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ARS Home » Midwest Area » Ames, Iowa » Corn Insects and Crop Genetics Research » Research » Publications at this Location » Publication #291348
Title: Metabolic pathway resources at MaizeGDB

Author
item Sen, Taner
item MONACO, MARCELA - Cold Spring Harbor Laboratory
item CHAE, LEE - Carnegie Institute - Stanford
item DHARMAWARDHANA, PALITHA - Oregon State University
item Schaeffer, Mary
item DREHER, KATE - Carnegie Institute - Stanford
item ZHANG, PEIFEN - Carnegie Institute - Stanford
item NAITHANI, SUSHMA - Oregon State University
item THOMASON, JIM - Cold Spring Harbor Laboratory
item Harper, Elisabeth
item GARDINER, JACK - Iowa State University
item CANNON, ETHALINDA - Iowa State University
item Andorf, Carson
item Campbell, Darwin
item RHEE, SEUNG - Carnegie Institute - Stanford
item Ware, Doreen
item JAISWAL, PANKAJ - Oregon State University
item Lawrence, Carolyn

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 2/1/2013
Publication Date: 3/14/2013
Citation: Sen, T.Z., Monaco, M., Chae, L., Dharmawardhana, P., Schaeffer, M.L., Dreher, K., Zhang, P., Naithani, S., Thomason, J., Harper, E.C., Gardiner, J., Cannon, E., Andorf, C.M., Campbell, D.A., Rhee, S.Y., Ware, D., Jaiswal, P., Lawrence, C.J. 2013. Metabolic pathway resources at MaizeGDB [abstract]. In: Proceedings of Maize Genetics Conference, March 14-17, St. Charles, Illinois. p. 3.

Interpretive Summary:

Technical Abstract: Two maize metabolic networks are available at MaizeGDB: MaizeCyc (http://maizecyc.maizegdb.org, also at Gramene) and CornCyc (http://corncyc.maizegdb.org, also at the Plant Metabolic Network). MaizeCyc was developed by Gramene, and CornCyc by the Plant Metabolic Network, both in collaboration with MaizeGDB. MaizeCyc and CornCyc are both based on B73 RefGen_v2 filtered gene set models, and offer visualization and analysis capabilities of Pathway Tools developed by SRI. Their pipelines for enzymatic function assignment indicate some differences: MaizeCyc is mainly based on the exonerate scores generated via the Ensembl XRef pipeline, whereas CornCyc employs a scoring matrix based on performances obtained using BLAST, CatFam, and Priam. As a result of these different assignment criteria, the metabolic networks differ in coverage and confidence levels. Here we present some statistics from both metabolic networks, provide snapshots of various views and analysis tools available in Pathway Tools, and show examples of how these tools and resources can be used to derive biologically-meaningful hypotheses.