{"id":49391,"date":"2024-11-20T14:03:15","date_gmt":"2024-11-20T13:03:15","guid":{"rendered":"https:\/\/www.h-its.org\/de\/event\/hits-simplaix-joint-colloquium-markus-meuwly-computational-protein-dynamics-in-the-era-of-machine-learned-atomistic-simulations\/"},"modified":"2026-01-26T11:15:14","modified_gmt":"2026-01-26T10:15:14","slug":"hits-simplaix-joint-colloquium-markus-meuwly","status":"publish","type":"tribe_events","link":"https:\/\/www.h-its.org\/de\/event\/hits-simplaix-joint-colloquium-markus-meuwly\/","title":{"rendered":"HITS-SIMPLAIX Joint Colloquium Markus Meuwly: Computational Protein Dynamics in the Era of Machine-Learned Atomistic Simulations"},"content":{"rendered":"<p>&nbsp;<\/p>\n<p>By <a href=\"https:\/\/chemie.unibas.ch\/en\/persons\/markus-meuwly\">Markus Meuwly<\/a>, Department of Chemistry, University of Basel, Switzerland<\/p>\n<p>&nbsp;<\/p>\n<p>Machine Learning-based techniques have the potential to fundamentally change how we approach characterizing and understanding chemical and biological materials. It is anticipated that ML applied to protein dynamics allows to carry out atomistic simulations on functionally relevant time scales using models approaching chemical accuracy. In the present seminar I will present methodological advances and their application to position-dependent spectroscopy and ligand (re-)binding reactions in small proteins with a focus on the links between simulations and experiment. Both, opportunities and limitations of machine learning-based techniques will also be discussed.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p><strong>REGISTRATION:<\/strong><\/p>\n<article>The talk will be hybrid.<\/article>\n<article>\n<article>If you would like to participate online, please register in advance <a href=\"https:\/\/kta-email.zoom.us\/j\/99499986239?pwd=o0hGaPhCDLzAVioX0rYhDpzrhh9KYc.1\">here<\/a>.<\/article>\n<article><\/article>\n<article><\/article>\n<article><\/article>\n<article>After registering, you will receive a confirmation email containing information about joining the meeting.<\/article>\n<article><\/article>\n<article><\/article>\n<article>In case you are not able to attend, you can watch the talk afterwards on the HITS YouTube channel:\u00a0<a href=\"https:\/\/www.youtube.com\/user\/TheHITSters\" target=\"_blank\" rel=\"noopener noreferrer\" data-fancybox-group=\"fb_gallery_0_0\">https:\/\/www.youtube.com\/user\/TheHITSters<\/a>.<\/article>\n<\/article>\n","protected":false},"excerpt":{"rendered":"<p>&nbsp; By Markus Meuwly, Department of Chemistry, University of Basel, Switzerland &nbsp; Machine Learning-based techniques have the potential to fundamentally change &#8230;<\/p>\n","protected":false},"author":42,"featured_media":49393,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"hits-research-group":[1319,1422],"tribe_events_cat":[1345,1408],"class_list":["post-49391","tribe_events","type-tribe_events","status-publish","has-post-thumbnail","hentry","hits-research-group-hits","hits-research-group-simplaix","tribe_events_cat-oeffentliche-veranstaltungen","tribe_events_cat-kolloquien","cat_oeffentliche-veranstaltungen","cat_kolloquien"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>HITS-SIMPLAIX Joint Colloquium Markus Meuwly: Computational Protein Dynamics in the Era of Machine-Learned Atomistic Simulations - HITS gGmbH<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.h-its.org\/de\/event\/hits-simplaix-joint-colloquium-markus-meuwly\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"HITS-SIMPLAIX Joint Colloquium Markus Meuwly: Computational Protein Dynamics in the Era of Machine-Learned Atomistic Simulations - HITS gGmbH\" \/>\n<meta property=\"og:description\" content=\"&nbsp; 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