Title |
IntPath--an integrated pathway gene relationship database for model organisms and important pathogens
|
---|---|
Published in |
BMC Systems Biology, December 2012
|
DOI | 10.1186/1752-0509-6-s2-s2 |
Pubmed ID | |
Authors |
Hufeng Zhou, Jingjing Jin, Haojun Zhang, Bo Yi, Michal Wozniak, Limsoon Wong |
Abstract |
Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. |
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Geographical breakdown
Country | Count | As % |
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United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Singapore | 2 | 4% |
United States | 1 | 2% |
United Kingdom | 1 | 2% |
Unknown | 48 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 12 | 23% |
Student > Ph. D. Student | 12 | 23% |
Student > Master | 10 | 19% |
Student > Bachelor | 6 | 12% |
Other | 3 | 6% |
Other | 6 | 12% |
Unknown | 3 | 6% |
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Computer Science | 14 | 27% |
Biochemistry, Genetics and Molecular Biology | 8 | 15% |
Medicine and Dentistry | 5 | 10% |
Unspecified | 1 | 2% |
Other | 3 | 6% |
Unknown | 6 | 12% |