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BMCBI
2010
154views more  BMCBI 2010»
13 years 6 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
13 years 4 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
2006
151views more  BMCBI 2006»
13 years 6 months ago
Modeling Sage data with a truncated gamma-Poisson model
Background: Serial Analysis of Gene Expressions (SAGE) produces gene expression measurements on a discrete scale, due to the finite number of molecules in the sample. This means t...
Helene H. Thygesen, Aeilko H. Zwinderman
BIOINFORMATICS
2005
151views more  BIOINFORMATICS 2005»
13 years 6 months ago
Differential and trajectory methods for time course gene expression data
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Yulan Liang, Bamidele Tayo, Xueya Cai, Arpad Kelem...
BMCBI
2005
153views more  BMCBI 2005»
13 years 6 months ago
Mining published lists of cancer related microarray experiments: Identification of a gene expression signature having a critical
Background: Routine application of gene expression microarray technology is rapidly producing large amounts of data that necessitate new approaches of analysis. The analysis of a ...
Giacomo Finocchiaro, Francesco Mancuso, Heiko M&uu...