Winkler, D*

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Morgan R AlexanderUniversity of NottinghamVerified email at nottingham.ac.uk
Vidana EpaPrincipal Research Scientist, CSIROVerified email at csiro.au
Andrew Leslie HookUniversity of NottinghamVerified email at nottingham.ac.uk
Olexandr IsayevCarl and Amy Jones Professor of Chemistry, Carnegie Mellon UniversityVerified email at olexandrisayev.com
Paul PigramLa Trobe University, Melbourne, AustraliaVerified email at latrobe.edu.au
Grazziela FigueredoAssociate Professor, University of NottinghamVerified email at nottingham.ac.uk
Dr Julianne D. HalleyDepartment of Public Health and Primary Care, University of Cambridge, UKVerified email at medschl.cam.ac.uk
Sakshi PiplaniBioinformatics ScientistVerified email at flinders.edu.au
Feng WangProfessor of Chemistry, Swinburne University of Technology, AustraliaVerified email at swin.edu.au
Nikolai PetrovskyProfessor, Australian Respiratory and Sleep Medicine Research InstituteVerified email at flinders.edu.au
Alexander TropshaProfessor at UNC-Chapel HillVerified email at unc.edu
Amir M GhaemmaghamiUniversity of NottinghamVerified email at nottingham.ac.uk
Aaron ThorntonPrincipal Research Scientist, CSIROVerified email at csiro.au
Andrew J. ChristoffersonRMIT UniversityVerified email at rmit.edu.au
Paul WilliamsProfessor of Molecular Microbiology, University of NottinghamVerified email at nottingham.ac.uk
Daniel G. AndersonMassachusetts Institute of TechnologyVerified email at mit.edu
Sviatlana LamakaHelmholtz-Zentrum HereonVerified email at hzg.de
WANG Frédéricprofesseur en langue et pensée chinoises, InalcoVerified email at inalco.fr
Michael BreedonResearch Scientist, CSIROVerified email at csiro.au
ivan coleRMITVerified email at rmit.edu.au

Winkler, D*

CSIRO or Monash or La Trobe or Defence or Nottingham or Pharmacy

Verified email at latrobe.edu.au - Homepage

regenerative medicine drugs/biomaterials/2D materials/porous materials design AI/machine learning cheminformatics complex sy


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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	753	2020
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	728	2015
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	581	2012
Robust QSAR models using Bayesian regularized neural networks FR Burden, DA Winkler Journal of Medicinal Chemistry 42 (16), 3183-3187, 1999	299	1999
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	290	2018
A renaissance of neural networks in drug discovery II Baskin, D Winkler, IV Tetko Expert opinion on drug discovery 11 (8), 785-795, 2016	275	2016
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	257	2022
Consistent concepts of self‐organization and self‐assembly JD Halley, DA Winkler Complexity 14 (2), 10-17, 2008	249	2008
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	237	2017
The role of quantitative structure-activity relationships (QSAR) in biomolecular discovery DA Winkler Briefings in bioinformatics 3 (1), 73-86, 2002	214	2002
Modeling biological activities of nanoparticles VC Epa, FR Burden, C Tassa, R Weissleder, S Shaw, DA Winkler Nano letters 12 (11), 5808-5812, 2012	211	2012
Discovery and optimization of materials using evolutionary approaches TC Le, DA Winkler Chemical reviews 116 (10), 6107-6132, 2016	209	2016
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	208	2013
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	199	2017
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	183	2021
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	183	2014
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	181*	2016
Design of potential anti-HIV agents. 1. Mannosidase inhibitors DA Winkler, G Holan Journal of medicinal chemistry 32 (9), 2084-2089, 1989	181	1989
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	180	2014

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