Context-Specific Ontology Integration: A Bayesian Approach

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Context-Specific Ontology Integration: A Bayesian Approach

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Title: Context-Specific Ontology Integration: A Bayesian Approach
Author: Marwah, Kshitij; Katzin, Dustin; Noy, Natalya F.; Ramoni, Marco; Zollanvari, Amin; Alterovitz, Gil

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Citation: Marwah, Kshitij, Dustin Katzin, Amin Zollanvari, Natalya F. Noy, Marco Ramoni, and Gil Alterovitz. 2012. Context-specific ontology integration: a Bayesian approach. AMIA Summits on Translational Science Proceedings 2012: 79-86.
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Abstract: We introduce a principled computational framework and methodology for automated discovery of context-specific functional links between ontologies. Our model leverages over disparate free-text literature resources to score the model of dependency linking two terms under a context against their model of independence. We identify linked terms as those having a significant bayes factor (p < 0.01). To scale our algorithm over massive ontologies, we propose a heuristic pruning technique as an efficient algorithm for inferring such links. We have applied this method to translationalize Gene Ontology to all other ontologies available at National Center of Biomedical Ontology (NCBO) BioPortal under the context of Human Disease ontology. Our results show that in addition to broadening the scope of hypothesis for researchers, our work can potentially be used to explore continuum of relationships among ontologies to guide various biological experiments.
Published Version: http://proceedings.amia.org/23509a/1
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392068/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10456095
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