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. Availability and implementation: Both DEEPrior and the protein fusions dataset are freely available from GitHub at (https://github.com/bioinformatics-polito/DEEPrior). The tool was designed to operate in Python 3.7, with minimal additional libraries. Supplementary information: Supplementary data are available at Bioinformatics online.

DEEPrior: a deep learning tool for the prioritization of gene fusions / Lovino, Marta; Ciaburri, Maria Serena; Urgese, Gianvito; Di Cataldo, Santa; Ficarra, Elisa. - In: BIOINFORMATICS. - ISSN 1367-4803. - 36:10(2020), pp. 3248-3250. [10.1093/bioinformatics/btaa069]

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

Lovino, Marta;Ficarra, Elisa
2020

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. Availability and implementation: Both DEEPrior and the protein fusions dataset are freely available from GitHub at (https://github.com/bioinformatics-polito/DEEPrior). The tool was designed to operate in Python 3.7, with minimal additional libraries. Supplementary information: Supplementary data are available at Bioinformatics online.
2020
36
10
3248
3250
DEEPrior: a deep learning tool for the prioritization of gene fusions / Lovino, Marta; Ciaburri, Maria Serena; Urgese, Gianvito; Di Cataldo, Santa; Ficarra, Elisa. - In: BIOINFORMATICS. - ISSN 1367-4803. - 36:10(2020), pp. 3248-3250. [10.1093/bioinformatics/btaa069]
Lovino, Marta; Ciaburri, Maria Serena; Urgese, Gianvito; Di Cataldo, Santa; Ficarra, Elisa
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1240365
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