01720nas a2200169 4500008004100000245010700041210006900148260000900217520116000226653001501386653000801401100002001409700001201429700001801441700001901459856007201478 2005 eng d 00 aLinking Ontological Resources Using Aggregatable Substance Identifiers to Organize Extracted Relations 0 aLinking Ontological Resources Using Aggregatable Substance Ident c2005 3 aSystems that extract biological regulatory pathway relations from free-text sources are
intended to help researchers leverage vast and growing collections of research literature.
Several systems to extract such relations have been developed but little work has focused on
how those relations can be usefully organized (aggregated) to support visualization systems or
analysis algorithms. Ontological resources that enumerate name strings for different types of
biomedical objects should play a key role in the organization process. In this paper we
delineate five potentially useful levels of relational granularity and propose the use of
aggregatable substance identifiers to help reduce lexical ambiguity. An aggregatable
substance identifier applies to a gene and its products. We merged 4 extensive lexicons and
compared the extracted strings to the text of five million MEDLINE abstracts. We report on
the ambiguity within and between name strings and common English words. Our results show
an 89% reduction in ambiguity for the extracted human substance name strings when using an
aggregatable substance approach. 10 aAccounting 10 aBIS 1 aMarshall, Byron 1 aSu, Hua 1 aMcDonald, Dan 1 aChen, Hsinchun uhttp://people.oregonstate.edu/~marshaby/Papers/marshall_PSB2005.pdf