build a rich ontology, integrating Wikipedia’s infobox-class schemata with WordNet. We demonstrate how the resulting ontology may be used to enhance Wikipedia with improved query processing and other features.

phenotypes using ontologies, we used an Entity-Quality (EQ) methodology, wherein the affected entity (E) and how it is affected (Q) are recorded using terms from a variety of ontologies. Using this EQ method, we annotated the phenotypes of 11 gene-linked human diseases described in Online Mendelian

methodology which exploits ontology population and enrichment methods to enhance the knowledge captured by the instances of the ontology and their various lexicalizations. Furthermore, we employ ontology learning techniques to alleviate as much as possible the intervention of human into the proposed

, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast. Here, we apply the PhenomeNET to identify related classes from four phenotype and disease ontologies using automated reasoning. We demonstrate that we can identify a large number of mappings, some of which require automated reasoning

The Nef protein of human immunodeficiency virus type 1 (HIV-1) stimulates viral infectivity. The mechanism of this phenotype was investigated. Viruses containing disrupted nef genes were 4 to 40 times less infectious than wild-type HIV-1 in a single-round infection. The Nef-mediated stimulation

methodology which exploits ontology population and enrichment methods to enhance the knowledge captured by the instances of the ontology and their various lexicalizations. Furthermore, we employ ontology learning techniques to alleviate as much as possible the intervention of human into the proposed

been enhanced by ontologies shared among genomic databases. Here, we suggest that evolutionary and genomics databases can be developed to exchange and use information through shared phenotype and anatomy ontologies. This would facilitate computing on evolutionary questions pertaining to the genetic

and test suite corpora

Background: Phenotype ontologies are queryable classifications of phenotypes. They provide a widely-used means for annotating phenotypes in a form that is human-readable, programatically accessible and that can be used to group annotations in biologically meaningful ways. Accurate manual annotation

Abstract: The use of model organisms as tools for the investigation of human genetic variation has significantly and rapidly advanced our understanding of the aetiolo-gies underlying hereditary traits. However, while equiva-lences in the DNA sequence of two species may be readily inferred through