DEEPrior: a deep learning tool for the prioritization of gene fusions.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

SUMMARY: In the last decade, increasing attention has been paid to the study of gene fusions. However, the problem of determining whether a gene fusion is a cancer driver or just a passenger mutation is still an open issue. Here we present DEEPrior, an inherently flexible deep learning tool with two modes (Inference and Retraining). Inference mode predicts the probability of a gene fusion being involved in an oncogenic process, by directly exploiting the amino acid sequence of the fused protein. Retraining mode allows to obtain a custom prediction model including new data provided by the user.

Authors

  • Marta Lovino
    Politecnico di Torino, Department of Control and Computer Engineering, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy. marta.lovino@polito.it.
  • Maria Serena Ciaburri
    Department of Control and Computer Engineering.
  • Gianvito Urgese
    Politecnico di Torino, Department of Control and Computer Engineering, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy. gianvito.urgese@polito.it.
  • Santa Di Cataldo
    Politecnico di Torino, Department of Control and Computer Engineering, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy. santa.dicataldo@polito.it.
  • Elisa Ficarra
    Politecnico di Torino, Department of Control and Computer Engineering, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy. elisa.ficarra@polito.it.