Matthew D. Segall

According to our database, Matthew D. Segall authored at least 16 papers between 1999 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

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., June, 2023

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

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

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

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

2019

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

2018

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

2016

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

2015

The challenges of making decisions using uncertain data.

Matthew D. Segall, Edmund J. Champness

J. Comput. Aided Mol. Des., 2015

2012

Can we really do computer-aided drug design?

Matthew D. Segall

J. Comput. Aided Mol. Des., 2012

2011

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

2010

Gaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity.

Olga Obrezanova, Matthew D. Segall

J. Chem. Inf. Model., 2010

Making priors a priority.

Matthew D. Segall, Andrew Chadwick

J. Comput. Aided Mol. Des., 2010

2008

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

2007

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

1999

Visualizing VHF Ultrasound of the Human Cornea.

Matthew D. Segall, Dan Z. Reinstein, Neil F. Johnson

IEEE Computer Graphics and Applications, 1999