Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Bioinformatics with Python Cookbook
  • Toc
  • feedback
Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

By : Tiago Antao
4 (8)
close
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)
close

Playing recursively with trees

This is not a book about programming in Python, as the topic is vast. Having said that, it’s not common for introductory Python books to discuss recursive programming at length. Usually, recursive programming techniques are well tailored to deal with trees. It is also a required programming strategy with functional programming dialects, which can be quite useful when you perform concurrent processing. This is common when processing very large datasets.

The phylogenetic notion of a tree is slightly different from that in computer science. Phylogenetic trees can be rooted (if so, then they are normal tree data structures) or unrooted, making them undirected acyclic graphs. Additionally, phylogenetic trees can have weights on their edges. Therefore, be mindful of this when you read the documentation; if the text is written by a phylogeneticist, you can expect the tree (rooted and unrooted), while most other documents will use undirected acyclic...

bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete