ENGLISH

Comparative Gene Finding: Models, Algorithms and Implementation

By Marina Axelson-Fisk (auth.)

Book information

Publisher
Springer-Verlag London
Year
2015
ISBN
978-1-4471-6692-4, 978-1-4471-6693-1
DOI
10.1007/978-1-4471-6693-1
Language
english
Format
PDF
Filesize
6 MB (6139684 bytes)
Series
Computational Biology 20
Edition
2
Pages
382\396
Topic
Biology
Time added
2015-04-23 16:00:00
Computational Biology/Bioinformatics; Bioinformati

Description

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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