Raquel Rodríguez-Pérez
Orcid: 0000-0002-2992-3402
According to our database1,
Raquel Rodríguez-Pérez
authored at least 9 papers
between 2017 and 2023.
Collaborative distances:
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Bibliography
2023
Explaining compound activity predictions with a substructure-aware loss for graph neural networks.
J. Cheminformatics, December, 2023
2022
Predicting In Vivo Compound Brain Penetration Using Multi-task Graph Neural Networks.
J. Chem. Inf. Model., 2022
Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds.
J. Cheminformatics, 2022
Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery.
J. Comput. Aided Mol. Des., 2022
2021
Evaluation of multi-target deep neural network models for compound potency prediction under increasingly challenging test conditions.
J. Comput. Aided Mol. Des., 2021
2020
PhD thesis, 2020
Assessing the information content of structural and protein-ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning.
J. Cheminformatics, 2020
Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions.
J. Comput. Aided Mol. Des., 2020
2017
Influence of Varying Training Set Composition and Size on Support Vector Machine-Based Prediction of Active Compounds.
J. Chem. Inf. Model., 2017