Georgina Stegmayer

  • Independent Researcher, CONICET
  • Assistant Professor, Department of Informatics, FICH-UNL
  • Leader of the Bioinformatics Research Group: computer science and machine learning people who essentially make algorithms for the integration, fusion and analysis of biological data. We develop novel data mining algorithms and computing tools, as well as intelligent algorithms, for biological data fusion and integration, and for new knowledge discovery.

Research lines in bioinformatics:

  • Gene function prediction – inference of GO annotations to genes
  • Gene regulatory network reconstruction
  • Metabolic engineering
  • Pre-miRNA prediction algorithms from genome-wide data
  • Data fusion and integration of biological sources

Research Interests

  • Bioinformatics
  • Machine learning
  • Neural networks
  • Data mining
  • Clustering

Teaching

Courses in Engineering Informatics:

Latest Publicactions

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

HextractoR: an R package for automatic extraction of hairpins from genome-wide data
  • C. Yones
  • N. Macchiaroli
  • L. Kamenetzky
  • G. Stegmayer
  • D. H. Milone

bioRxiv - 2020

Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning
  • L. A. Bugnon
  • C. Yones
  • D. H. Milone
  • G. Stegmayer

Oxford Briefings in Bioinformatics - 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

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