Chapter title |
Evaluating Computational Gene Ontology Annotations
|
---|---|
Chapter number | 8 |
Book title |
The Gene Ontology Handbook
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-3743-1_8 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3741-7, 978-1-4939-3743-1
|
Authors |
Nives Škunca, Richard J. Roberts, Martin Steffen, Škunca, Nives, Roberts, Richard J., Steffen, Martin |
Editors |
Christophe Dessimoz, Nives Škunca |
Abstract |
Two avenues to understanding gene function are complementary and often overlapping: experimental work and computational prediction. While experimental annotation generally produces high-quality annotations, it is low throughput. Conversely, computational annotations have broad coverage, but the quality of annotations may be variable, and therefore evaluating the quality of computational annotations is a critical concern.In this chapter, we provide an overview of strategies to evaluate the quality of computational annotations. First, we discuss why evaluating quality in this setting is not trivial. We highlight the various issues that threaten to bias the evaluation of computational annotations, most of which stem from the incompleteness of biological databases. Second, we discuss solutions that address these issues, for example, targeted selection of new experimental annotations and leveraging the existing experimental annotations. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Mexico | 1 | 6% |
United States | 1 | 6% |
Unknown | 15 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Other | 3 | 18% |
Student > Bachelor | 3 | 18% |
Student > Ph. D. Student | 3 | 18% |
Researcher | 3 | 18% |
Professor > Associate Professor | 1 | 6% |
Other | 0 | 0% |
Unknown | 4 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 4 | 24% |
Biochemistry, Genetics and Molecular Biology | 2 | 12% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 6% |
Veterinary Science and Veterinary Medicine | 1 | 6% |
Mathematics | 1 | 6% |
Other | 3 | 18% |
Unknown | 5 | 29% |