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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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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. |
format | Online Article Text |
id | pubmed-5408918 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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