Positional Paper on a Semantic Web for Life Sciences
October 2004
Alexander A. Morgan, The MITRE Corporation
Alexander S. Yeh, The MITRE Corporation
Marc Colosimo, The MITRE Corporation
ABSTRACT
Our research primarily involves the application of natural language processing
technology to biomedical literature in support of such applications as semi-automated
functional annotation of proteins and genes, and gene name normalization for improved
search and retrieval of text information. We have performed studies in the use of existing
database resources in these efforts (Morgan, Hirschman et al. 2003) and together with
CNB/CSIC-Madrid, we have organized and administered a challenge evaluation,
BioCreAtIvE (Valencia, Blaschke et al. 2004), for text mining systems applied to
biomedical literature. Our primary experience with ontologies is with GO (The Gene
Ontology Consortium 2000), and with some of the specific hierarchical controlled
vocabularies. These include the FlyBase Controlled Vocabulary (The FlyBase
Consortium 1993) and the TVFac Hierarchy (http://www.tvfac.lanl.gov/right.html); our
focus has been on automating the association of small excerpts of text and the underlying
entities described (mentioned) in the text with concepts in the ontologies. We focus here
on how existing ontologies and related resources can be augmented to aid text-mining
and how text mining evaluation techniques can contribute to ontology evolution, by
viewing ontologies as annotation guidelines when constructing/populating them.
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