Exon splicing enhancers or intron splicing silencers

Exon splicing silencers or intron splicing

enhancers

We made software to predict splicing factor binding sites in human genes. It helps to foresee the effect of mutations and polymorphisms. This is the most accurate splicing predictor available on the web.

We made software to predict nuclear export factor binding sites in human genes. It is useful to foresee if a genetic variation lying in a gene affects the RNA nuclear export. This is the only software for RNA export available on the web.

We made database collecting all data about splicing proteins, as expression across tissues, interactors, functional effects, target genes… This resource, that we made freely available to all on the web, is useful to plan experiments.

REFERENCES • Giulietti M, Milantoni SA, Armeni T, Principato G, Piva F. ExportAid: database of RNA elements regulating nuclear RNA export in mammals. Bioinformatics 2015 • Andrikou K, Santoni M, Piva F, Bittoni A, Lanese A, Pellei C, Conti A, Loretelli C, Mandolesi A, Giulietti M, Scarpelli M, Principato G, Falconi M, Cascinu S. Lgr5 expression, cancer stem cells and pancreatic cancer: results from biological and computational analyses. Future Oncology 2015 • Giulietti M, Piva F, D'Antonio M, D'Onorio De Meo P, Paoletti D, Castrignanò T, D'Erchia AM, Picardi E, Zambelli F, Principato G, Pavesi G, Pesole G. SpliceAid-F: a database of human splicing factors and their RNA-binding sites. Nucleic Acids Research 2013 • Piva F, Giulietti M, Burini AB, Principato G. SpliceAid 2: A database of human splicing factors expression data and RNA target motifs. Human Mutation 2011 • Piva F, Giulietti M, Nocchi L, Principato G. SpliceAid: a database of experimental RNA target motifs bound by splicing proteins in humans. Bioinformatics 2009

We analyze RNA sequencing data to detect gene differential expression between cancer and normal tissues

Normal

Cancer We extract and quantify exosomes from plasma of ductal pancreatic cancer patients in order to find biomarkers of drug efficacy, metastasis and survival.

WET BIOLOGY

Francesco Piva, Matteo Giulietti, Giulia Occhipinti, Klaudia Stermasi, Alessandra Righetti, Giovanni Principato

COMPUTATIONAL BIOLOGY

Pathway reconstruction

We analyze literature and database data in order to reconstruct pathways important in pancreatic cancer.

AIRC financed.