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» Clustering gene expression patterns of fly embryos
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99
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BMCBI
2006
127views more  BMCBI 2006»
14 years 10 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...
77
Voted
AIIA
2009
Springer
15 years 5 months ago
Ontology-Driven Co-clustering of Gene Expression Data
Abstract. The huge volume of gene expression data produced by microarrays and other high-throughput techniques has encouraged the development of new computational techniques to eva...
Francesca Cordero, Ruggero G. Pensa, Alessia Visco...
BMCBI
2008
126views more  BMCBI 2008»
14 years 10 months ago
Relating gene expression data on two-component systems to functional annotations in Escherichia coli
Background: Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionall...
Anne M. Denton, Jianfei Wu, Megan K. Townsend, Pre...
BMCBI
2007
152views more  BMCBI 2007»
14 years 10 months ago
Difference-based clustering of short time-course microarray data with replicates
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain know...
Jihoon Kim, Ju Han Kim
BMCBI
2011
14 years 5 months ago
RedundancyMiner: De-replication of redundant GO categories in microarray and proteomics analysis
Background: The Gene Ontology (GO) Consortium organizes genes into hierarchical categories based on biological process, molecular function and subcellular localization. Tools such...
Barry Zeeberg, Hongfang Liu, Ari B. Kahn, Martin E...