Magnetic Resonance
Magnetic Resonance
MR
Articles | Volume 2, issue 1
Articles | Volume 2, issue 1
https://doi.org/10.5194/mr-2-251-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/mr-2-251-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 2, issue 1
Research article
 | 
05 May 2021
Research article |  | 05 May 2021

Bootstrap aggregation for model selection in the model-free formalism

Timothy Crawley and Arthur G. Palmer III

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Cited articles

Abergel, D., Volpato, A., Coutant, E. P., and Polimeno, A.: On the reliability of NMR relaxation data analyses: A Markov Chain Monte Carlo approach, J. Magn. Reson., 246, 94–103, 2014. a
Abyzov, A., Salvi, N., Schneider, R., Maurin, D., Ruigrok, R. W., Jensen, M. R., and Blackledge, M.: Identification of dynamic modes in an intrinsically disordered protein using temperature-dependent NMR relaxation, J. Am. Chem. Soc., 138, 6240–6251, 2016. a
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NMR relaxation rate constants are powerful probes of the functional dynamics of biological macromolecules, such as proteins and nucleic acids. However, variations in choice of models used to analyze relaxation data obscure variations due to critical biological or chemical effects. Bootstrap aggregation, a recently developed statistical method, circumvents the model selection problem and enables more consistent and insightful interpretation of NMR relaxation data.
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