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» Combined Gene Selection Methods for Microarray Data Analysis
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BICOB
2009
Springer
15 years 25 days ago
A Biclustering Method to Discover Co-regulated Genes Using Diverse Gene Expression Datasets
We propose a two-step biclustering approach to mine co-regulation patterns of a given reference gene to discover other genes that function in a common biological process. Currently...
Doruk Bozdag, Jeffrey D. Parvin, Ümit V. &Cce...
JCB
2002
160views more  JCB 2002»
15 years 2 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
IMSCCS
2006
IEEE
15 years 9 months ago
Combining Comparative Genomics with de novo Motif Discovery to Identify Human Transcription Factor DNA-Binding Motifs
Background: As more and more genomes are sequenced, comparative genomics approaches provide a methodology for identifying conserved regulatory elements that may be involved in gen...
Linyong Mao, W. Jim Zheng
BMCBI
2007
173views more  BMCBI 2007»
15 years 3 months ago
Ringo - an R/Bioconductor package for analyzing ChIP-chip readouts
Background: Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is a high-throughput assay for DNA-protein-binding or post-translational chromatin/histone modi...
Joern Toedling, Oleg Sklyar, Tammo Krueger, Jenny ...
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
15 years 8 months ago
Latent Structure Models for the Analysis of Gene Expression Data
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Dong Hua, Dechang Chen, Xiuzhen Cheng, Abdou Youss...