Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. \copyright The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
%0 Journal Article
%1 King2015BiGG
%A King, Zachary A.
%A Lu, Justin
%A Dräger, Andreas
%A Miller, Philip
%A Federowicz, Stephen
%A Lerman, Joshua A.
%A Ebrahim, Ali
%A Palsson, Bernhard O.
%A Lewis, Nathan E.
%D 2015
%J Nucleic acids research
%K database genome-scale metabolic-networks
%R 10.1093/nar/gkv1049
%T BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.
%U http://dx.doi.org/10.1093/nar/gkv1049
%X Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. \copyright The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
@article{King2015BiGG,
abstract = {Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present {BiGG} Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. {BiGG} Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. {BiGG} Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, {BiGG} Models provides a comprehensive application programming interface for accessing {BiGG} Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, {BiGG} Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. {\copyright} The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.},
added-at = {2018-12-02T16:09:07.000+0100},
author = {King, Zachary A. and Lu, Justin and Dr\"{a}ger, Andreas and Miller, Philip and Federowicz, Stephen and Lerman, Joshua A. and Ebrahim, Ali and Palsson, Bernhard O. and Lewis, Nathan E.},
biburl = {https://www.bibsonomy.org/bibtex/2c16eb668be8fd7c8349fdc3db01ab37f/karthikraman},
citeulike-article-id = {13827483},
citeulike-linkout-0 = {http://dx.doi.org/10.1093/nar/gkv1049},
citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/26476456},
citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=26476456},
day = 17,
doi = {10.1093/nar/gkv1049},
interhash = {32ae70c4c906e617db6213d00d2b6d82},
intrahash = {c16eb668be8fd7c8349fdc3db01ab37f},
issn = {1362-4962},
journal = {Nucleic acids research},
keywords = {database genome-scale metabolic-networks},
month = oct,
pmid = {26476456},
posted-at = {2015-11-04 06:29:39},
priority = {2},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {{BiGG} Models: A platform for integrating, standardizing and sharing genome-scale models.},
url = {http://dx.doi.org/10.1093/nar/gkv1049},
year = 2015
}