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BMCBI
2011
12 years 11 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto
CSB
2004
IEEE
173views Bioinformatics» more  CSB 2004»
13 years 11 months ago
Gene Ontology Friendly Biclustering of Expression Profiles
The soundness of clustering in the analysis of gene expression profiles and gene function prediction is based on the hypothesis that genes with similar expression profiles may imp...
Jinze Liu, Wei Wang 0010, Jiong Yang
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
BMCBI
2007
138views more  BMCBI 2007»
13 years 7 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...