Overview
- Provides detailed descriptions of the models and algorithms and how to implement them
- Summarizes the advances in the field and gives clear and concise instructions on how to proceed though the project process
- Updated and expanded new edition, now covering next-generation sequencing technology and conditional random fields
- Includes supplementary material: sn.pub/extras
Part of the book series: Computational Biology (COBO, volume 20)
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About this book
This book presents a guide to building computational gene finders, and describes the state of the art in computational gene finding methods, with a focus on comparative approaches. Fully updated and expanded, this new edition examines next-generation sequencing (NGS) technology. The book also discusses conditional random fields, enhancing the broad coverage of topics spanning probability theory, statistics, information theory, optimization theory and numerical analysis. Features: introduces the fundamental terms and concepts in the field; discusses algorithms for single-species gene finding, and approaches to pairwise and multiple sequence alignments, then describes how the strengths in both areas can be combined to improve the accuracy of gene finding; explores the gene features most commonly captured by a computational gene model, and explains the basics of parameter training; illustrates how to implement a comparative gene finder; examines NGS techniques and how to build a genome annotation pipeline.
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Keywords
Table of contents (8 chapters)
Reviews
“The structure of the book mirrors the learning steps for understanding how to perform gene finding. … Its target audience is mainly post-graduate researchers or established researchers with a background in mathematics or statistics applied in bioinformatics who need a thorough yet concise overview of this field.” (Irina Ioana Mohorianu, zbMATH 1350.92001, 2017)
“It skillfully introduces readers to a difficult subject, while at the same time motivating them to enter this very important area. … It is best suited for a graduate course or as an introduction for researchers not familiar with this field. … this is an excellent introduction to comparative gene finding. … I especially recommend this book to any computer scientist with an interest in current problems in bioinformatics.” (Burkhard Englert, Computing Reviews, December, 2015)
Authors and Affiliations
Bibliographic Information
Book Title: Comparative Gene Finding
Book Subtitle: Models, Algorithms and Implementation
Authors: Marina Axelson-Fisk
Series Title: Computational Biology
DOI: https://doi.org/10.1007/978-1-4471-6693-1
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London 2015
Hardcover ISBN: 978-1-4471-6692-4Published: 22 April 2015
Softcover ISBN: 978-1-4471-6875-1Published: 05 October 2016
eBook ISBN: 978-1-4471-6693-1Published: 13 April 2015
Series ISSN: 1568-2684
Series E-ISSN: 2662-2432
Edition Number: 2
Number of Pages: XX, 382
Number of Illustrations: 81 b/w illustrations
Topics: Computational Biology/Bioinformatics, Bioinformatics