The (Re)-Evolution of Quantitative Structure–Activity Relationship (QSAR) Studies Propelled by the Surge of Machine Learning Methods


Journal article


Thereza A. Soares, Ariane Nunes-Alves, Angelica Mazzolari, Fiorella Ruggiu, Guo-Wei Wei, Kenneth Merz
Journal of Chemical Information and Modeling, vol. 62, 2022, pp. 5317-5320

Cite

Cite

APA   Click to copy
Soares, T. A., Nunes-Alves, A., Mazzolari, A., Ruggiu, F., Wei, G.-W., & Merz, K. (2022). The (Re)-Evolution of Quantitative Structure–Activity Relationship (QSAR) Studies Propelled by the Surge of Machine Learning Methods. Journal of Chemical Information and Modeling, 62, 5317–5320.


Chicago/Turabian   Click to copy
Soares, Thereza A., Ariane Nunes-Alves, Angelica Mazzolari, Fiorella Ruggiu, Guo-Wei Wei, and Kenneth Merz. “The (Re)-Evolution of Quantitative Structure–Activity Relationship (QSAR) Studies Propelled by the Surge of Machine Learning Methods.” Journal of Chemical Information and Modeling 62 (2022): 5317–5320.


MLA   Click to copy
Soares, Thereza A., et al. “The (Re)-Evolution of Quantitative Structure–Activity Relationship (QSAR) Studies Propelled by the Surge of Machine Learning Methods.” Journal of Chemical Information and Modeling, vol. 62, 2022, pp. 5317–20.


BibTeX   Click to copy

@article{soares2022a,
  title = {The (Re)-Evolution of Quantitative Structure–Activity Relationship (QSAR) Studies Propelled by the Surge of Machine Learning Methods},
  year = {2022},
  journal = {Journal of Chemical Information and Modeling},
  pages = {5317-5320},
  volume = {62},
  author = {Soares, Thereza A. and Nunes-Alves, Ariane and Mazzolari, Angelica and Ruggiu, Fiorella and Wei, Guo-Wei and Merz, Kenneth}
}


Share
Tools
Translate to