Sciweavers

7 search results - page 1 / 2
» Probe-level linear model fitting and mixture modeling result...
Sort
View
BMCBI
2006
103views more  BMCBI 2006»
13 years 3 months ago
Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression
Background: The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level ...
Sébastien Lemieux
BMCBI
2005
113views more  BMCBI 2005»
13 years 3 months ago
Normal uniform mixture differential gene expression detection for cDNA microarrays
Background: One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the ...
Nema Dean, Adrian E. Raftery
BMCBI
2010
176views more  BMCBI 2010»
13 years 3 months ago
Reverse engineering gene regulatory network from microarray data using linear time-variant model
nd: Gene regulatory network is an abstract mapping of gene regulations in living cells that can help to predict the system behavior of living organisms. Such prediction capability...
Mitra Kabir, Nasimul Noman, Hitoshi Iba
BMCBI
2007
197views more  BMCBI 2007»
13 years 3 months ago
Boolean networks using the chi-square test for inferring large-scale gene regulatory networks
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Haseong Kim, Jae K. Lee, Taesung Park
BMCBI
2006
165views more  BMCBI 2006»
13 years 3 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin