Understanding the host-pathogen evolutionary balance through Gaussian process modeling of SARS-CoV-2
Description
We have developed a machine learning (ML) approach using Gaussian process (GP)-based spatial covariance (SCV) to track the impact of spatial-temporal mutational events driving host-pathogen balance in biology. We show how SCV can be applied to
