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ValTrendsDB: bringing Protein Data Bank validation information closer to the user
SUMMARY: Structures in PDB tend to contain errors. This is a very serious issue for authors that rely on such potentially problematic data. The community of structural biologists develops validation methods as countermeasures, which are also included in the PDB deposition system. But how are these v...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954638/ https://www.ncbi.nlm.nih.gov/pubmed/31263870 http://dx.doi.org/10.1093/bioinformatics/btz532 |
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author | Horský, Vladimír Bendová, Veronika Toušek, Dominik Koča, Jaroslav Svobodová, Radka |
author_facet | Horský, Vladimír Bendová, Veronika Toušek, Dominik Koča, Jaroslav Svobodová, Radka |
author_sort | Horský, Vladimír |
collection | PubMed |
description | SUMMARY: Structures in PDB tend to contain errors. This is a very serious issue for authors that rely on such potentially problematic data. The community of structural biologists develops validation methods as countermeasures, which are also included in the PDB deposition system. But how are these validation efforts influencing the structure quality of subsequently published data? Which quality aspects are improving, and which remain problematic? We developed ValTrendsDB, a database that provides the results of an extensive exploratory analysis of relationships between quality criteria, size and metadata of biomacromolecules. Key input data are sourced from PDB. The discovered trends are presented via precomputed information-rich plots. ValTrendsDB also supports the visualization of a set of user-defined structures on top of general quality trends. Therefore, ValTrendsDB enables users to see the quality of structures published by selected author, laboratory or journal, discover quality outliers, etc. ValTrendsDB is updated weekly. AVAILABILITY AND IMPLEMENTATION: Freely accessible at http://ncbr.muni.cz/ValTrendsDB. The web interface was implemented in JavaScript. The database was implemented in C++. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6954638 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-69546382020-01-16 ValTrendsDB: bringing Protein Data Bank validation information closer to the user Horský, Vladimír Bendová, Veronika Toušek, Dominik Koča, Jaroslav Svobodová, Radka Bioinformatics Applications Notes SUMMARY: Structures in PDB tend to contain errors. This is a very serious issue for authors that rely on such potentially problematic data. The community of structural biologists develops validation methods as countermeasures, which are also included in the PDB deposition system. But how are these validation efforts influencing the structure quality of subsequently published data? Which quality aspects are improving, and which remain problematic? We developed ValTrendsDB, a database that provides the results of an extensive exploratory analysis of relationships between quality criteria, size and metadata of biomacromolecules. Key input data are sourced from PDB. The discovered trends are presented via precomputed information-rich plots. ValTrendsDB also supports the visualization of a set of user-defined structures on top of general quality trends. Therefore, ValTrendsDB enables users to see the quality of structures published by selected author, laboratory or journal, discover quality outliers, etc. ValTrendsDB is updated weekly. AVAILABILITY AND IMPLEMENTATION: Freely accessible at http://ncbr.muni.cz/ValTrendsDB. The web interface was implemented in JavaScript. The database was implemented in C++. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-12-15 2019-07-02 /pmc/articles/PMC6954638/ /pubmed/31263870 http://dx.doi.org/10.1093/bioinformatics/btz532 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Horský, Vladimír Bendová, Veronika Toušek, Dominik Koča, Jaroslav Svobodová, Radka ValTrendsDB: bringing Protein Data Bank validation information closer to the user |
title | ValTrendsDB: bringing Protein Data Bank validation information closer to the user |
title_full | ValTrendsDB: bringing Protein Data Bank validation information closer to the user |
title_fullStr | ValTrendsDB: bringing Protein Data Bank validation information closer to the user |
title_full_unstemmed | ValTrendsDB: bringing Protein Data Bank validation information closer to the user |
title_short | ValTrendsDB: bringing Protein Data Bank validation information closer to the user |
title_sort | valtrendsdb: bringing protein data bank validation information closer to the user |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954638/ https://www.ncbi.nlm.nih.gov/pubmed/31263870 http://dx.doi.org/10.1093/bioinformatics/btz532 |
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