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BMCBI
2007
126views more  BMCBI 2007»
15 years 4 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
BMCBI
2006
216views more  BMCBI 2006»
15 years 4 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...
BMCBI
2006
127views more  BMCBI 2006»
15 years 4 months ago
Using local gene expression similarities to discover regulatory binding site modules
Background: We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to rela...
Bartek Wilczynski, Torgeir R. Hvidsten, Andriy Kry...
IADIS
2008
15 years 5 months ago
Sisa: Seeded Iterative Signature Algorithm for Biclustering Gene Expression Data
One approach to reduce the complexity of the task in the analysis of large scale genome-wide expression is to group the genes showing similar expression patterns into what are cal...
Neelima Gupta, Seema Aggarwal
BMCBI
2002
188views more  BMCBI 2002»
15 years 4 months ago
The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data
Background: The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic an...
David M. Mutch, Alvin Berger, Robert Mansourian, A...