Evaluating the botanical coverage of PATO using an unsupervised learning algorithm

Authors:
Alyssa Janning;Hong Cui
Affiliations:
University of Arizona, Tucson, AZ;University of Arizona, Tucson, AZ
Venue:
Proceedings of the 2012 iConference
Year:
2012

Citing 3
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Abstract

In this paper, we explore issues in adopting PATO as a standard phenotypic quality ontology for the biological community. Using CharaParser's unsupervised learning algorithm and the Stanford Parser, we extract morphological descriptions from Flora of North America to be matched to terms in PATO. Using the resulting data, we examine PATO's coverage of botanically interesting terms in order to find gaps and to determine accuracy. To maintain PATO's neutrality, we recommend that term definitions be reevaluated and propose that complimentary ontologies be enhanced to close any outstanding gaps in terminology.