Bioinformatics: An Introduction

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Springer Science & Business Media, Aug 25, 2004 - Science - 244 pages
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An Introduction to Bioinformatics is intended to be a complete study companion for the advanced undergraduate or beginning graduate student. It is self-contained in the sense that whatever the starting point may be, the reader will gain insight into bioinformatics. Underlying the work is the belief that bioinformatics is a kind of metaphoric lens through which the entire field of biology can be brought into focus, admittedly as yet imperfect, and understood in a unified way. Reflecting the highly incomplete present state of the field, emphasis is placed on the underlying fundamentals and acquisitions of a broad and comprehensive grasp of the field as a whole.

Bioinformatics is interpreted as the application of information science to biology, in which it plays a fundamental and all-pervasive role. This interpretation enables a remarkably unified view of the entire field of biology to be taken and hence offers an excellent entry point into the life sciences for those for whom biology is unfamiliar.

 

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Contents

Introduction
1
Information
7
The nature of information
9
21 Structure and quantity
16
22 Constraint
19
221 The value of information
22
23 Accuracy meaning and effect
23
232 Meaning
24
962 Prokaryotic transcriptional regulation
128
964 RNA processing
131
97 Ontogeny development
132
971 r and K selection
133
972 Homeotic genes
134
98 Phylogeny and evolution
135
982 Sources of genome variation
140
99 Geological eras and taxonomy
141

233 Effect
28
24 Further remarks on information generation
29
The transmission of information
31
31 The capacity of a channel
34
32 Coding
36
33 Decoding
38
35 Noise
42
36 Error correction
44
37 Summary
46
Sets and combinatorics
47
42 Combinatorics
48
423 Unordered sampling without replacement
49
424 Unordered sampling with replacement
51
Probability and likelihood 51 The notion of probability
53
52 Fundamentals
54
521 Generalized union
56
522 Conditional probability
57
523 BernouUi triafe
59
53 Moments of distributions
61
531 Runs
62
532 The hypergeometric distribution
63
54 Likelihood
64
541 The maximum entropy method
67
Randomness and complexity
69
61 Random processes
73
62 Markov chains
74
621 Tlir entropy of a Markov process
75
63 Random walks
76
65 Complexity
78
Systems networks and circuits
83
71 General systems theory
84
711 Automata
86
712 Cellular automata
88
72 Networks
89
721 Trees
91
722 Complexity parameters
92
723 Dynamical properties
93
731 Some examples
95
733 Evolutionary systems
97
Biology
99
Introduction to Part II
101
82 Regulation
103
83 The concept of machine
105
The nature of living things
107
911 The structure of a cell
109
92 The cell cycle
111
921 The chromosome
114
922 The structure of genes and genome
116
93 Molecular mechanisms
121
932 Proofreading and repair
123
933 Recombination
124
94 Summary of sources of genome variation
125
95 Gene expression
126
96 Transcription
127
The molecules of life
145
102 Water
148
103 DNA
149
1031 Structure of DNA
154
104 RNA
155
1041 Folding of RNA
157
1051 Amino acids
158
1053 Experimental techniques for protein structure determination
163
1054 Protein structure overview
164
106 Poly sacchar ides
165
107 Lipids
166
Applications
169
Introduction to Part III
171
Genomics
175
121 DNA sequencin
176
1213 Sequencing
177
1214 Expressed sequence tags
178
122 Gene identification
179
1231 Database reliability
180
125 Intrinsic methods
184
1252 Signals
185
126 Beyond sequence
186
Proteomics
189
131 Transcriptomics
190
132 Proteomic analysis
195
1321 Two dimensional gel electrophoresis 2DGE
196
1322 Column chromatography
198
1323 Other kinds of electrophoresis
199
134 Isotope coded affinity tags ICAT
200
135 Protein microarrays
201
136 Protein expression patterns
202
137 Regulatory networks
203
Interactions
205
141 Basic intermolecular interactions
208
142 In vivo experimental methods
211
1422 Crosslinking
212
143 In vitro experimental methods
213
1431 Chromatography
214
1433 Protein chips
216
145 The immune repertoire
217
146 Small systems
219
Metabolomics and metabonomics
221
151 Data collection
222
152 Data analysis
223
153 Metabolic regulation
224
1532 The metabolic code
225
Medical applications
227
161 The genetic basis of disease
228
162 Diagnosis
229
163 Drug discovery and testing
230
Bibliography
233
Index
240
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