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NMRtist: an online platform for automated biomolecular NMR spectra analysis
SUMMARY: We present NMRtist, an online platform that combines deep learning, large-scale optimization and cloud computing to automate protein NMR spectra analysis. Our website provides virtual storage for NMR spectra deposition together with a set of applications designed for automated peak picking,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913044/ https://www.ncbi.nlm.nih.gov/pubmed/36723167 http://dx.doi.org/10.1093/bioinformatics/btad066 |
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author | Klukowski, Piotr Riek, Roland Güntert, Peter |
author_facet | Klukowski, Piotr Riek, Roland Güntert, Peter |
author_sort | Klukowski, Piotr |
collection | PubMed |
description | SUMMARY: We present NMRtist, an online platform that combines deep learning, large-scale optimization and cloud computing to automate protein NMR spectra analysis. Our website provides virtual storage for NMR spectra deposition together with a set of applications designed for automated peak picking, chemical shift assignment and protein structure determination. The system can be used by non-experts and allows protein assignments and structures to be determined within hours after the measurements, strictly without any human intervention. AVAILABILITY AND IMPLEMENTATION: NMRtist is freely available to non-commercial users at https://nmrtist.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9913044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-99130442023-02-13 NMRtist: an online platform for automated biomolecular NMR spectra analysis Klukowski, Piotr Riek, Roland Güntert, Peter Bioinformatics Applications Note SUMMARY: We present NMRtist, an online platform that combines deep learning, large-scale optimization and cloud computing to automate protein NMR spectra analysis. Our website provides virtual storage for NMR spectra deposition together with a set of applications designed for automated peak picking, chemical shift assignment and protein structure determination. The system can be used by non-experts and allows protein assignments and structures to be determined within hours after the measurements, strictly without any human intervention. AVAILABILITY AND IMPLEMENTATION: NMRtist is freely available to non-commercial users at https://nmrtist.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2023-02-01 /pmc/articles/PMC9913044/ /pubmed/36723167 http://dx.doi.org/10.1093/bioinformatics/btad066 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://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 Note Klukowski, Piotr Riek, Roland Güntert, Peter NMRtist: an online platform for automated biomolecular NMR spectra analysis |
title | NMRtist: an online platform for automated biomolecular NMR spectra analysis |
title_full | NMRtist: an online platform for automated biomolecular NMR spectra analysis |
title_fullStr | NMRtist: an online platform for automated biomolecular NMR spectra analysis |
title_full_unstemmed | NMRtist: an online platform for automated biomolecular NMR spectra analysis |
title_short | NMRtist: an online platform for automated biomolecular NMR spectra analysis |
title_sort | nmrtist: an online platform for automated biomolecular nmr spectra analysis |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9913044/ https://www.ncbi.nlm.nih.gov/pubmed/36723167 http://dx.doi.org/10.1093/bioinformatics/btad066 |
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