BioNoculars: extracting protein-protein interactions from biomedical text

Authors:
Amgad Madkour;Kareem Darwish;Hany Hassan;Ahmed Hassan;Ossama Emam
Affiliations:
IBM Cairo Technology Development Center, Giza, Egypt;IBM Cairo Technology Development Center, Giza, Egypt;IBM Cairo Technology Development Center, Giza, Egypt;IBM Cairo Technology Development Center, Giza, Egypt;IBM Cairo Technology Development Center, Giza, Egypt
Venue:
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
Year:
2007

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Abstract

The vast number of published medical documents is considered a vital source for relationship discovery. This paper presents a statistical unsupervised system, called BioNoculars, for extracting protein-protein interactions from biomedical text. BioNoculars uses graph-based mutual reinforcement to make use of redundancy in data to construct extraction patterns in a domain independent fashion. The system was tested using MEDLINE abstract for which the protein-protein interactions that they contain are listed in the database of interacting proteins and protein-protein interactions (DIPPPI). The system reports an F-Measure of 0.55 on test MEDLINE abstracts.