Comparative Gene Finding (2nd Ed., Softcover reprint of the original 2nd ed. 2015)
Models, Algorithms and Implementation

Computational Biology Series, Vol. 20

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Language: English

105.49 €

In Print (Delivery period: 15 days).

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Comparative Gene Finding
Publication date:
Support: Print on demand

105.49 €

In Print (Delivery period: 15 days).

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Comparative Gene Findind (2nd Ed.)
Publication date:
382 p. · 15.5x23.5 cm · Hardback
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.

Introduction

Single Species Gene Finding

Sequence Alignment

Comparative Gene Finding

Gene Structure Submodels

Parameter Training

Implementation of a Comparative Gene Finder

Annotation Pipelines for Next Generation Sequencing Projects

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