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» Analysis of variance components in gene expression data
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SDM
2009
SIAM
161views Data Mining» more  SDM 2009»
15 years 6 months ago
Feature Weighted SVMs Using Receiver Operating Characteristics.
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...
BMCBI
2006
150views more  BMCBI 2006»
14 years 9 months ago
Instance-based concept learning from multiclass DNA microarray data
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
Daniel P. Berrar, Ian Bradbury, Werner Dubitzky
BMCBI
2010
105views more  BMCBI 2010»
14 years 9 months ago
Effects of scanning sensitivity and multiple scan algorithms on microarray data quality
Background: Maximizing the utility of DNA microarray data requires optimization of data acquisition through selection of an appropriate scanner setting. To increase the amount of ...
Andrew Williams, Errol M. Thomson
BMCBI
2010
144views more  BMCBI 2010»
14 years 9 months ago
Finding sRNA generative locales from high-throughput sequencing data with NiBLS
Background: Next-generation sequencing technologies allow researchers to obtain millions of sequence reads in a single experiment. One important use of the technology is the seque...
Daniel MacLean, Vincent Moulton, David J. Studholm...
TNN
2008
128views more  TNN 2008»
14 years 9 months ago
Nonnegative Matrix Factorization in Polynomial Feature Space
Abstract--Plenty of methods have been proposed in order to discover latent variables (features) in data sets. Such approaches include the principal component analysis (PCA), indepe...
Ioan Buciu, Nikos Nikolaidis, Ioannis Pitas