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K. Kitano

dblp:22/883 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2002
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
association rule mining		 0.012002
Extraction of knowledge on protein-protein interaction by association rule discovery · Bioinform. 2002
Bioinformatics and computational biology › protein analysis
protein-protein interaction		 0.012002
Extraction of knowledge on protein-protein interaction by association rule discovery · Bioinform. 2002

Methods — techniques the papers use, named apart from their topics

data mining · 0.0association rule mining · 0.0
YearPublicationVenuePosition
2002 Extraction of knowledge on protein-protein interaction by association rule discovery
abstract
MOTIVATION: 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.
T. Oyama, K. Kitano, Kenji Satou, Takashi Ito
 Bioinform.2