Comparative Gene Finding

1. Front Matter

   Pages i-xx

   PDF

2. Introduction

   • Marina Axelson-Fisk

   Pages 1-28

3. Single Species Gene Finding

   • Marina Axelson-Fisk

   Pages 29-105

4. Sequence Alignment

   • Marina Axelson-Fisk

   Pages 107-174

5. Comparative Gene Finding

   • Marina Axelson-Fisk

   Pages 175-200

6. Gene Structure Submodels

   • Marina Axelson-Fisk

   Pages 201-267

7. Parameter Training

   • Marina Axelson-Fisk

   Pages 269-310

8. Implementation of a Comparative Gene Finder

   • Marina Axelson-Fisk

   Pages 311-324

9. Annotation Pipelines for Next-Generation Sequencing Projects

   • Marina Axelson-Fisk

   Pages 325-367

10. Back Matter

    Pages 369-382

    PDF

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.

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

“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)

• Chalmers University of Technology, Göteborg, Sweden

  Marina Axelson-Fisk

Policies and ethics