Main description:

This invaluable textbook presents a self-contained introduction to the field of bioinformatics. Providing a comprehensive breadth of coverage while remaining accessibly concise, the text promotes a deep understanding of the field, supported by basic mathematical concepts, an emphasis on biological knowledge, and a holistic approach that highlights the connections unifying bioinformatics with other areas of science.

The thoroughly revised and enhanced fourth edition features new chapters focusing on cancer research applications, data mining, and causal inference in biology. This edition additionally includes new and updated material on inference engines, stem cell programmability, the ontology of bioinformatics, and natural and artificial ecosystems. Also covered are new developments in sequencing technologies, gene editing methods, and the modelling of the brain, as well as state-of-the-art medical applications. Of especial topicality is a new chapter on bioinformatics aspects of the present coronavirus epidemic.

Topics and features: explains the fundamentals of set theory, combinatorics, probability, likelihood, causality, clustering, pattern recognition, randomness, complexity, systems, and networks; discusses topics on ontogeny, phylogeny, and genome structure, as well as aspects of molecular biology; critically examines the most significant practical applications, offering detailed descriptions of both the experimental process and the analysis of the data; provides a varied selection of problems throughout the book, to stimulate further thinking; encourages further reading through the inclusion of an extensive bibliography.

This classic textbook builds upon the successful formula of previous editions with coverage of the latest advances in this exciting and fast-moving field. With its interdisciplinary scope, this unique guide will prove to be an essential study companion to a broad audience of undergraduate and beginning graduate students, spanning computer scientists focusing on bioinformatics, students of the physical sciences seeking a helpful primer on biology, and biologists desiring to better understand the theory underlying important applications of information science in biology.

Contents:

Introduction

Part I: Information

The Nature of Information

The Transmission of Information

Sets and Combinatorics

Probability and Likelihood

Randomness and Complexity

Systems and Networks

Algorithms

Part II: Biology

Introduction to Part II

The Nature of Living Things

The Molecules of Life

Part III: Applications

Introduction to Part III

Genomics

Proteomics

The Glycome, Lipidome and Microbiome

Interactomics: Interactions and Regulatory Networks

The Nervous System

Metabolomics and Metabonomics

Phenomics

Medical Applications Other than Cancer

Cancer

Ecosystems Management

The Organization of Knowledge

Data Mining

Causal Inference