Evidence map›Paper›PMID 28708831›Full record

ArticlePloS one2017

biochem4j: Integrated and extensible biochemical knowledge through graph databases.

Neil Swainston, Riza Batista-Navarro, Pablo Carbonell, Paul D Dobson, Mark Dunstan, Adrian J Jervis, Maria Vinaixa, Alan R Williams, Sophia Ananiadou, Jean-Loup Faulon and 4 more

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. FGDB: a comprehensive graph database of ligand fragments from the Protein Data Bank.Database : the journal of biological databases and curation · 2022
    Article
  7. Article
  8. An overview of graph databases and their applications in the biomedical domain.Database : the journal of biological databases and curation · 2021
    Article
  9. Article
  10. Article
  11. Selenzyme: enzyme selection tool for pathway design.Bioinformatics (Oxford, England) · 2018
    Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Neil SwainstonManchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.ORCID http://orcid.org/0000-0001-7020-1236
Riza Batista-NavarroSchool of Computer Science, The University of Manchester, Manchester, United Kingdom.
Pablo CarbonellManchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.ORCID http://orcid.org/0000-0002-0993-5625
Paul D DobsonSchool of Computer Science, The University of Manchester, Manchester, United Kingdom.ORCID http://orcid.org/0000-0002-5996-0511
Mark DunstanManchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.
Adrian J JervisManchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.
Maria VinaixaManchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.
Alan R WilliamsSchool of Computer Science, The University of Manchester, Manchester, United Kingdom.ORCID http://orcid.org/0000-0003-3156-2105
Sophia AnaniadouSchool of Computer Science, The University of Manchester, Manchester, United Kingdom.
Jean-Loup FaulonManchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.
Pedro MendesCenter for Quantitative Medicine, UConn Health, 263 Farmington Avenue, Farmington, CT, United States of America.ORCID http://orcid.org/0000-0001-6507-9168
Douglas B KellManchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.
Nigel S ScruttonManchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.ORCID http://orcid.org/0000-0002-4182-3500
Rainer BreitlingManchester Centre for Synthetic Biology of Fine and Specialty Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom.ORCID http://orcid.org/0000-0001-7173-0922

Funding

Biotechnology and Biological Sciences Research Council BB/K019783/1Biotechnology and Biological Sciences Research Council BB/M017702/1
6 · The paper itself

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.

Indexed as

Databases, FactualUser-Computer InterfaceComputational BiologyInternet

Identifiers

PMID28708831
PMCPMC5510799

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.