Title |
The representation of protein complexes in the Protein Ontology (PRO)
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Published in |
BMC Bioinformatics, September 2011
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DOI | 10.1186/1471-2105-12-371 |
Pubmed ID | |
Authors |
Carol J Bult, Harold J Drabkin, Alexei Evsikov, Darren Natale, Cecilia Arighi, Natalia Roberts, Alan Ruttenberg, Peter D'Eustachio, Barry Smith, Judith A Blake, Cathy Wu |
Abstract |
Representing species-specific proteins and protein complexes in ontologies that are both human- and machine-readable facilitates the retrieval, analysis, and interpretation of genome-scale data sets. Although existing protin-centric informatics resources provide the biomedical research community with well-curated compendia of protein sequence and structure, these resources lack formal ontological representations of the relationships among the proteins themselves. The Protein Ontology (PRO) Consortium is filling this informatics resource gap by developing ontological representations and relationships among proteins and their variants and modified forms. Because proteins are often functional only as members of stable protein complexes, the PRO Consortium, in collaboration with existing protein and pathway databases, has launched a new initiative to implement logical and consistent representation of protein complexes. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Japan | 1 | 17% |
Unknown | 5 | 83% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 6 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 2 | 4% |
France | 2 | 4% |
Germany | 1 | 2% |
Brazil | 1 | 2% |
Portugal | 1 | 2% |
Canada | 1 | 2% |
United Kingdom | 1 | 2% |
Japan | 1 | 2% |
Spain | 1 | 2% |
Other | 0 | 0% |
Unknown | 38 | 78% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 18 | 37% |
Student > Ph. D. Student | 8 | 16% |
Student > Master | 5 | 10% |
Student > Bachelor | 3 | 6% |
Professor > Associate Professor | 3 | 6% |
Other | 7 | 14% |
Unknown | 5 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 18 | 37% |
Computer Science | 6 | 12% |
Biochemistry, Genetics and Molecular Biology | 5 | 10% |
Medicine and Dentistry | 3 | 6% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
Other | 7 | 14% |
Unknown | 9 | 18% |