Revised Edition: Self-Study Python Bioinformatics Analysis - Learn the basics of Jupyter, NumPy, pandas, Matplotlib, and Scanpy to help you analyze si

This long-awaited revision of the classic Python textbook is here! Learn the fundamentals of bioinformatics, from general-purpose Python techniques like handling large-scale data and visualizing data with diagrams to single-cell and RNA-seq analysis. Sample data and code examples are included, so you can start learning by doing today. This revision adds detailed explanations of how to use generative AI and Scanpy, and includes updates to various libraries.

[Table of Contents] Revision Notes Introduction (First Edition)

Chapter 1: How to Use This Book and Preparation Chapter 2: Programming with Generative AI Chapter 3: Using Jupyter Notebook Chapter 4: Python Crash Course Chapter 5: String Processing Basics - Reading and Writing Files, Regular Expressions Chapter 6: Working with Base Sequence Data Using Biopython - Introduction to Object-Oriented Programming Chapter 7: Getting Started with pandas - Working with Tabular Data Chapter 8: Processing RNA-Seq Count Data - Practical Guide Chapter 9: Data Visualization - Creating Graphs with Matplotlib and Seaborn Chapter 10: Statistical Hypothesis Testing - From the Basics of Testing RNA-Seq Data to Model Selection Chapter 11: Single-Cell Analysis (1) - Preprocessing Table Data Chapter 12: Single-Cell Analysis (2) - Dimensionality Reduction Chapter 13: Single-Cell Analysis (3) - Clustering

Appendix A: Introduction to NumPy Appendix B: Single-Cell Analysis with Scanpy

Index List of Authors