RENATO (REgulatory Network Analysis TOol) is a network-based analysis web tool for the interpretation and visualization of transcriptional and post-transcriptional regulatory information, designed to identify common regulatory elements in a list of genes. RENATO maps these genes to the regulatory network, extracts the corresponding regulatory connections and evaluate each regulator for significant over-representation in the list.
Here you can find detailed information describing the implemented methods, a tutorial, worked examples and news related with RENATO.
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But… why RENATO?
The final aim of a typical genomic experiment is to find a molecular explanation for a given macroscopic observation. The common scenario is based on the comparison of expression patterns between different groups (i.e. control and disease, time series experiments, etc.) which results in a group genes of interest either because they co-express in a cluster or because they are significantly over- or under-expressed when two classes of experiments are compared. The deregulated list of genes can easily grow up to one hundred. Logically, one could conclude that there are not hundreds of errors (mutations, deregulation, etc.) but one common cause leading to the abnormal expression of these genes. Regulatory elements, which generally interact and regulate several genes, are features of interest because of its potential to cause this deregulated profile.
To date, transcription factors (TFs) and microRNAs (miRNAs) are the best-studied and the most important dynamic regulators in the control of gene expression. Alterations in these elements have been extensively related with human malignancies including cancer. The increasing interest in identifying putative alterations in regulatory elements has lead to the development of RENATO.