Title |
The pathway ontology – updates and applications
|
---|---|
Published in |
Journal of Biomedical Semantics, February 2014
|
DOI | 10.1186/2041-1480-5-7 |
Pubmed ID | |
Authors |
Victoria Petri, Pushkala Jayaraman, Marek Tutaj, G Thomas Hayman, Jennifer R Smith, Jeff De Pons, Stanley JF Laulederkind, Timothy F Lowry, Rajni Nigam, Shur-Jen Wang, Mary Shimoyama, Melinda R Dwinell, Diane H Munzenmaier, Elizabeth A Worthey, Howard J Jacob |
Abstract |
The Pathway Ontology (PW) developed at the Rat Genome Database (RGD), covers all types of biological pathways, including altered and disease pathways and captures the relationships between them within the hierarchical structure of a directed acyclic graph. The ontology allows for the standardized annotation of rat, and of human and mouse genes to pathway terms. It also constitutes a vehicle for easy navigation between gene and ontology report pages, between reports and interactive pathway diagrams, between pathways directly connected within a diagram and between those that are globally related in pathway suites and suite networks. Surveys of the literature and the development of the Pathway and Disease Portals are important sources for the ongoing development of the ontology. User requests and mapping of pathways in other databases to terms in the ontology further contribute to increasing its content. Recently built automated pipelines use the mapped terms to make available the annotations generated by other groups. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 2 | 50% |
Spain | 1 | 25% |
China | 1 | 25% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 50% |
Scientists | 2 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 3% |
Pakistan | 1 | 2% |
Netherlands | 1 | 2% |
Spain | 1 | 2% |
Mexico | 1 | 2% |
Unknown | 52 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 16 | 28% |
Student > Ph. D. Student | 13 | 22% |
Other | 6 | 10% |
Student > Doctoral Student | 4 | 7% |
Professor > Associate Professor | 4 | 7% |
Other | 9 | 16% |
Unknown | 6 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 15 | 26% |
Biochemistry, Genetics and Molecular Biology | 11 | 19% |
Medicine and Dentistry | 9 | 16% |
Computer Science | 9 | 16% |
Engineering | 3 | 5% |
Other | 3 | 5% |
Unknown | 8 | 14% |