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Predict the effect of mutations on protein stability and protein-protein interaction affinity.

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ELASPIC

conda pipeline status coverage report

Introduction

Welcome to the ELASPIC code repository!

Complete documentation is available on ReadTheDocs.

For a small number of mutations, you can try running ELASPIC using our webserver.

Development

  • Use the issue tracker to discuss changes.

References

Strokach, A., Kim, P.M. (2016) Predicting the Effect of Mutations on a Genome-Wide Scale. MSc Thesis, University of Toronto.

Witvliet, D., Strokach, A., Giraldo-Forero, A.F., Teyra, J., Colak, R., and Kim, P.M. (2016) ELASPIC web-server: proteome-wide structure based prediction of mutation effects on protein stability and binding affinity. Bioinformatics 32(10): 1589-1591. doi: 10.1093/bioinformatics/btw031.

Berliner N, Teyra J, Çolak R, Garcia Lopez S, Kim PM (2014) Combining Structural Modeling with Ensemble Machine Learning to Accurately Predict Protein Fold Stability and Binding Affinity Effects upon Mutation. PLoS ONE 9(9): e107353. doi: 10.1371/journal.pone.0107353.

License

MIT

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Predict the effect of mutations on protein stability and protein-protein interaction affinity.

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  • Python 96.7%
  • Shell 2.3%
  • Jupyter Notebook 1.0%