AIMC Topic: Gene Expression Regulation, Leukemic

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A novel random forests-based feature selection method for microarray expression data analysis.

International journal of data mining and bioinformatics
High-dimensional data and a large number of redundancy features in bioinformatics research have created an urgent need for feature selection. In this paper, a novel random forests-based feature selection method is proposed that adopts the idea of str...

A genetic filter for cancer classification on gene expression data.

Bio-medical materials and engineering
We present a new genetic filter to identify a predictive gene subset for cancer-type classification on gene expression profiles. This approach pursues to not only maximize correlation between selected genes and cancer types but also minimize inter-co...