BIOINFORMATICS BOOKS

Top Bioinformatics Books to Read in 2026!

Bioinformatics has evolved over time from developing a few databases to creating complex algorithms and software models that can be used to solve complicated biological problems. To keep up with this fast-paced field of study, it has become necessary to read books providing in-depth knowledge about different aspects of bioinformatics. Here are some highly recommended bioinformatics books for people who want to explore this area further:

Computational Structural Biology and Drug Discovery

Molecular Docking for Computer-Aided Drug Design

Bioinformatics and Computational Biology in Drug Discovery and Development

Computational Drug Discovery and Design

Pathway Analysis for Drug Discovery: Computational Infrastructure and Applications

Bioinformatics

Bioinformatics: Sequence and Genome Analysis by David Mount

Essential Bioinformatics

Understanding Bioinformatics

An Introduction to Bioinformatics Algorithms

Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, 2nd Edition

Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, 3rd Edition

Guide to Human Genome Computing

Introduction to Bioinformatics

Problems and Solutions in Biological Sequence Analysis

Bioinformatics: Genes, Proteins and Computers

Computational Biology: Unix/Linux, Data Processing and Programming

Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology

Algorithms in Bioinformatics: A Practical Introduction

Computational Methods for Mass Spectrometry Proteomics

Bioinformatics and Functional Genomics

Introduction to Bioinformatics

Bioinformatics: The Machine Learning Approach

Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids

Molecular Evolution and Phylogenetics

Bioinformatics Methods: From Omics to Next Generation Sequencing

Gene Genealogies, Variation and Evolution: A primer in coalescent theory

Bioinformatics and Molecular Evolution

Discovering Genomics, Proteomics and Bioinformatics

Microarray Bioinformatics

A Practical Introduction to the Simulation of Molecular Systems

The Art of Molecular Dynamics Simulation

Current Protocols in Bioinformatics

Inferring Phylogenies

RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods

Proteomics

Introduction to Computational Proteomics

Introducing Proteomics: From Concepts to Sample Separation, Mass Spectrometry and Data Analysis

Protein Bioinformatics: An Algorithmic Approach to Sequence and Structure Analysis

Statistics in Bioinformatics

Practical Statistics for Data Scientists

Computational Genome Analysis: An Introduction (Statistics for Biology & Health S)

Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health)

R & Bioconductor

Bioinformatics and Computational Biology Solutions Using R and Bioconductor

Bioconductor Case Studies

R Programming for Bioinformatics

R for data science : Import, Tidy, Transform, Visualize, And Model Data

Bioinformatics with R Cookbook

Python

Bioinformatics Programming Using Python

Bioinformatics with Python Cookbook

Mastering Python for Bioinformatics

Practical Data Science with Python

Learn Python Quickly

Fluent Python: Clear, Concise, and Effective Programming

Python Crash Course

Python Data Science Handbook: Essential Tools for Working with Data

Perl

Beginning Perl for Bioinformatics

Bioinformatics Biocomputing and Perl: An Introduction to Bioinformatics Computing Skills and Practice

Building Bioinformatics Solutions with Perl, R and SQL

AI & Machine Learning

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Deep Learning for the Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More

Machine Learning in Bioinformatics

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics

Unsupervised Feature Extraction Applied to Bioinformatics: A PCA Based and TD Based Approach (Unsupervised and Semi-Supervised Learning)

Next Generation Sequencing Data Analysis

Bioinformatics Data Skills

Bioinformatics: A Practical Handbook of Next Generation Sequencing and Its Applications

Algorithms for Next-Generation Sequencing (Chapman & Hall/CRC Computational Biology Series)

Others

Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures

Learning SQL, 3e: Generate, Manipulate, and Retrieve Data

Clinical Bioinformatics

Plant bioinformatics: methods and protocols

Genomics in the Cloud: Using Docker, GATK, and WDL in Terra

XML for Bioinformatics

PostgreSQL: Introduction and Concepts

Computational Systems Biology Approaches in Cancer Research

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