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BMCBI
2004
169views more  BMCBI 2004»
13 years 7 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
BIBE
2007
IEEE
127views Bioinformatics» more  BIBE 2007»
13 years 11 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
BMCBI
2007
144views more  BMCBI 2007»
13 years 7 months ago
Spectral estimation in unevenly sampled space of periodically expressed microarray time series data
Background: Periodogram analysis of time-series is widespread in biology. A new challenge for analyzing the microarray time series data is to identify genes that are periodically ...
Alan Wee-Chung Liew, Jun Xian, Shuanhu Wu, David K...
SDM
2009
SIAM
130views Data Mining» more  SDM 2009»
14 years 4 months ago
FuncICA for Time Series Pattern Discovery.
We introduce FuncICA, a new independent component analysis method for pattern discovery in inherently functional data, such as time series data. FuncICA can be considered an analo...
Alexander Gray, Nishant Mehta
BMCBI
2006
216views more  BMCBI 2006»
13 years 7 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...