Reconocimiento de estados afectivos a partir de señales biomédicas - Leandro A Bugnon (2018)

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)

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)

Dimensional Affect Recognition from HRV: An Approach Based on Supervised SOM and ELM. - Leandro A Bugnon; Rafael A. Calvo; Diego H. Milone (IEEE Trans. Affect. Comput., 2020)

Deep Neural Architectures for Highly Imbalanced Data in Bioinformatics. - Leandro A Bugnon; Cristian A. Yones; Diego H. Milone; Georgina Stegmayer (IEEE Trans. Neural Networks Learn. Syst., 2020)

Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning. - Leandro A Bugnon; Cristian A. Yones; Diego H. Milone; Georgina Stegmayer (Briefings Bioinform., 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)

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)

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; et al. (Briefings Bioinform., 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)

Affective Computing as a Tool for Understanding Emotion Dynamics from Physiology: A Predictive Modeling Study of Arousal and Valence. - Tomás A. D'Amelio; Nicolás M. Bruno; Leandro A Bugnon; Federico Zamberlan; Enzo Tagliazucchi (ACIIW, 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, 2023)

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)

Evaluating large language models for annotating proteins. - Rosario Vitale; Leandro A Bugnon; Emilio Fenoy; Diego H. Milone; Georgina Stegmayer (Briefings Bioinform., 2024)

Comprehensive benchmarking of large language models for RNA secondary structure prediction. - Luciano I Zablocki; Leandro A Bugnon; Matias Gerard; Leandro E. Di Persia; Georgina Stegmayer; Diego H. Milone (Briefings Bioinform., 2024)