Title |
A computational platform to maintain and migrate manual functional annotations for BioCyc databases
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Published in |
BMC Systems Biology, October 2014
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DOI | 10.1186/s12918-014-0115-1 |
Pubmed ID | |
Authors |
Jesse R Walsh, Taner Z Sen, Julie A Dickerson |
Abstract |
BackgroundBioCyc databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integration as new knowledge is discovered. As functional annotations are improved, scalable methods are needed for curators to manage annotations without detailed knowledge of the specific design of the BioCyc database.ResultsWe have developed CycTools, a software tool which allows curators to maintain functional annotations in a model organism database. This tool builds on existing software to improve and simplify annotation data imports of user provided data into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers.ConclusionsAutomating steps in the manual data entry process can improve curation efforts for major biological databases. The functionality of CycTools is demonstrated by transferring GO term annotations from MaizeCyc to matching proteins in CornCyc, both maize metabolic pathway databases available at MaizeGDB, and by creating strain specific databases for metabolic engineering. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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France | 1 | 4% |
Brazil | 1 | 4% |
Tunisia | 1 | 4% |
Singapore | 1 | 4% |
United States | 1 | 4% |
Unknown | 18 | 78% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 9 | 39% |
Student > Ph. D. Student | 5 | 22% |
Student > Postgraduate | 2 | 9% |
Professor > Associate Professor | 2 | 9% |
Student > Master | 1 | 4% |
Other | 3 | 13% |
Unknown | 1 | 4% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 10 | 43% |
Medicine and Dentistry | 3 | 13% |
Biochemistry, Genetics and Molecular Biology | 2 | 9% |
Business, Management and Accounting | 2 | 9% |
Computer Science | 2 | 9% |
Other | 2 | 9% |
Unknown | 2 | 9% |