Keith Bioinformatics

Volume I: Data, Sequence Analysis, and Evolution
2. Auflage 2017
ISBN: 978-1-4939-6622-6
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 1525, 491 Seiten, eBook

Reihe: Methods in Molecular Biology

This 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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Keith, Jonathan M.

Inhaltsverzeichnis

Genome Sequencing.- Sequence Assembly.- A Practical Approach to Protein Crystallography.- Managing Sequence Data.- Genome Annotation.- Working with Ontologies.- The Classification of Protein Domains.- Multiple Sequence Alignment.- Large-Scale Sequence Comparison.- Genomic Database Searching.- Finding Genes in Genome Sequence.- Sequence Segmentation with changeptGUI.- 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.