Visualizing VHF Ultrasound of the Human Cornea. - Matthew D. Segall; Dan Z. Reinstein; Neil F. Johnson 002 (IEEE Computer Graphics and Applications, 1999)

Gaussian Processes: A Method for Automatic QSAR Modeling of ADME Properties. - Olga Obrezanova; Gábor Csányi; Joelle M. R. Gola; Matthew D. Segall (J. Chem. Inf. Model., 2007)

Automatic QSAR modeling of ADME properties: blood-brain barrier penetration and aqueous solubility. - Olga Obrezanova; Joelle M. R. Gola; Edmund J. Champness; Matthew D. Segall (J. Comput. Aided Mol. Des., 2008)

Making priors a priority. - Matthew D. Segall; Andrew Chadwick (J. Comput. Aided Mol. Des., 2010)

Gaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity. - Olga Obrezanova; Matthew D. Segall (J. Chem. Inf. Model., 2010)

Applying Medicinal Chemistry Transformations and Multiparameter Optimization to Guide the Search for High-Quality Leads and Candidates. - Matthew D. Segall; Edmund J. Champness; Chris Leeding; Ryan H. Lilien; Ramgopal R. Mettu; Brian W. Stevens (J. Chem. Inf. Model., 2011)

Can we really do computer-aided drug design? - Matthew D. Segall (J. Comput. Aided Mol. Des., 2012)

The challenges of making decisions using uncertain data. - Matthew D. Segall; Edmund J. Champness (J. Comput. Aided Mol. Des., 2015)

Predicting Regioselectivity and Lability of Cytochrome P450 Metabolism Using Quantum Mechanical Simulations. - Jonathan D. Tyzack; Peter A. Hunt; Matthew D. Segall (J. Chem. Inf. Model., 2016)

WhichP450: a multi-class categorical model to predict the major metabolising CYP450 isoform for a compound. - Peter A. Hunt; Matthew D. Segall; Jonathan D. Tyzack (J. Comput. Aided Mol. Des., 2018)

Imputation of Assay Bioactivity Data Using Deep Learning. - Thomas M. Whitehead; Benedict W. J. Irwin; Peter A. Hunt; Matthew D. Segall; Gareth John Conduit (J. Chem. Inf. Model., 2019)

Predicting pKa Using a Combination of Semi-Empirical Quantum Mechanics and Radial Basis Function Methods. - Peter A. Hunt; Layla Hosseini-Gerami; Tomas Chrien; Jeffrey Plante; David J. Ponting; Matthew D. Segall (J. Chem. Inf. Model., 2020)

Practical Applications of Deep Learning To Impute Heterogeneous Drug Discovery Data. - Benedict W. J. Irwin; Julian R. Levell; Thomas M. Whitehead; Matthew D. Segall; Gareth John Conduit (J. Chem. Inf. Model., 2020)

Imputation of sensory properties using deep learning. - Samar Mahmoud; Benedict W. J. Irwin; Dmitriy Chekmarev; Shyam Vyas; Jeff Kattas; Thomas M. Whitehead; Tamsin Mansley; Jack Bikker; Gareth John Conduit; Matthew D. Segall (J. Comput. Aided Mol. Des., 2021)

Predicting reactivity to drug metabolism: beyond P450s - modelling FMOs and UGTs. - Mario Öeren; Peter J. Walton; Peter A. Hunt; David J. Ponting; Matthew D. Segall (J. Comput. Aided Mol. Des., 2021)

Predicting Regioselectivity of Cytosolic Sulfotransferase Metabolism for Drugs. - Mario Öeren; Sylvia C. Kaempf; David J. Ponting; Peter A. Hunt; Matthew D. Segall (J. Chem. Inf. Model., 2023)