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Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks

SUMMARY: The goal of this work is to offer a computational framework for exploring data from the Recon2 human metabolic reconstruction model. Advanced user access features have been developed using the Neo4j graph database technology and this paper describes key features such as efficient management...

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Autores principales: Balaur, Irina, Mazein, Alexander, Saqi, Mansoor, Lysenko, Artem, Rawlings, Christopher J, Auffray, Charles
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408918/
https://www.ncbi.nlm.nih.gov/pubmed/27993779
http://dx.doi.org/10.1093/bioinformatics/btw731
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author Balaur, Irina
Mazein, Alexander
Saqi, Mansoor
Lysenko, Artem
Rawlings, Christopher J
Auffray, Charles
author_facet Balaur, Irina
Mazein, Alexander
Saqi, Mansoor
Lysenko, Artem
Rawlings, Christopher J
Auffray, Charles
author_sort Balaur, Irina
collection PubMed
description SUMMARY: The goal of this work is to offer a computational framework for exploring data from the Recon2 human metabolic reconstruction model. Advanced user access features have been developed using the Neo4j graph database technology and this paper describes key features such as efficient management of the network data, examples of the network querying for addressing particular tasks, and how query results are converted back to the Systems Biology Markup Language (SBML) standard format. The Neo4j-based metabolic framework facilitates exploration of highly connected and comprehensive human metabolic data and identification of metabolic subnetworks of interest. A Java-based parser component has been developed to convert query results (available in the JSON format) into SBML and SIF formats in order to facilitate further results exploration, enhancement or network sharing. AVAILABILITY AND IMPLEMENTATION: The Neo4j-based metabolic framework is freely available from: https://diseaseknowledgebase.etriks.org/metabolic/browser/. The java code files developed for this work are available from the following url: https://github.com/ibalaur/MetabolicFramework. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-54089182017-05-03 Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks Balaur, Irina Mazein, Alexander Saqi, Mansoor Lysenko, Artem Rawlings, Christopher J Auffray, Charles Bioinformatics Applications Notes SUMMARY: The goal of this work is to offer a computational framework for exploring data from the Recon2 human metabolic reconstruction model. Advanced user access features have been developed using the Neo4j graph database technology and this paper describes key features such as efficient management of the network data, examples of the network querying for addressing particular tasks, and how query results are converted back to the Systems Biology Markup Language (SBML) standard format. The Neo4j-based metabolic framework facilitates exploration of highly connected and comprehensive human metabolic data and identification of metabolic subnetworks of interest. A Java-based parser component has been developed to convert query results (available in the JSON format) into SBML and SIF formats in order to facilitate further results exploration, enhancement or network sharing. AVAILABILITY AND IMPLEMENTATION: The Neo4j-based metabolic framework is freely available from: https://diseaseknowledgebase.etriks.org/metabolic/browser/. The java code files developed for this work are available from the following url: https://github.com/ibalaur/MetabolicFramework. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-04-01 2016-12-30 /pmc/articles/PMC5408918/ /pubmed/27993779 http://dx.doi.org/10.1093/bioinformatics/btw731 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Balaur, Irina
Mazein, Alexander
Saqi, Mansoor
Lysenko, Artem
Rawlings, Christopher J
Auffray, Charles
Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks
title Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks
title_full Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks
title_fullStr Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks
title_full_unstemmed Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks
title_short Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks
title_sort recon2neo4j: applying graph database technologies for managing comprehensive genome-scale networks
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408918/
https://www.ncbi.nlm.nih.gov/pubmed/27993779
http://dx.doi.org/10.1093/bioinformatics/btw731
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