Title |
Open Biomedical Ontology-based Medline exploration
|
---|---|
Published in |
BMC Bioinformatics, May 2009
|
DOI | 10.1186/1471-2105-10-s5-s6 |
Pubmed ID | |
Authors |
Weijian Xuan, Manhong Dai, Barbara Mirel, Jean Song, Brian Athey, Stanley J Watson, Fan Meng |
Abstract |
Effective Medline database exploration is critical for the understanding of high throughput experimental results and the development of novel hypotheses about the mechanisms underlying the targeted biological processes. While existing solutions enhance Medline exploration through different approaches such as document clustering, network presentations of underlying conceptual relationships and the mapping of search results to MeSH and Gene Ontology trees, we believe the use of multiple ontologies from the Open Biomedical Ontology can greatly help researchers to explore literature from different perspectives as well as to quickly locate the most relevant Medline records for further investigation. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 12% |
United Kingdom | 4 | 8% |
Portugal | 1 | 2% |
Canada | 1 | 2% |
Switzerland | 1 | 2% |
Spain | 1 | 2% |
New Zealand | 1 | 2% |
Unknown | 34 | 69% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 19 | 39% |
Student > Ph. D. Student | 9 | 18% |
Student > Master | 6 | 12% |
Other | 5 | 10% |
Student > Bachelor | 3 | 6% |
Other | 6 | 12% |
Unknown | 1 | 2% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 16 | 33% |
Agricultural and Biological Sciences | 12 | 24% |
Medicine and Dentistry | 8 | 16% |
Mathematics | 2 | 4% |
Arts and Humanities | 2 | 4% |
Other | 5 | 10% |
Unknown | 4 | 8% |