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Tiago Antao - Bioinformatics with Python Cookbook: Use modern Python libraries and applications to solve real-world computational biology problems, 3rd Edition

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Tiago Antao Bioinformatics with Python Cookbook: Use modern Python libraries and applications to solve real-world computational biology problems, 3rd Edition
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Bioinformatics with Python Cookbook: Use modern Python libraries and applications to solve real-world computational biology problems, 3rd Edition: summary, description and annotation

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Discover modern, next-generation sequencing libraries from the powerful Python ecosystem to perform cutting-edge research and analyze large amounts of biological data

Key Features
  • Perform complex bioinformatics analysis using the most essential Python libraries and applications
  • Implement next-generation sequencing, metagenomics, automating analysis, population genetics, and much 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, 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, youll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. Youll 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, youll explore the application of machine learning algorithms in bioinformatics.

By the end of this bioinformatics Python book, youll 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.

What you will learn
  • Become well-versed with data processing libraries such as NumPy, pandas, arrow, and zarr in the context of bioinformatic analysis
  • Interact with genomic databases
  • Solve real-world problems in the fields of population genetics, phylogenetics, and proteomics
  • Build bioinformatics pipelines using a Galaxy server and Snakemake
  • Work with functools and itertools for functional programming
  • Perform parallel processing with Dask on biological data
  • Explore principal component analysis (PCA) techniques with scikit-learn
Who this book is for

This book is for bioinformatics analysts, data scientists, computational biologists, researchers, and Python developers who want to address intermediate-to-advanced biological and bioinformatics problems. Working knowledge of the Python programming language is expected. Basic knowledge of biology will also be helpful.

Table of Contents
  1. Python and the Surrounding Software Ecology
  2. Using Data Processing Libraries: numpy, pandas, arrow, and zarr
  3. Next Generation Sequencing
  4. Advanced NGS Data Processing
  5. Working with Genomes
  6. Population Genetics
  7. Phylogenetics
  8. Using the Protein Data Bank
  9. Bioinformatics Pipelines
  10. Machine Learning for Bioinformatics
  11. Parallel Processing with Dask
  12. Functional and Asynchronous Programming

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Bioinformatics with Python Cookbook Third Edition Use modern Python libraries - photo 1
Bioinformatics with Python Cookbook Third Edition

Use modern Python libraries and applications to solve real-world computational biology problems

Tiago Antao

BIRMINGHAMMUMBAI Bioinformatics with Python CookbookThi rd Edition Copyright - photo 2

BIRMINGHAMMUMBAI

Bioinformatics with Python CookbookThird Edition

Copyright 2022 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Publishing Product Manager: Devika Battike

Senior Editor: David Sugarman

Content Development Editor: Joseph Sunil

Technical Editor: Rahul Limbachiya

Copy Editor: Safis Editing

Project Coordinator: Farheen Fathima

Proofreader: Safis Editing

Indexer: Pratik Shirodkar

Production Designer: Shankar Kalbhor

Marketing Coordinator: Priyanka Mhatre

First published: June 2015

Second edition: November 2018

Third edition: September 2022

Production reference: 1090922

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-80323-642-1

www.packt.com

Contributors
About the author

Tiago Antao is a bioinformatician who is currently working in the field of genomics. A former computer scientist, Tiago moved into computational biology with an MSc in bioinformatics from the Faculty of Sciences at the University of Porto, Portugal, and a PhD on the spread of drug-resistant malaria from the Liverpool School of Tropical Medicine, UK. Post his doctoral, Tiago worked with human datasets at the University of Cambridge, UK and with mosquito whole-genome sequencing data at the University of Oxford, UK, before helping to set up the bioinformatics infrastructure at the University of Montana, USA. He currently works as a data engineer in the biotechnology field in Boston, MA. He is one of the co-authors of Biopython, a major bioinformatics package written in Python.

About the reviewers

Urminder Singh is a bioinformatician, computer scientist, and developer of multiple open source bioinformatics tools. His educational background encompasses physics, computer science, and computational biology degrees, including a Ph.D. in bioinformatics from Iowa State University, USA.

His diverse research interests include novel gene evolution, precision medicine, sociogenomics, machine learning in medicine, and developing tools and algorithms for big heterogeneous data. You can visit him online at urmi-21.github.io.

Tiffany Ho works as a bioinformatics associate at Embark Veterinary. She holds a BSc from the University of California, Davis in genetics and genomics, and an MPS from Cornell University in plant breeding and genetics.

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