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» Gene finding in novel genomes
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BMCBI
2007
194views more  BMCBI 2007»
13 years 8 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
BMCBI
2010
155views more  BMCBI 2010»
13 years 8 months ago
FunctSNP: an R package to link SNPs to functional knowledge and dbAutoMaker: a suite of Perl scripts to build SNP databases
Background: Whole genome association studies using highly dense single nucleotide polymorphisms (SNPs) are a set of methods to identify DNA markers associated with variation in a ...
Stephen J. Goodswen, Cedric Gondro, Nathan S. Wats...
CSB
2005
IEEE
165views Bioinformatics» more  CSB 2005»
13 years 10 months ago
Sequential Diagonal Linear Discriminant Analysis (SeqDLDA) for Microarray Classification and Gene Identification
In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA),...
Roger Pique-Regi, Antonio Ortega, Shahab Asgharzad...
TCSB
2008
13 years 8 months ago
Clustering Time-Series Gene Expression Data with Unequal Time Intervals
Clustering gene expression data given in terms of time-series is a challenging problem that imposes its own particular constraints, namely exchanging two or more time points is not...
Luis Rueda, Ataul Bari, Alioune Ngom
CINQ
2004
Springer
138views Database» more  CINQ 2004»
14 years 1 months ago
Relevancy in Constraint-Based Subgroup Discovery
This chapter investigates subgroup discovery as a task of constraint-based mining of local patterns, aimed at describing groups of individuals with unusual distributional character...
Nada Lavrac, Dragan Gamberger