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BMCBI
2004
128views more  BMCBI 2004»
13 years 7 months ago
Comparing transformation methods for DNA microarray data
Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed ...
Helene H. Thygesen, Aeilko H. Zwinderman
HIPC
2009
Springer
13 years 5 months ago
Comparing the performance of clusters, Hadoop, and Active Disks on microarray correlation computations
Abstract--Microarray-based comparative genomic hybridization (aCGH) offers an increasingly fine-grained method for detecting copy number variations in DNA. These copy number variat...
Jeffrey A. Delmerico, Nathanial A. Byrnes, Andrew ...
BMCBI
2006
122views more  BMCBI 2006»
13 years 7 months ago
A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets
Background: Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifi...
Carmen Lai, Marcel J. T. Reinders, Laura J. van't ...
CEC
2007
IEEE
13 years 11 months ago
Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms
In this work we compare the use of a Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA) (both augmented with Support Vector Machines SVM) for the classification of high...
Enrique Alba, José García-Nieto, Lae...
BMCBI
2007
164views more  BMCBI 2007»
13 years 7 months ago
Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks
Background: The regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a...
Peng Li, Chaoyang Zhang, Edward J. Perkins, Ping G...