纳米结构
纳米材料
纳米技术
计算机科学
材料科学
作者
Tong Wang,Daniel P. Russo,Philip Demokritou,Xuelian Jia,Heng Huang,Xinyu Yang,Hao Zhu
出处
期刊:Nano Letters
[American Chemical Society]
日期:2024-08-09
卷期号:24 (33): 10228-10236
被引量:13
标识
DOI:10.1021/acs.nanolett.4c02568
摘要
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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