| URL: | http://www.pubvinas.com |
| Full name: | Public Virtual Nanostructure Simulation Database |
| Description: | PubVINAS is a friendly online nanomodeling tool based on big data curation of nano-biological activities and nanostructure annotations. A large number of experimental data were collected and curated from our lab and publications, including various physic-chemical properties and biological activities. Based on the experimental data, the protein data bank (PDB) files were generated from nanostructure annotations. Then, the PDB files can be used for nanostructure analysis, visualization and descriptor generation for predictive modeling. |
| Year founded: | 2020 |
| Last update: | |
| Version: | |
| Accessibility: |
Accessible
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| Country/Region: | United States |
| Data type: | |
| Data object: |
NA
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| Database category: | |
| Major species: |
NA
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| Keywords: |
| University/Institution: | Rutgers Center for Computational and Integrative Biology |
| Address: | Camden, NJ 08102 USA |
| City: | Camden |
| Province/State: | |
| Country/Region: | United States |
| Contact name (PI/Team): | Hao Zhu |
| Contact email (PI/Helpdesk): | hao.zhu99@rutgers.edu |
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Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations. [PMID: 32433469]
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. |