ArticleJournal of biomolecular NMR2016
Probabilistic validation of protein NMR chemical shift assignments.
Article in Journal of biomolecular NMR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- POKY software tools encapsulating assignment strategies for solution and solid-state protein NMR data.Journal of structural biology: X · 2022Article
- BioMagResBank (BMRB) as a Resource for Structural Biology.Methods in molecular biology (Clifton, N.J.) · 2020Article
- Solution structure of human myeloid-derived growth factor suggests a conserved function in the endoplasmic reticulum.Nature communications · 2019Article
- NMR-STAR: comprehensive ontology for representing, archiving and exchanging data from nuclear magnetic resonance spectroscopic experiments.Journal of biomolecular NMR · 2019Review
- PINE-SPARKY.2 for automated NMR-based protein structure research.Bioinformatics (Oxford, England) · 2018Article
- NMR assignments of sparsely labeled proteins using a genetic algorithm.Journal of biomolecular NMR · 2017Article
- Integrative NMR for biomolecular research.Journal of biomolecular NMR · 2016Article
- NMRFAM-SDF: a protein structure determination framework.Journal of biomolecular NMR · 2015Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data . ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/.
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Registered trials
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