Skip to main content
ARS Home » Midwest Area » Ames, Iowa » Corn Insects and Crop Genetics Research » Research » Publications at this Location » Publication #306202

Title: A computational platform to maintain and migrate manual functional annotations for BioCyc databases

item WALSH, JESSE - Iowa State University
item Sen, Taner
item DICKERSON, JULIE - Iowa State University

Submitted to: BMC Systems Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/23/2014
Publication Date: 10/12/2014
Citation: Walsh, J.R., Sen, T.Z., Dickerson, J.A. 2014. A computational platform to maintain and migrate manual functional annotations for BioCyc databases. BMC Systems Biology. 8:115. DOI: 10.1186/s12918-014-0115-1.

Interpretive Summary: The knowledge of metabolic networks enable researchers to discover new marker candidates to understand the underlying genotype and develop better plants. MaizeCyc and CornCyc are two corn metabolic networks available at MaizeGDB. These metabolic networks are largely derived computationally, and therefore may contain missannotations. These networks also contain some proteins with manually annotated functions. Because these annotations were performed by expert scientists, they are high-confidence, and they are virtually error-free. In this manuscript, we describe a tool we developed that can facilitate the migration of these manual annotations from one metabolic network to another when they are available in the commonly used Pathway Tools platform. The migration and the preservation of these annotations will enhance the value and the usefulness of different corn metabolic networks for maize researchers.

Technical Abstract: Model organism 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 within the database independent of the specifics of the particular database design. We 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 into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers. Automating 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 pathways available at MaizeGDB, and by creating strain specific databases for metabolic engineering.