Skip to content

RPIBioinformatics/ComparativeRecall

main
Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
November 17, 2022 16:25

Comparative Recall (CR)

The Comparative Recall (CR) metric assesses a pair of protein structure models against experimental NOESY and chemical shift data, and identifies NOESY peaks that, considering any possible NOESY peak assignment consistent with the chemical shift data, can be explained by the model. In this analysis, “recall violations” for a given model are the experimental NOESY data that are inconsistent with the model, as previously described (Huang et al., 2005; Huang et al., 2012). Comparing a pair of structures (e.g. an AF model and an experimental NMR model), the CR analysis allows identification of the experimental NOESY data supporting both models, and the specific data supporting only one or the other model.

Huang, Y.J., Powers, R., and Montelione, G.T. (2005). Protein NMR recall, precision, and F-measure scores (RPF scores): structure quality assessment measures based on information retrieval statistics. Journal of the American Chemical Society 127(6), 1665-1674. doi:https://doi.org/10.1021/ja047109h.

Huang, Y.J., Rosato, A., Singh, G., and Montelione, G.T. (2012). RPF: a quality assessment tool for protein NMR structures. Nucleic Acids Research 40(Web Server issue), W542-546. doi:https://doi.org/10.1093/nar/gks373.

How to run CR

  1. Run RPF for each model: https://montelionelab.chem.rpi.edu/rpf/
  2. Download the RPF results (zip file, please don't rename the zip file)
  3. Run Comparative Recall Analysis on Colab: https://colab.research.google.com/drive/1ALfz5VaFEupI7ggl0oTm3qbJX4R5JZsg?usp=sharing

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published