Bioinformatics with Python Cookbook: Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology,2nd Edition
Authors: Tiago Antao
ISBN-10: 1789344697
ISBN-13: 9781789344691
Edition 版次: 2nd Revised edition
Publication Date 出版日期: 2018-11-30
Print Length 页数: 360 pages
Publisher finelybook 出版社: Packt
Book Description
By finelybook
Discover modern,next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data
Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data.
This book covers next-generation sequencing,genomics,metagenomics,population genetics,phylogenetics,and proteomics. You’ll learn modern programming techniques to analyze large amounts of biological data. With the help of real-world examples,you’ll convert,analyze,and visualize datasets using various Python tools and libraries.
This book will help you get a better understanding of working with a Galaxy server,which is the most widely used bioinformatics web-based pipeline system. This updated edition also includes advanced next-generation sequencing filtering techniques. You’ll also explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks such as Dask and Spark.
By the end of this book,you’ll be able to use and implement modern programming techniques and frameworks to deal with the ever-increasing deluge of bioinformatics data.
What you will learn
Learn how to process large next-generation sequencing (NGS) datasets
Work with genomic dataset using the FASTQ,BAM,and VCF formats
Learn to perform sequence comparison and phylogenetic reconstruction
Perform complex analysis with protemics data
Use Python to interact with Galaxy servers
Use High-performance computing techniques with Dask and Spark
Visualize protein dataset interactions using Cytoscape
Use PCA and Decision Trees,two machine learning techniques,with biological datasets
contents
1 Python and the Surrounding Software Ecology
2 Next-Generation Sequencing
3 Working with Genomes
4 Population Genetics
5 Population Genetics Simulation
6 Phylogenetics
7 Using the Protein Data Bank
8 Bioinformatics Pipelines
9 Python for Big Genomics Datasets
10 Other Topics in Bioinformatics
11 Advanced NGS Processing
