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» Combining microarrays and genetic analysis
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IDA
2005
Springer
14 years 3 months ago
Bayesian Networks Learning for Gene Expression Datasets
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi...
BMCBI
2007
130views more  BMCBI 2007»
13 years 10 months ago
A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression da
Background: Proteins are the primary regulatory agents of transcription even though mRNA expression data alone, from systems like DNA microarrays, are widely used. In addition, th...
Reuben Thomas, Carlos J. Paredes, Sanjay Mehrotra,...
BIBE
2004
IEEE
14 years 1 months ago
Identifying the Combination of Genetic Factors that Determine Susceptibility to Cervical Cancer
Cervical cancer is common among women all over the world. Although infection with high-risk types of human papillomavirus (HPV) has been identified as the primary cause of cervical...
Jorng-Tzong Horng, Kai-Chih Hu, Li-Cheng Wu, Hsien...
BMCBI
2006
154views more  BMCBI 2006»
13 years 10 months ago
Analysis with respect to instrumental variables for the exploration of microarray data structures
Background: Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various fa...
Florent Baty, Michaël Facompré, Jan Wi...
BMCBI
2004
106views more  BMCBI 2004»
13 years 9 months ago
Spotting effect in microarray experiments
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Tristan Mary-Huard, Jean-Jacques Daudin, Sté...