2 citations · 2 across the 3 of their papers we have counts for
3 papers
Unsupervised Feature Selection for Tumor Profiles using Autoencoders and Kernel Methods
Martin Palazzo, Pierre Beauseroy, Patricio Yankilevich
Molecular data from tumor profiles is high dimensional. Tumor profiles can be characterized by tens of thousands of gene expression features. Due to the size of the gene expression…
Latent regularization for feature selection using kernel methods in tumor classification
Martin Palazzo, Patricio Yankilevich, Pierre Beauseroy
The transcriptomics of cancer tumors are characterized with tens of thousands of gene expression features. Patient prognosis or tumor stage can be assessed by machine learning tech…
Asterias: a parallelized web-based suite for the analysis of expression and aCGH data
Andreu Alibes, Edward R. Morrissey, Andres Canada +4
Asterias (\url{http://www.asterias.info}) is an integrated collection of freely-accessible web tools for the analysis of gene expression and aCGH data. Most of the tools use parall…