Fuzz Testing Molecular Representation Using Deep Variational Anomaly Generation.

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Bibliographic Details
Title: Fuzz Testing Molecular Representation Using Deep Variational Anomaly Generation.
Authors: Nogueira VHR; São Carlos Institute of Physics, University of São Paulo, São Paulo 13563-120, Brazil.; Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstrasse 3, Gatersleben, Seeland D-06466, Germany., Sharma R; Department of Pharmaceutical Chemistry, Department of Bioengineering & Therapeutic Sciences, Institute for Neurodegenerative Diseases, Kavli Institute for Fundamental Neuroscience, Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California 94158, United States., Guido RVC; São Carlos Institute of Physics, University of São Paulo, São Paulo 13563-120, Brazil., Keiser MJ; Department of Pharmaceutical Chemistry, Department of Bioengineering & Therapeutic Sciences, Institute for Neurodegenerative Diseases, Kavli Institute for Fundamental Neuroscience, Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California 94158, United States.
Source: Journal of chemical information and modeling [J Chem Inf Model] 2025 Feb 24; Vol. 65 (4), pp. 1911-1927. Date of Electronic Publication: 2025 Feb 05.
Publication Type: Journal Article
Journal Info: Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1549-960X
DOI:10.1021/acs.jcim.4c01876