Title |
A systematic comparison of the MetaCyc and KEGG pathway databases
|
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Published in |
BMC Bioinformatics, March 2013
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DOI | 10.1186/1471-2105-14-112 |
Pubmed ID | |
Authors |
Tomer Altman, Michael Travers, Anamika Kothari, Ron Caspi, Peter D Karp |
Abstract |
The MetaCyc and KEGG projects have developed large metabolic pathway databases that are used for a variety of applications including genome analysis and metabolic engineering. We present a comparison of the compound, reaction, and pathway content of MetaCyc version 16.0 and a KEGG version downloaded on Feb-27-2012 to increase understanding of their relative sizes, their degree of overlap, and their scope. To assess their overlap, we must know the correspondences between compounds, reactions, and pathways in MetaCyc, and those in KEGG. We devoted significant effort to computational and manual matching of these entities, and we evaluated the accuracy of the correspondences. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 17% |
Japan | 2 | 11% |
France | 1 | 6% |
India | 1 | 6% |
United Kingdom | 1 | 6% |
Israel | 1 | 6% |
China | 1 | 6% |
Norway | 1 | 6% |
Colombia | 1 | 6% |
Other | 1 | 6% |
Unknown | 5 | 28% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 12 | 67% |
Scientists | 6 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 11 | 3% |
Netherlands | 5 | 1% |
Germany | 3 | <1% |
United Kingdom | 3 | <1% |
Brazil | 2 | <1% |
Sweden | 2 | <1% |
Norway | 1 | <1% |
Hong Kong | 1 | <1% |
Latvia | 1 | <1% |
Other | 9 | 2% |
Unknown | 334 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 94 | 25% |
Researcher | 85 | 23% |
Student > Master | 42 | 11% |
Student > Bachelor | 25 | 7% |
Student > Doctoral Student | 17 | 5% |
Other | 51 | 14% |
Unknown | 58 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 137 | 37% |
Biochemistry, Genetics and Molecular Biology | 68 | 18% |
Computer Science | 31 | 8% |
Medicine and Dentistry | 12 | 3% |
Engineering | 10 | 3% |
Other | 44 | 12% |
Unknown | 70 | 19% |