QSAR Modeling Based on Conformation Ensembles Using a Multi-Instance Learning Approach-Reference-Cited by-同舟云学术

QSAR Modeling Based on Conformation Ensembles Using a Multi-Instance Learning Approach

Published:2021-09-23 Issue:10 Volume:61 Page:4913-4923
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Zankov Dmitry V.¹²^ORCID,Matveieva Mariia³,Nikonenko Aleksandra V.³,Nugmanov Ramil I.¹^ORCID,Baskin Igor I.⁴^ORCID,Varnek Alexandre²^ORCID,Polishchuk Pavel³^ORCID,Madzhidov Timur I.¹^ORCID

Affiliation:

1. Laboratory of Chemoinformatics and Molecular Modeling, A. M. Butlerov Institute of Chemistry, Kazan Federal University, Kremlyovskaya 29, 420111 Kazan, Russia

2. Laboratory of Chemoinformatics, Institute Le Bel, University of Strasbourg, B. Pascal 4, 67081 Strasbourg, France

3. Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University and University Hospital in Olomouc, Hnevotinska 5, 77900 Olomouc, Czech Republic

4. Department of Materials Science and Engineering, Technion—Israel Institute of Technology, 3200003 Haifa, Israel

Funder

Russian Science Foundation

Ministerstvo ??kolstv??, Ml??de??e a T??lov??chovy

Ministry of Science and Higher Education of the Russian Federation

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.1c00692

Reference43 articles.