Molecular dynamics and docking simulations as a proof of high flexibility in E. coli FabH and its relevance for accurate inhibitor modeling. - Yunierkis Pérez-Castillo; Matheus Froeyen; Miguel Ángel Cabrera-Pérez; Ann Nowé (J. Comput. Aided Mol. Des., 2011)

GA(M)E-QSAR: A Novel, Fully Automatic Genetic-Algorithm-(Meta)-Ensembles Approach for Binary Classification in Ligand-Based Drug Design. - Yunierkis Pérez-Castillo; Cosmin Lazar; Jonatan Taminau; Matheus Froeyen; Miguel Ángel Cabrera-Pérez; Ann Nowé (J. Chem. Inf. Model., 2012)

Harmonization of QSAR Best Practices and Molecular Docking Provides an Efficient Virtual Screening Tool for Discovering New G-Quadruplex Ligands. - Daimel Castillo-González; Jean-Louis Mergny; Aurore De Rache; Gisselle Pérez-Machado; Miguel Ángel Cabrera-Pérez; Orazio Nicolotti; Antonellina Introcaso; Giuseppe Felice Mangiatordi; Aurore Guédin; Anne Bourdoncle; Teresa M. Garrigues; Federico Pallardó; et al. (J. Chem. Inf. Model., 2015)

ADME Prediction with KNIME: Development and Validation of a Publicly Available Workflow for the Prediction of Human Oral Bioavailability. - Gabriela Falcón-Cano; Christophe Molina; Miguel Ángel Cabrera-Pérez (J. Chem. Inf. Model., 2020)

A Novel Automated Framework for QSAR Modeling of Highly Imbalanced Leishmania High-Throughput Screening Data. - Omar Casanova-Alvarez; Aliuska Morales Helguera; Miguel Ángel Cabrera-Pérez; Reinaldo Molina Ruiz; Christophe Molina (J. Chem. Inf. Model., 2021)