The (Re)-Evolution of Quantitative Structure-Activity Relationship (QSAR) Studies Propelled by the Surge of Machine Learning Methods
J Chem Inf Model
.
2022 Nov 28;62(22):5317-5320.
doi: 10.1021/acs.jcim.2c01422.
Authors
Thereza A Soares
1
2
,
Ariane Nunes-Alves
3
,
Angelica Mazzolari
4
,
Fiorella Ruggiu
5
,
Guo-Wei Wei
6
,
Kenneth Merz
7
Affiliations
1
Department of Chemistry, University of São Paulo, Ribeirão Preto 055508-090, Brazil.
2
Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, Oslo 0315, Norway.
3
Institute of Chemistry, Technische Universität Berlin, Berlin 10623, Germany.
4
Department of Pharmaceutical Sciences, University of Milan, Via Mangiagalli 25, Milan I-20133, Italy.
5
Insitro Inc., 279 East Grand Avenue, South San Francisco 94080, California, United States.
6
Department of Mathematics, Michigan State University, East Lansing 48824, Michigan, United States.
7
Department of Chemistry, Michigan State University, East Lansing 48824, Michigan, United States.
PMID:
36437763
DOI:
10.1021/acs.jcim.2c01422
No abstract available
Publication types
Editorial
Research Support, Non-U.S. Gov't
MeSH terms
Machine Learning*
Models, Molecular
Quantitative Structure-Activity Relationship*