COLONOMICS - integrative omics data of one hundred paired normal-tumoral samples from colon cancer patients

Colonomics is a multi-omics dataset that includes 250 samples: 50 samples from healthy colon mucosa donors and 100 paired samples from colon cancer patients (tumor/adjacent). From these samples, Colonomics project includes data from genotyping, DNA methylation, gene expression, whole exome sequencing and micro-RNAs (miRNAs) expression. It also includes data from copy number variation (CNV) from tumoral samples. In addition, clinical data from all these samples is available. The aims of the project were to explore and integrate these datasets to describe colon cancer at molecular level and to compare normal and tumoral tissues. Also, to improve screening by finding biomarkers for the diagnosis and prognosis of colon cancer. This project has its own website including four browsers allowing users to explore Colonomics datasets. Since generated data could be reuse for the scientific community for exploratory or validation purposes, here we describe omics datasets included in the Colonomics project as well as results from multi-omics layers integration

Logo: orientacions metodològiques

El Sistema Logo, concebut per Seymour Papert (matemàtic de l'Institut de Tecnologia de Massachussetts) a final dels anys setanta i concretat en el seu llibre "Mindstorms: Children, Computers and Powerful Ideas" (1980), podríem dir que té com a característica principal la potenciació de l'aprenentatge heurístic, o el que és el mateix, de l'aprenentatge per descobriment, on el nen reconstruint les coses de nou arriba a assimilar-ne el significat..