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» Microarray results: how accurate are they
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BMCBI
2004
111views more  BMCBI 2004»
13 years 9 months ago
Multiclass discovery in array data
Background: A routine goal in the analysis of microarray data is to identify genes with expression levels that correlate with known classes of experiments. In a growing number of ...
Yingchun Liu, Markus Ringnér
BMCBI
2008
169views more  BMCBI 2008»
13 years 10 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
BMCBI
2005
121views more  BMCBI 2005»
13 years 9 months ago
Evaluation of gene importance in microarray data based upon probability of selection
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
Li M. Fu, Casey S. Fu-Liu
BMCBI
2007
107views more  BMCBI 2007»
13 years 9 months ago
Linking microarray reporters with protein functions
Background: The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biologi...
Stan Gaj, Arie van Erk, Rachel I. M. van Haaften, ...
JMLR
2008
209views more  JMLR 2008»
13 years 9 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger