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Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations
Modern nanotechnology research has generated numerous experimental data for various nanomaterials. However, the few nanomaterial databases available are not suitable for modeling studies due to the way they are curated. Here, we report the construction of a large nanomaterial database containing ann...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239871/ https://www.ncbi.nlm.nih.gov/pubmed/32433469 http://dx.doi.org/10.1038/s41467-020-16413-3 |
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author | Yan, Xiliang Sedykh, Alexander Wang, Wenyi Yan, Bing Zhu, Hao |
author_facet | Yan, Xiliang Sedykh, Alexander Wang, Wenyi Yan, Bing Zhu, Hao |
author_sort | Yan, Xiliang |
collection | PubMed |
description | Modern nanotechnology research has generated numerous experimental data for various nanomaterials. However, the few nanomaterial databases available are not suitable for modeling studies due to the way they are curated. Here, we report the construction of a large nanomaterial database containing annotated nanostructures suited for modeling research. The database, which is publicly available through http://www.pubvinas.com/, contains 705 unique nanomaterials covering 11 material types. Each nanomaterial has up to six physicochemical properties and/or bioactivities, resulting in more than ten endpoints in the database. All the nanostructures are annotated and transformed into protein data bank files, which are downloadable by researchers worldwide. Furthermore, the nanostructure annotation procedure generates 2142 nanodescriptors for all nanomaterials for machine learning purposes, which are also available through the portal. This database provides a public resource for data-driven nanoinformatics modeling research aimed at rational nanomaterial design and other areas of modern computational nanotechnology. |
format | Online Article Text |
id | pubmed-7239871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72398712020-05-29 Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations Yan, Xiliang Sedykh, Alexander Wang, Wenyi Yan, Bing Zhu, Hao Nat Commun Article Modern nanotechnology research has generated numerous experimental data for various nanomaterials. However, the few nanomaterial databases available are not suitable for modeling studies due to the way they are curated. Here, we report the construction of a large nanomaterial database containing annotated nanostructures suited for modeling research. The database, which is publicly available through http://www.pubvinas.com/, contains 705 unique nanomaterials covering 11 material types. Each nanomaterial has up to six physicochemical properties and/or bioactivities, resulting in more than ten endpoints in the database. All the nanostructures are annotated and transformed into protein data bank files, which are downloadable by researchers worldwide. Furthermore, the nanostructure annotation procedure generates 2142 nanodescriptors for all nanomaterials for machine learning purposes, which are also available through the portal. This database provides a public resource for data-driven nanoinformatics modeling research aimed at rational nanomaterial design and other areas of modern computational nanotechnology. Nature Publishing Group UK 2020-05-20 /pmc/articles/PMC7239871/ /pubmed/32433469 http://dx.doi.org/10.1038/s41467-020-16413-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Yan, Xiliang Sedykh, Alexander Wang, Wenyi Yan, Bing Zhu, Hao Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations |
title | Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations |
title_full | Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations |
title_fullStr | Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations |
title_full_unstemmed | Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations |
title_short | Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations |
title_sort | construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239871/ https://www.ncbi.nlm.nih.gov/pubmed/32433469 http://dx.doi.org/10.1038/s41467-020-16413-3 |
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