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» Mining Gene Expression Data using Domain Knowledge
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KDD
1995
ACM
193views Data Mining» more  KDD 1995»
15 years 3 months ago
Analyzing the Benefits of Domain Knowledge in Substructure Discovery
Discovering repetitive, interesting, and functional substructures in a structural database improves the ability to interpret and compress the data. However, scientists working wit...
Surnjani Djoko, Diane J. Cook, Lawrence B. Holder
BMCBI
2010
76views more  BMCBI 2010»
14 years 11 months ago
Validation and characterization of DNA microarray gene expression data distribution and associated moments
Background: The data from DNA microarrays are increasingly being used in order to understand effects of different conditions, exposures or diseases on the modulation of the expres...
Reuben Thomas, Luis de la Torre, Xiaoqing Chang, S...
BMCBI
2004
169views more  BMCBI 2004»
14 years 11 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
DMKD
2003
ACM
96views Data Mining» more  DMKD 2003»
15 years 5 months ago
Using transposition for pattern discovery from microarray data
We analyze expression matrices to identify a priori interesting sets of genes, e.g., genes that are frequently co-regulated. Such matrices provide expression values for given biol...
François Rioult, Jean-François Bouli...
KDD
1994
ACM
123views Data Mining» more  KDD 1994»
15 years 3 months ago
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we cal...
David Heckerman, Dan Geiger, David Maxwell Chicker...