Vasyl Kovalishyn \ Ковалішин Василь Володимирович
Vasyl Kovalishyn \ Ковалішин Василь Володимирович
V.P. Kukhar Institute of Bioorganic Chemistry and Petroсhemistry, NAS of Ukraine, PhD, Senior
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Synthesis and structure–antituberculosis activity relationship of 1H-indole-2, 3-dione derivatives
N Karalı, A Gürsoy, F Kandemirli, N Shvets, FB Kaynak, S Özbey, ...
Bioorganic & medicinal chemistry 15 (17), 5888-5904, 2007
Neural network studies. 3. Variable selection in the cascade-correlation learning architecture
VV Kovalishyn, IV Tetko, AI Luik, VV Kholodovych, AEP Villa, ...
Journal of Chemical Information and Computer Sciences 38 (4), 651-659, 1998
Volume learning algorithm artificial neural networks for 3D QSAR studies
IV Tetko, VV Kovalishyn, DJ Livingstone
Journal of Medicinal Chemistry 44 (15), 2411-2420, 2001
Design, synthesis and biological evaluation of novel isoniazid derivatives with potent antitubercular activity
F Martins, S Santos, C Ventura, R Elvas-Leitão, L Santos, S Vitorino, ...
European journal of medicinal chemistry 81, 119-138, 2014
Applicability domain for in silico models to achieve accuracy of experimental measurements
I Sushko, S Novotarskyi, R Körner, AK Pandey, VV Kovalishyn, ...
Journal of Chemometrics 24 (3‐4), 202-208, 2010
Synthesis and structure–antibacterial activity relationship investigation of isomeric 2, 3, 5-substituted perhydropyrrolo [3, 4-d] isoxazole-4, 6-diones
H Agirbas, S Guner, F Budak, S Keceli, F Kandemirli, N Shvets, ...
Bioorganic & medicinal chemistry 15 (6), 2322-2333, 2007
QSAR modeling of antitubercular activity of diverse organic compounds
V Kovalishyn, J Aires-de-Sousa, C Ventura, RE Leitão, F Martins
Chemometrics and Intelligent Laboratory Systems 107 (1), 69-74, 2011
1, 3-Oxazole derivatives as potential anticancer agents: computer modeling and experimental study
I Semenyuta, V Kovalishyn, V Tanchuk, S Pilyo, V Zyabrev, V Blagodatnyy, ...
Computational biology and chemistry 65, 8-15, 2016
Antibacterial Activity of Imidazolium‐Based Ionic Liquids Investigated by QSAR Modeling and Experimental Studies
D Hodyna, V Kovalishyn, S Rogalsky, V Blagodatnyi, K Petko, ...
Chemical Biology & Drug Design 88 (3), 422-433, 2016
The structure-antituberculosis activity relationships study in a series of 5-(4-aminophenyl)-4-substituted-2, 4-dihydro-3h-1, 2, 4-triazole-3-thione derivatives. A combined …
F Kandemirli, N Shvets, S Unsalan, I Kucukguzel, S Rollas, V Kovalishyn, ...
Medicinal Chemistry 2 (4), 415-422, 2006
Design, synthesis and evaluation of novel sulfonamides as potential anticancer agents
MV Kachaeva, DM Hodyna, IV Semenyuta, SG Pilyo, VM Prokopenko, ...
Computational biology and chemistry 74, 294-303, 2018
Modelling the toxicity of a large set of metal and metal oxide nanoparticles using the OCHEM platform
V Kovalishyn, N Abramenko, I Kopernyk, L Charochkina, L Metelytsia, ...
Food and Chemical Toxicology 112, 507-517, 2018
Development of nanostructure–activity relationships assisting the nanomaterial hazard categorization for risk assessment and regulatory decision-making
G Chen, WJGM Peijnenburg, V Kovalishyn, MG Vijver
RSC advances 6 (57), 52227-52235, 2016
Predictive QSAR modeling of phosphodiesterase 4 inhibitors
V Kovalishyn, V Tanchuk, L Charochkina, I Semenuta, V Prokopenko
Journal of Molecular Graphics and Modelling 32, 32-38, 2012
Investigation of the physical and rheological properties of SBR-1712 rubber compounds by neural network approaches
E Demirhan, F Kandemirli, M Kandemirli, V Kovalishyn
Materials & design 28 (5), 1737-1741, 2007
The structure-inhibitory activity relationships study in a series of cyclooxygenase-2 inhibitors: a combined electronic-topological and neural networks approach
A Dimoglo, V Kovalishyn, N Shvets, V Ahsen
Mini reviews in medicinal chemistry 5 (10), 879-892, 2005
Human acetylcholinesterase inhibitors: electronic-topological and neural network approaches to the structure-activity relationships study
F Kandemirli, M Saraçoglu, V Kovalishyn
Mini Reviews in Medicinal Chemistry 5 (5), 479-487, 2005
Application of artificial neural networks for the prediction of sulfur polycyclic aromatic compounds retention indices
H Can, A Dimoglo, V Kovalishyn
Journal of Molecular Structure: THEOCHEM 723 (1-3), 183-188, 2005
Volume learning algorithm significantly improved PLS model for predicting the estrogenic activity of xenoestrogens
VV Kovalishyn, V Kholodovych, IV Tetko, WJ Welsh
Journal of Molecular Graphics and Modelling 26 (2), 591-594, 2007
Design and synthesis of new potent inhibitors of farnesyl pyrophosphate synthase
V Prokopenko, V Kovalishyn, M Shevchuk, I Kopernyk, L Metelytsia, ...
Current drug discovery technologies 11 (2), 133-144, 2014
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