Ballester, Pedro J.

Performance of machine-learning scoring functions in structure-based virtual screening.

Wójcikowski, M., Ballester, P. J., & Siedlecki, P. (2017) · Scientific Reports

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 364

Machine‐learning scoring functions to improve structure‐based binding affinity prediction and virtual screening

Ain, Q. U., Aleksandrova, A., Roessler, F. D., & Ballester, P. J. (2015) · WIREs Computational Molecular Science

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 357

Improving AutoDock Vina using random forest: the growing accuracy of binding affinity prediction by the effective exploitation of larger data sets

Li, H., Leung, K., Wong, M., & Ballester, P. J. (2015) · Molecular Informatics

Computational Drug Discovery MethodsProtein Structure and Dynamics

Cited by 252

Precision and recall oncology: combining multiple gene mutations for improved identification of drug-sensitive tumours

Naulaerts, S., Dang, C. C., & Ballester, P. J. (2017) · Oncotarget

Computational Drug Discovery MethodsCancer Genomics and Diagnostics

Cited by 41

A precise comparison of molecular target prediction methods

He, T., Caba, K., & Ballester, P. J. (2025) · Digital Discovery

Computational Drug Discovery MethodsProtein Degradation and Inhibitors

Cited by 4

Using Stochastic Computing for Virtual Screening Acceleration

Frasser, C. F., de Benito, C., Skibinsky-Gitlin, E. S., Canals, V., Font-Rosselló, J., Roca, M., Ballester, P. J., & Rosselló, J. L. (2021) · Electronics

Computational Drug Discovery MethodsDNA and Biological Computing

Cited by 3

NextTopDocker: A Large-Scale Docking-Power Benchmark Reveals Limitations of Current End-to-End Machine-Learning Docking and the Strength of Hybrid Rescoring

Truong, C.-M., Ballester, P. J., Taboureau, O., & Tran-Nguyen, V.-K. (2026) · Journal of Medicinal Chemistry

Computational Drug Discovery MethodsProtein Degradation and Inhibitors

Cited by 2