ValTrendsDB: bringing Protein Data Bank validation information closer to the user

Author:

Horský Vladimír12,Bendová Veronika123,Toušek Dominik12,Koča Jaroslav12,Svobodová Radka12

Affiliation:

1. National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Brno, Czech Republic

2. CEITEC – Central European Institute of Technology, Masaryk University, Brno, Czech Republic

3. Institute of Mathematics and Statistics, Faculty of Science, Masaryk University, Brno, Czech Republic

Abstract

Abstract 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.

Funder

Ministry of Education, Youth and Sports of the Czech Republic

CEITEC 2020

European Union’s Horizon 2020

European Regional Development Fund

Grant Agency of Masaryk University

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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