Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 549140
Title Consistency, inconsistency, and ambiguity of metabolite names in biochemical databases used for genome-scale metabolic modelling
Author(s) Pham, Nhung; Heck, Ruben G.A. van; Dam, Jesse C.J. van; Schaap, Peter J.; Saccenti, Edoardo; Suarez-Diez, Maria
Source Metabolites 9 (2019)2. - ISSN 2218-1989
DOI https://doi.org/10.3390/metabo9020028
Department(s) Systems and Synthetic Biology
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2019
Keyword(s) Chemical nomenclature - Databases - GEM - GEM interoperability - Identifier multiplicity - Name ambiguity - Naming conventions - Standardization
Abstract

Genome-scale metabolic models (GEMs) are manually curated repositories describing the metabolic capabilities of an organism. GEMs have been successfully used in different research areas, ranging from systems medicine to biotechnology. However, the different naming conventions (namespaces) of databases used to build GEMs limit model reusability and prevent the integration of existing models. This problem is known in the GEM community, but its extent has not been analyzed in depth. In this study, we investigate the name ambiguity and the multiplicity of non-systematic identifiers and we highlight the (in)consistency in their use in 11 biochemical databases of biochemical reactions and the problems that arise when mapping between different namespaces and databases. We found that such inconsistencies can be as high as 83.1%, thus emphasizing the need for strategies to deal with these issues. Currently, manual verification of the mappings appears to be the only solution to remove inconsistencies when combining models. Finally, we discuss several possible approaches to facilitate (future) unambiguous mapping.

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