The success of individualized medicine, advanced crops, and new and sustainable energy sources requires thoroughly annotated genomic information and the integration of this information into a coherent model. A thorough overview of this field, Genome Annotation explores automated genome analysis and annotation from its origins to the challenges of next-generation sequencing data analysis.
The book initially takes you through the last 16 years since the sequencing of the first complete microbial genome. It explains how current analysis strategies were developed, including sequencing strategies, statistical models, and early annotation systems. The authors then present visualization techniques for displaying integrated results as well as state-of-the-art annotation tools, including MAGPIE, Ensembl, Bluejay, and Galaxy. They also discuss the pipelines for the analysis and annotation of complex, next-generation DNA sequencing data. Each chapter includes references and pointers to relevant tools.
As very few existing genome annotation pipelines are capable of dealing with the staggering amount of DNA sequence information, new strategies must be developed to accommodate the needs of today’s genome researchers. Covering this topic in detail, Genome Annotation provides you with the foundation and tools to tackle this challenging and evolving area. Suitable for both students new to the field and professionals who deal with genomic information in their work, the book offers two genome annotation systems on an accompanying downloadable resources.
Table of Contents
DNA Sequencing Strategies
The Evolution of DNA Sequencing Technologies
DNA Sequence Assembly Strategies
Sequencing Bias and Error Rates
Coding Sequence Prediction
Mapping Messenger RNA (mRNA)
Combining Gene Predictions
Between the Genes
Characterization of Gene Function through Bioinformatics: The Early Days
Stand-Alone Tools and Tools for the Early Internet
From FASTA Files to Annotated Genomes
Visualization Techniques and Tools for Genomic Data
Visualization of Sequencing Data
Visualization of Multiple Sequence Alignments
Visualization of Hierarchical Structures
Visualization of Gene Expression Data
Biophysical and Biochemical Feature
Pairwise Alignment Methods
Automated Annotation Systems
Generic Model Organism Database (GMOD)
Dynamic Annotation Systems: End-User-Driven Annotation and Visualization
Web-Based Genome Annotation Browsers
Stand-Alone Genome Annotation Browsers
Comparative Visualization of Genomes
Principles of Web-Based Workflows
Analysis Pipelines for Next-Generation Sequencing Data
Genome Sequence Reconstruction
Analysis Pipelines: Case Studies
Next-Generation Genome Browsing
References appear at the end of each chapter.
Jung Soh is a research associate at the University of Calgary. He earned a Ph.D. in computer science from the University at Buffalo, The State University of New York, where he worked at the Center of Excellence for Document Analysis and Recognition (CEDAR). He also worked as a principal research scientist at the Electronics and Telecommunications Research Institute (ETRI) in Daejeon, Korea. His research interests are in bioinformatics, machine learning, and biomedical data visualization.
Paul M.K. Gordon is the bioinformatics support specialist for the Alberta Children’s Hospital Research Institute at the University of Calgary. He has worked at the National Research Council of Canada’s Institute for Information Technology (NRC-IIT) and Institute for Marine Biosciences (NRC-IMB). His current work focuses on developing bioinformatics techniques for personalized medicine.
Christoph W. Sensen is a professor of bioinformatics at the University of Calgary. He has previously worked as a research officer at the National Research Council of Canada’s Institute for Marine Biosciences (NRC-IMB) and as a visiting scientist at the European Molecular Biology Laboratory (EMBL) in Heidelberg. His research interests are in genome research and bioinformatics.