Alex M. Clark
Alex M. Clark
President, Molecular Materials Informatics
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Trichoderma virens, a plant beneficial fungus, enhances biomass production and promotes lateral root growth through an auxin-dependent mechanism in Arabidopsis
HA Contreras-Cornejo, L Macías-Rodríguez, C Cortés-Penagos, ...
Plant physiology 149 (3), 1579-1592, 2009
2D depiction of protein− ligand complexes
AM Clark, P Labute
Journal of chemical information and modeling 47 (5), 1933-1944, 2007
Electrophilic Substitution Reactions at the Phenyl Ring of the Chelated 2-(2 ‘-Pyridyl) phenyl Ligand Bound to Ruthenium (II) or Osmium (II)
AM Clark, CEF Rickard, WR Roper, LJ Wright
Organometallics 18 (15), 2813-2820, 1999
Exploiting machine learning for end-to-end drug discovery and development
S Ekins, AC Puhl, KM Zorn, TR Lane, DP Russo, JJ Klein, AJ Hickey, ...
Nature materials 18 (5), 435, 2019
Open source Bayesian models. 1. Application to ADME/Tox and drug discovery datasets
AM Clark, K Dole, A Coulon-Spektor, A McNutt, G Grass, JS Freundlich, ...
Journal of chemical information and modeling 55 (6), 1231-1245, 2015
2D structure depiction
AM Clark, P Labute, M Santavy
Journal of chemical information and modeling 46 (3), 1107-1123, 2006
Open source Bayesian models. 2. Mining a “big dataset” to create and validate models with ChEMBL
AM Clark, S Ekins
Journal of chemical information and modeling 55 (6), 1246-1260, 2015
Mobile apps for chemistry in the world of drug discovery
AJ Williams, S Ekins, AM Clark, JJ Jack, RL Apodaca
Drug Discovery Today, 2011
Detection and assignment of common scaffolds in project databases of lead molecules
AM Clark, P Labute
Journal of medicinal chemistry 52 (2), 469-483, 2009
Flexible 3D pharmacophores as descriptors of dynamic biological space
JH Nettles, JL Jenkins, C Williams, AM Clark, A Bender, Z Deng, ...
Journal of Molecular Graphics and Modelling 26 (3), 622-633, 2007
Machine learning models identify molecules active against the Ebola virus in vitro
S Ekins, JS Freundlich, AM Clark, M Anantpadma, RA Davey, P Madrid
F1000Research 4, 2015
Comparing multiple machine learning algorithms and metrics for estrogen receptor binding prediction
DP Russo, KM Zorn, AM Clark, H Zhu, S Ekins
Molecular pharmaceutics 15 (10), 4361-4370, 2018
Incorporating green chemistry concepts into mobile chemistry applications and their potential uses
S Ekins, AM Clark, AJ Williams
ACS Sustainable Chemistry & Engineering 1 (1), 8-13, 2013
Bromination and nitration reactions of metallated (Ru and Os) multiaromatic ligands and crystal structures of selected products
AM Clark, CEF Rickard, WR Roper, LJ Wright
Journal of Organometallic Chemistry 598 (2), 262-275, 2000
New target prediction and visualization tools incorporating open source molecular fingerprints for TB Mobile 2.0
AM Clark, M Sarker, S Ekins
Journal of cheminformatics 6 (1), 38, 2014
Open drug discovery teams: a chemistry mobile app for collaboration
S Ekins, AM Clark, AJ Williams
Molecular informatics 31 (8), 585-597, 2012
Looking Back to the Future: Predicting in Vivo Efficacy of Small Molecules versus Mycobacterium tuberculosis
S Ekins, R Pottorf, RC Reynolds, AJ Williams, AM Clark, JS Freundlich
Journal of chemical information and modeling 54 (4), 1070-1082, 2014
TB Mobile: a mobile app for anti-tuberculosis molecules with known targets
S Ekins, AM Clark, M Sarker
Journal of cheminformatics 5 (1), 13, 2013
Four disruptive strategies for removing drug discovery bottlenecks
S Ekins, CL Waller, MP Bradley, AM Clark, AJ Williams
Drug discovery today 18 (5-6), 265-271, 2013
Electron-probe microanalysis of gold-platinoid concentrates from southeast Borneo
EF Stumpfl, AM Clark
Transactions of the Institution of Mining and Metallurgy 74, 933-946, 1965
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