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BMCBI
2005
112views more  BMCBI 2005»
13 years 4 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
BMCBI
2005
148views more  BMCBI 2005»
13 years 4 months ago
Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments
Background: Numerous nonparametric approaches have been proposed in literature to detect differential gene expression in the setting of two user-defined groups. However, there is ...
Xin Gao, Peter X. K. Song
BMCBI
2005
80views more  BMCBI 2005»
13 years 4 months ago
Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
Background: Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently ...
Kevin Dawson, Raymond L. Rodriguez, Wasyl Malyj
BMCBI
2005
153views more  BMCBI 2005»
13 years 4 months ago
A comparative review of estimates of the proportion unchanged genes and the false discovery rate
Background: In the analysis of microarray data one generally produces a vector of p-values that for each gene give the likelihood of obtaining equally strong evidence of change by...
Per Broberg
BMCBI
2005
121views more  BMCBI 2005»
13 years 4 months ago
Evaluation of gene importance in microarray data based upon probability of selection
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
Li M. Fu, Casey S. Fu-Liu
BIOINFORMATICS
2005
151views more  BIOINFORMATICS 2005»
13 years 4 months ago
Differential and trajectory methods for time course gene expression data
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Yulan Liang, Bamidele Tayo, Xueya Cai, Arpad Kelem...
BIOINFORMATICS
2005
105views more  BIOINFORMATICS 2005»
13 years 4 months ago
MADE4: an R package for multivariate analysis of gene expression data
Summary: MADE4, microarray ade4, is a software package that facilitates multivariate analysis of microarray gene expression data. MADE4 accepts a wide variety of gene expression d...
Aedín C. Culhane, Jean Thioulouse, Guy Perr...
KES
2006
Springer
13 years 4 months ago
Combined Gene Selection Methods for Microarray Data Analysis
In recent years, the rapid development of DNA Microarray technology has made it possible for scientists to monitor the expression level of thousands of genes in a single experiment...
Hong Hu, Jiuyong Li, Hua Wang, Grant Daggard
JBI
2008
159views Bioinformatics» more  JBI 2008»
13 years 4 months ago
SEGS: Search for enriched gene sets in microarray data
Gene Ontology (GO) terms are often used to interpret the results of microarray experiments. The most common approach is to perform Fisher's exact tests to find gene sets anno...
Igor Trajkovski, Nada Lavrac, Jakub Tolar
IJON
2006
99views more  IJON 2006»
13 years 4 months ago
Feature selection in independent component subspace for microarray data classification
A novel method for microarray data classification is proposed in this letter. In this scheme, the sequential floating forward selection (SFFS) technique is used to select the inde...
Chun-Hou Zheng, De-Shuang Huang, Li Shang