Sciweavers

1162 search results - page 60 / 233
» Unfolding of Microarray Data
Sort
View
DMKD
2003
ACM
96views Data Mining» more  DMKD 2003»
14 years 1 months ago
Using transposition for pattern discovery from microarray data
We analyze expression matrices to identify a priori interesting sets of genes, e.g., genes that are frequently co-regulated. Such matrices provide expression values for given biol...
François Rioult, Jean-François Bouli...
HIS
2004
13 years 9 months ago
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
CSDA
2008
128views more  CSDA 2008»
13 years 8 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
BMCBI
2006
88views more  BMCBI 2006»
13 years 8 months ago
A two-sample Bayesian t-test for microarray data
Background: Determining whether a gene is differentially expressed in two different samples remains an important statistical problem. Prior work in this area has featured the use ...
Richard J. Fox, Matthew W. Dimmic
BMCBI
2004
132views more  BMCBI 2004»
13 years 8 months ago
Two-stage normalization using background intensities in cDNA microarray data
Background: In the microarray experiment, many undesirable systematic variations are commonly observed. Normalization is the process of removing such variation that affects the me...
Dankyu Yoon, Sung-Gon Yi, Ju-Han Kim, Taesung Park