This thesis aims to improve the current state of the art in microarray classification and to contribute to understand how signal processing techniques can be ...

This thesis aims to improve the current state of the art in microarray classification and to contribute to understand how signal processing techniques can be ...

Hierarchical information representation and e cient classification of gene expression microarray data. PhD Thesis. Student: Mattia Bosio. Thesis advisors ...

This thesis aims to improve the current state of the art in microarray classification and to contribute to understand how signal processing techniques can be ...

Multi-parameter modeling of channel-level data (e.g.. Gaussian mixed models), hierarchical Bayesian models, etc. May borrow information across genes and use.

Jun 8, 2015 · PDF | A general framework for microarray data classification is proposed in this paper. It produces precise and reliable classifiers through ...

Jul 18, 2020 · Gene expression data classification combining hierarchical representation and efficient feature selection. J. Biol. Syst. 2012;20:349–375 ...

The hierarchical clustering algorithm has been widely in use for the gene expression data analysis, especially because of its simple visualization tool (Johnson ...

A general framework for microarray data classification is proposed in this paper. It produces precise and reliable classifiers through a two-step approach.

The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types ...