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- Title
Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks.
- Authors
Balaur, Irina; Mazein, Alexander; Saqi, Mansoor; Lysenko, Artem; Rawlings, Christopher J.; Auffray, Charles
- Abstract
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.
- Subjects
METABOLIC models; METABOLIC regulation; BIOLOGICAL networks; SYSTEMS biology; BIOLOGICAL databases
- Publication
Bioinformatics, 2017, Vol 33, Issue 7, p1096
- ISSN
1367-4803
- Publication type
Article
- DOI
10.1093/bioinformatics/btw731