Python Programming for Biology Bioinformatics and Beyond 1st edition by Tim Stevens – Ebook PDF Instant Download/Delivery: 0521720095, 978-0521720090
Full download Python Programming for Biology Bioinformatics and Beyond 1st edition after payment
Product details:
ISBN 10: 0521720095
ISBN 13: 978-0521720090
Author: Tim Stevens
Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners’ 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 straightforward 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.
Python Programming for Biology Bioinformatics and Beyond 1st Table of contents:
Acknowledgements
1 Prologue
Python programming for biology
2 A beginners’ guide
Programming principles
Basic data types
Program flow
3 Python basics
Introducing the fundamentals
Simple data types
Collection data types
Importing modules
4 Program control and logic
Controlling command execution
Conditional execution
Loops
Error exceptions
Further considerations
5 Functions
Function basics
Input arguments
Variable scope
Further considerations
6 Files
Computer files
Reading files
File reading examples
Writing files
Further considerations
7 Object orientation
Creating classes
Further details
8 Object data modelling
Data models
Implementing a data model
Refined implementation
9 Mathematics
Using Python for mathematics
Linear algebra
NumPy package
Linear algebra examples
10 Coding tips
Improving Python code
A compendium of tips
11 Biological sequences
Bio-molecules for non-biologists
Using biological sequences in computing
Simple sub-sequence properties
Obtaining sequences with BioPython
12 Pairwise sequence alignments
Sequence alignment
Calculating an alignment score
Optimising pairwise alignment
Quick database searches
13 Multiple-sequence alignments
Multiple alignments
Alignment consensus and profiles
Generating simple multiple alignments in Python
Interfacing multiple-alignment programs
14 Sequence variation and evolution
A basic introduction to sequence variation
Similarity measures
Phylogenetic trees
15 Macromolecular structures
An introduction to 3D structures of bio-molecules
Using Python for macromolecular structures
Coordinate superimposition
External macromolecular structure modules
16 Array data
Multiplexed experiments
Reading array data
The ‘Microarray’ class
Array analysis
17 High-throughput sequence analyses
High-throughput sequencing
Mapping sequences to a genome
Using the HTSeq library
18 Images
Biological images
Basic image operations
Adjustments and filters
Feature detection
19 Signal processing
Signals
Fast Fourier transform
Peaks
20 Databases
A brief introduction to relational databases
Basic SQL
Designing a molecular structure database
21 Probability
The basics of probability theory
Restriction enzyme example
Random variables
Markov chains
22 Statistics
Statistical analyses
Simple statistical parameters
Statistical tests
Correlation and covariance
23 Clustering and discrimination
Separating and grouping data
Clustering methods
Data discrimination
24 Machine learning
A guide to machine learning
k-nearest neighbours
Self-organising maps
Feed-forward artificial neural networks
Support vector machines
25 Hard problems
Solving hard problems
The Monte Carlo method
Simulated annealing
26 Graphical interfaces
An introduction to graphical user interfaces
Python GUI examples
27 Improving speed
Running things faster
Parallelisation
Writing faster modules
Appendices
Appendix 1 Simplified language reference
Appendix 2 Selected standard type methods and operations
Appendix 3 Standard module highlights
Appendix 4 String formatting
Appendix 5 Regular expressions
Appendix 6 Further statistics
Glossary
Index
People also search for Python Programming for Biology Bioinformatics and Beyond 1st :
python programming for biology bioinformatics and beyond
python programming for biology bioinformatics and beyond pdf
how is python used in biology
use of python in bioinformatics
how to learn python for bioinformatics
Tags: Tim Stevens, Python Programming, Biology Bioinformatics