Evidence map›Paper›PMID 27076900›Full record

ArticleJournal of biomedical semantics2016

MicrO: an ontology of phenotypic and metabolic characters, assays, and culture media found in prokaryotic taxonomic descriptions.

Carrine E Blank, Hong Cui, Lisa R Moore, Ramona L Walls

Abstract read
In one paragraph

Article in Journal of biomedical semantics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Review
  3. OHMI: the ontology of host-microbiome interactions.Journal of biomedical semantics · 2019
    Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. Article
  10. Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Carrine E BlankDepartment of Geosciences, University of Montana, Missoula, MT 59812 USA.
Hong CuiSchool of Information, University of Arizona, Tucson, AZ 85719 USA.
Lisa R MooreDepartment of Biological Sciences, University of Southern Maine, Portland, ME 04104 USA.
Ramona L WallsCyVerse, University of Arizona, Tucson, AZ 85721 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMicrO is an ontology of microbiological terms, including prokaryotic qualities and processes, material entities (such as cell components), chemical entities (such as microbiological culture media and medium ingredients), and assays. The ontology was built to support the ongoing development of a natural language processing algorithm, MicroPIE (or, Microbial Phenomics Information Extractor). During the MicroPIE design process, we realized there was a need for a prokaryotic ontology which would capture the evolutionary diversity of phenotypes and metabolic processes across the tree of life, capture the diversity of synonyms and information contained in the taxonomic literature, and relate microbiological entities and processes to terms in a large number of other ontologies, most particularly the Gene Ontology (GO), the Phenotypic Quality Ontology (PATO), and the Chemical Entities of Biological Interest (ChEBI). We thus constructed MicrO to be rich in logical axioms and synonyms gathered from the taxonomic literature.

resultsMicrO currently has ~14550 classes (~2550 of which are new, the remainder being microbiologically-relevant classes imported from other ontologies), connected by ~24,130 logical axioms (5,446 of which are new), and is available at (http://purl.obolibrary.org/obo/MicrO.owl) and on the project website at https://github.com/carrineblank/MicrO. MicrO has been integrated into the OBO Foundry Library (http://www.obofoundry.org/ontology/micro.html), so that other ontologies can borrow and re-use classes. Term requests and user feedback can be made using MicrO's Issue Tracker in GitHub. We designed MicrO such that it can support the ongoing and future development of algorithms that can leverage the controlled vocabulary and logical inference power provided by the ontology.

conclusionsBy connecting microbial classes with large numbers of chemical entities, material entities, biological processes, molecular functions, and qualities using a dense array of logical axioms, we intend MicrO to be a powerful new tool to increase the computing power of bioinformatics tools such as the automated text mining of prokaryotic taxonomic descriptions using natural language processing. We also intend MicrO to support the development of new bioinformatics tools that aim to develop new connections between microbial phenotypes and genotypes (i.e., the gene content in genomes). Future ontology development will include incorporation of pathogenic phenotypes and prokaryotic habitats.

Indexed as

Biological OntologiesCulture MediaPhenotypeArchaeaBacteriaCulture MediaArchaeaBacteriaChEBIGene OntologyMetabolic charactersMicrobesMicrobial bioinformaticsNatural language processingOntologyProkaryotesProkaryotic taxonomy

Identifiers

PMID27076900
PMCPMC4830071

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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.