Computational analysis of metabolic networks with Apostolos Chalkis

Apostolos Chalkis is a PhD student from the University of Athens. As part of his recent Tweag fellowship, he developed dingo, a Python package to analyze steady states of metabolic networks—networks of biochemical reactions that take place in any living cell—using geometric random walks and other methods from computational geometry. In this episode, Apostolos explains what metabolic networks are and how he applies Markov Chains Monte Carlo methods to understand them. Also check out Apostolos's blog post, where he shows a particular application of his package to the search for potential COVID-19 treatments.Special Guest: Apostolos Chalkis.Links:Searching for COVID-19 treatments using metabolic networkshttps://github.com/GeomScale/dingohttps://github.com/GeomScale/volume_approximationhttps://geomscale.github.io/