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.

Table of Contents

• Introduction
  • Database pipeline
  • Local pipeline
• Installation Guide
  • Installing Python and ELASPIC
  • Downloading external datasets
  • Updating the configuration file
  • Importing precalculated data
• Command Line Interface
  • elaspic run
  • elaspic train
  • elaspic database
• Benchmarks
  • Existing approaches
• Statistics
• Database
  • Database schema
  • Database tables
• Modules
  • elaspic package
  • Indices and tables