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© 2015

Comparative Gene Finding

Models, Algorithms and Implementation

Book

Part of the Computational Biology book series (COBO, volume 20)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Marina Axelson-Fisk
    Pages 1-28
  3. Marina Axelson-Fisk
    Pages 29-105
  4. Marina Axelson-Fisk
    Pages 107-174
  5. Marina Axelson-Fisk
    Pages 175-200
  6. Marina Axelson-Fisk
    Pages 201-267
  7. Marina Axelson-Fisk
    Pages 269-310
  8. Marina Axelson-Fisk
    Pages 311-324
  9. Back Matter
    Pages 369-382

About this book

Introduction

This unique text/reference presents a concise guide to building computational gene finders, and describes the state of the art in computational gene finding methods, with a particular focus on comparative approaches. Fully updated and expanded, this new edition examines next-generation sequencing (NGS) technology, including annotation pipelines for NGS data. The book also discusses conditional random fields, enhancing the broad coverage of topics spanning probability theory, statistics, information theory, optimization theory, and numerical analysis.

Topics and features:

  • Introduces the fundamental terms and concepts in the field, and provides an historical overview of algorithm development
  • 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, reviewing the different steps and accuracy assessment measures used to debug and benchmark the software
  • Examines NGS techniques, and how to build a genome annotation pipeline, discussing sequence assembly, de novo repeat masking, and gene prediction (NEW)

Postgraduate students, and researchers wishing to enter the field quickly, will find this accessible text a valuable source of insights and examples. A suggested course outline for instructors is provided in the preface.

Dr. Marina Axelson-Fisk is an Associate Professor at the Department of Mathematical Sciences of Chalmers University of Technology, Gothenburg, Sweden.

Keywords

Algorithms Bioinformatics Biological Sequence Analysis Comparative Genomics Computational Biology Computational Gene Finding Genes Genetics Information Theory Sequence Alignment

Authors and affiliations

  1. 1.Chalmers University of TechnologyGöteborgSweden

Bibliographic information

  • Book Title Comparative Gene Finding
  • Book Subtitle Models, Algorithms and Implementation
  • Authors Marina Axelson-Fisk
  • Series Title Computational Biology
  • Series Abbreviated Title Computational Biology
  • DOI https://doi.org/10.1007/978-1-4471-6693-1
  • Copyright Information Springer-Verlag London 2015
  • Publisher Name Springer, London
  • eBook Packages Computer Science Computer Science (R0)
  • Hardcover ISBN 978-1-4471-6692-4
  • Softcover ISBN 978-1-4471-6875-1
  • eBook ISBN 978-1-4471-6693-1
  • Series ISSN 1568-2684
  • Edition Number 2
  • Number of Pages XX, 382
  • Number of Illustrations 81 b/w illustrations, 0 illustrations in colour
  • Topics Computational Biology/Bioinformatics
    Bioinformatics
  • Buy this book on publisher's site
Industry Sectors
Biotechnology
Pharma

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)