Improved CoMFA Modeling by Optimization of Settings. - Shane D. Peterson; Wesley Schaal; Anders Karlén (J. Chem. Inf. Model., 2006)

Automated QuantMap for rapid quantitative molecular network topology analysis. - Wesley Schaal; Ulf Hammerling; Mats G. Gustafsson; Ola Spjuth (Bioinform., 2013)

Toward a Benchmarking Data Set Able to Evaluate Ligand- and Structure-based Virtual Screening Using Public HTS Data. - Martin Lindh; Fredrik Svensson; Wesley Schaal; Jin Zhang; Christian Sköld; Peter Brandt; Anders Karlén (J. Chem. Inf. Model., 2015)

Large-scale ligand-based predictive modelling using support vector machines. - Jonathan Alvarsson; Samuel Lampa; Wesley Schaal; Claes R. Andersson; Jarl E. S. Wikberg; Ola Spjuth (J. Cheminformatics, 2016)

Large-scale virtual screening on public cloud resources with Apache Spark. - Marco Capuccini; Laeeq Ahmed; Wesley Schaal; Erwin Laure; Ola Spjuth (J. Cheminformatics, 2017)

Docking of Macrocycles: Comparing Rigid and Flexible Docking in Glide. - Hiba Alogheli; Gustav Olanders; Wesley Schaal; Peter Brandt; Anders Karlén (J. Chem. Inf. Model., 2017)

Efficient iterative virtual screening with Apache Spark and conformal prediction. - Laeeq Ahmed; Valentin Georgiev; Marco Capuccini; Salman Zubair Toor; Wesley Schaal; Erwin Laure; Ola Spjuth (J. Cheminformatics, 2018)

A confidence predictor for logD using conformal regression and a support-vector machine. - Maris Lapins; Staffan Arvidsson; Samuel Lampa; Arvid Berg; Wesley Schaal; Jonathan Alvarsson; Ola Spjuth (J. Cheminformatics, 2018)

Predicting target profiles with confidence as a service using docking scores. - Laeeq Ahmed; Hiba Alogheli; Staffan Arvidsson McShane; Jonathan Alvarsson; Arvid Berg; Anders Larsson; Wesley Schaal; Erwin Laure; Ola Spjuth (J. Cheminformatics, 2020)

Approaches for containerized scientific workflows in cloud environments with applications in life science. - Ola Spjuth; Marco Capuccini; Matteo Carone; Anders Larsson; Wesley Schaal; Jon Ander Novella; Oliver Stein; Morgan Ekmefjord; Paolo Di Tommaso; Evan W. Floden; Cédric Notredame; Pablo A. Moreno; et al. (F1000Research, 2021)

Predicting protein network topology clusters from chemical structure using deep learning. - Akshai P. Sreenivasan; Philip J. Harrison; Wesley Schaal; Damian J. Matuszewski; Kim Kultima; Ola Spjuth (J. Cheminformatics, 2022)