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Molecular Pharmaceutics|November 4, 2017
Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data SetsAlexandru Korotcov, Valery Tkachenko, Daniel P Russo, et al.Molecular Pharmaceutics|April 20, 2018
Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug DiscoveryThomas Lane, Daniel P Russo, Kimberley M Zorn, et al.Journal of Chemical Information and Modeling|December 21, 2019
Graph Convolutional Neural Networks as "General-Purpose" Property Predictors: The Universality and Limits of ApplicabilityVadim Korolev, Artem Mitrofanov, Alexandru Korotcov, et al.Drug Discovery Today|March 20, 2012
Towards a gold standard: regarding quality in public domain chemistry databases and approaches to improving the situationAntony J Williams, Sean Ekins, Valery TkachenkoMolecules (Basel, Switzerland)|June 2, 2021
Deep Learning Insights into Lanthanides Complexation ChemistryArtem A Mitrofanov, Petr I Matveev, Kristina V Yakubova, et al.Molecular Pharmaceutics|August 18, 2018
Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding PredictionDaniel P Russo, Kimberley M Zorn, Alex M Clark, et al.Journal of Cheminformatics|January 12, 2021
Open-source QSAR models for pKa prediction using multiple machine learning approachesKamel Mansouri, Neal F Cariello, Alexandru Korotcov, et al.Molecular Pharmaceutics|February 20, 2019
Multiple Machine Learning Comparisons of HIV Cell-based and Reverse Transcriptase Data SetsKimberley M Zorn, Thomas R Lane, Daniel P Russo, et al.GEN Biotechnology|October 31, 2022
Al-novation: Finding New Uses for Artificial Intelligence Across IndustriesSean EkinsTuberculosis (Edinburgh, Scotland)|October 8, 2014
Hacking into the granuloma: could antibody antibiotic conjugates be developed for TB?Sean EkinsPageof 43