Modelos que aprenden el lenguaje de las moléculas y cómo utilizarlos para predecir sus propiedades
Published:
Keynote talk discussing pre-trained language models and their application in modelling for biomedicine and drug discovery.
Talks and presentations
See a map of all the places I've given a talk!
Keynote
Talk
Partitioning, representation, and automation in canonical and non-canonical peptide modelling
Published:
Talk discussing the importance of proper dataset partitioning and choice of negative peptides, the choice of representation and how can we automate Machine Learning models for natural and synthetic peptide property prediction, with the aim of accelerating peptide/peptidomimetic drug development.
How to generalize machine learning models to both canonical and non-canonical peptides
Published:
Talk discussing our work automating Machine Learning models for natural and synthetic peptide property prediction, with the aim of accelerating peptide/peptidomimetic drug development
AutoPeptideML2: An open-source library for democratising machine learning for peptide bioactivity prediction.
Published:
Talk discussing the latest update to the AutoPeptideML library. Presentation given to the Student Council Symposium (SCS) and the Bioinformatics Open Source Conference (BOSC) as part of ISMB 2025.
AutoPeptideML: automated machine learning for building peptide bioactivity predictors leveraging protein language models
Published:
Talk introducing the AutoPeptideML library.
Poster
A new framework for evaluating model out-of-distribution generalization for the biochemical domain
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