Analyzing Multitarget Activity Landscapes Using Protein-Ligand Interaction Fingerprints: Interaction Cliffs. - Oscar Méndez-Lucio; Albert J. Kooistra; Chris de Graaf; Andreas Bender 002; José L. Medina-Franco (J. Chem. Inf. Model., 2015)

ARWAR: A network approach for predicting Adverse Drug Reactions. - Hossein Rahmani 002; Gerhard Weiss 001; Oscar Méndez-Lucio; Andreas Bender 002 (Comput. Biol. Medicine, 2016)

Activity Landscape Plotter: A Web-Based Application for the Analysis of Structure-Activity Relationships. - Mariana González-Medina; Oscar Méndez-Lucio; José L. Medina-Franco (J. Chem. Inf. Model., 2017)

Data-driven approaches used for compound library design, hit triage and bioactivity modeling in high-throughput screening. - Shardul Paricharak; Oscar Méndez-Lucio; Aakash Chavan Ravindranath; Andreas Bender 002; Adriaan P. IJzerman; Gerard J. P. van Westen (Briefings Bioinform., 2018)

A geometric deep learning approach to predict binding conformations of bioactive molecules. - Oscar Méndez-Lucio; Mazen Ahmad; Ehecatl Antonio del Rio-Chanona; Jörg Kurt Wegner (Nat. Mach. Intell., 2021)

MolE: a molecular foundation model for drug discovery. - Oscar Méndez-Lucio; Christos A. Nicolaou; Berton Earnshaw (CoRR, 2022)

Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds. - Jürgen Bajorath; Ana L. Chávez-Hernández; Miquel Duran-Frigola; Eli Fernández-de Gortari; Johann Gasteiger; Edgar López-López; Gerald M. Maggiora; José L. Medina-Franco; Oscar Méndez-Lucio; Jordi Mestres; Ramón Alain Miranda-Quintana; Tudor I. Oprea; et al. (J. Cheminformatics, 2022)