title: An ontology for microbial phenotypes.
abstract: BACKGROUND
  Phenotypic 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.
  
  
  RESULTS
  The 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.
  
  
  CONCLUSIONS
  We 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.
authors.affiliation: Institute for Genome Sciences and Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD, USA. mchibucos@som.umaryland.edu.
authors.forename: Marcus C
authors.initials: MC
authors.lastname: Chibucos
authors.affiliation: Department of Biochemistry and Biophysics, Texas A&M University and Texas AgriLife Research, College Station, TX, USA. adrienne.zweifel@ucsf.edu.|Current address: University of California, San Francisco, CA, USA. adrienne.zweifel@ucsf.edu.
authors.forename: Adrienne E
authors.initials: AE
authors.lastname: Zweifel
authors.affiliation: Department of Biology, Texas A&M University, College Station, TX, USA. jherrera@bio.tamu.edu.
authors.forename: Jonathan C
authors.initials: JC
authors.lastname: Herrera
authors.affiliation: Department of Biology, Texas A&M University, College Station, TX, USA. wmeza@bio.tamu.edu.
authors.forename: William
authors.initials: W
authors.lastname: Meza
authors.affiliation: Department of Biochemistry and Biophysics, Texas A&M University and Texas AgriLife Research, College Station, TX, USA. shabnam127@hotmail.com.
authors.forename: Shabnam
authors.initials: S
authors.lastname: Eslamfam
authors.affiliation: Virginia Commonwealth University, Richmond, VA, USA. phuetz@vcu.edu.
authors.forename: Peter
authors.initials: P
authors.lastname: Uetz
authors.affiliation: Department of Biology, Texas A&M University, College Station, TX, USA. d-siegele@tamu.edu.
authors.forename: Deborah A
authors.initials: DA
authors.lastname: Siegele
authors.affiliation: Department of Biochemistry and Biophysics, Texas A&M University and Texas AgriLife Research, College Station, TX, USA. jimhu@tamu.edu.
authors.forename: James C
authors.initials: JC
authors.lastname: Hu
authors.affiliation: Institute for Genome Sciences and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA. mgiglio@som.umaryland.edu.
authors.forename: Michelle G
authors.initials: MG
authors.lastname: Giglio
mesh_terms: D018407:Bacterial Physiological Phenomena; D019295:Computational Biology / Q000379:methods*; D010641:Phenotype; D012984:Software