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Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

By : Tiago Antao
4 (8)
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Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

4 (8)
By: Tiago Antao

Overview of this book

Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python. This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you’ll explore the application of machine learning algorithms in bioinformatics. By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale.
Table of Contents (15 chapters)
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Phylogenetics

Phylogenetics is the application of molecular sequencing that is used to study the evolutionary relationship among organisms. The typical way to illustrate this process is through the use of phylogenetic trees. The computation of these trees from genomic data is an active field of research with many real-world applications.

In this book, we will take the practical approach that is mentioned to a new level: most of the recipes here are inspired by a recent study on the Ebola virus, researching the recent Ebola outbreak in Africa. This study is called Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak, by Gire et al., published in Science. It is available at https://pubmed.ncbi.nlm.nih.gov/25214632/. Here, we will try to follow a similar methodology to arrive at similar results to the paper.

In this chapter, we will use DendroPy (a phylogenetics library) and Biopython. The bioinformatics_phylo Docker image includes all the...

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