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» Microarray Gene Expression Data Analysis
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BMCBI
2006
119views more  BMCBI 2006»
14 years 9 months 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
BMCBI
2008
132views more  BMCBI 2008»
14 years 9 months ago
Very Important Pool (VIP) genes - an application for microarray-based molecular signatures
Background: Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicin...
Zhenqiang Su, Huixiao Hong, Hong Fang, Leming M. S...
BMCBI
2008
178views more  BMCBI 2008»
14 years 9 months ago
Identification of coherent patterns in gene expression data using an efficient biclustering algorithm and parallel coordinate vi
Background: The DNA microarray technology allows the measurement of expression levels of thousands of genes under tens/hundreds of different conditions. In microarray data, genes ...
Kin-On Cheng, Ngai-Fong Law, Wan-Chi Siu, Alan Wee...
CSB
2003
IEEE
153views Bioinformatics» more  CSB 2003»
15 years 3 months ago
Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks
We propose a statistical method for estimating a gene network based on Bayesian networks from microarray gene expression data together with biological knowledge including protein-...
Seiya Imoto, Tomoyuki Higuchi, Takao Goto, Kousuke...
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BIOINFORMATICS
2004
119views more  BIOINFORMATICS 2004»
14 years 9 months ago
Analysis of variance components in gene expression data
Motivation: A microarray experiment is a multi-step process, and each step is a potential source of variation. There are two major sources of variation: biological variation and t...
James J. Chen, Robert R. Delongchamp, Chen-An Tsai...