BOOK SERIES


Chapman & Hall/CRC Mathematical and Computational Biology


About the Series

This series aims to capture new developments and summarize what is known over the entire spectrum of mathematical and computational biology and medicine. It seeks to encourage the integration of mathematical, statistical, and computational methods into biology by publishing a broad range of textbooks, reference works, and handbooks. The titles included in the series are meant to appeal to students, researchers, and professionals in the mathematical, statistical, and computational sciences and fundamental biology and bioengineering, as well as interdisciplinary researchers involved in the field. The inclusion of concrete examples and applications and programming techniques and examples is highly encouraged.

64 Series Titles

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Genome Analysis in R

Genome Analysis in R

Forthcoming

Pawel Michalak
September 30, 2017

In recent years the amount of biological sequence data available for research has increased significantly and complete genome sequences have become commonplace. Next-generation sequencing (NGS) is expected to revolutionize biomedical research. However, the analysis of millions of DNA/RNA sequences...

Mathematical Models of Plant-Herbivore Interactions

Mathematical Models of Plant-Herbivore Interactions

Forthcoming

Zhilan Feng, Donald DeAngelis
September 15, 2017

This book covers the use of mathematical models in ecology, particularly factors that affect herbivory. The aim is to provide models that are motivated by and can be used for evaluation of alternative management scenarios. By incorporating case studies the book is pitched at a level suitable for a...

Python for Bioinformatics, Second Edition

Python for Bioinformatics, Second Edition

Forthcoming

Sebastian Bassi
August 11, 2017

In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of...

Chromatin: Structure, Dynamics, Regulation

Chromatin: Structure, Dynamics, Regulation

Forthcoming

Ralf Blossey
May 25, 2017

An invaluable resource for computational biologists and researchers from other fields seeking an introduction to the topic, Chromatin: Structure, Dynamics, Regulation offers comprehensive coverage of this dynamic interdisciplinary field, from the basics to the latest research. Computational methods...

Algorithms for Next-Generation Sequencing

Algorithms for Next-Generation Sequencing

Forthcoming

Wing-Kin Sung
May 11, 2017

Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before – as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data? Algorithms for...

An Introduction to Physical Oncology: How Mechanistic Mathematical Modeling Can Improve Cancer Therapy Outcomes

An Introduction to Physical Oncology: How Mechanistic Mathematical Modeling Can Improve Cancer Therapy Outcomes

Forthcoming

Vittorio Cristini, Eugene Koay, Zhihui Wang
April 24, 2017

This book presents a theoretical multiscale modeling framework for the integration of processes spanning from molecular signaling to individual and collective cellular behavior to complex spatiotemporal dynamics at the tissue and organ levels. It then gives a detailed discussion on how to...

Statistical Modeling and Machine Learning for Molecular Biology

Statistical Modeling and Machine Learning for Molecular Biology

Alan Moses
January 04, 2017

Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts...

Introduction to Mathematical Oncology

Introduction to Mathematical Oncology

Yang Kuang, John D. Nagy, Steffen E. Eikenberry
February 18, 2016

Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and...

Big Data Analysis for Bioinformatics and Biomedical Discoveries

Big Data Analysis for Bioinformatics and Biomedical Discoveries

Shui Qing Ye
December 22, 2015

Demystifies Biomedical and Biological Big Data Analyses Big Data Analysis for Bioinformatics and Biomedical Discoveries provides a practical guide to the nuts and bolts of Big Data, enabling you to quickly and effectively harness the power of Big Data to make groundbreaking biological discoveries,...

RNA-seq Data Analysis: A Practical Approach

RNA-seq Data Analysis: A Practical Approach

Eija Korpelainen, Jarno Tuimala, Panu Somervuo, Mikael Huss, Garry Wong
September 19, 2014

The State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine...

Computational and Visualization Techniques for Structural Bioinformatics Using Chimera

Computational and Visualization Techniques for Structural Bioinformatics Using Chimera

Forbes J. Burkowski
July 29, 2014

A Step-by-Step Guide to Describing Biomolecular Structure Computational and Visualization Techniques for Structural Bioinformatics Using Chimera shows how to perform computations with Python scripts in the Chimera environment. It focuses on the three core areas needed to study structural...

Bayesian Phylogenetics: Methods, Algorithms, and Applications

Bayesian Phylogenetics: Methods, Algorithms, and Applications

Ming-Hui Chen, Lynn Kuo, Paul O. Lewis
May 27, 2014

Offering a rich diversity of models, Bayesian phylogenetics allows evolutionary biologists, systematists, ecologists, and epidemiologists to obtain answers to very detailed phylogenetic questions. Suitable for graduate-level researchers in statistics and biology, Bayesian Phylogenetics: Methods,...

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