{"id":1823,"date":"2022-05-25T18:36:37","date_gmt":"2022-05-25T18:36:37","guid":{"rendered":"https:\/\/eccb2022.org\/?page_id=1823"},"modified":"2022-09-08T15:16:09","modified_gmt":"2022-09-08T15:16:09","slug":"ntb-w03","status":"publish","type":"page","link":"https:\/\/eccb2022.org\/ntb-w03\/","title":{"rendered":"NTB-W03"},"content":{"rendered":"\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-6f6b038\" data-block-id=\"6f6b038\"><style>.stk-6f6b038 .stk-block-heading__bottom-line{height:1px !important;background-color:var(u002du002dpaletteColor2,#f7b032) !important;margin-top:12px !important}<\/style><h5 class=\"stk-block-heading__text\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong>Title<\/strong><\/span><\/h5><div class=\"stk-block-heading__bottom-line\"><\/div><\/div>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-508698e\" data-block-id=\"508698e\"><h3 class=\"stk-block-heading__text\">Simulating cellular behaviours: advancing HPC-enabled Computational Biology<\/h3><\/div>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-77074a6\" data-block-id=\"77074a6\"><style>.stk-77074a6 .stk-block-heading__bottom-line{height:1px !important;background-color:var(u002du002dpaletteColor2,#f7b032) !important;margin-top:12px !important}<\/style><h5 class=\"stk-block-heading__text\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><span style=\"color: var(--paletteColor4, #1a928e);\" class=\"stk-highlight\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">Workshop details<\/span><\/span><\/span><\/strong><\/span><\/h5><div class=\"stk-block-heading__bottom-line\"><\/div><\/div>\n\n\n\n<ul><li>Date: Tuesday, September 13th<\/li><li>Time: 13:30 to 16:30 CEST<\/li><li>Format: Virtual<\/li><\/ul>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-0994530\" data-block-id=\"0994530\"><style>.stk-0994530 .stk-block-heading__bottom-line{height:1px !important;background-color:var(u002du002dpaletteColor2,#f7b032) !important;margin-top:12px !important}<\/style><h5 class=\"stk-block-heading__text\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong>Organisers<\/strong><\/span><\/h5><div class=\"stk-block-heading__bottom-line\"><\/div><\/div>\n\n\n\n<ul><li><strong>Arnau Montagud<\/strong>, Barcelona Supercomputing Center (BSC), Barcelona (Spain)<\/li><li><strong>Marta Lloret-Llinares<\/strong>, European Bioinformatics Institute, (EMBL-EBI) (United Kingdom)<\/li><li><strong>Renata Gim\u00e9nez<\/strong>, Barcelona Supercomputing Center (BSC), Barcelona (Spain)&nbsp;\u2013 Helper<\/li><li><strong>Mariola T\u00e0rrega-Molt\u00f3<\/strong>, Barcelona Supercomputing Center (BSC), Barcelona (Spain)&nbsp;\u2013 Helper<\/li><\/ul>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-4a8e43e\" data-block-id=\"4a8e43e\"><style>.stk-4a8e43e .stk-block-heading__bottom-line{height:1px !important;background-color:var(u002du002dpaletteColor2,#f7b032) !important;margin-top:12px !important}<\/style><h5 class=\"stk-block-heading__text\">Topic<\/h5><div class=\"stk-block-heading__bottom-line\"><\/div><\/div>\n\n\n\n<ul><li>Simulations of cells<\/li><li>Metabolic modelling<\/li><li>Multiscale modelling<\/li><li>Signalling networks modelling<\/li><li>HPC<\/li><li>Data analysis <\/li><li>Machine learning<\/li><\/ul>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-4cdfd01\" data-block-id=\"4cdfd01\"><style>.stk-4cdfd01 .stk-block-heading__bottom-line{height:1px !important;background-color:var(u002du002dpaletteColor2,#f7b032) !important;margin-top:12px !important}<\/style><h5 class=\"stk-block-heading__text\">Abstract<\/h5><div class=\"stk-block-heading__bottom-line\"><\/div><\/div>\n\n\n\n<p>High-Performance Computing (HPC) environments are fundamental infrastructures in current research communities. They are becoming an essential tool in many different fields like climate prediction, engineering simulations or material science, among others, due to their ability to power up data analysis, storage and large-scale processing.<\/p>\n\n\n\n<p>In Computational Biology, HPC has been crucial for storing, processing and analysing the<br>exponentially growing amount of biomedical data provided by the new sequencing technologies. These resources paved the way for novel modelling tools that yielded results in a wide variety of biomedical applications, including cell fate, chromatin dynamics, genome integrity, molecular pathways and tissue simulations. The use of these tools in combination with clinical data provide a unique and valuable description of aberrant molecular features behind complex diseases, like cancer or infections. In this context, new computational tools have been designed to properly leverage HPC resources and address more realistic scenarios. Scaling up the tools\u2019 scope usually allows for the integration of different data types, but also requires using model parameterization and optimization techniques to deal with the higher number of parameters. HPC benefits such approaches either by<br>offering the opportunity to use shared memory or parallel processes to address complex problems. Another aspect is the development of workflows and infrastructure to ease the parallelisation of otherwise sequential code and use of tools for model parameterization and exploration.<\/p>\n\n\n\n<p>These ongoing developments will shape future directions, essential to solving challenging paradigms in personalised medicine and drug design or drug repurposing, to name a few.<\/p>\n\n\n\n<ul><li>Scope: The aim of the workshop is to bring together researchers working in computational systems biology and High-performance computing (HPC) to foster novel developments at the interface of these fields.<\/li><li>Motivation: Researchers from computational modelling and HPC fields rarely have the opportunity to exchange, discuss and identify limitations, complementarities and common grounds.<\/li><li>Goals: We aim to bring together researchers that develop or employ methodologies and tools for data analytics, modelling and\/or machine learning focusing on simulating cellular behaviours. The focus will be on identifying ways to combine HPC-based methods to scale up computation with mechanistic and statistical modelling to build predictive dynamical models.<\/li><\/ul>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-cdd954b\" data-block-id=\"cdd954b\"><style>.stk-cdd954b .stk-block-heading__bottom-line{height:1px !important;background-color:var(u002du002dpaletteColor2,#f7b032) !important;margin-top:12px !important}<\/style><h5 class=\"stk-block-heading__text\">Invited speaker<\/h5><div class=\"stk-block-heading__bottom-line\"><\/div><\/div>\n\n\n\n<p><span style=\"color: var(--paletteColor5, #1a1a1a);\" class=\"stk-highlight\"><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/fertiglab.com\/\" target=\"_blank\">Elana J. Fertig<\/a><\/strong><br><\/span>Director of the Research Program in Quantitative Sciences, Co-Director of<br>the Convergence Institute and Associate Director of Quantitative Sciences at the Johns Hopkins Kimmel Cancer Center.<\/p>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-f484540\" data-block-id=\"f484540\"><style>.stk-f484540 .stk-block-heading__bottom-line{height:1px !important;background-color:var(u002du002dpaletteColor2,#f7b032) !important;margin-top:12px !important}<\/style><h5 class=\"stk-block-heading__text\">Target Audience<\/h5><div class=\"stk-block-heading__bottom-line\"><\/div><\/div>\n\n\n\n<p>The target audience encompasses:<\/p>\n\n\n\n<ul><li>PhDs<\/li><li>Post-doctorant fellows<\/li><li>Advanced researchers and participants from private companies from the field of Systems Biology<\/li><li>Computational Biology<\/li><li>Computer Science and Bioinformatics who apply or are interested in applying computational modelling techniques for studying cellular functions<\/li><\/ul>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-98a9197\" data-block-id=\"98a9197\"><style>.stk-98a9197 .stk-block-heading__bottom-line{height:1px !important;background-color:var(u002du002dpaletteColor2,#f7b032) !important;margin-top:12px !important}<\/style><h5 class=\"stk-block-heading__text\">Programme<\/h5><div class=\"stk-block-heading__bottom-line\"><\/div><\/div>\n\n\n\n<figure class=\"wp-block-table tabla-ntb is-style-regular\" style=\"font-size:15px\"><table><thead><tr><th class=\"has-text-align-left\" data-align=\"left\"> <strong>T<\/strong>IME <\/th><th class=\"has-text-align-left\" data-align=\"left\"><strong>CONTENT<\/strong><\/th><\/tr><\/thead><tbody><tr><td class=\"has-text-align-left\" data-align=\"left\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong>13:30 \u2013 14:15<\/strong><\/span><\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>\u201cMachine learning for spatial multi-omics in cancer\u201d<\/strong><br>Elana J Fertig <\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong>1<\/strong>4:15<\/span> \u2013 <span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">14:3<\/span><\/strong><\/span><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">0<\/span><\/strong><\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>Scalable Calibration of Large Cancer Related Signaling Pathway Models in HPC<br>Environments<\/strong><br>Fabian Fr\u00f6hlich<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">14:3<\/span><\/strong><\/span>0 \u2013 <span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">14:45<\/span><\/strong><\/span><\/span><\/strong><\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>EpiLog, a computational tool for logical multicellular models<\/strong><br>Claudine Chaouiya and Pedro T. Monteiro<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">14:<\/span><\/strong><\/span>45 \u2013 <span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">15:00<\/span><\/strong><\/span><\/span><\/strong><\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>Break<\/strong><\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">15:00 \u2013 15:15<\/span><\/strong><\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>A global method for simulating intracellular signaling reduces computational time in<br>multiscale agent-based models with systems biology applications<br><\/strong>Daniel Bergman and Trachette Jackson<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">15:<\/span><\/strong>15 \u2013 <strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">15:30<\/span><\/strong><\/span><\/strong> <\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>Agent-based model to simulate immune cell response during early bone fracture<br>healing<br><\/strong>Edoardo Borgiani, Gabriele Nasello and Liesbet Geris<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\">15:30<\/span><\/strong><\/span><\/strong> <span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong>&#8211; 15:45<\/strong><\/span><\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>Interfacing the agent-based modelling software BioDynaMo with Approximate<br>Bayesian Computation to simulate the growth of neuronal morphologies<br><\/strong>Tobias Duswald, Tom Thorne, Barbara Wohlmuth and Roman Bauer<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><strong>15:45<\/strong><\/strong> <strong>&#8211; 16:00<\/strong><\/span><\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>An agent-based model of tumor-associated macrophage differentiation in chronic<br>lymphocytic leukemia<\/strong><br>Nina Verstraete, Malvina Marku, Marcin Domagala, H\u00e9l\u00e8ne Arduin, Julie Bordenave, Jean-Jacques Fourni\u00e9, Lo\u00efc Ysebaert, Mary Poupot and Vera Pancaldi<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><strong>16:00<\/strong><\/strong> <strong>&#8211; 16:15<\/strong><\/span><\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>Multiscale modeling allows to study the different modes of cancer cell invasion<\/strong><br>Marco Ruscone, Arnau Montagud, Philippe Chavrier, Olivier Destaing, Andrei<br>Zinovyev, Emmanuel Barillot, Vincent No\u00ebl and Laurence Calzone<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\"><span style=\"color: var(--paletteColor4, #0081a7);\" class=\"stk-highlight\"><strong><strong>16:15<\/strong><\/strong> <strong>&#8211; 16:30<\/strong><\/span><\/td><td class=\"has-text-align-left\" data-align=\"left\"><strong>PhysiBoSS allows for drug synergies studies in real-size tumours simulations<\/strong><br>Miguel Ponce de Leon, Arnau Montagud, Othmane Hayoun-Mya, Thaleia Ntiniakou,<br>Gaurav Saxena, David Vicente and Alfonso Valencia<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div class=\"wp-block-stackable-heading stk-block-heading stk-block stk-026526c\" data-block-id=\"026526c\"><style>.stk-026526c .stk-block-heading__bottom-line{height:1px !important;background-color:var(u002du002dpaletteColor2,#f7b032) !important;margin-top:12px !important}<\/style><h5 class=\"stk-block-heading__text\">Call for abstracts<\/h5><div class=\"stk-block-heading__bottom-line\"><\/div><\/div>\n\n\n\n<p>We will select most of the speakers from abstracts sent to the <a rel=\"noreferrer noopener\" href=\"https:\/\/easychair.org\/conferences\/?conf=eccb2022\" data-type=\"URL\" data-id=\"https:\/\/easychair.org\/conferences\/?conf=eccb2022\" target=\"_blank\">NTB-W03 | Simulating<br>cellular behaviours: advancing HPC-enabled Computational Biology<\/a> Easychair track before August 21st.<\/p>\n\n\n\n<p>The scientific committee to select abstracts consists of:<\/p>\n\n\n\n<ul><li>Thaleia Ntiniakou, Barcelona Supercomputing Center (BSC)<\/li><li>Miroslav Kratochvil, University of Luxembourg<\/li><li>Laurence Calzone, Institut Curie<\/li><li>Jesse Harrison, CSC \u2013 IT Center for Science<\/li><li>Pablo Rodr\u00edguez Mier, Universit\u00e4tsklinikum Heidelberg (UKHD)<\/li><li>Vincent Noel, Institut Curie<\/li><li>Marco Ruscone, Institut Curie<\/li><li>Javier Conejero, Barcelona Supercomputing Center (BSC)<\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Title Simulating cellular behaviours: advancing HPC-enabled Computational Biology Workshop details Date: Tuesday, September 13th Time: 13:30 to 16:30 CEST Format: Virtual Organisers Arnau Montagud, Barcelona Supercomputing Center (BSC), Barcelona (Spain) Marta Lloret-Llinares, European Bioinformatics Institute, (EMBL-EBI) (United Kingdom) Renata Gim\u00e9nez, Barcelona Supercomputing Center (BSC), Barcelona (Spain)&nbsp;\u2013 Helper Mariola T\u00e0rrega-Molt\u00f3, Barcelona Supercomputing Center (BSC), Barcelona (Spain)&nbsp;\u2013 Helper Topic Simulations of cells Metabolic modelling Multiscale modelling Signalling networks modelling HPC Data analysis Machine learning Abstract High-Performance Computing (HPC) environments are fundamental infrastructures in current research communities. They are becoming an essential tool in many different fields like climate prediction, engineering simulations or\u2026<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":4},"page_title_panel":"","has_hero_section":"default","7b9ded946d4680066060ddae606a4869":"","hero_section":"type-1","hero_elements":[{"id":"custom_title","enabled":true,"heading_tag":"h1","title":"Inicio"},{"id":"custom_description","enabled":true,"description_visibility":{"desktop":true,"tablet":true,"mobile":false}},{"id":"custom_meta","enabled":false,"meta_elements":[{"id":"author","enabled":true,"label":"Por","has_author_avatar":"yes","avatar_size":25},{"id":"post_date","enabled":true,"label":"El","date_format_source":"default","date_format":"M j, 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Kingdom)Renata Gim\u00e9nez, Barcelona Supercomputing Center (BSC), Barcelona (Spain)&nbsp;\u2013 HelperMariola T\u00e0rrega-Molt\u00f3, Barcelona Supercomputing Center (BSC), Barcelona (Spain)&nbsp;\u2013 Helper Topic Simulations of cellsMetabolic modellingMultiscale modellingSignalling networks modellingHPCData analysis Machine learning Abstract High-Performance Computing (HPC) environments are fundamental infrastructures in current research communities. They are becoming an essential tool in many different fields like climate prediction, engineering simulations or material science, among others, due to their ability to power&hellip;<\/p>\n","category_list":"","author_info":{"name":"victorcuencaharo","url":"https:\/\/eccb2022.org\/author\/victorcuencaharo\/"},"comments_num":"0 comments","_links":{"self":[{"href":"https:\/\/eccb2022.org\/wp-json\/wp\/v2\/pages\/1823"}],"collection":[{"href":"https:\/\/eccb2022.org\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/eccb2022.org\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/eccb2022.org\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/eccb2022.org\/wp-json\/wp\/v2\/comments?post=1823"}],"version-history":[{"count":23,"href":"https:\/\/eccb2022.org\/wp-json\/wp\/v2\/pages\/1823\/revisions"}],"predecessor-version":[{"id":3101,"href":"https:\/\/eccb2022.org\/wp-json\/wp\/v2\/pages\/1823\/revisions\/3101"}],"wp:attachment":[{"href":"https:\/\/eccb2022.org\/wp-json\/wp\/v2\/media?parent=1823"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}