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» Clustering cancer gene expression data: a comparative study
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BMCBI
2005
121views more  BMCBI 2005»
15 years 6 months ago
Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data
Background: A critical step in processing oligonucleotide microarray data is combining the information in multiple probes to produce a single number that best captures the express...
Kerby Shedden, Wei Chen, Rork Kuick, Debashis Ghos...
GECCO
2005
Springer
160views Optimization» more  GECCO 2005»
15 years 11 months ago
Exploring relationships between genotype and oral cancer development through XCS
In medical research, being able to justify decisions is generally as important as taking the right ones. Interpretability is then one of the chief characteristics a learning algor...
Alessandro Passaro, Flavio Baronti, Valentina Magg...
ISMB
2001
15 years 7 months ago
Molecular classification of multiple tumor types
Using gene expression data to classify tumor types is a very promising tool in cancer diagnosis. Previous works show several pairs of tumor types can be successfully distinguished...
Chen-Hsiang Yeang, Sridhar Ramaswamy, Pablo Tamayo...
BIB
2007
59views more  BIB 2007»
15 years 6 months ago
Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity
Gene expression signatures from microarray experiments promise to provide important prognostic tools for predicting disease outcome or response to treatment. A number of microarra...
Jason C. Hsu, Jane Chang, Tao Wang, Eiríkur...
JBI
2006
107views Bioinformatics» more  JBI 2006»
15 years 6 months ago
Knowledge guided analysis of microarray data
To microarray expression data analysis, it is well accepted that biological knowledge-guided clustering techniques show more advantages than pure mathematical techniques. In this ...
Zhuo Fang, Jiong Yang, Yixue Li, Qing-ming Luo, Le...