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» Smoothing Gene Expression Using Biological Networks
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BMCBI
2004
134views more  BMCBI 2004»
13 years 7 months 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...
BIBM
2008
IEEE
212views Bioinformatics» more  BIBM 2008»
14 years 2 months ago
Analysis of Multiplex Gene Expression Maps Obtained by Voxelation
Background: Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelatio...
Li An, Hongbo Xie, Mark H. Chin, Zoran Obradovic, ...
BMCBI
2006
137views more  BMCBI 2006»
13 years 7 months ago
Biologically relevant effects of mRNA amplification on gene expression profiles
Background: Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies an...
Rachel I. M. van Haaften, Blanche Schroen, Ben J. ...
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identifica
Background: Comparative analysis of gene expression profiling of multiple biological categories, such as different species of organisms or different kinds of tissue, promises to e...
Wensheng Zhang, Andrea Edwards, Wei Fan, Dongxiao ...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali