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» A Parallel Algorithm for Gene Expressing Data Biclustering
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BMCBI
2006
103views more  BMCBI 2006»
15 years 17 days 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
126
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BMCBI
2004
134views more  BMCBI 2004»
15 years 12 days ago
Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)
Background: An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature ...
Ricardo Z. N. Vêncio, Helena Brentani, Diogo...
93
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BMCBI
2006
119views more  BMCBI 2006»
15 years 18 days ago
Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip stu
Background: The choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with know...
Zihua Hu, Gail R. Willsky
111
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BMCBI
2008
114views more  BMCBI 2008»
15 years 19 days ago
Partial mixture model for tight clustering of gene expression time-course
Background: Tight clustering arose recently from a desire to obtain tighter and potentially more informative clusters in gene expression studies. Scattered genes with relatively l...
Yinyin Yuan, Chang-Tsun Li, Roland Wilson
BMCBI
2004
146views more  BMCBI 2004»
15 years 12 days ago
Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data
Background: Functional genomics studies are yielding information about regulatory processes in the cell at an unprecedented scale. In the yeast S. cerevisiae, DNA microarrays have...
Feng Gao, Barrett C. Foat, Harmen J. Bussemaker