A hybrid feature selection method for DNA microarray data
LY Chuang, CH Yang, KC Wu, CH Yang - Computers in biology and …, 2011 - Elsevier
Gene expression profiles, which represent the state of a cell at a molecular level, have great
potential as a medical diagnosis tool. In cancer classification, available training data sets are …
potential as a medical diagnosis tool. In cancer classification, available training data sets are …
Comparative study of classification algorithms for various DNA microarray data
Microarrays are applications of electrical engineering and technology in biology that allow
simultaneous measurement of expression of numerous genes, and they can be used to …
simultaneous measurement of expression of numerous genes, and they can be used to …
[PDF][PDF] Feature selection for cancer classification using microarray gene expression data
W Zhong - 2014 - prism.ucalgary.ca
The rapid development of DNA microarray technology enables researchers to measure the
expression levels of thousands of genes simultaneously and allows biologists easily gain …
expression levels of thousands of genes simultaneously and allows biologists easily gain …
A novel feature extraction approach based on ensemble feature selection and modified discriminant independent component analysis for microarray data …
M Mollaee, MH Moattar - Biocybernetics and Biomedical Engineering, 2016 - Elsevier
Microarray data play critical role in cancer classification. However, with respect to the
samples scarcity compared to intrinsic high dimensionality, most approaches fail to classify …
samples scarcity compared to intrinsic high dimensionality, most approaches fail to classify …
A hybrid gene selection method for microarray recognition
DNA microarray data is expected to be a great help in the development of efficient diagnosis
and tumor classification. However, due to the small number of instances compared to a large …
and tumor classification. However, due to the small number of instances compared to a large …
[PDF][PDF] Gene Microarray Cancer Classification using Correlation Based Feature Selection Algorithm and Rules Classifiers.
Gene microarray classification problems are considered a challenge task since the datasets
contain few number of samples with high number of genes (features). The genes subset …
contain few number of samples with high number of genes (features). The genes subset …
An expert system to classify microarray gene expression data using gene selection by decision tree
JT Horng, LC Wu, BJ Liu, JL Kuo, WH Kuo… - Expert Systems with …, 2009 - Elsevier
Gene selection can help the analysis of microarray gene expression data. However, it is very
difficult to obtain a satisfactory classification result by machine learning techniques because …
difficult to obtain a satisfactory classification result by machine learning techniques because …
A two-stage feature selection method for gene expression data
Microarray data referencing gene expression profiles provide valuable answers to a variety
of problems, and contributes to advances in clinical medicine. Gene expression data …
of problems, and contributes to advances in clinical medicine. Gene expression data …
An integrated feature selection algorithm for cancer classification using gene expression data
Aim and Objective: Cancer is a dangerous disease worldwide, caused by somatic mutations
in the genome. Diagnosis of this deadly disease at an early stage is exceptionally new …
in the genome. Diagnosis of this deadly disease at an early stage is exceptionally new …
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 a …
they have the potential to discover gene expression patterns that are characteristic for a …