Jonathan Raad

  • Doctoral Scholarship, CONICET

Research Interests

  • Machine learning
  • Bioinformatics

Advisor

Coadvisor

Latest Publicactions

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

Deep learning for reading and interpreting biomedical papers
  • L. A. Bugnon
  • C. Yones
  • J. Raad
  • M. Gerard
  • M. Rubiolo
  • G. Merino
  • M. Pividori
  • L. Di Persia
  • D. H. Milone
  • G. Stegmayer

A2B2C 10th Meeting - 2019

Improving pre-miRNA prediction with complexity measures of the mature and deep learning
  • J. Raad
  • D. H. Milone
  • G. Stegmayer

A2B2C 10th Meeting - 2019

Genome-wide hairpins datasets of animals and plants for novel miRNA prediction
  • L. A. Bugnon
  • C. Yones
  • J. Raad
  • D. H. Milone
  • G. Stegmayer

Data in Brief (in press) - 2019

More Publications

Personal Contact

  • Phone: +54 (342) 4575233/34, ext. 190
  • Office number: 9
  • E-mail: jraad@sinc.unl.edu.ar