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CIBCB
2005
IEEE
14 years 2 months ago
Two-Phase EA/k-NN for Feature Selection and Classification in Cancer Microarray Datasets
Efficient and reliable methods that can find a small sample of informative genes amongst thousands are of great importance. In this area, much research is investigating the combina...
Thorhildur Juliusdottir, David Corne, Ed Keedwell,...
APBC
2003
128views Bioinformatics» more  APBC 2003»
13 years 10 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
ISMIS
2003
Springer
14 years 1 months ago
Evolutionary Computation for Optimal Ensemble Classifier in Lymphoma Cancer Classification
Owing to the development of DNA microarray technologies, it is possible to get thousands of expression levels of genes at once. If we make the effective classification system with ...
Chanho Park, Sung-Bae Cho
ACSC
2005
IEEE
14 years 2 months ago
Integer Programming Models and Algorithms for Molecular Classification of Cancer from Microarray Data
Novel, high-throughput technologies are challenging the core of algorithmic methods available in Computer Science. Microarray technologies give Life Sciences researchers the oppor...
Regina Berretta, Alexandre Mendes, Pablo Moscato
BMCBI
2004
205views more  BMCBI 2004»
13 years 8 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma