Raquel Rodríguez-Pérez

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 16

Top Topics

Machine Learning

Top Venues

Molecular pharmaceutics

Nature communications

Chemical research in toxicology

Journal of chemical information and modeling

This page only lists publications with an associated author ORCID identifier.

Publications

Andrin Fluetsch, Elena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Adapting Deep Learning QSPR Models to Specific Drug Discovery Projects. Molecular pharmaceutics 21 (4) (2024)
Andrin Fluetsch, Elena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Adapting Deep Learning QSPR Models to Specific Drug Discovery Projects. Molecular pharmaceutics (2024)
Andrin Fluetsch, Markus Trunzer, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent Inhibition. Chemical research in toxicology 37 (4) (2024)
Giulia Peteani, Minh Tam Davide Huynh, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Application of machine learning models for property prediction to targeted protein degraders. Nature communications 15 (1) (2024)
Andrin Fluetsch, Markus Trunzer, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent Inhibition. Chemical research in toxicology (2024)
Giulia Peteani, Minh Tam Davide Huynh, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Application of machine learning models for property prediction to targeted protein degraders. Nature communications 15 (1) (2024)
Andrin Fluetsch, Markus Trunzer, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Deep Learning Models Compared to Experimental Variability for the Prediction of CYP3A4 Time-Dependent Inhibition. Chemical research in toxicology 37 (4) (2024)
Giulia Peteani, Minh Tam Davide Huynh, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Application of machine learning models for property prediction to targeted protein degraders. Nature communications 15 (1) (2024)
Giulia Peteani, Minh Tam Davide Huynh, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Application of machine learning models for property prediction to targeted protein degraders. Nature communications 15 (1) (2024)
Andrin Fluetsch, Elena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Adapting Deep Learning QSPR Models to Specific Drug Discovery Projects. Molecular pharmaceutics 21 (4) (2024)
Elena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Properties. Molecular pharmaceutics (2023)
Elena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Properties. Molecular pharmaceutics 20 (3) (2023)
Elena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Properties. Molecular pharmaceutics 20 (3) (2023)
Elena Di Lascio, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Properties. Molecular pharmaceutics 20 (3) (2023)
Raquel Rodríguez-Pérez, Markus Trunzer, Nadine Schneider, Bernard Faller, Grégori Gerebtzoff
Multispecies Machine Learning Predictions of In Vitro Intrinsic Clearance with Uncertainty Quantification Analyses. Molecular pharmaceutics (2022)
Seid Hamzic, Richard A Lewis, Sandrine Desrayaud, Cihan Soylu, Michael E Fortunato, Grégori Gerebtzoff, Raquel Rodríguez-Pérez
Predicting In Vivo Compound Brain Penetration Using Multi-task Graph Neural Networks. Journal of chemical information and modeling 62 (13) (2022)