Bioinformatics with Python Cookbook

£46.99

Bioinformatics with Python Cookbook

Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology, 2nd Edition

Computational biology / bioinformatics Programming and scripting languages: general Computer science

Author: Tiago Antao

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Language: English

Published by: Packt Publishing

Published on: 30th November 2018

Format: LCP-protected ePub

Size: 360 pages

ISBN: 9781789349986


Discover modern, next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data

Key Features

Perform complex bioinformatics analysis using the most important Python libraries and applications

Implement next-generation sequencing, metagenomics, automating analysis, population genetics, and more

Explore various statistical and machine learning techniques for bioinformatics data analysis

Book Description

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 proteomics 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

Who this book is for

This book is for data scientists, bioinformatics analysts, researchers, and Python developers who want to address intermediate-to-advanced biological and bioinformatics problems using a recipe-based approach. Working knowledge of the Python programming language is expected.

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