Title |
An ontology for microbial phenotypes
|
---|---|
Published in |
BMC Microbiology, November 2014
|
DOI | 10.1186/s12866-014-0294-3 |
Pubmed ID | |
Authors |
Marcus C Chibucos, Adrienne E Zweifel, Jonathan C Herrera, William Meza, Shabnam Eslamfam, Peter Uetz, Deborah A Siegele, James C Hu, Michelle G Giglio |
Abstract |
BackgroundPhenotypic data are routinely used to elucidate gene function in organisms amenable to genetic manipulation. However, previous to this work, there was no generalizable system in place for the structured storage and retrieval of phenotypic information for bacteria.ResultsThe Ontology of Microbial Phenotypes (OMP) has been created to standardize the capture of such phenotypic information from microbes. OMP has been built on the foundations of the Basic Formal Ontology and the Phenotype and Trait Ontology. Terms have logical definitions that can facilitate computational searching of phenotypes and their associated genes. OMP can be accessed via a wiki page as well as downloaded from SourceForge. Initial annotations with OMP are being made for Escherichia coli using a wiki-based annotation capture system. New OMP terms are being concurrently developed as annotation proceeds.ConclusionsWe anticipate that diverse groups studying microbial genetics and associated phenotypes will employ OMP for standardizing microbial phenotype annotation, much as the Gene Ontology has standardized gene product annotation. The resulting OMP resource and associated annotations will facilitate prediction of phenotypes for unknown genes and result in new experimental characterization of phenotypes and functions. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Zambia | 1 | 2% |
Germany | 1 | 2% |
France | 1 | 2% |
Brazil | 1 | 2% |
Unknown | 60 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 14 | 22% |
Student > Master | 12 | 19% |
Student > Ph. D. Student | 11 | 17% |
Student > Bachelor | 6 | 9% |
Professor > Associate Professor | 5 | 8% |
Other | 10 | 16% |
Unknown | 6 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 20 | 31% |
Biochemistry, Genetics and Molecular Biology | 11 | 17% |
Immunology and Microbiology | 6 | 9% |
Computer Science | 5 | 8% |
Medicine and Dentistry | 3 | 5% |
Other | 9 | 14% |
Unknown | 10 | 16% |