- Doctoral Scholarship, CONICET
Research Interests
- Machine learning
- Bioinformatics
Advisor
Coadvisor
Latest Publicactions
miRe2e: a full end-to-end deep model based on transformers for prediction of pre-miRNAs
- J. Raad
- L. A. Bugnon
- D. H. Milone
- G. Stegmayer
Bioinformatics - 2021
Deep Learning for the discovery of new pre-miRNAs: helping the fight against COVID-19
- L. A. Bugnon
- J. Raad
- G. Merino
- C. Yones
- F. Ariel
- D. H. Milone
- G. Stegmayer
Machine Learning with Applications - 2021
High precision in microRNA prediction: a novel genome-wide approach with convolutional deep residual networks
- C. Yones
- J. Raad
- L. A. Bugnon
- D. H. Milone
- G. Stegmayer
Computers in Biology and Medicine - 2021
Novel SARS-CoV-2 encoded small RNAs in the passage to humans
- G. Merino
- J. Raad
- L. A. Bugnon
- C. Yones
- L. Kamenetzky
- J. Claus
- F. Ariel
- D. H. Milone
- G. Stegmayer
Bioinformatics - 11 2020
DL4papers: a deep learning approach for the automatic interpretation of scientific articles
- L. A. Bugnon
- C. Yones
- J. Raad
- M. Gerard
- M. Rubiolo
- G. Merino
- M. Pividori
- L. Di Persia
- D. H. Milone
- G. Stegmayer
Oxford Bioinformatics - 2020
Complexity measures of the mature miRNA for improving pre-miRNAs prediction
- J. Raad
- G. Stegmayer
- D. H. Milone
Bioinformatics - 2020
MicroRNA prediction from genome-wide data with deep learning: a novel approach based on convolutional residual networks
- C. Yones
- L. A. Bugnon
- J. Raad
- D. H. Milone
- G. Stegmayer
A2B2C 10th Meeting - 2019
More Publications
Personal Contact
- Phone: +54 (342) 4575233/34, ext. 190
- Office number: 9
- E-mail: jraad@sinc.unl.edu.ar