ArticlePloS one2017
biochem4j: Integrated and extensible biochemical knowledge through graph databases.
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.
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.
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.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Graph databases in systems biology: a systematic review.Briefings in bioinformatics · 2024Pooled it
- Microbiome knowledge graph as a tool to understand bacteria-host associations.Archives of microbiology · 2025Article
- Article
- Integrating biological knowledge for mechanistic inference in the host-associated microbiome.Frontiers in microbiology · 2024Review
- InCliniGene enables high-throughput and comprehensive in vivo clonal tracking toward clinical genomics data integration.Database : the journal of biological databases and curation · 2023Article
- FGDB: a comprehensive graph database of ligand fragments from the Protein Data Bank.Database : the journal of biological databases and curation · 2022Article
- GeneORator: An Efficient Method for the Systematic Mutagenesis of Entire Genes.Methods in molecular biology (Clifton, N.J.) · 2022Article
- An overview of graph databases and their applications in the biomedical domain.Database : the journal of biological databases and curation · 2021Article
- Advantages of using graph databases to explore chromatin conformation capture experiments.BMC bioinformatics · 2021Article
- A strategy for large-scale comparison of evolutionary- and reaction-based classifications of enzyme function.Database : the journal of biological databases and curation · 2020Article
- Selenzyme: enzyme selection tool for pathway design.Bioinformatics (Oxford, England) · 2018Article
- Reactome graph database: Efficient access to complex pathway data.PLoS computational biology · 2018Article
- An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals.Communications biology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
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.
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What OpenQuestion holds
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.