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PLoS One. 2017 Jul 14;12(7):e0179130. doi: 10.1371/journal.pone.0179130. eCollection 2017.

biochem4j: Integrated and extensible biochemical knowledge through graph databases.

Author information

1
Manchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.
2
School of Computer Science, The University of Manchester, Manchester, United Kingdom.
3
Institute of Systems and Synthetic Biology, University of Evry, Val d'Essonne, Evry, France.
4
School of Chemistry, The University of Manchester, Manchester, United Kingdom.
5
Center for Quantitative Medicine, UConn Health, 263 Farmington Avenue, Farmington, CT, United States of America.

Abstract

Biologists and biochemists have at their disposal a number of excellent, publicly available data resources such as UniProt, KEGG, and NCBI Taxonomy, which catalogue biological entities. Despite the usefulness of these resources, they remain fundamentally unconnected. While links may appear between entries across these databases, users are typically only able to follow such links by manual browsing or through specialised workflows. Although many of the resources provide web-service interfaces for computational access, performing federated queries across databases remains a non-trivial but essential activity in interdisciplinary systems and synthetic biology programmes. What is needed are integrated repositories to catalogue both biological entities and-crucially-the relationships between them. Such a resource should be extensible, such that newly discovered relationships-for example, those between novel, synthetic enzymes and non-natural products-can be added over time. With the introduction of graph databases, the barrier to the rapid generation, extension and querying of such a resource has been lowered considerably. With a particular focus on metabolic engineering as an illustrative application domain, biochem4j, freely available at http://biochem4j.org, is introduced to provide an integrated, queryable database that warehouses chemical, reaction, enzyme and taxonomic data from a range of reliable resources. The biochem4j framework establishes a starting point for the flexible integration and exploitation of an ever-wider range of biological data sources, from public databases to laboratory-specific experimental datasets, for the benefit of systems biologists, biosystems engineers and the wider community of molecular biologists and biological chemists.

PMID:
28708831
PMCID:
PMC5510799
DOI:
10.1371/journal.pone.0179130
[Indexed for MEDLINE]
Free PMC Article

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