Keith J.M. (Ed.) Bioinformatics. Volume I: Data, Sequence Analysis, and Evolution

2nd Edition. — Springer Science+Business Media, New York, USA, 2017. — 491 p. — (Methods in Molecular Biology 1525) — ISBN: 1493966200This second edition provides updated and expanded chapters covering a broad sampling of useful and current methods in the rapidly developing and expanding field of bioinformatics. Bioinformatics, Volume I: Data, Sequence Analysis, and Evolution, Second Edition is comprised of three sections: Data and Databases, Sequence Analysis, and Phylogenetics and Evolution. The first section details bioinformatics methodologies in the generation of sequence and structural data and its organization into conceptual categories, and databases to facilitate further analyses. The Sequence Analysis section describes the fundamental methodologies for processing the sequences of biological molecules: techniques that are used in almost every pipeline of bioinformatics analysis, particularly in the preliminary stages of such pipelines. Last but not least, the phylogenetics and evolution section deals with methodologies that compare biological sequences for the purpose of understanding how they evolved. As a volume in the highly successful Methods in Molecular Biology series, chapters feature the kind of detail and expert implementation advice to ensure positive results.
Comprehensive and practical, Bioinformatics, Volume I: Data, Sequence Analysis, and Evolution, Second Edition is an essential resource for graduate students, early career researchers, and others who are in the process of integrating new bioinformatics methods into their research.Data and Databases
Genome Sequencing
Sequence Assembly
A Practical Approach to Protein Crystallography
Managing Sequence Data
Genome Annotation
Working with Ontologies
The Classification of Protein Domains and Christine A. Orengo
Sequence Analysis
Multiple Sequence Alignment
Large-Scale Sequence Comparison
Genomic Database Searching
Finding Genes in Genome Sequence
Sequence Segmentation with changeptGUI
Phylogenetics and Evolution
Measuring Natural Selection
Inferring Trees
Identifying Optimal Models of Evolution
Scaling Up the Phylogenetic Detection of Lateral Gene Transfer Events
Detecting and Analyzing Genetic Recombination Using RDP4
Species Tree Estimation from Genome-Wide Data with Guenomu