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Key benefits

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

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, 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.

Who is this book 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.

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

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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Paul Darby Oct 16, 2022

If you are proficient with python and need a good reference book for bioinformatics. This book covers many of the important applications one may come across in bioinformatics. From basic NCBI I/O applications to NGS this book covers many of the topics with excellent code examples. The book covers several important topics in scientific programming like Machine Learning, NUMPY, PANDAS and DOCKER which are some core tools used in the data sciences.

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Seth Oct 17, 2022

Disclaimer: I was sent a copy of this book to review.I have been working in the bioinformatics industry for 5+ years on all manner of bioinformatics problems. It's a shame this book didn't enter my life sooner. It's both a cookbook, and more than that. Each sections recipes build upon themselves in a cohesive and useful manner. I've found myself just working through a 5-page recipe per day as a method of self study, and gaining exposure to some of the niche facets of bioinformatics that we don't tackle day-to-day.All the tools referenced are up to date, and while the methods for doing things may not always fall into "best practices" they are all good foundations that someone could start with an build upon. I specifically enjoyed the sections at the end about processing data with Dask / Zarr, and the section on population genomics, both of which I was able to make use of in my own work.Overall, I'd recommend this book both to those that have just started down the bioinformatics path and need sample code to get going on tasks (but have a least beginner Python knowledge), and to those who have already been at this a while and just want to see some new and updated ways of doing things.

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Qirui Cui Sep 28, 2022

There are many books explaining the need for bioinformatics using Python, its methodology, and the myriad designs and implementation pathways that can be taken. The missing book is one that covers all of these from start to finish in a complete, detailed, and comprehensive fashion. From justifying the project, gathering requirements, developing the bioinformatic architectural framework, designing the proper approach for NGS data, integrating the data, generating advanced analytics, dealing with “shadow systems,” understanding and dealing with organizational relationships, managing the full project life cycle, and finally creating centers of excellence—this book covers the entire gambit of creating a sustainable bioinformatic system in Python environment.Mr. Tiago Antao’s deep understanding of technical implementations is only matched by his understanding of the underpinning rudiments behind many of the decision points in the development of the bioinformatic components. These rudiments will help you determine the best deployment options for your specific situation—so invaluable in today’s confusing and mixed messages bioinformatic world!I highly recommend this book to anyone just starting out in bioinformatics using Python particularly, who has a legacy environment that needs renovating or just wants to understand the entire implementation picture from start to finish. Mr. Tiago Antao’s mastery of all the critical implementation activities means you are receiving the best advice for creating a world-class python environment for bioinformatics that will last for long haul. Nicely done, Mr. Tiago Antao.

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Jun, D. Oct 14, 2022

A good entry-level book, covers quite a bit of the most popular packages, such as Biopython, scikit-learn, qiime, etc, covers sequencing, phylogenetics, metagenomics, etc., A good book to get familiar with the bioinformatics, it is especially good for one want to practice both python and bioinformatics, since it provide relatively good coverage for both.

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LadyGator Nov 12, 2022

I was very pleased to receive a review copy of Tiago Antao’s latest edition of the Bioinformatics with Python Cookbook.As an instructor and researcher who works in a bioinformatics core at a university in Boston, I can highly recommend this book as a resource for instruction as well as a practical guide to everyday problems in bioinformatics. Some highlights of the book are the excellent practical exercises which walkthrough common tasks, such as downloading data from NCBI and constructing meaningful plots using matplotlib.I was impressed with the more advanced materials, such as how to access the Galaxy platform using the API and running workflows with snakemake. The book assumes some familiarity with Python code, but even a beginner can follow the logic of the exercises and examples. Many helpful links are provided to freely available resources on the topics that are discussed. I would highly recommend this manual to put on your office bookshelf if you teach or use Python to analyze bioinformatics data.

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

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