Bücher der Reihe Chapman & Hall/CRC Computational Biology Series

This will be the first book to systematically describe the process and provide corresponding methods for analysing data generated from genetic- and epigenetic-studies. Specifically, the book aims to provide a "pipe line" for genetic and epigenetic data analysis starting from raw genome- and epigenome-scale data.

Emphasizing the search for patterns within and between biological sequences, trees, and graphs, this book shows how combinatorial pattern matching algorithms can solve computational biology problems that arise in the analysis of genomic, transcriptomic, proteomic, metabolomic, and interactomic data.

From the elucidation and analysis of a genomic sequence to the prediction of a protein structure and the identification of the molecular function, this book describes the rationale and limitations of the bioinformatics methods and tools that can help solve biological problems. It addresses the ways to store and retrieve biological data.

The unprecedented amount of data produced with high-throughput experimentation forces biologists to employ mathematical representation and computation to glean meaningful information in systems-level biology. This book introduces the concepts and theories of systems biology and the applications of systems biology in cancer research.

A guide for applying basic informatics algorithms to medical data sets. It includes examples using three most common programming languages (Perl, Python, and Ruby). It provides basic methods for retrieving, organizing, merging, and analyzing their data sources. It covers building blocks, primary tasks of medical informatics, and medical discovery.

Written by SeqAn project founders, this book describes the general library design of SeqAn. It introduces biological sequence analysis problems, discusses the benefit of using software libraries, summarizes SeqAn design principles and goals, details SeqAn programming techniques, and demonstrates the application of these techniques in various examples. Focusing on SeqAn components, the second part explores basic functionality, sequence data structures, alignments, pattern and motif searching, string indices, and graphs. The last part describes applications of SeqAn to genome alignment, consensus sequence, suffix array construction.

The unprecedented amount of data produced with high-throughput experimentation forces biologists to employ mathematical representation and computation to glean meaningful information in systems-level biology. Applying this approach to the underlying molecular mechanisms of tumorgenesis, cancer research is enjoying a series of new discoveries and biological insights. Unique in its dualistic approach, this book introduces the concepts and theories of systems biology and their applications in cancer research. It presents basic cancer biology and cutting-edge topics of cancer research for computational biologists alongside systems biology analysis tools for experimental biologists.

This book provides many novel techniques for analyzing data from modern biological studies that involve multiple data sets, either of the same type or multiple data sources. It addresses the combination of similar data types: genotype data from genome-wide linkage scans and data derived from microarray gene expression experiments, and solves data combination problems that can arise within the same basic framework. It demonstrates the combined analysis of different data types, showing data combination approaches in action across a wide variety of genome-scale investigations.

This book covers Metabolomics, the scientific study of the chemical processes of the metabolic system. It is based on a course taught to masters and postgraduate students of bioinformatics and statistics at the European Bioinformatics Institute at Cambridge.