https://bioinfo.cipf.es/WODA.CSIC/ 2026-04-08T06:54:46+0200 https://bioinfo.cipf.es/WODA.CSIC/ https://bioinfo.cipf.es/WODA.CSIC/lib/tpl/prsnl10/images/favicon.ico text/html 2019-06-07T10:50:55+0200 Anonymous (anonymous@undisclosed.example.com) https://bioinfo.cipf.es/WODA.CSIC/doku.php/supervised.class/exercises/ej1?rev=1559897455&do=diff Class prediction in acute leukemia In this example we are going to analyse a dataset from Golub et al. (1999). In that paper they were studying two different types of leukemia (acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) in order to detect differences between them. This dataset have 3051 genes and 38 arrays, 27 of them labeled as ALL and 11 of them as AML. text/html 2019-06-07T10:50:55+0200 Anonymous (anonymous@undisclosed.example.com) https://bioinfo.cipf.es/WODA.CSIC/doku.php/supervised.class/exercises/ej2?rev=1559897455&do=diff Supervised classification for RNA-Seq data of Lung squamous cell carcinoma Data description RNA-Seq data of Lung squamous cell carcinoma (LUSC) samples taken from The Cancer Genome Atlas (TCGA) data portal. Goals * We want to train several classification models in Babelomics.