Literature DB >> 28302053

A fast and efficient python library for interfacing with the Biological Magnetic Resonance Data Bank.

Andrey Smelter1,2, Morgan Astra3, Hunter N B Moseley4,5,6,7.   

Abstract

BACKGROUND: The Biological Magnetic Resonance Data Bank (BMRB) is a public repository of Nuclear Magnetic Resonance (NMR) spectroscopic data of biological macromolecules. It is an important resource for many researchers using NMR to study structural, biophysical, and biochemical properties of biological macromolecules. It is primarily maintained and accessed in a flat file ASCII format known as NMR-STAR. While the format is human readable, the size of most BMRB entries makes computer readability and explicit representation a practical requirement for almost any rigorous systematic analysis.
RESULTS: To aid in the use of this public resource, we have developed a package called nmrstarlib in the popular open-source programming language Python. The nmrstarlib's implementation is very efficient, both in design and execution. The library has facilities for reading and writing both NMR-STAR version 2.1 and 3.1 formatted files, parsing them into usable Python dictionary- and list-based data structures, making access and manipulation of the experimental data very natural within Python programs (i.e. "saveframe" and "loop" records represented as individual Python dictionary data structures). Another major advantage of this design is that data stored in original NMR-STAR can be easily converted into its equivalent JavaScript Object Notation (JSON) format, a lightweight data interchange format, facilitating data access and manipulation using Python and any other programming language that implements a JSON parser/generator (i.e., all popular programming languages). We have also developed tools to visualize assigned chemical shift values and to convert between NMR-STAR and JSONized NMR-STAR formatted files. Full API Reference Documentation, User Guide and Tutorial with code examples are also available. We have tested this new library on all current BMRB entries: 100% of all entries are parsed without any errors for both NMR-STAR version 2.1 and version 3.1 formatted files. We also compared our software to three currently available Python libraries for parsing NMR-STAR formatted files: PyStarLib, NMRPyStar, and PyNMRSTAR.
CONCLUSIONS: The nmrstarlib package is a simple, fast, and efficient library for accessing data from the BMRB. The library provides an intuitive dictionary-based interface with which Python programs can read, edit, and write NMR-STAR formatted files and their equivalent JSONized NMR-STAR files. The nmrstarlib package can be used as a library for accessing and manipulating data stored in NMR-STAR files and as a command-line tool to convert from NMR-STAR file format into its equivalent JSON file format and vice versa, and to visualize chemical shift values. Furthermore, the nmrstarlib implementation provides a guide for effectively JSONizing other older scientific formats, improving the FAIRness of data in these formats.

Entities:  

Keywords:  Biological Magnetic Resonance Bank; JSON; NMR-STAR; Nuclear magnetic resonance; Python; nmrstarlib

Mesh:

Year:  2017        PMID: 28302053      PMCID: PMC5356280          DOI: 10.1186/s12859-017-1580-5

Source DB:  PubMed          Journal:  BMC Bioinformatics        ISSN: 1471-2105            Impact factor:   3.169


  3 in total

1.  The worldwide Protein Data Bank (wwPDB): ensuring a single, uniform archive of PDB data.

Authors:  Helen Berman; Kim Henrick; Haruki Nakamura; John L Markley
Journal:  Nucleic Acids Res       Date:  2006-11-16       Impact factor: 16.971

2.  BioMagResBank.

Authors:  Eldon L Ulrich; Hideo Akutsu; Jurgen F Doreleijers; Yoko Harano; Yannis E Ioannidis; Jundong Lin; Miron Livny; Steve Mading; Dimitri Maziuk; Zachary Miller; Eiichi Nakatani; Christopher F Schulte; David E Tolmie; R Kent Wenger; Hongyang Yao; John L Markley
Journal:  Nucleic Acids Res       Date:  2007-11-04       Impact factor: 16.971

3.  The FAIR Guiding Principles for scientific data management and stewardship.

Authors:  Mark D Wilkinson; Michel Dumontier; I Jsbrand Jan Aalbersberg; Gabrielle Appleton; Myles Axton; Arie Baak; Niklas Blomberg; Jan-Willem Boiten; Luiz Bonino da Silva Santos; Philip E Bourne; Jildau Bouwman; Anthony J Brookes; Tim Clark; Mercè Crosas; Ingrid Dillo; Olivier Dumon; Scott Edmunds; Chris T Evelo; Richard Finkers; Alejandra Gonzalez-Beltran; Alasdair J G Gray; Paul Groth; Carole Goble; Jeffrey S Grethe; Jaap Heringa; Peter A C 't Hoen; Rob Hooft; Tobias Kuhn; Ruben Kok; Joost Kok; Scott J Lusher; Maryann E Martone; Albert Mons; Abel L Packer; Bengt Persson; Philippe Rocca-Serra; Marco Roos; Rene van Schaik; Susanna-Assunta Sansone; Erik Schultes; Thierry Sengstag; Ted Slater; George Strawn; Morris A Swertz; Mark Thompson; Johan van der Lei; Erik van Mulligen; Jan Velterop; Andra Waagmeester; Peter Wittenburg; Katherine Wolstencroft; Jun Zhao; Barend Mons
Journal:  Sci Data       Date:  2016-03-15       Impact factor: 6.444

  3 in total
  4 in total

1.  Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping.

Authors:  Andrey Smelter; Eric C Rouchka; Hunter N B Moseley
Journal:  J Biomol NMR       Date:  2017-08-16       Impact factor: 2.835

2.  An effective biomedical data migration tool from resource description framework to JSON.

Authors:  Jian Liu; Mo Yang; Lei Zhang; Weijun Zhou
Journal:  Database (Oxford)       Date:  2019-01-01       Impact factor: 3.451

Review 3.  The exposome paradigm to predict environmental health in terms of systemic homeostasis and resource balance based on NMR data science.

Authors:  Jun Kikuchi; Shunji Yamada
Journal:  RSC Adv       Date:  2021-09-13       Impact factor: 4.036

4.  BaMORC: A Software Package for Accurate and Robust 13C Reference Correction of Protein NMR Spectra.

Authors:  Xi Chen; Andrey Smelter; Hunter N B Moseley
Journal:  Nat Prod Commun       Date:  2019-05-28       Impact factor: 1.496

  4 in total

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