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iSEE: Interface structure, evolution, and energy‐based machine learning predictor of binding affinity changes upon mutations
Quantitative evaluation of binding affinity changes upon mutations is crucial for protein engineering and drug design. Machine learning‐based methods are gaining increasing momentum in this field. Due to the limited number of experimental data, using a small number of sensitive predictive features i...
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| Publicado no: | Proteins |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
John Wiley & Sons, Inc.
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6587874/ https://ncbi.nlm.nih.gov/pubmed/30417935 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/prot.25630 |
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