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» Smoothing Gene Expression Using Biological Networks
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BMCBI
2007
182views more  BMCBI 2007»
13 years 9 months ago
Additive risk survival model with microarray data
Background: Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with ...
Shuangge Ma, Jian Huang
EVOW
2005
Springer
14 years 2 months ago
Order Preserving Clustering over Multiple Time Course Experiments
Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
Stefan Bleuler, Eckart Zitzler
BMCBI
2010
147views more  BMCBI 2010»
13 years 9 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
ENTCS
2007
96views more  ENTCS 2007»
13 years 8 months ago
Semantics of Biological Regulatory Networks
The aim of the paper is to revisit the model of Biological Regulatory Networks (BRN) which was proposed by René Thomas to model the interactions between a set of genes. We give a...
Gilles Bernot, Franck Cassez, Jean-Paul Comet, Fra...
IJKDB
2010
170views more  IJKDB 2010»
13 years 6 months ago
Clustering Genes Using Heterogeneous Data Sources
Clustering of gene expression data is a standard exploratory technique used to identify closely related genes. Many other sources of data are also likely to be of great assistance...
Erliang Zeng, Chengyong Yang, Tao Li, Giri Narasim...