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Frontiers in Genetics|November 12, 2019
Paclitaxel Response Can Be Predicted With Interpretable Multi-Variate Classifiers Exploiting DNA-Methylation and miRNA DataAlexandra Bomane, Anthony Gonçalves, Pedro J BallesterAdvanced Science (Weinheim, Baden-Wurttemberg, Germany)|July 5, 2022
Interpretable Machine Learning Models to Predict the Resistance of Breast Cancer Patients to Doxorubicin from Their microRNA ProfilesAdeolu Z Ogunleye, Chayanit Piyawajanusorn, Anthony Gonçalves, et al.Future Medicinal Chemistry|March 25, 2011
Ultrafast shape recognition: method and applicationsPedro J BallesterDrug Discovery Today. Technologies|January 2, 2021
Selecting machine-learning scoring functions for structure-based virtual screeningPedro J BallesterBriefings in Bioinformatics|June 23, 2020
The impact of compound library size on the performance of scoring functions for structure-based virtual screeningLouison Fresnais, Pedro J BallesterJournal of Computational Chemistry|March 8, 2007
Ultrafast shape recognition to search compound databases for similar molecular shapesPedro J Ballester, W Graham RichardsBiomolecules|March 29, 2023
On the Best Way to Cluster NCI-60 MoleculesSaiveth Hernández-Hernández, Pedro J BallesterCurrent Opinion in Chemical Biology|May 30, 2021
Recent progress on the prospective application of machine learning to structure-based virtual screeningGhita Ghislat, Taufiq Rahman, Pedro J BallesterJournal of Chemical Information and Modeling|February 27, 2023
Beware of Simple Methods for Structure-Based Virtual Screening: The Critical Importance of Broader ComparisonsViet-Khoa Tran-Nguyen, Pedro J BallesterPageof 22