Winkler, D*
Winkler, D*
CSIRO or Monash or La Trobe or Defence or Nottingham or Pharmacy
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Cited by
Cited by
Quantitative structure–property relationship modeling of diverse materials properties
T Le, VC Epa, FR Burden, DA Winkler
Chemical Reviews 112 (5), 2889-2919, 2012
Beware of R2: simple, unambiguous assessment of the prediction accuracy of QSAR and QSPR models
DLJ Alexander, A Tropsha, DA Winkler
Journal of chemical information and modeling 55 (7), 1316-1322, 2015
Bayesian regularization of neural networks
F Burden, D Winkler
Artificial neural networks, 23-42, 2008
Robust QSAR models using Bayesian regularized neural networks
FR Burden, DA Winkler
Journal of medicinal chemistry 42 (16), 3183-3187, 1999
The role of quantitative structure-activity relationships (QSAR) in biomolecular discovery
DA Winkler
Briefings in bioinformatics 3 (1), 73-86, 2002
Consistent concepts of self‐organization and self‐assembly
JD Halley, DA Winkler
Complexity 14 (2), 10-17, 2008
Design of potential anti-HIV agents. 1. Mannosidase inhibitors
DA Winkler, G Holan
Journal of medicinal chemistry 32 (9), 2084-2089, 1989
Use of automatic relevance determination in QSAR studies using Bayesian neural networks
FR Burden, MG Ford, DC Whitley, DA Winkler
Journal of Chemical Information and Computer Sciences 40 (6), 1423-1430, 2000
Modeling biological activities of nanoparticles
VC Epa, FR Burden, C Tassa, R Weissleder, S Shaw, DA Winkler
Nano letters 12 (11), 5808-5812, 2012
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
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
The X-ray Structure of a Hemipteran Ecdysone Receptor Ligand-binding Domain comparison with a Lepidopteran ecdysone receptor ligand-binding domain and implications for …
JA Carmichael, MC Lawrence, LD Graham, PA Pilling, VC Epa, L Noyce, ...
Journal of Biological Chemistry 280 (23), 22258-22269, 2005
Classification of emergence and its relation to self‐organization
JD Halley, DA Winkler
Complexity 13 (5), 10-15, 2008
Artificial neural networks: methods and applications
DJ Livingstone
Humana Press, 2008
A renaissance of neural networks in drug discovery
II Baskin, D Winkler, IV Tetko
Expert opinion on drug discovery 11 (8), 785-795, 2016
Neural networks as robust tools in drug lead discovery and development
DA Winkler
Molecular biotechnology 27 (2), 139-167, 2004
Comparison of linear and nonlinear classification algorithms for the prediction of drug and chemical metabolism by human UDP-glucuronosyltransferase isoforms
MJ Sorich, JO Miners, RA McKinnon, DA Winkler, FR Burden, PA Smith
Journal of chemical information and computer sciences 43 (6), 2019-2024, 2003
Discovery and optimization of materials using evolutionary approaches
TC Le, DA Winkler
Chemical reviews 116 (10), 6107-6132, 2016
Modelling blood–brain barrier partitioning using Bayesian neural nets
DA Winkler, FR Burden
Journal of Molecular Graphics and Modelling 22 (6), 499-505, 2004
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
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