ArticlePloS one2023
Omnicrobe, an open-access database of microbial habitats and phenotypes using a comprehensive text mining and data fusion approach.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
- Comparing optimal transport and machine learning approaches for databases merging in scenarios involving missing data in covariates. Application to medical research.Bioinformatics (Oxford, England) · 2026Article
- microntology: a lightweight, data-driven controlled vocabulary to describe earth's microbial habitats.Bioinformatics (Oxford, England) · 2026Article
- Integrative phylogenomic and pangenome landscape of Bacillus: insights from 10,000 genomes into taxonomy, functional potential, and biotechnological applications.World journal of microbiology & biotechnology · 2026Article
- proGenomes4: providing 2 million accurately and consistently annotated high-quality prokaryotic genomes.Nucleic acids research · 2026Article
- Advancing the study of microbial symbionts of amphibians and reptiles.Frontiers in amphibian and reptile science · 2026Article
- Integrating natural language processing and genome analysis enables accurate bacterial phenotype prediction.NAR genomics and bioinformatics · 2025Article
- BacDive in 2025: the core database for prokaryotic strain data.Nucleic acids research · 2025Article
- Genetic Signatures of Contrasted Outbreak Histories of "Evolutionary applications · 2024Article
- Interpretation knowledge extraction for genetic testing via question-answer model.BMC genomics · 2024Article
- TaeC: A manually annotated text dataset for trait and phenotype extraction and entity linking in wheat breeding literature.PloS one · 2024Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The dramatic increase in the number of microbe descriptions in databases, reports, and papers presents a two-fold challenge for accessing the information: integration of heterogeneous data in a standard ontology-based representation and normalization of the textual descriptions by semantic analysis. Recent text mining methods offer powerful ways to extract textual information and generate ontology-based representation. This paper describes the design of the Omnicrobe application that gathers comprehensive information on habitats, phenotypes, and usages of microbes from scientific sources of high interest to the microbiology community. The Omnicrobe database contains around 1 million descriptions of microbe properties. These descriptions are created by analyzing and combining six information sources of various kinds, i.e. biological resource catalogs, sequence databases and scientific literature. The microbe properties are indexed by the Ontobiotope ontology and their taxa are indexed by an extended version of the taxonomy maintained by the National Center for Biotechnology Information. The Omnicrobe application covers all domains of microbiology. With simple or rich ontology-based queries, it provides easy-to-use support in the resolution of scientific questions related to the habitats, phenotypes, and uses of microbes. We illustrate the potential of Omnicrobe with a use case from the food innovation domain.
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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 Socratic graph.