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RECOMB
2002
Springer
14 years 7 months ago
From promoter sequence to expression: a probabilistic framework
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
Eran Segal, Yoseph Barash, Itamar Simon, Nir Fried...
BIBM
2009
IEEE
172views Bioinformatics» more  BIBM 2009»
14 years 20 days ago
Identifying Gene Signatures from Cancer Progression Data Using Ordinal Analysis
—A comprehensive understanding of cancer progression may shed light on genetic and molecular mechanisms of oncogenesis, and it may provide much needed information for effective d...
Yoon Soo Pyon, Jing Li
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
13 years 5 months ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
BMCBI
2010
148views more  BMCBI 2010»
13 years 7 months ago
Applying unmixing to gene expression data for tumor phylogeny inference
Background: While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall int...
Russell Schwartz, Stanley Shackney
BMCBI
2008
158views more  BMCBI 2008»
13 years 7 months ago
Analyzing M-CSF dependent monocyte/macrophage differentiation: Expression modes and meta-modes derived from an independent compo
Background: The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and ...
Dominik Lutter, Peter Ugocsai, Margot Grandl, Evel...