Computable visually observed phenotype ontological framework for plants

Background: The ability to search for and precisely compare similar phenotypic appearances within and across species has vast potential in plant science and genetic research. The difficulty in doing so lies in the fact that many visual phenotypic data, especially visually observed phenotypes that often times cannot be directly measured quantitatively, are in the form of text annotations, and these descriptions are plagued by semantic ambiguity, heterogeneity, and low granularity. Though several bio-ontologies have been developed to standardize phenotypic (and genotypic) information and permit comparisons across species, these semantic issues persist and prevent precise analysis and retrieval of information. A framework suitable for the modeling and analysis of precise computable representations of such phenotypic appearances is needed. Results: We have developed a new framework called the Computable Visually Observed Phenotype Ontological Framework for plants. This work provides a nov...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Jaturon Harnsomburana, Jason M. Green, Adrian S. Barb, Mary Schaeffer, Leszek Vincent, Chi-Ren Shyu
• Keywords: Automatic Annotation, Biometrics, BMCBI 2011, Semantic Ambiguity, Text Annotations