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BMCBI
2011
13 years 1 months ago
Multivariate analysis of microarray data: differential expression and differential connection
Background: Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically all...
Harri T. Kiiveri
BMCBI
2010
116views more  BMCBI 2010»
13 years 6 months ago
FiGS: a filter-based gene selection workbench for microarray data
Background: The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene sel...
Taeho Hwang, Choong-Hyun Sun, Taegyun Yun, Gwan-Su...
BMCBI
2008
121views more  BMCBI 2008»
13 years 6 months ago
Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...
ISNN
2007
Springer
14 years 13 days ago
Memetic Algorithms for Feature Selection on Microarray Data
In this paper, we present two novel memetic algorithms (MAs) for gene selection. Both are synergies of Genetic Algorithm (wrapper methods) and local search methods (filter methods...
Zexuan Zhu, Yew-Soon Ong
BMCBI
2004
169views more  BMCBI 2004»
13 years 6 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...