Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Free-Sets: A Condensed Representation of Boolean Data for the Approximation of Frequency Queries
Data Mining and Knowledge Discovery
Modeling KDD Processes within the Inductive Database Framework
DaWaK '99 Proceedings of the First International Conference on Data Warehousing and Knowledge Discovery
Efficient Local Search in Conceptual Clustering
DS '01 Proceedings of the 4th International Conference on Discovery Science
A perspective on inductive databases
ACM SIGKDD Explorations Newsletter
Using transposition for pattern discovery from microarray data
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Information-theoretic co-clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Constraint-based concept mining and its application to microarray data analysis
Intelligent Data Analysis
Review: Formal concept analysis in knowledge processing: A survey on applications
Expert Systems with Applications: An International Journal
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One of the exciting scientific challenges in functional genomics concerns the discovery of biologically relevant patterns from gene expression data. For instance, it is extremely useful to provide putative synexpression groups or transcription modules to molecular biologists. We propose a methodology that has been proved useful in real cases. It is described as a prototypical KDD scenario which starts from raw expression data selection until useful patterns are delivered. It has been validated on real data sets. Our conceptual contribution is (a) to emphasize how to take the most from recent progress in constraint-based mining of set patterns, and (b) to propose a generic approach for gene expression data enrichment. Doing so, we survey our algorithmic breakthrough which has been the core of our contribution to the IST FET cInQ project.