ELASPIC is a metapredictor which combines sequential features (most important being PROVEAN) with structural features (most important being FoldX). It uses the Stochastic Gradient Boosting algorithm for machine learning.

• ELASPIC is designed to work on the genome-wide scale by using homology models.
• It predicts mutation $$\Delta \Delta G$$ for protein folding and protein interactions.
• It is open source and can be installed and ran locally.