Modeling the Zinc Chelating Rosette Nanotube. - Fuqiang Ban; Savariraj Kingsley; Ross Johnson; Hicham Fenniri; Andriy Kovalenko 001 (ICMENS, 2005)

SimBoost: a read-across approach for predicting drug-target binding affinities using gradient boosting machines. - Tong He; Marten Heidemeyer; Fuqiang Ban; Artem Cherkasov; Martin Ester (J. Cheminformatics, 2017)

Best Practices of Computer-Aided Drug Discovery: Lessons Learned from the Development of a Preclinical Candidate for Prostate Cancer with a New Mechanism of Action. - Fuqiang Ban; Kush Dalal; Huifang Li; Eric Leblanc; Paul S. Rennie; Artem Cherkasov (J. Chem. Inf. Model., 2017)

Toxic Colors: The Use of Deep Learning for Predicting Toxicity of Compounds Merely from Their Graphic Images. - Michael Fernández; Fuqiang Ban; Godwin Woo; Michael Hsing; Takeshi Yamazaki; Eric Leblanc; Paul S. Rennie; William J. Welch; Artem Cherkasov (J. Chem. Inf. Model., 2018)

Progressive Docking - Deep Learning Based Approach for Accelerated Virtual Screening. - Vibudh Agrawal; Francesco Gentile; Michael Hsing; Fuqiang Ban; Artem Cherkasov (ICANN (Workshop), 2019)

Quantitative Structure-Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects. - Michael Fernández; Fuqiang Ban; Godwin Woo; Olexandr Isayev; Carl Perez; Valery Fokin; Alexander Tropsha; Artem Cherkasov (J. Chem. Inf. Model., 2019)

Large-Scale Virtual Screening for the Discovery of SARS-CoV-2 Papain-like Protease (PLpro) Non-covalent Inhibitors. - Olivia Garland; Anh-Tien Ton; Shoeib Moradi; Jason R. Smith 003; Suzana Kovacic; Kurtis Ng; Mohit Pandey; Fuqiang Ban; Jaeyong Lee; Marija Vuckovic; Liam J. Worrall; Robert N. Young; et al. (J. Chem. Inf. Model., 2023)

CACHE Challenge #1: Targeting the WDR Domain of LRRK2, A Parkinson's Disease Associated Protein. - Fengling Li; Suzanne Ackloo; Cheryl H. Arrowsmith; Fuqiang Ban; Christopher J. Barden; Hartmut Beck; Jan Beránek; Francois Berenger; Albina Bolotokova; Guillaume Bret; Marko Breznik; Emanuele Carosati; et al. (J. Chem. Inf. Model., 2024)

PROTACable Is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning To Automate the De Novo Design of PROTACs. - Hazem Mslati; Francesco Gentile; Mohit Pandey; Fuqiang Ban; Artem Cherkasov (J. Chem. Inf. Model., 2024)

Active Learning-Guided Hit Optimization for the Leucine-Rich Repeat Kinase 2 WDR Domain Based on In Silico Ligand-Binding Affinities. - Filipp Gusev; Evgeny Gutkin; Francesco Gentile; Fuqiang Ban; S. Benjamin Koby; Fengling Li; Irene Chau; Suzanne Ackloo; Cheryl H. Arrowsmith; Albina Bolotokova; Pegah Ghiabi; Elisa Gibson; et al. (J. Chem. Inf. Model., 2025)