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ПросмотрНаучные публикации в Scopus по теме "QSAR"

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A novel approach to the analysis of substituent effects: Quantitative description of ionization energies and gas basicity of amines

Cherkasov A.; Jonsson M.; Galkin V. (1999)

In this work, a new topological approach based on simple matrix algebra is introduced to explore substituent effects at the level of atomic additivity in the absence of significant resonance contributions. In the framework ...
Binding constants of substituted benzoic acids with bovine serum albumin

Khaibrakhmanova D.; Nikiforova A.; Sedov I. (2020)

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Experimental data on the affinity of various substances to albumin are essential for the development of empirical models to predict plasma binding of drug candidates. ...
GTM-Based QSAR Models and Their Applicability Domains

Gaspar H.; Baskin I.; Marcou G.; Horvath D.; Varnek A. (2015)

© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. In this paper we demonstrate that Generative Topographic Mapping (GTM), a machine learning method traditionally used for data visualisation, can be efficiently applied to ...
GTM-Based QSAR Models and Their Applicability Domains

Gaspar H.; Baskin I.; Marcou G.; Horvath D.; Varnek A. (2015)

© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. In this paper we demonstrate that Generative Topographic Mapping (GTM), a machine learning method traditionally used for data visualisation, can be efficiently applied to ...
Machine learning modelling of chemical reaction characteristics: yesterday, today, tomorrow

Madzhidov T.I.; Rakhimbekova A.; Afonina V.A.; Gimadiev T.R.; Mukhametgaleev R.N.; Nugmanov R.I.; Baskin I.I.; Varnek A. (2021)

The synthesis of the desired chemical compound is the main task of synthetic organic chemistry. The predictions of reaction conditions and some important quantitative characteristics of chemical reactions as yield and ...
Multi-instance learning for structure-activity modeling for molecular properties

Zankov D.V.; Shevelev M.D.; Nikonenko A.V.; Polishchuk P.G.; Rakhimbekova A.I.; Madzhidov T.I. (2020)

© Springer Nature Switzerland AG 2020. In this paper, the approach of multi-instance learning is used for modeling the biological properties of molecules. We have proposed two approaches for the implementation of multi-instance ...
Prediction-driven matched molecular pairs to interpret QSARs and aid the molecular optimization process

Sushko Y.; Novotarskyi S.; Körner R.; Vogt J.; Abdelaziz A.; Tetko I. (2014)

© 2014 Sushko et al.; licensee Springer. Background: QSAR is an established and powerful method for cheap in silico assessment of physicochemical properties and biological activities of chemical compounds. However, QSAR ...
Public (Q)SAR Services, Integrated Modeling Environments, and Model Repositories on the Web: State of the Art and Perspectives for Future Development

Tetko I.; Maran U.; Tropsha A. (2017)

© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, WeinheimThousands of (Quantitative) Structure-Activity Relationships (Q)SAR models have been described in peer-reviewed publications; however, this way of sharing seldom makes models ...

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ПросмотрНаучные публикации в Scopus по теме "QSAR"

ПросмотрНаучные публикации в Scopus по теме "QSAR"

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