If you use results generated by the ELASPIC webserver, please cite the paper:

Daniel K. Witvliet, Alexey Strokach, Andrés Felipe Giraldo-Forero, Joan Teyra, Recep Colak, Philip M. Kim (2016) ELASPIC web-server: proteome-wide structure based prediction of mutation effects on protein stability and binding affinity. Bioinformatics 32 (10): 1589-1591.

For more information about the ELASPIC algorithm, please see:

Niklas Berliner, Joan Teyra, Recep Çolak, Sebastian Garcia Lopez, and Philip M. Kim (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.

For more information about the ELASPIC2 algorithm, please see:

Alexey Strokach, Tian Yu Lu, Philip M. Kim (2020) ELASPIC2 (EL2): Combining contextualized language models and graph neural networks to predict effects of mutations.