This series aims to capture new developments in computational biology, as well as high-quality work summarizing or contributing to more established topics. Publishing a broad range of reference works, textbooks, and handbooks, the series is designed to appeal to students, researchers, and professionals in all areas of computational biology, including genomics, proteomics, and cancer computational biology, as well as interdisciplinary researchers involved in associated fields, such as bioinformatics and systems biology.
For more information or to submit a book proposal, please contact Elliott Morsia ([email protected]).
Edited
By Edwin Wang
June 14, 2017
The unprecedented amount of data produced with high-throughput experimentation forces biologists to employ mathematical representation and computation methods to glean meaningful information in systems-level biology. Applying this approach to the underlying molecular mechanisms of tumorigenesis, ...
By Gabriel Valiente
June 14, 2017
Emphasizing the search for patterns within and between biological sequences, trees, and graphs, Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R shows how combinatorial pattern matching algorithms can solve computational biology problems that arise in the analysis...
By Rudy Guerra, Darlene R. Goldstein
June 14, 2017
Novel Techniques for Analyzing and Combining Data from Modern Biological StudiesBroadens the Traditional Definition of Meta-Analysis With the diversity of data and meta-data now available, there is increased interest in analyzing multiple studies beyond statistical approaches of formal ...
By Wing-Kin Sung
May 24, 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 ...
By Alan Moses
December 15, 2016
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 ...
Edited
By 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, ...
By Eija Korpelainen, Jarno Tuimala, Panu Somervuo, Mikael Huss, Garry Wong
September 19, 2014
The State of the Art in Transcriptome Analysis RNA 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 ...
By 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 ...
Edited
By 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, ...
By Allegra Via, Kristian Rother, Anna Tramontano
March 18, 2014
Take Control of Your Data and Use Python with Confidence Requiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to ...
By Zehua Chen
November 01, 2013
While numerous advanced statistical approaches have recently been developed for quantitative trait loci (QTL) mapping, the methods are scattered throughout the literature. Statistical Methods for QTL Mapping brings together many recent statistical techniques that address the data complexity of QTL ...
By Jung Soh, Paul M.K. Gordon, Christoph W. Sensen
August 30, 2012
The success of individualized medicine, advanced crops, and new and sustainable energy sources requires thoroughly annotated genomic information and the integration of this information into a coherent model. A thorough overview of this field, Genome Annotation explores automated genome analysis and...