Bioinformatics Biocomputing and Perl : An Introduction to Bioinformatics Computing Skills and Practice

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  • Format: Paperback
  • Copyright: 2004-07-02
  • Publisher: WILEY
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Bioinformatics, Biocomputing and Perl presents a modern introduction to bioinformatics computing skills and practice. Structuring its presentation around four main areas of study, this book covers the skills vital to the day-to-day activities of today's bioinformaticians. Book jacket.

Author Biography

<b>Michael Moorhouse</b> works as a Bioinformatics Researcher for Erasmus MC in Rotterdam, The Netherlands. He holds a B.Sc. from UMIST and an M.Sc. from The University of Manchester. Michael recently completed a Ph.D. from The University of Birmingham in the UK. He has been involved in numerous bioinformatics courses throughout the UK and Netherlands. This is Michael&#8217;s first book. <p> <b>Paul Barry</b> works as a Lecturer in Computing Science at The Institute of Technology, Carlow in Ireland. He holds a B.Sc. from The University of Ulster in Jordanstown, Northern Ireland and recently completed an M.Sc. from The Institute of Technology, Sligo in Ireland. He is the author of <i>Programming the Network with Perl</i> (Wiley, 2002).

Table of Contents

Prefacep. xv
Setting the Biological Scenep. 1
Introducing Biological Sequence Analysisp. 1
Protein and Polypeptidesp. 4
Generalised Models and their Usep. 5
The Central Dogma of Molecular Biologyp. 6
Genome Sequencingp. 10
The Example DNA-gene-protein system we will usep. 12
Where to from Herep. 13
Setting the Technological Scenep. 15
The Layers of Technologyp. 15
Finding perp. 17
Where to from Herep. 18
Working with Perlp. 19
The Basicsp. 21
Let's Get Started!p. 21
Iterationp. 26
More Iterationsp. 30
Selectionp. 34
There Really is MTOWTDIp. 36
Processing Data Filesp. 41
Introducing Patternsp. 44
Where to from Herep. 46
The Maxims Repeatedp. 46
Places to Put Thingsp. 49
Beyond Scalarsp. 49
Arrays: Associating Data with Numbersp. 49
Hashes: Associating Data with Wordsp. 60
Where to from Herep. 68
The Maxims Repeatedp. 68
Getting Organisedp. 71
Named Blocksp. 71
Introducing Subroutinesp. 73
Creating Subroutinesp. 74
Visibility and Scopep. 85
In-built Subroutinesp. 90
Grouping and Reusing Subroutinesp. 92
The Standard Modulesp. 96
CPAN: The Module Repositoryp. 96
Where to from Herep. 100
The Maxims Repeatedp. 100
About Filesp. 103
I/O: Input and Outputp. 103
Reading Filesp. 105
Writing Filesp. 116
Chopping and Chompingp. 118
Where to from Herep. 119
The Maxims Repeatedp. 119
Patterns, Patterns and More Patternsp. 121
Pattern Basicsp. 121
Introducing the Pattern Metacharactersp. 124
Anchorsp. 132
The Binding Operatorsp. 134
Remembering What Was Matchedp. 135
Greedy by Defaultp. 137
Alternative Pattern Delimitersp. 138
Another Useful Utilityp. 139
Substitutions: Search and Replacep. 140
Finding a Sequencep. 142
Where to from Herep. 146
The Maxims Repeatedp. 146
Perl Grabbagp. 147
Introductionp. 147
Strictnessp. 147
Perl One-linersp. 149
Running Other Programs from perp. 152
Recovering from Errorsp. 153
Sortingp. 155
HERE Documentsp. 159
Where to from Herep. 160
The Maxims Repeatedp. 161
Working with Datap. 163
Downloading Datasetsp. 165
Let's Get Datap. 165
Downloading from the Webp. 165
Where to from Herep. 171
The Maxims Repeatedp. 171
The Protein Databankp. 173
Introductionp. 173
Determining Biomolecule Structuresp. 174
The Protein Databankp. 177
The PDB Data-file Formatsp. 179
Accessing Data in PDB Entriesp. 182
Accessing PDB Annotation Datap. 183
Contact Mapsp. 192
STRIDE: Secondary Structure Assignmentp. 196
Assigning Secondary Structuresp. 197
Introducing the mmCIF Protein Formatp. 205
Where to from Herep. 210
The Maxims Repeatedp. 210
Non-redundant Datasetsp. 211
Introducing Non-redundant Datasetsp. 211
Non-redundant Protein Structuresp. 213
Where to from Herep. 217
The Maxims Repeatedp. 217
Databasesp. 219
Introducing Databasesp. 219
Available Database Systemsp. 224
SQL: the Language of Databasesp. 226
A Database Case Study: MERp. 227
Where to from Herep. 269
The Maxims Repeatedp. 269
Databases and Perlp. 273
Why Program Databases?p. 273
Perl Database Technologiesp. 274
Preparing Perlp. 275
Programming Databases with DBIp. 276
Customising Outputp. 282
Customising Inputp. 285
Extending SQLp. 289
Where to from Herep. 292
The Maxims Repeatedp. 292
Working with the Webp. 295
The Sequence Retrieval Systemp. 297
An Example of What's Possiblep. 297
Why SRS?p. 298
Using SRSp. 298
Where to from Herep. 300
The Maxims Repeatedp. 300
Web Technologiesp. 303
The Web Development Infrastructurep. 303
Creating Content for the WWWp. 305
Preparing Apache for Perlp. 310
Sending Data to a Web Serverp. 315
Web Databasesp. 320
Where to from Herep. 327
The Maxims Repeatedp. 327
Web Automationp. 329
Why Automate Surfing?p. 329
Automated Surfing with Perlp. 330
Where to from Herep. 335
The Maxims Repeatedp. 336
Working with Applicationsp. 337
Tools and Datasetsp. 339
Introductionp. 339
Sequence Databasesp. 340
General Concepts and Methodsp. 347
Introducing Bioinformatics Toolsp. 357
BLASTp. 362
Where to from Herep. 371
The Maxims Repeatedp. 371
Applicationsp. 373
Introductionp. 373
Scientific Background to Mer Operonp. 374
Downloading the Raw DNA Sequencep. 377
Initial BLAST Sequence Similarity Searchp. 378
GeneMarkp. 380
Structural Prediction with SWISS-MODELp. 388
DeepView as a Structural Alignment Toolp. 396
PROSITE and Sequence Motifsp. 401
Phylogeneticsp. 407
Where to from Here?p. 410
The Maxims Repeatedp. 411
Data Visualisationp. 413
Introducing Visualisationp. 413
Displaying Tabular Data Using HTMLp. 415
Creating High-quality Graphics with GDp. 422
Plotting Graphsp. 431
Where to from Herep. 439
The Maxims Repeatedp. 439
Introducing Bioperlp. 441
What is Bioperl?p. 441
Bioperl's Relationship to Project Ensemblp. 442
Installing Bioperlp. 442
Using Bioperl: Fetching Sequencesp. 444
Remote BLAST Searchesp. 448
Where to from Herep. 451
The Maxims Repeatedp. 452
Appendix Ap. 453
Appendix Bp. 457
Appendix Cp. 459
Appendix Dp. 461
Appendix Ep. 467
Appendix Fp. 471
Indexp. 475
Table of Contents provided by Rittenhouse. All Rights Reserved.

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