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Apostolos Chalkis

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OwlTail

In this episode, Apostolos Chalkis presents sampling steadystates of metabolic networks as an alternative to the widely used flux balanceanalysis (FBA). We also discuss dingo, aPython package written by Apostolos that employs geometric random walks tosample steady states. You can see dingo in actionhere. Links:  Dingo on GitHub Searching for COVID-19 treatments using metabolic networks Tweag open source fellowships This episode was originally published on the Compositional podcast.  If you enjoyed this episode, please consider supporting the podcast on Patreon!

In this episode, <a href="https://tolischal.github.io/" rel="nofollow" target="_blank">Apostolos Chalkis</a> presents sampling steady states of metabolic networks as an alternative to the widely used flux balance analysis (FBA). We also discuss <a href="https://github.com/GeomScale/dingo" rel="nofollow" target="_blank">dingo</a>, a Python package written by Apostolos that employs geometric random walks to sample steady states. You can see dingo in action <a href="https://www.tweag.io/blog/2021-07-14-metabolic-networks/" rel="nofollow" target="_blank">here</a>. Links: <ul> <li><a href="https://github.com/GeomScale/dingo" rel="nofollow" target="_blank">Dingo on GitHub</a></li> <li><a href="https://tweag.io/blog/2021-07-14-metabolic-networks/" rel="nofollow" target="_blank">Searching for COVID-19 treatments using metabolic networks</a></li> <li><a href="https://www.tweag.io/blog/tags/fellowship/" rel="nofollow" target="_blank">Tweag open source fellowships</a></li> <li>This episode was <a href="https://www.compositional.fm/dingo-metabolic-networks" rel="nofollow" target="_blank">originally published</a> on the <a href="https://www.compositional.fm/" rel="nofollow" target="_blank">Compositional</a> podcast.</li> </ul> If you enjoyed this episode, please consider supporting the podcast on <a href="https://www.patreon.com/bioinfochat" rel="nofollow" target="_blank">Patreon</a>!

#62 Steady states of metabolic networks and Dingo 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/

Apostolos Chalkis is a PhD student from the University of Athens. As part of his recent Tweag fellowship, he developed <a href="https://github.com/GeomScale/dingo" rel="nofollow" target="_blank">dingo</a>, 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 <a href="https://www.tweag.io/blog/2021-07-14-metabolic-networks/" rel="nofollow" target="_blank">Apostolos's blog post</a>, where he shows a particular application of his package to the search for potential COVID-19 treatments.Special Guest: Apostolos Chalkis.Links:<ul><li><a href="https://tweag.io/blog/2021-07-14-metabolic-networks/" rel="nofollow" target="_blank">Searching for COVID-19 treatments using metabolic networks</a></li><li><a href="https://github.com/GeomScale/dingo" rel="nofollow" target="_blank">https://github.com/GeomScale/dingo</a></li><li><a href="https://github.com/GeomScale/volume_approximation" rel="nofollow" target="_blank">https://github.com/GeomScale/volume_approximation</a></li><li><a href="https://geomscale.github.io/" rel="nofollow" target="_blank">https://geomscale.github.io/</a></li></ul>

Computational analysis of metabolic networks with Apostolos Chalkis