Python programming for biology bioinformatics and beyond
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| Hauptverfasser: | , |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
[2015]
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| Ausgabe: | First published |
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| Online-Zugang: | Klappentext Inhaltsverzeichnis |
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MARC
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| 245 | 1 | 0 | |a Python programming for biology |b bioinformatics and beyond |c Tim J. Stevens, MRC Laboratory of Molecular Biology; Wayne Boucher, University of Cambridge |
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Datensatz im Suchindex
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| adam_text | Python Programming for Biology
Bioinformatics and Beyond
Do you have a biological question that could be readily answered by computa-
tional techniques, but little experience in programming? Do you want to learn
more about the core techniques used in computational biology and bioinfor-
matics? Written in an accessible style, this guide provides a foundation for both
newcomers to computer programming and those who want to learn more about
computational biology. The chapters guide the reader through: a complete begin-
ners’ course to programming in Python, with an introduction to computing jargon;
descriptions of core bioinformatics methods with working Python examples;
scientific computing techniques, including image analysis, statistics and machine
learning. This book also functions as a language reference written in straightfor-
ward English, covering the most common Python language elements and a
glossary of computing and biological terms. This title will teach undergraduates,
postgraduates and professionals working in the life sciences how to program with
Python, a powerful, flexible and easy-to-use language.
Tim J, Stevens, a biochemist by training, is a Senior Investigator Scientist at the
MRC Laboratory of Molecular Biology in Cambridge. He researches three-
dimensional genome architecture and provides computational biology oversight,
development and training within the Cell Biology Division.
Wayne Boucher, a mathematician and theoretical physicist by training, is a Senior
Post-Doctoral Associate and computing technician for the Department of Biochem-
istry at the University of Cambridge. He teaches undergraduate mathematics and
postgraduate programming courses. Wayne is currently developing software for the
analysis of biological molecules by nuclear magnetic resonance spectroscopy.
Contents
H
Preface page ix
Acknowledgements X
1 Prologue 1
Python programming for biology 1
2 A beginners’ guide 5
Programming principles 5
Basic data types 9
Program flow 13
3 Python basics 17
Introducing the fundamentals 17
Simple data types 24
Collection data types 32
Importing modules 40
4 Program control and logic 43
Controlling command execution 43
Conditional execution 46
Loops 51
Error exceptions 57
Further considerations 61
5 Functions 63
Function basics 63
Input arguments 67
Variable scope 72
Further considerations 74
6 Files 78
Computer files 78
Reading files 81
File reading examples 84
Writing files 92
Further considerations 97
7 Object orientation 100
Creating classes 100
Further details 112
VI
Table of Contents
8 Object data modelling 117
Data models 117
Implementing a data model 119
Refined implementation 132
9 Mathematics 137
Using Python for mathematics 137
Linear algebra 144
NumPy package 150
Linear algebra examples 154
10 Coding tips 160
Improving Python code 160
A compendium of tips 164
11 Biological sequences 181
Bio-molecules for non-biologists 181
Using biological sequences in computing 188
Simple sub-sequence properties 193
Obtaining sequences with BioPython 205
12 Pairwise sequence alignments 208
Sequence alignment 208
Calculating an alignment score 214
Optimising pairwise alignment 219
Quick database searches 225
13 Multiple-sequence alignments 232
Multiple alignments 232
Alignment consensus and profiles 233
Generating simple multiple alignments in Python 239
Interfacing multiple-alignment programs 241
14 Sequence variation and evolution 244
A basic introduction to sequence variation 244
Similarity measures 253
Phylogenetic trees 262
15 Macromolecular structures 278
An introduction to 3D structures of bio-molecules 278
Using Python for macromolecular structures 286
Coordinate superimposition 299
External macromolecular structure modules 312
16 Array data 316
Multiplexed experiments 316
Reading array data 319
Table of Contents vii
The ‘Microarray’ class 323
Array analysis 336
17 High-throughput sequence analyses 341
High-throughput sequencing 341
Mapping sequences to a genome 344
Using the HTSeq library 355
18 Images 361
Biological images 361
Basic image operations 364
Adjustments and filters 369
Feature detection 378
19 Signal processing 382
Signals 382
Fast Fourier transform 385
Peaks 389
20 Databases 401
A brief introduction to relational databases 401
Basic SQL 402
Designing a molecular structure database 406
21 Probability 421
The basics of probability theory 421
Restriction enzyme example 425
Random variables 431
Markov chains 438
22 Statistics 454
Statistical analyses 454
Simple statistical parameters 457
Statistical tests 462
Correlation and covariance 480
23 Clustering and discrimination 486
Separating and grouping data 486
Clustering methods 490
Data discrimination 504
24 Machine learning 511
A guide to machine learning 511
^-nearest neighbours 515
Self-organising maps 518
Feed-forward artificial neural networks 523
Support vector machines 534
Table of Contents
25 Hard problems 545
Solving hard problems 545
The Monte Carlo method 547
Simulated annealing 557
26 Graphical interfaces 566
An introduction to graphical user interfaces 566
Python GUI examples 568
27 Improving speed 582
Running things faster 582
Parallelisation 583
Writing faster modules 587
Appendices 606
Appendix 1 Simplified language reference 607
Appendix 2 Selected standard type methods and operations 621
Appendix 3 Standard module highlights 634
Appendix 4 String formatting 653
Appendix 5 Regular expressions 658
Appendix 6 Further statistics 668
Glossary 671
Index 696
The colour plates are to be found between pages 342 and 343
|
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| discipline | Biologie Informatik |
| edition | First published |
| format | Book |
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| language | English |
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| spellingShingle | Stevens, Tim J. 1976- Boucher, Wayne Python programming for biology bioinformatics and beyond Datenverarbeitung Biology Data processing Python (Computer program language) Bioinformatik (DE-588)4611085-9 gnd Python Programmiersprache (DE-588)4434275-5 gnd Biologie (DE-588)4006851-1 gnd |
| subject_GND | (DE-588)4611085-9 (DE-588)4434275-5 (DE-588)4006851-1 |
| title | Python programming for biology bioinformatics and beyond |
| title_auth | Python programming for biology bioinformatics and beyond |
| title_exact_search | Python programming for biology bioinformatics and beyond |
| title_full | Python programming for biology bioinformatics and beyond Tim J. Stevens, MRC Laboratory of Molecular Biology; Wayne Boucher, University of Cambridge |
| title_fullStr | Python programming for biology bioinformatics and beyond Tim J. Stevens, MRC Laboratory of Molecular Biology; Wayne Boucher, University of Cambridge |
| title_full_unstemmed | Python programming for biology bioinformatics and beyond Tim J. Stevens, MRC Laboratory of Molecular Biology; Wayne Boucher, University of Cambridge |
| title_short | Python programming for biology |
| title_sort | python programming for biology bioinformatics and beyond |
| title_sub | bioinformatics and beyond |
| topic | Datenverarbeitung Biology Data processing Python (Computer program language) Bioinformatik (DE-588)4611085-9 gnd Python Programmiersprache (DE-588)4434275-5 gnd Biologie (DE-588)4006851-1 gnd |
| topic_facet | Datenverarbeitung Biology Data processing Python (Computer program language) Bioinformatik Python Programmiersprache Biologie |
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