Jonathan Raad

According to our database, Jonathan Raad authored at least 9 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure.

Leandro A Bugnon, Leandro E. Di Persia, Matias Gerard, Jonathan Raad, Santiago Prochetto, Emilio Fenoy, Uciel Chorostecki, Federico Ariel, Georgina Stegmayer, Diego H. Milone

Briefings Bioinform., 2024

2023

Transfer learning: The key to functionally annotate the protein universe.

Leandro A Bugnon, Emilio Fenoy, Alejandro A. Edera, Jonathan Raad, Georgina Stegmayer, Diego H. Milone

Patterns, February, 2023

2022

miRe2e: a full end-to-end deep model based on transformers for prediction of pre-miRNAs.

Jonathan Raad, Leandro A Bugnon, Diego H. Milone, Georgina Stegmayer

Bioinform., 2022

Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches.

Leandro A Bugnon, Alejandro A. Edera, Santiago Prochetto, Matias Gerard, Jonathan Raad, Emilio Fenoy, Mariano Rubiolo, Uciel Chorostecki, Toni Gabaldón, Federico Ariel, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer

Briefings Bioinform., 2022

2021

High precision in microRNA prediction: A novel genome-wide approach with convolutional deep residual networks.

Cristian A. Yones, Jonathan Raad, Leandro A Bugnon, Diego H. Milone, Georgina Stegmayer

Comput. Biol. Medicine, 2021

Novel SARS-CoV-2 encoded small RNAs in the passage to humans.

Gabriela Alejandra Merino, Jonathan Raad, Leandro A Bugnon, Cristian A. Yones, Laura Kamenetzky, Juan Claus, Federico Ariel, Diego H. Milone, Georgina Stegmayer

Bioinform., 2021

2020

Complexity measures of the mature miRNA for improving pre-miRNAs prediction.

Jonathan Raad, Georgina Stegmayer, Diego H. Milone

Bioinform., 2020

DL4papers: a deep learning approach for the automatic interpretation of scientific articles.

Leandro A Bugnon, Cristian A. Yones, Jonathan Raad, Matias Gerard, Mariano Rubiolo, Gabriela Alejandra Merino, Milton Pividori, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer

Bioinform., 2020

2019

Predicting novel microRNA: a comprehensive comparison of machine learning approaches.

Georgina Stegmayer, Leandro E. Di Persia, Mariano Rubiolo, Matias Gerard, Milton Pividori, Cristian A. Yones, Leandro A Bugnon, Tadeo Rodriguez, Jonathan Raad, Diego H. Milone

Briefings Bioinform., 2019