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» A stable gene selection in microarray data analysis
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BMCBI
2010
125views more  BMCBI 2010»
13 years 7 months ago
Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types
Background: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in stand...
Noor B. Dawany, Aydin Tozeren
BMCBI
2011
13 years 2 months ago
Multiclass classification of microarray data samples with a reduced number of genes
Background: Multiclass classification of microarray data samples with a reduced number of genes is a rich and challenging problem in Bioinformatics research. The problem gets hard...
Elizabeth Tapia, Leonardo Ornella, Pilar Bulacio, ...
ISNN
2007
Springer
14 years 1 months 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
2006
147views more  BMCBI 2006»
13 years 7 months ago
Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data
Background: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find...
Alex Lewin, Ian C. Grieve
BMCBI
2004
165views more  BMCBI 2004»
13 years 7 months ago
Analysis of oligonucleotide array experiments with repeated measures using mixed models
Background: Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients...
Hao Li, Constance L. Wood, Thomas V. Getchell, Mar...