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An Online Nanoinformatics Platform Empowering Computational Modeling of Nanomaterials by Nanostructure Annotations and Machine Learning Toolkits.
Wang, Tong; Russo, Daniel P; Demokritou, Philip; Jia, Xuelian; Huang, Heng; Yang, Xinyu; Zhu, Hao.
Afiliação
  • Wang T; Tulane Center for Biomedical Informatics and Genomics, Tulane University, New Orleans, Louisiana 70112, United States.
  • Russo DP; Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, Louisiana 70112, United States.
  • Demokritou P; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States.
  • Jia X; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States.
  • Huang H; Center for Nanotechnology and Nanotoxicology, Department of Environmental Health, T.H. Chan School of Public Health, Harvard University, 655 Huntington Ave, Boston, Massachusetts 02115, United States.
  • Yang X; Nanoscience and Advanced Materials Center, Environmental Occupational Health Sciences Institute, School of Public Health, Rutgers University, Piscataway, New Jersey 08854, United States.
  • Zhu H; Tulane Center for Biomedical Informatics and Genomics, Tulane University, New Orleans, Louisiana 70112, United States.
Nano Lett ; 24(33): 10228-10236, 2024 Aug 21.
Article em En | MEDLINE | ID: mdl-39120132
ABSTRACT
Modern nanotechnology has generated numerous datasets from in vitro and in vivo studies on nanomaterials, with some available on nanoinformatics portals. However, these existing databases lack the digital data and tools suitable for machine learning studies. Here, we report a nanoinformatics platform that accurately annotates nanostructures into machine-readable data files and provides modeling toolkits. This platform, accessible to the public at https//vinas-toolbox.com/, has annotated nanostructures of 14 material types. The associated nanodescriptor data and assay test results are appropriate for modeling purposes. The modeling toolkits enable data standardization, data visualization, and machine learning model development to predict properties and bioactivities of new nanomaterials. Moreover, a library of virtual nanostructures with their predicted properties and bioactivities is available, directing the synthesis of new nanomaterials. This platform provides a data-driven computational modeling platform for the nanoscience community, significantly aiding in the development of safe and effective nanomaterials.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Nanoestruturas / Aprendizado de Máquina Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Nanoestruturas / Aprendizado de Máquina Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article