<p>This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p> <p><italic>The Dictionary of Interacting Proteins</italic> (DIP) (Xenarios <italic>et al.</italic>, 2000) is a large repository
of protein interactions: its March 2000 release included 2379 protein pairs whose
interactions have been detected by experimental methods. Even if many of these
correspond to poorly characterized proteins, the result of massive yeast two-hybrid
screenings, as many as 851 correspond to interactions detected using direct biochemical
methods.</p> <p>We used information retrieval technology to search automatically for sentences in
Medline abstracts that support these 851 DIP interactions. Surprisingly, we found
correspondence between DIP protein pairs and Medline sentences describing their
interactions in only 30% of the cases. This low coverage has interesting consequences
regarding the quality of annotations (references) introduced in the database and the
limitations of the application of information extraction (IE) technology to Molecular
Biology. It is clear that the limitation of analyzing abstracts rather than full papers and the
lack of standard protein names are difficulties of considerably more importance than the
limitations of the IE methodology employed. A positive finding is the capacity of the IE
system to identify new relations between proteins, even in a set of proteins previously
characterized by human experts. These identifications are made with a considerable degree
of precision.</p> <p>This is, to our knowledge, the first large scale assessment of IE capacity to detect
previously known interactions: we thus propose the use of the DIP data set as a biological
reference to benchmark IE systems.</p>
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Comp Funct Genomics. 2001 Aug; 2(4):196-206