The comprehension of the molecular mechanisms involved in the physiology of human cells and in the pathogenesis of complex disorders, requires the development of new bioinformatic and biostatistic approaches able to integrate and interpret the huge amount of data derived from different kind of "omics" technologies. Nowadays, the interpretation of the transcriptional state of the cell and its alterations in particular experimental or pathological conditions is of particular interest. To this aim several technologies have been developed to identify and quantify the entire set of cellular transcripts, thus resulting in the availability of expression profiles of many different cell types in many different conditions. With the aim of contributing to the elucidation of transcriptional dynamics in the cell, we developed CorrelaGenes, a new bioinformatic tool that exploits the expression data available in the Gene Expression Omnibus (GEO) database: http://www.ncbi.nlm.nih.gov/geo/ (Last accessed on Sep 26, 2012). The main goal of this tool is to help identifying sets of genes whose expression appeared simultaneously altered in different experiments, thus suggesting co-regulation or coordinated action in the same biological process.
CorrelaGenes: a new tool for the interpretation of the human trascriptome.
Cremaschi P;Rovida S;Lisa A;Montecucco A;Biamonti G;Bione S;Sacchi G
2012
Abstract
The comprehension of the molecular mechanisms involved in the physiology of human cells and in the pathogenesis of complex disorders, requires the development of new bioinformatic and biostatistic approaches able to integrate and interpret the huge amount of data derived from different kind of "omics" technologies. Nowadays, the interpretation of the transcriptional state of the cell and its alterations in particular experimental or pathological conditions is of particular interest. To this aim several technologies have been developed to identify and quantify the entire set of cellular transcripts, thus resulting in the availability of expression profiles of many different cell types in many different conditions. With the aim of contributing to the elucidation of transcriptional dynamics in the cell, we developed CorrelaGenes, a new bioinformatic tool that exploits the expression data available in the Gene Expression Omnibus (GEO) database: http://www.ncbi.nlm.nih.gov/geo/ (Last accessed on Sep 26, 2012). The main goal of this tool is to help identifying sets of genes whose expression appeared simultaneously altered in different experiments, thus suggesting co-regulation or coordinated action in the same biological process.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
