Protein association discovery can directly contribute toward developing protein pathways; hence it is a significant problem in bioinformatics. LUCAS (Library of User-Oriented Concepts for Access Services) was designed to automatically extract and determine associations among proteins from biomedical literature. Such a tool has notable potential to automate database construction in biomedicine, instead of relying on experts' analysis. This paper reports on the mechanisms for automatically generating clusters of proteins. A formal evaluation of the system, based on a subset of 2000 MEDLINE titles and abstracts, has been conducted against Swiss-Prot database in which the associations among concepts are entered by experts manually.
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