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» Tests for gene clustering
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129
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BMCBI
2006
153views more  BMCBI 2006»
15 years 19 days ago
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
117
Voted
BMCBI
2006
119views more  BMCBI 2006»
15 years 19 days ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
91
Voted
BIBE
2007
IEEE
127views Bioinformatics» more  BIBE 2007»
15 years 4 months ago
Gene Selection via Matrix Factorization
The recent development of microarray gene expression techniques have made it possible to offer phenotype classification of many diseases. However, in gene expression data analysis...
Fei Wang, Tao Li
104
Voted
BMCBI
2010
151views more  BMCBI 2010»
15 years 21 days ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
103
Voted
BMCBI
2010
132views more  BMCBI 2010»
15 years 21 days ago
Error margin analysis for feature gene extraction
Background: Feature gene extraction is a fundamental issue in microarray-based biomarker discovery. It is normally treated as an optimization problem of finding the best predictiv...
Chi Kin Chow, Hai Long Zhu, Jessica Lacy, Winston ...