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The potential distributions derived from the SDM ensemble are given in figure 3.
Ramachandran statistics per re-refined single structure and ensemble are given in Figure 6 source data 2. (D ) Correlation of Ramachandran statistics with R free values obtained from ensemble refinement.
Details on the ligand-bound conformational ensemble as well as a detailed comparison with the free state conformational ensemble are given in the Supporting Information (Supporting Figures 8a,b and 9).
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Adaptations and new procedures developed for ensemble refinement are given in section 'Ensemble refinement methods'.
Details of the single-structure re-refinements used for comparison with the ensemble models are given in section 'Single structure re-refinements'.
Validation of the global disorder TLS model, the dependency of ensemble refinement on the starting structure and additional ensemble refinement calculations are given in 'Additional ensemble refinement calculations'.
The pseudo-code description and graphical representation of our proposed ensemble learning algorithms are given in Pseudocode 2 and Figure 3, respectively.
Examples for modeling ensembles of ODE models are given in [ 19, 20].
The probability of a given energy level being populated in the canonical ensemble is given by its Boltzmann factor P(E_{n}) = \frac{e^{-n\beta h\nu}}{Z}, where β = 1/kBT and the denominator Z is the partition function, here a geometric series Z = \sum_{n=0}^{\infty} e^{-n\beta h\nu} = \frac{1}{1 - e^{-\beta h\nu}}.
Structure and quality statistics are given in Table 2 for the ensemble of 20 lowest energy structures, indicating the high quality of the structure.
For the entire benchmark set, the average displacement per residue in NMR ensembles is 1.68 Å (the values for each protein are given in Supplementary Table S1).
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