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» Gene set analysis for longitudinal gene expression data
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AIIA
2009
Springer
14 years 2 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
2010
151views more  BMCBI 2010»
13 years 7 months ago
TF-finder: A software package for identifying transcription factors involved in biological processes using microarray data and e
Background: Identification of transcription factors (TFs) involved in a biological process is the first step towards a better understanding of the underlying regulatory mechanisms...
Xiaoqi Cui, Tong Wang, Huann-Sheng Chen, Victor Bu...
NAR
2010
123views more  NAR 2010»
13 years 2 months ago
Discovering causal signaling pathways through gene-expression patterns
High-throughput gene-expression studies result in lists of differentially expressed genes. Most current meta-analyses of these gene lists include searching for significant members...
Jignesh R. Parikh, Bertram Klinger, Yu Xia, Jarrod...
KDD
2003
ACM
133views Data Mining» more  KDD 2003»
14 years 8 months ago
Interactive Analysis of Gene Interactions Using Graphical gaussian model
DNA microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that sho...
Xintao Wu, Yong Ye, Kalpathi R. Subramanian