https://doi.org/10.1186/1755-8794-6-S3-S5">
 

Advancing Data Reuse in Phyloinformatics Using an Ontology-Driven Semantic Web Approach

Document Type

Article

Abstract

Phylogenetic analyses can resolve historical relationships among genes, organisms or higher taxa. Understanding such relationships can elucidate a wide range of biological phenomena, including, for example, the importance of gene and genome duplications in the evolution of gene function, the role of adaptation as a driver of diversification, or the evolutionary consequences of biogeographic shifts. Phyloinformaticists are developing data standards, databases and communication protocols (e.g. Application Programming Interfaces, APIs) to extend the accessibility of gene trees, species trees, and the metadata necessary to interpret these trees, thus enabling researchers across the life sciences to reuse phylogenetic knowledge. Specifically, Semantic Web technologies are being developed to make phylogenetic knowledge interpretable by web agents, thereby enabling intelligently automated, high-throughput reuse of results generated by phylogenetic research. This manuscript describes an ontology-driven, semantic problem-solving environment for phylogenetic analyses and introduces artefacts that can promote phyloinformatic efforts to promote accessibility of trees and underlying metadata. PhylOnt is an extensible ontology with concepts describing tree types and tree building methodologies including estimation methods, models and programs. In addition we present the PhylAnt platform for annotating scientific articles and NeXML files with PhylOnt concepts. The novelty of this work is the annotation of NeXML files and phylogenetic related documents with PhylOnt Ontology. This approach advances data reuse in phyloinformatics.

Digital Object Identifier (DOI)

https://doi.org/10.1186/1755-8794-6-S3-S5

APA Citation

Panahiazar, M., Sheth, A. P., Ranabahu, A. H., Vos, R., & Leebens-Mack, J. (2013). Advancing Data Reuse in Phyloinformatics using an Ontology-Driven Semantic Web Approach. BMC Medical Genomics, 6 (S3), S5.
https://doi.org/10.1186/1755-8794-6-S3-S5

Share

COinS