Splicing Modulation by Advanced RNA Technologies


Claudia Coronnello




Fondazione Ri.MED



Our group focuses on the development of bioinformatic tools useful to understand post-transcriptional regulatory mechanisms, like microRNA or long non-coding RNA activity. In this project, we will use the experimental results obtained with the ASO targeting AS to enrich a database useful to train machine learning based algorithms. Specifically, we will collect information about the efficiency of ASO designed for different targets and develop a prediction algorithm useful to optimize the design of ASO’s sequences. Progerin production will be used as test-bed model. Progerin is a pathological AS form of Lamin A produced by the LMNA gene.

Collectively, this project will provide pre-clinical proof of concept for the use of innovative RNA-based technologies for the precision medicine treatment of cancer and other aging-related diseases.

Relevant publications

  1. Arancio W, Sciaraffa N and Coronnello C. MBS: a genome browser annotation track for high-confident microRNA binding sites in whole human transcriptome. Database. 2023, 2023:baad015
  2. Bertolazzi G, Benos PV, Tumminello M and Coronnello C. An improvement of ComiR algorithm for microRNA target prediction by exploiting coding region sequences of mRNAs. BMC Bioinformatics. 2020, 21(8):1-10

Related Projects

PI: Laura Poliseno