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Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook - Third Edition

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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Understanding immutability

Another common trait of functional programming is that data structures are typically immutable. This is a tough concept to get around when you are used to imperative programming – the idea of programming without objects that change state over time. Here, we are going to see a simple example of making a function from the previous recipe work in an immutable way: that is, so that no objects are changed, and if we need to pass new information, we create new ones.

This recipe will give a short presentation on immutability from a data structure perspective. It will be, in a sense, the standard presentation that you can find in most books. Our main consideration, though, is to discuss mutability as a code design pattern, the topic of the following recipe. But for this, we need to understand immutability first.

We will be looking at two functions: one that mutates data structures and another that doesn’t. This will be done in the context of...

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