title: Ontologies as integrative tools for plant science.
abstract: OBJECTIVE
  Bio-ontologies are essential tools for accessing and analyzing the rapidly growing pool of plant genomic and phenomic data. Ontologies provide structured vocabularies to support consistent aggregation of data and a semantic framework for automated analyses and reasoning. They are a key component of the semantic web.
  
  
  METHODS
  This paper provides background on what bio-ontologies are, why they are relevant to botany, and the principles of ontology development. It includes an overview of ontologies and related resources that are relevant to plant science, with a detailed description of the Plant Ontology (PO). We discuss the challenges of building an ontology that covers all green plants (Viridiplantae).
  
  
  RESULTS
  Ontologies can advance plant science in four keys areas: (1) comparative genetics, genomics, phenomics, and development; (2) taxonomy and systematics; (3) semantic applications; and (4) education.
  
  
  CONCLUSIONS
  Bio-ontologies offer a flexible framework for comparative plant biology, based on common botanical understanding. As genomic and phenomic data become available for more species, we anticipate that the annotation of data with ontology terms will become less centralized, while at the same time, the need for cross-species queries will become more common, causing more researchers in plant science to turn to ontologies.
authors: New York Botanical Garden, Bronx, 10458-5126, USA.
authors: Ramona L
authors: RL
authors: Walls
authors: Balaji
authors: B
authors: Athreya
authors: Laurel
authors: L
authors: Cooper
authors: Justin
authors: J
authors: Elser
authors: Maria A
authors: MA
authors: Gandolfo
authors: Pankaj
authors: P
authors: Jaiswal
authors: Christopher J
authors: CJ
authors: Mungall
authors: Justin
authors: J
authors: Preece
authors: Stefan
authors: S
authors: Rensing
authors: Barry
authors: B
authors: Smith
authors: Dennis W
authors: DW
authors: Stevenson
mesh_terms: D001901:Botany / Q000379:methods; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D003628:Database Management Systems; D016208:Databases, Factual; D018745:Genome, Plant / Q000235:genetics; D023281:Genomics; D058977:Molecular Sequence Annotation; D010641:Phenotype; D010944:Plants / Q000033:anatomy & histology / Q000145:classification / Q000235:genetics*; D012660:Semantics; D009626:Terminology as Topic; D018875:Vocabulary, Controlled