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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...

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Detalles Bibliográficos
Autores principales: Yan, Xiliang, Sedykh, Alexander, Wang, Wenyi, Yan, Bing, Zhu, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
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.
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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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