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Nicola J Richmond
Nicola J Richmond
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GALAHAD: 1. Pharmacophore identification by hypermolecular alignment of ligands in 3D
NJ Richmond, CA Abrams, PRN Wolohan, E Abrahamian, P Willett, ...
Journal of computer-aided molecular design 20, 567-587, 2006
2342006
Lead optimization using matched molecular pairs: inclusion of contextual information for enhanced prediction of HERG inhibition, solubility, and lipophilicity
G Papadatos, M Alkarouri, VJ Gillet, P Willett, V Kadirkamanathan, ...
Journal of chemical information and modeling 50 (10), 1872-1886, 2010
1342010
Validity of ligand efficiency metrics
CW Murray, DA Erlanson, AL Hopkins, GM Keserü, PD Leeson, ...
ACS medicinal chemistry letters 5 (6), 616-618, 2014
1302014
Alignment of three-dimensional molecules using an image recognition algorithm
NJ Richmond, P Willett, RD Clark
Journal of Molecular Graphics and Modelling 23 (2), 199-209, 2004
852004
Process validation and screen reproducibility in high-throughput screening
I Coma, L Clark, E Diez, G Harper, J Herranz, G Hofmann, M Lennon, ...
Journal of biomolecular screening 14 (1), 66-76, 2009
552009
Over expression of wild type or a catalytically dead mutant of Sirtuin 6 does not influence NFκB responses
R Grimley, O Polyakova, J Vamathevan, J McKenary, B Hayes, C Patel, ...
PloS one 7 (7), e39847, 2012
352012
Solvation of metal nanoparticles in a subcritical—supercritical fluid: a computer simulation study
M Lal, M Plummer, NJ Richmond, W Smith
The Journal of Physical Chemistry B 108 (19), 6052-6061, 2004
342004
A stratification for varieties of modules
NJ Richmond
Bulletin of the London Mathematical Society 33 (5), 565-577, 2001
172001
Unsupervised 3D ring template searching as an ideas generator for scaffold hopping: use of the LAMDA, RigFit, and field-based similarity search (FBSS) methods
M Bohl, B Loeprecht, B Wendt, T Heritage, NJ Richmond, P Willett
Journal of chemical information and modeling 46 (5), 1882-1890, 2006
122006
Intrinsic uncertainties and where to find them
F Farina, L Phillips, NJ Richmond
ICML 2021 Workshop on Uncertainty and Robustness in Deep Learning, 2021
2021
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Artiklar 1–10