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.