Publicaciones seleccionadas


  1. tlpfam.jpg
    Transfer learning: The key to functionally annotate the protein universe
    L.A. Bugnon, E. Fenoy, A Edera, J. Raad, G. Stegmayer, and 1 more author
    Patterns, 2023


  1. rna_structure.png
    Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches
    L. A. Bugnon, A. Edera, S. Prochetto, M. Gerard, J. Raad, and 8 more authors
    Briefing in Bioinformatics, 2022
  2. mire2e.png
    miRe2e: a full end-to-end deep model based on transformers for prediction of pre-miRNAs
    J. Raad, L. A. Bugnon, D. H. Milone, and G. Stegmayer
    Bioinformatics, 2022


  1. sarscov2_pipeline.png
    Deep Learning for the discovery of new pre-miRNAs: Helping the fight against COVID-19
    L. A. Bugnon, J. Raad, G.A. Merino, C. Yones, F. Ariel, and 2 more authors
    Machine Learning with Applications, 2021
  2. mirdnn.png
    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, and G. Stegmayer
    Computers in Biology and Medicine, 2021


  1. sarscov2.png
    Novel SARS-CoV-2 encoded small RNAs in the passage to humans
    G. Merino, J. Raad, L. A. Bugnon, C. Yones, L. Kamenetzky, and 4 more authors
    Bioinformatics, 2020
  2. genome-wide.png
    Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning
    L. A. Bugnon, C. Yones, D. H. Milone, and G. Stegmayer
    Briefings in Bioinformatics, 2020
  3. dl4papers.png
    DL4papers: a deep learning model for reading papers
    L. A. Bugnon, C. Yones, J. Raad, M. Gerard, M. Rubiolo, and 5 more authors
    Oxford Bioinformatics, 2020


  1. deesom.png
    Deep neural architectures for highly imbalanced data in bioinformatics
    L. A. Bugnon, Cristian A. Yones, D. H. Milone, and G. Stegmayer
    IEEE Transactions on Neural Networks and Learning Systems, 2019
  2. genome-wide-dataset.png
    Genome-wide hairpins datasets of animals and plants for novel miRNA prediction
    L. A. Bugnon, C. Yones, D. H. Milone, and G. Stegmayer
    Data in Brief, 2019
  3. mirna_benchmark.png
    Predicting novel microRNA: a comprehensive comparison of machine learning approaches
    G. Stegmayer, L. Di Persia, Mariano Rubiolo, Matías Gerard, Milton Pividori, and 5 more authors
    Briefings in Bioinformatics, 2019


  1. emohr.png
    Dimensional Affect Recognition from HRV: an Approach Based on Supervised SOM and ELM
    L. A. Bugnon, R. A. Calvo, and D. H. Milone
    IEEE Transactions on Affective Computing, 2017