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» Discovering Interesting Subsets Using Statistical Analysis
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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 10 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...
BMCBI
2006
127views more  BMCBI 2006»
13 years 10 months ago
Using local gene expression similarities to discover regulatory binding site modules
Background: We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to rela...
Bartek Wilczynski, Torgeir R. Hvidsten, Andriy Kry...
IJDMB
2008
128views more  IJDMB 2008»
13 years 9 months ago
Protein homology detection with biologically inspired features and interpretable statistical models
: Computational classification of proteins using methods such as string kernels and Fisher-SVM has demonstrated great success. However, the resulting models do not offer an immedia...
Pai-Hsi Huang, Vladimir Pavlovic
TVCG
2008
103views more  TVCG 2008»
13 years 9 months ago
Who Votes For What? A Visual Query Language for Opinion Data
Surveys and opinion polls are extremely popular in the media, especially in the months preceding a general election. However, the available tools for analyzing poll results often r...
Geoffrey M. Draper, Richard F. Riesenfeld
SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
13 years 11 months ago
Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data
Microarray experiments have been extensively used for simultaneously measuring DNA expression levels of thousands of genes in genome research. A key step in the analysis of gene e...
Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvri...