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» E-CAST: A Data Mining Algorithm for Gene Expression Data
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KDD
2004
ACM
314views Data Mining» more  KDD 2004»
14 years 6 months ago
Assessment of discretization techniques for relevant pattern discovery from gene expression data
In the domain of gene expression data analysis, various researchers have recently emphasized the promising application of pattern discovery techniques like association rule mining...
Ruggero G. Pensa, Claire Leschi, Jéré...
CINQ
2004
Springer
116views Database» more  CINQ 2004»
13 years 9 months ago
Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining
Abstract. One of the exciting scientific challenges in functional genomics concerns the discovery of biologically relevant patterns from gene expression data. For instance, it is e...
Ruggero G. Pensa, Jérémy Besson, C&e...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 6 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...
KDD
2001
ACM
156views Data Mining» more  KDD 2001»
14 years 6 months ago
Classification of genes using probabilistic models of microarray expression profiles
Paul Pavlidis, Christopher Tang, William Stafford ...
CIKM
2006
Springer
13 years 9 months ago
Mining coherent patterns from heterogeneous microarray data
Microarray technology is a powerful tool for geneticists to monitor interactions among tens of thousands of genes simultaneously. There has been extensive research on coherent sub...
Xiang Zhang, Wei Wang 0010