Use of a global metabolic network to curate organismal metabolic networks
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Publication Details
Output type: Journal article
Author list: Pah AR, Guimera R, Mustoe AM, Amaral LAN
Publisher: Nature Research
Publication year: 2013
Journal: Scientific Reports (2045-2322)
Volume number: 3
ISSN: 2045-2322
eISSN: 2045-2322
Languages: English-Great Britain (EN-GB)
Unpaywall Data
Open access status: gold
Full text URL: https://www.nature.com/articles/srep01695.pdf
Abstract
The difficulty in annotating the vast amounts of biological information poses one of the greatest current challenges in biological research. The number of genomic, proteomic, and metabolomic datasets has increased dramatically over the last two decades, far outstripping the pace of curation efforts. Here, we tackle the challenge of curating metabolic network reconstructions. We predict organismal metabolic networks using sequence homology and a global metabolic network constructed from all available organismal networks. While sequence homology has been a standard to annotate metabolic networks it has been faulted for its lack of predictive power. We show, however, that when homology is used with a global metabolic network one is able to predict organismal metabolic networks that have enhanced network connectivity. Additionally, we compare the annotation behavior of current database curation efforts with our predictions and find that curation efforts are biased towards adding (rather than removing) reactions to organismal networks.
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