{"id":8440,"date":"2023-09-01T18:10:12","date_gmt":"2023-09-01T09:10:12","guid":{"rendered":"https:\/\/www.ibs.re.kr\/bimag\/?post_type=tribe_events&#038;p=8440"},"modified":"2023-09-06T17:37:20","modified_gmt":"2023-09-06T08:37:20","slug":"2023-09-22-jc","status":"publish","type":"tribe_events","link":"https:\/\/www.ibs.re.kr\/bimag\/event\/2023-09-22-jc\/","title":{"rendered":"Yun Min Song, A data-driven approach for timescale decomposition of biochemical reaction networks"},"content":{"rendered":"<p>We will discuss about \u201c<span class=\"notion-enable-hover\" data-token-index=\"0\">A data-driven approach for timescale decomposition of biochemical reaction networks<\/span>\u201d, Amir Akbari, Zachary B. Haiman, Bernhard O. Palsson, bioRxiv (2023)<\/p>\n<p>Abstract<\/p>\n<div id=\"abstract-1\" class=\"section abstract\">\n<p id=\"p-2\">Understanding the dynamics of biological systems in evolving environments is a challenge due to their scale and complexity. Here, we present a computational framework for timescale decomposition of biochemical reaction networks to distill essential patterns from their intricate dynamics. This approach identifies timescale hierarchies, concentration pools, and coherent structures from time-series data, providing a system-level description of reaction networks at physiologically important timescales. We apply this technique to kinetic models of hypothetical and biological pathways, validating it by reproducing analytically characterized or previously known concentration pools of these pathways. Moreover, by analyzing the timescale hierarchy of the glycolytic pathway, we elucidate the connections between the stoichiometric and dissipative structures of reaction networks and the temporal organization of coherent structures. Specifically, we show that glycolysis is a cofactor driven pathway, the slowest dynamics of which are described by a balance between high-energy phosphate bond and redox trafficking. Overall, this approach provides more biologically interpretable characterizations of network dynamics than large-scale kinetic models, thus facilitating model reduction and personalized medicine applications.<\/p>\n<\/div>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We will discuss about \u201cA data-driven approach for timescale decomposition of biochemical reaction networks\u201d, Amir Akbari, Zachary B. Haiman, Bernhard O. Palsson, bioRxiv (2023) Abstract Understanding the dynamics of biological &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/2023-09-22-jc\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Yun Min Song, A data-driven approach for timescale decomposition of biochemical reaction networks&#8221;<\/span><\/a><\/p>\n","protected":false},"author":4,"featured_media":0,"template":"","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","_uag_custom_page_level_css":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[219],"class_list":["post-8440","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-journal-club","cat_journal-club"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Yun Min Song, A data-driven approach for timescale decomposition of biochemical reaction networks - Biomedical Mathematics Group<\/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.ibs.re.kr\/bimag\/event\/2023-09-22-jc\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Yun Min Song, A data-driven approach for timescale decomposition of biochemical reaction networks - Biomedical Mathematics Group\" \/>\n<meta property=\"og:description\" content=\"We will discuss about \u201cA data-driven approach for timescale decomposition of biochemical reaction networks\u201d, Amir Akbari, Zachary B. 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