Research Project, PhylOnt, A Domain-Specific Ontology for Phylogenetic Analysis
PhylOnt is a collabotation project with University of Georgia. The specific objective of this reserach was to develop and deploy an ontology for a novel ontology-driven semantic problem solving approach in phylogenetic analysis and down- stream use of phylogenetic trees. This is a foundation to allow an integrated platform in phylogenetically based comparative analysis and data integration. PhylOnt is an extensible ontology, that describes the methods employed to estimate trees given a data matrix, models and programs used for phylogenetic analysis and descriptions of phylogenetic trees including branch-length information and support values. It also describes the provenance information for phylogenetics analysis data such as information about publications and studies related to phylogenetic analyses. To illustrate the utility of PhylOnt, I annotated scientific literature and files to support semantic search.
Download the last version from NCBO
PhylOnt has been publicly shared through the BioPortal at the National Center for Biomedical Ontologies (NCBO) PhylOnt
- I described the PhylOnt ontology, an extensible ontology targeted towards data integration
- I described the systematic process taken in developing PhylOnt.
- I provided a comprehensive use case of using PhylOnt in annotation. I used a subset
of our Kino annotation Tools (Ranabahu et al., 2011a; Panahiazar et al., 2011), which enables annotation and faceted search over the annotated publications. The subsequent sections are organized.
- Using Ontology for Annotation
Kino-Phylo is an integrated suite of tools that enables scientists to annotate phylogenetic related web-based documents as a branch of Kino(Ranabahu, panahiazar, et al., 2011). Kino-Phylo can annotate documents by accessing PhylOnt and other NCBO ontologies.
2010 – 2012
Maryam Panahiazar, Ajith, Ranabahu, Vahid Taslimi, Hima, Yalamanchili, Arlin Stoltzfus, Jim Leebens-Mack, and Amit Sheth. IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012, 52: 1, 106-116 lower than 20% acceptance rate
Maryam Panahiazar, Amit Sheth, Jim Leebens-Mack. To be published in BMC Medical Genomics Special Issue in Feb 2013