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Winkler, D*
Winkler, D*
CSIRO or Monash or La Trobe or Defence or Nottingham or Pharmacy
Подтвержден адрес электронной почты в домене latrobe.edu.au - Главная страница
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Процитировано
Процитировано
Год
Bayesian regularization of neural networks
F Burden, D Winkler
Artificial neural networks, 23-42, 2008
1196*2008
QSAR without Borders – ISI Highly Cited Paper: ISI Hot Paper
EN Muratov, J Bajorath, RP Sheridan, I Tetko, D Filimonov, V Poroikov, ...
Chemical Society Reviews 49, 3525, 2020
7542020
Beware of R2: simple, unambiguous assessment of the prediction accuracy of QSAR and QSPR models – ISI Highly Cited paper
DLJ Alexander, A Tropsha, DA Winkler
Journal of Chemical Information and Modeling 55 (7), 1316-1322, 2015
7312015
Quantitative structure–property relationship modeling of diverse materials properties - ISI Highly Cited paper
T Le, VC Epa, FR Burden, DA Winkler
Chemical Reviews 112 (5), 2889-2919, 2012
5812012
Robust QSAR models using Bayesian regularized neural networks
FR Burden, DA Winkler
Journal of Medicinal Chemistry 42 (16), 3183-3187, 1999
2991999
Opening the black box of neural networks: methods for interpreting neural network models in clinical applications.
Z Zhang, MW Beck, DA Winkler, B Huang, W Sibanda, H Goyal
Ann. Transl. Med. 6 (11), 216, 2018
2902018
A renaissance of neural networks in drug discovery
II Baskin, D Winkler, IV Tetko
Expert opinion on drug discovery 11 (8), 785-795, 2016
2752016
Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery – ISI Highly Cited paper
H Mai, TC Le, D Chen, DA Winkler, RA Caruso
Chemical Reviews 122 (16), 13478-13515, 2022
2572022
Consistent concepts of self‐organization and self‐assembly
JD Halley, DA Winkler
Complexity 14 (2), 10-17, 2008
2492008
The Materials Genome in Action: Identifying the Performance Limits of Physical Hydrogen Storage
AW Thornton, CM Simon, J Kim, O Kwon, KS Deeg, K Konstas, SJ Pas, ...
Chemistry of Materials 29 (7), 2844-2854, 2017
2372017
The role of quantitative structure-activity relationships (QSAR) in biomolecular discovery
DA Winkler
Briefings in bioinformatics 3 (1), 73-86, 2002
2142002
Modeling biological activities of nanoparticles
VC Epa, FR Burden, C Tassa, R Weissleder, S Shaw, DA Winkler
Nano letters 12 (11), 5808-5812, 2012
2112012
Discovery and optimization of materials using evolutionary approaches
TC Le, DA Winkler
Chemical reviews 116 (10), 6107-6132, 2016
2092016
Applying quantitative structure–activity relationship approaches to nanotoxicology: current status and future potential
DA Winkler, E Mombelli, A Pietroiusti, L Tran, A Worth, B Fadeel, ...
Toxicology 313 (1), 15-23, 2013
2082013
Computational Modelling and Simulation of CO2 Capture by Aqueous Amines
X Yang, Q Yang, G Puxty, R Rees, DA Winkler
Chemical Reviews 117 (14), 9524–9593, 2017
1992017
A critical overview of computational approaches employed for COVID-19 drug discovery – ISI Highly Cited paper
E Muratov, N Brown, D Fourches, D Kozakov, JL Medina-Franco, K Merz, ...
Chemical Society Reviews 50 (21 August), 9121-9151, 2021
1842021
Materials for stem cell factories of the future
AD Celiz, JGW Smith, R Langer, DG Anderson, DA Winkler, DA Barrett, ...
Nature Materials 13 (6), 570-579, 2014
1832014
Validating Eaton's hypothesis: Cubane as a benzene bioisostere
BA Chalmers, H Xing, S Houston, C Clark, S Ghassabian, A Kuo, B Cao, ...
Angewandte Chemie International Edition 55 (11), 3580-3585, 2016
182*2016
Towards chromate-free corrosion inhibitors: structure–property models for organic alternatives
DA Winkler, M Breedon, AE Hughes, FR Burden, AS Barnard, TG Harvey, ...
Green Chemistry 16 (6), 3349-3357, 2014
1812014
Design of potential anti-HIV agents. 1. Mannosidase inhibitors
DA Winkler, G Holan
Journal of medicinal chemistry 32 (9), 2084-2089, 1989
1811989
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