ArticleBioinformatics (Oxford, England)2017
Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Graph databases in systems biology: a systematic review.Briefings in bioinformatics · 2024Pooled it
- Deciphering shared molecular dysregulation across Parkinson's disease variants using a multi-modal network-based data integration and analysis.NPJ Parkinson's disease · 2025Article
- Comprehensive applications of the artificial intelligence technology in new drug research and development.Health information science and systems · 2024Review
- Article
- GenomicKB: a knowledge graph for the human genome.Nucleic acids research · 2023Article
- A guide for developing comprehensive systems biology maps of disease mechanisms: planning, construction and maintenance.Frontiers in bioinformatics · 2023Article
- Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data.Psychiatry investigation · 2022Article
- A knowledge graph to interpret clinical proteomics data.Nature biotechnology · 2022Article
- LinkedImm: a linked data graph database for integrating immunological data.BMC bioinformatics · 2021Article
- Head and Tail Entity Fusion Model in Medical Knowledge Graph Construction: Case Study for Pituitary Adenoma.JMIR medical informatics · 2021Article
- An overview of graph databases and their applications in the biomedical domain.Database : the journal of biological databases and curation · 2021Article
- COMBAT-TB-NeoDB: fostering tuberculosis research through integrative analysis using graph database technologies.Bioinformatics (Oxford, England) · 2020Article
- A linked data graph approach to integration of immunological data.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2019Article
- Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.Briefings in bioinformatics · 2019Review
- Navigating the disease landscape: knowledge representations for contextualizing molecular signatures.Briefings in bioinformatics · 2019Review
- Systems medicine disease maps: community-driven comprehensive representation of disease mechanisms.NPJ systems biology and applications · 2018Article
- Reactome graph database: Efficient access to complex pathway data.PLoS computational biology · 2018Article
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Corrections and comments
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Authors and funding
6 authors.
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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. 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 . Contact: ibalaur@eisbm.org. Supplementary information: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.