Chapter title |
Annotation Extensions
|
---|---|
Chapter number | 17 |
Book title |
The Gene Ontology Handbook
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-3743-1_17 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3741-7, 978-1-4939-3743-1
|
Authors |
Rachael P. Huntley, Ruth C. Lovering, Huntley, RP, Lovering, RC, Huntley, Rachael P. H, Lovering, Ruth C. |
Editors |
Christophe Dessimoz, Nives Škunca |
Abstract |
The specificity of knowledge that Gene Ontology (GO) annotations currently can represent is still restricted by the legacy format of the GO annotation file, a format intentionally designed for simplicity to keep the barriers to entry low and thus encourage initial adoption. Historically, the information that could be captured in a GO annotation was simply the role or location of a gene product, although genetically interacting or binding partners could be specified. While there was no mechanism within the original GO annotation format for capturing additional information about the context of a GO term, such as the target gene of an activity or the location of a molecular function, the long-term vision for the GO Consortium was to provide greater expressivity in its annotations to capture physiologically relevant information.Thus, as a step forwards, the GO Consortium has introduced a new field into the annotation format, annotation extensions, which can be used to capture valuable contextual detail. This provides experimentally verified links between gene products and other physiological information that is crucial for accurate analysis of pathway and network data. This chapter will provide a simple overview of annotation extensions, illustrated with examples of their usage, and explain why they are useful for scientists and bioinformaticians alike. |
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Unknown | 2 | 100% |
Demographic breakdown
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
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Mexico | 1 | 5% |
Unknown | 19 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 5 | 25% |
Student > Ph. D. Student | 5 | 25% |
Student > Bachelor | 2 | 10% |
Student > Master | 2 | 10% |
Student > Doctoral Student | 1 | 5% |
Other | 1 | 5% |
Unknown | 4 | 20% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 6 | 30% |
Computer Science | 3 | 15% |
Agricultural and Biological Sciences | 3 | 15% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
Mathematics | 1 | 5% |
Other | 2 | 10% |
Unknown | 4 | 20% |