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Journal of Chemical Information and Modeling|November 10, 2018
Application of Bioactivity Profile-Based Fingerprints for Building Machine Learning ModelsNoé Sturm, Jiangming Sun, Yves Vandriessche, et al.Journal of Biomolecular Screening|August 27, 2013
On the Relationship between Molecular Hit Rates in High-Throughput Screening and Molecular DescriptorsMari Hansson, John Pemberton, Ola Engkvist, et al.Journal of Chemical Information and Modeling|October 29, 2020
REINVENT 2.0: An AI Tool for De Novo Drug DesignThomas Blaschke, Josep Arús-Pous, Hongming Chen, et al.Journal of Chemical Information and Computer Sciences|October 16, 2002
High-throughput, in silico prediction of aqueous solubility based on one- and two-dimensional descriptorsOla Engkvist, Paul WredeJournal of Cheminformatics|January 12, 2021
SMILES-based deep generative scaffold decorator for de-novo drug designJosep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, et al.Journal of Pharmaceutical Sciences|December 30, 2014
Exploring in silico prediction of the unbound brain-to-plasma drug concentration ratio: model validation, renewal, and interpretationSrinidhi Varadharajan, Susanne Winiwarter, Lars Carlsson, et al.Journal of Cheminformatics|January 12, 2021
A de novo molecular generation method using latent vector based generative adversarial networkOleksii Prykhodko, Simon Viet Johansson, Panagiotis-Christos Kotsias, et al.Chemmedchem|September 4, 2019
Identification of Compounds That Interfere with High-Throughput Screening Assay TechnologiesLaurianne David, Jarrod Walsh, Noé Sturm, et al.Journal of Cheminformatics|December 19, 2020
From Big Data to Artificial Intelligence: chemoinformatics meets new challengesIgor V Tetko, Ola EngkvistJournal of Chemical Information and Modeling|May 13, 2009
ProSAR: a new methodology for combinatorial library designHongming Chen, Ulf Börjesson, Ola Engkvist, et al.Pageof 27