K
Káthia Maria Honório
Researcher at University of São Paulo
Publications - 139
Citations - 2429
Káthia Maria Honório is an academic researcher from University of São Paulo. The author has contributed to research in topics: Quantitative structure–activity relationship & Docking (molecular). The author has an hindex of 22, co-authored 130 publications receiving 1908 citations. Previous affiliations of Káthia Maria Honório include Universidade Federal do ABC & Federal University of Paraná.
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Journal ArticleDOI
Use of machine learning approaches for novel drug discovery.
Angélica Nakagawa Lima,Eric Allison Philot,Gustavo Henrique Goulart Trossini,Luis Paulo Barbour Scott,Vinícius Gonçalves Maltarollo,Káthia Maria Honório +5 more
TL;DR: An important application of ML techniques is related to the calculation of scoring functions used in docking and virtual screening assays from a consensus, combining traditional and ML techniques in order to improve the prediction of binding sites and docking solutions.
Journal ArticleDOI
Machine learning techniques and drug design.
Jadson Castro Gertrudes,Vinícius Gonçalves Maltarollo,Ricardo Silva,Patrícia R. Oliveira,Káthia Maria Honório,A. B. F. da Silva +5 more
TL;DR: A critical point of view on the main MLT shows their potential ability as a valuable tool in drug design and shows that MLT have significant advantages.
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Applying machine learning techniques for ADME-Tox prediction: a review.
Vinícius Gonçalves Maltarollo,Jadson Castro Gertrudes,Patrícia R. Oliveira,Káthia Maria Honório +3 more
TL;DR: An application of this procedure would be the prediction of ADME-Tox properties from studies of quantitative structure–activity relationships or the discovery of new compounds from a virtual screening using filters based on results obtained from ML techniques.
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Understanding the Molecular Aspects of Tetrahydrocannabinol and Cannabidiol as Antioxidants
Rosivaldo S. Borges,João M. Batista,Rommel B. Viana,Ana Cristina Baetas,Ednilsom Orestes,Marcieni Ataíde de Andrade,Káthia Maria Honório,Albérico B. F. da Silva +7 more
TL;DR: The properties calculated here predict that THC has a sightly higher antioxidant potential than CBD.
Journal ArticleDOI
Transfer and Multi-task Learning in QSAR Modeling: Advances and Challenges.
Rodolfo da Silva Simoes,Vinícius Gonçalves Maltarollo,Patrícia R. Oliveira,Káthia Maria Honório,Káthia Maria Honório +4 more
TL;DR: This review will present the main features of transfer and multi-task learning studies, as well as some applications and its potentiality in drug design projects.