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BMCBI
2008
186views more  BMCBI 2008»
13 years 5 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
BMCBI
2006
118views more  BMCBI 2006»
13 years 5 months ago
Predicting the effect of missense mutations on protein function: analysis with Bayesian networks
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...
Chris J. Needham, James R. Bradford, Andrew J. Bul...
SUM
2009
Springer
13 years 11 months ago
Modeling Unreliable Observations in Bayesian Networks by Credal Networks
Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
Alessandro Antonucci, Alberto Piatti
BIOINFORMATICS
2007
190views more  BIOINFORMATICS 2007»
13 years 4 months ago
Towards clustering of incomplete microarray data without the use of imputation
Motivation: Clustering technique is used to find groups of genes that show similar expression patterns under multiple experimental conditions. Nonetheless, the results obtained by...
Dae-Won Kim, Ki Young Lee, Kwang H. Lee, Doheon Le...
BMCBI
2010
108views more  BMCBI 2010»
13 years 4 months ago
iGTP: A software package for large-scale gene tree parsimony analysis
Background: The ever-increasing wealth of genomic sequence information provides an unprecedented opportunity for large-scale phylogenetic analysis. However, species phylogeny infe...
Ruchi Chaudhary, Mukul S. Bansal, André Weh...