Revised Edition: Mastering Python Bioinformatics
Build essential skills in Jupyter, NumPy, pandas, Matplotlib, and Scanpy for the era of generative AI, and learn hands-on analysis of single-cell and RNA-Seq data.
Overview
The classic introductory Python text for bioinformatics returns in an eagerly awaited revised edition!
Learn everything from general-purpose Python techniques—handling large-scale data and visualizing results—to the fundamentals of single-cell and RNA-seq analysis.
With sample datasets and code examples, you can start practicing right away.
This revised edition adds new content on using generative AI, detailed explanations of Scanpy, and updates corresponding to the latest library versions.
Revised Edition: Mastering Python Bioinformatics
Build essential skills in Jupyter, NumPy, pandas, Matplotlib, and Scanpy for the era of generative AI, and learn hands-on analysis of single-cell and RNA-Seq data.
Selected Table of Contents
- Chapter 1: How to Use This Book & Initial Setup — Hiroshi Mori
- Chapter 2: Programming with Generative AI — Koichi Higashi
- Chapter 3: How to Use Jupyter Notebook — Yasuhiro Tanizawa
- Chapter 4: Fast-Track Python Course — Norio Shinkai
- Chapter 5: String Processing and Regular Expressions — Hiroki Takahashi
- Chapter 6: Biopython & Nucleotide Sequence Data Processing — Yasuhiro Tanizawa
- Chapter 7: Tabular Data Processing with pandas — Mika Sakamoto
- Chapter 8: RNA-Seq Count Data Processing — Mika Sakamoto
- Chapter 9: Visualization with Matplotlib & Seaborn — Jianqiang Sun
- Chapter 10: Statistical Hypothesis Testing & Model Selection — Hiroshi Mori
- Chapters 11–13: Single-Cell Analysis (Preprocessing, Dimensionality Reduction, Clustering) — Koichi Higashi
- Appendix A: Introduction to NumPy — Koichi Higashi
- Appendix B: Single-Cell Analysis with Scanpy — Koichi Higashi
…Plus index, author list, and a total of 13 chapters + 2 appendices.
