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» Combined Gene Selection Methods for Microarray Data Analysis
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KDD
2002
ACM
147views Data Mining» more  KDD 2002»
16 years 3 months ago
Visualized Classification of Multiple Sample Types
The goal of the knowledge discovery and data mining is to extract the useful knowledge from the given data. Visualization enables us to find structures, features, patterns, and re...
Li Zhang, Aidong Zhang, Murali Ramanathan
BMCBI
2007
154views more  BMCBI 2007»
15 years 3 months ago
Classification of heterogeneous microarray data by maximum entropy kernel
Background: There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are c...
Wataru Fujibuchi, Tsuyoshi Kato
BMCBI
2008
128views more  BMCBI 2008»
15 years 3 months ago
Meta-analysis of breast cancer microarray studies in conjunction with conserved cis-elements suggest patterns for coordinate reg
Background: Gene expression measurements from breast cancer (BrCa) tumors are established clinical predictive tools to identify tumor subtypes, identify patients showing poor/good...
David D. Smith, Pål Sætrom, Ola R. Sn&...
BMCBI
2004
127views more  BMCBI 2004»
15 years 2 months ago
Optimized LOWESS normalization parameter selection for DNA microarray data
Background: Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normaliza...
John A. Berger, Sampsa Hautaniemi, Anna-Kaarina J&...
BMCBI
2008
76views more  BMCBI 2008»
15 years 3 months ago
Empirical Bayes analysis of single nucleotide polymorphisms
Background: An important goal of whole-genome studies concerned with single nucleotide polymorphisms (SNPs) is the identification of SNPs associated with a covariate of interest s...
Holger Schwender, Katja Ickstadt