methods      106—112
Extremal statistical methods, global sequence comparisons      94—99
Extremal statistical methods, local sequence comparisons      99—106
False negatives and positives      51
Familial adenomatous polyopsis (FAP)      37—38
FASTA algorithm      82 83 84
Fingerprinting methods      42—47
Finitely-many-sites model      132—135
Fleming — Viot process      148
Foldases      237—238
Fourier transforms, coefficient      240
Fractionation      2—3
Free energy      154 180 182 186—195
Gap costs      70—72 77—78
Gaussian processes      41
Gel electrophoresis      210—211 227
GENBANK database      81
Gene splicing      see “Recombinant DNA technology”
Gene therapy      18
Generalized Levenshtein measure      73 87
genetic code      12 239
Genetic diagnostics      16 17
Genetic distance      28—29
Genetic heterogeneity      34
Genetic maps and mapping      16 18—19 26 27—30 51
Genetic maps and mapping, and incomplete pedigree information      30 31 34—35
Genetic maps and mapping, and maximum likelihood estimation      34—42
Genetic maps and mapping, and non-Mendelian genetics      30 31 33—34
Genetic maps and mapping, markers in      31
Genetic markers      31 34 42
Genetics      5—7
Genotype      38 40
Geometry      166 203 210 211 220 223
Geometry, descriptors and methods      155—163 (see also “Topology”)
Global alignment      5 58—64 94—99
Global alignment, maximum-scoring      63

Graph theory      46 51
Guanine (G)      8 9 99
Haldane mapping function      29 41
Helical periodicity      154
Helix      8 9 153
Helix, destabilization      184 188 196
Heterozygotes      6 16 31
Heuristic algorithms      82—84
Hierarchical condensation methods      248—251
Histones      154 175
HIV protease structure      254—255
Homeomorphisms      212—213
Homology modeling      252
Homozygotes      6 31
Human genome project      18—22 26
Hydrophilic side chains      244 253 263
Hydrophobic side chains      244 245 253
Hydrophobicity      4
In vitro assays      3
Incomplete penetrance      31 33 34
Independent assortment      29
Indexing, of databases      87
Infmitely-many-sites/alleles model      122 124 125 127—130
Isomerases      238
K-allele model      130—132
K-best alignments      76—78
kDNA (kinetoplast DNA)      231
Kingman’s subadditive ergodic theorem      97
Knot theory      212 (see also “Tangles and knots”)
Large Deviation Theory of Diffusion Processes      37—42
Levenshtein measure      73 87
LexA binding sites      198—199
Ligases      13
Likelihood methods      34—42 146—148
Linear DNA      155 156
Linking number (Lk)      155 157—158 163—164 173—174 181
Linking number (Lk), mini chromosomes      175 177
Linking number (Lk), surface      167—171 173—174
Linking number (Lk), topoisomerase reactions      164—166
Local alignment      5 65—70 99—106
Longest common subsequence      99
Macromolecules      3
Mapping      see “Genetic maps and mapping” “Physical “Restriction “Sequencing
markers      see “Genetic markers”
Markov models, processes      36 146—147 249
Maximum Likelihood Estimation      34—35
Maximum likelihood estimation, and efficient algorithms      35—36
Maximum likelihood estimation, and statistical significance      37—42
Measure-valued diffusions      148
Membrane-bound transporters      17—18 20
Mendelian genetics      5—7 27 31
Min (multiple intestinal neoplasia) trait      38—39
Minichromosomes      174—177
Mirror images      213—215
Mismatch ratio      86
Mitochondrial DNA (mtDNA)      115—116 117 118 135 148—149 204
mobius      143 181
Molecular biology, overview      7—12
Monte Carlo methods      146—147 149 241
Morgans      28
mRNA (messenger RNA)      9 12 92
Multiple alignments      73—76
Multiple minima problem      241
Mutation      see “DNA polymorphisms and mutations”
Myoglobin      265—266
Native American population studies      116 117
Neighborhood concept      83
Neural networks      259—263
Nonadditive scoring schemes      87
Nuclear magnetic resonance (NMR)      203 240
Nucleic acids      3
Nucleosomes      154 166 174—177
nucleotides      8 57 118 204
Nucleotides, distances      29 81
Oncogenes      58 91 196
Ornstein — Uhlenbeck process      41
Overwinding      154
Packing density      252
Palindromes      87
Papillomavirus      196 199—200
Parallel computing      79—81 84 87
Penetrance      31 33 35
Phenocopy      34
Phenotype      38 40
Physical maps and mapping      17 19 26 29
Physical maps and mapping, fingerprinting methods      42—47
Phytogeny      73 76 87
PIR database      81
PLANS (Pattern Language for Amino and Nucleic Acids Sequences)      263—264
Platelet-derived growth factor (PDGF)      9
Plectonemic forms      154 156 169 170 215—216
Poisson distributions      144
Poisson distributions, Boltzmann equation      254
Poisson distributions, Dirichlet distribution      144
Poisson distributions, in coalescent trees      121 124—127
Poisson distributions, in sequence comparisons      29 100—104 108—110
Poly-adenylation      196
Polygenic inheritance      34
Polymerase chain reaction (PCR)      13 15 16 46
Polymorphism      see “DNA polymorphisms and mutations”
Polyoma virus      196
Primers      13 15 16
Principle of optimality      63
Probabilistic combinatorics      136
Processing time      see “Computing time and memory capacity”
Protein folding      5 12 236—248
Protein folding, hierarchical condensation methods      248—251 256—265
Protein folding, prediction of      5 254—255 265—266
Protein folding, threading methods      248—254
Proteins      3—5 7—8 57 92 “Protein “Sequence
Public databases      see “Databases of DNA sequences”
Pure breeding      5
Purines (R)      99 117 200
Pyrimidines (Y)      99 117 118 123 128 200
QUEST systems      87
R-group      237
Rational tangles      218—221 228—229
RecA binding      198—199 211 227
Recessive traits      16
Recombinant DNA technology      13—16 17
Recombination      27—28 205 213 225—230
Recombination, frequency      28—30 31 35
Recombination, site-specific      207—212 222—225
Replication processes      92 154 179—180 183 204
Resolvase      213 225—230
Restriction enzymes      13
Restriction fragment lists      45—46
Restriction maps      44—45 87
Ribosomes      9 10 12 92
RNA (ribonucleic acid)      9 179 196 237
RNA (ribonucleic acid), evolutionary analysis      92—93 106—107 110—112
RNA (ribonucleic acid), polymerase      9
RNA (ribonucleic acid), rRNA      92 93 106 107 110 112 “tRNA”)
Rule-based methods      263—264
Scoring schemes, gap cost penalties      70—72
Scoring schemes, global alignments      59—64
Scoring schemes, K-best alignments      76—78
Scoring schemes, local alignments      65—68
Scoring schemes, minimal cost alignments      72—73
Scoring schemes, multiple alignments      74—76
Scoring schemes, nonadditive      87
Scoring schemes, unit-cost      58—59 86
Sedimentation rate      100
self-replication      92
Sequence similarity, and comparison      56—58 86—87 91 199
Sequence similarity, approximate pattern matching      78—79 86
Sequence similarity, database searches      78—79 82—86 87 91—92 94
Sequence similarity, difference measures      72—73
Sequence similarity, gap cost penalties      70—72
Sequence similarity, global alignment      5 58—64 94—99

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