Extraction of knowledge on protein-protein interaction by association rule discovery.
BACKGROUND
Protein-protein interactions are systematically examined using the yeast two-hybrid method. Consequently, a lot of protein-protein interaction data are currently being accumulated. Nevertheless, general information or knowledge on protein-protein interactions is poorly extracted from these data. Thus we have been trying to extract the knowledge from the protein-protein interaction data using data mining.


RESULTS
A data mining method is proposed to discover association rules related to protein-protein interactions. To evaluate the detected rules by the method, a new scoring measure of the rules is introduced. The method allowed us to detect popular interaction rules such as "An SH3 domain binds to a proline-rich region." These results indicate that the method may detect novel knowledge on protein-protein interactions.
Oyama
T
T
INTEC Web and Genome Informatics Corporation, 3-23 Shimoshin-machi, Toyama 930-0804, Japan. oyama@isl.intec.co.jp
Kitano
K
K
Satou
K
K
Ito
T
T
D000465:Algorithms; D001185:Artificial Intelligence; D030562:Databases, Protein; D005069:Evaluation Studies as Topic; D016247:Information Storage and Retrieval / Q000379:methods*; D011485:Protein Binding; D011506:Proteins / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000737:chemistry / Q000378:metabolism; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods; D020539:Sequence Analysis, Protein / Q000379:methods
D011506:Proteins