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» Smoothing Gene Expression Using Biological Networks
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RECOMB
2004
Springer
14 years 9 months ago
Modeling and Analysis of Heterogeneous Regulation in Biological Networks
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Irit Gat-Viks, Amos Tanay, Ron Shamir
BMCBI
2004
181views more  BMCBI 2004»
13 years 8 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
BMCBI
2004
154views more  BMCBI 2004»
13 years 8 months ago
Accuracy of cDNA microarray methods to detect small gene expression changes induced by neuregulin on breast epithelial cells
Background: cDNA microarrays are a powerful means to screen for biologically relevant gene expression changes, but are often limited by their ability to detect small changes accur...
Bin Yao, Sanjay N. Rakhade, Qunfang Li, Sharlin Ah...
BMCBI
2007
126views more  BMCBI 2007»
13 years 9 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
167views more  BMCBI 2006»
13 years 8 months ago
GOurmet: A tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributi
Background: The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental conditions is an important but difficu...
Jason M. Doherty, Lynn K. Carmichael, Jason C. Mil...