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Bioinformatics with Python Cookbook

You're reading from   Bioinformatics with Python Cookbook Solve advanced computational biology problems and build production pipelines with Python and AI tools

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Product type Paperback
Published in Dec 2025
Publisher Packt
ISBN-13 9781836642756
Length 618 pages
Edition 4th Edition
Languages
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Author (1):
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Shane Brubaker Shane Brubaker
Author Profile Icon Shane Brubaker
Shane Brubaker
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Toc

Table of Contents (22) Chapters Close

Preface 1. Chapter 1: Computer Specifications and Python Setup 2. Chapter 2: Basics of Data Manipulation FREE CHAPTER 3. Chapter 3: Modern Coding Practices and AI-Generated Coding 4. Chapter 4: Data Science and Graphing 5. Chapter 5: Alignment and Variant Calling 6. Chapter 6: Annotation and Biological Interpretation 7. Chapter 7: Genomes and Genome Assembly 8. Chapter 8: Accessing Public Databases 9. Chapter 9: Protein Structure and Proteomics 10. Chapter 10: Phylogenetics 11. Chapter 11: Population Genetics 12. Chapter 12: Metabolic Modeling and Other Applications 13. Chapter 13: Genome Editing 14. Chapter 14: Cloud Basics 15. Chapter 15: Workflow Systems 16. Chapter 16: More Workflow Systems 17. Chapter 17: Deep Learning and LLMs for Nucleic Acid and Protein Design 18. Chapter 18: Single-Cell Technology and Imaging 19. Chapter 19: Unlock Your Exclusive Benefits 20. Index 21. Other Books You May Enjoy

Computer Specifications and Python Setup

We will start by installing the basic software that is required for most of this book. This will include the Python distribution, some fundamental Python libraries, and our Jupyter Notebook environment. We will also set up our GitHub environment and gain access to the repository for the book. As different users have different requirements, we will cover two different approaches for installing the software. One approach is using the Anaconda Python (http://docs.continuum.io/anaconda/) distribution and the other is via Docker (a server virtualization method based on containers sharing the same operating system kernel; please refer to https://www.docker.com/). This will still install Anaconda for you but inside a container.

If you are using a Windows-based operating system, you are strongly encouraged to consider changing your operating system or using Docker via some of the existing options on Windows. On macOS, you should be able to install most of the software natively, though Docker is also available. Learning using a local distribution (Anaconda or something else) is easier than Docker, but given that package management can be complex in Python, Docker images provide a level of stability.

Most modern data scientists use a Mac due to the ease with which you can interact with a native Linux-style operating system. We recommend using a similar computer for this book. In the Technical requirements section, we provide the specifications of the computer and libraries used to develop this book. In most cases, deviations from such a system should work fine with minimal modifications, but if you have trouble, you can try the Docker container. Another alternative could be to use a cloud workstation (some options follow).

In this chapter, we will cover the following recipes:

  • Installing the required software with Anaconda
  • Installing the required software with Docker
  • Introduction to Jupyter Notebook

In this chapter, we will first install some prerequisite software – details of which are given in the Technical requirements section. Each recipe will then take you through the software and the steps that are needed to install it. Each chapter and section might have extra requirements on top of these – we will make those clear as the book progresses. An alternative way to start is to use the Installing the required software with Docker recipe, after which everything will be taken care of for you via a Docker container.

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