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DTSTAMP:20260721T092307Z
UID:1f48c7b1-86f3-4de1-9037-ab5fc38f4327
DTSTART:20220621T090000Z
DTEND:20220621T170000Z
DESCRIPTION:Mathematical models of the biological processes that are deregu
 lated in diseases show a high complexity not only because of the number of
  genes and pathways involved\, but also because of the numerous patients o
 r samples to include in the simulations in order to be predictive. One way
  to address these issues is to combine High Performance Computer (HPC)-bas
 ed methods to scale up the power of the computation with mechanistic and s
 tatistical modelling approaches.\n\nIn the context of the PerMedCoE projec
 t\, we have brought together computer scientists and modellers to define t
 he needs and the methods that need to be developed to optimise the simulat
 ions of these computationally-demanding models. Two use cases were defined
 : the first one describes a workflow that inputs omics data of cancer pati
 ents and outputs personalised combinations of drugs per patient based on a
  model of intracellular signalling pathways\; and the second one aims at u
 ncovering COVID-19-related mechanisms that explain the differences in seve
 rity among patients using personalised agent-based models of different cel
 l types.\n\nWe will conclude by briefly discussing the possible clinical a
 pplications of such types of models.\n\n \n\n### About the speaker\n\n[Dr
  Laurence Calzone](https://institut-curie.org/personne/laurence-calzone) 
 is a research scientist at Institut Curie. France. She has published mathe
 matical models using several formalisms including nonlinear ordinary diffe
 rential equations and Boolean formalism to address specific biological que
 stions related to cancer (cell fate decision processes in response to cell
  death signals\, interplays between MAPK pathways\, metastasis process\, e
 tc.) with the aim to provide personalised treatments. She has experience i
 n constructing these models based on published articles and in analysing p
 atient data using these models. She has participated in developing methods
  and tools to improve the simulations of the mathematical models she build
 s. She is an active member of modelling communities such as [CoLoMoTo](ht
 tp://www.colomoto.org/) and [SysMod](https://sysmod.info/).\n\n \n\n[Dr
  Arnau Montagud](https://www.bsc.es/montagud-arnau) is a research scienti
 st at the Life Sciences department of the Barcelona Supercomputing Center.
  During his last undergrad year Arnau participated in synthetic biology’
 s iGEM competition where he dove into the use of models in Biology\, which
  pushed him to pursue a PhD in the Department of Applied Mathematics in th
 e Technical University of Valencia. His research on Metabolic Engineering 
 of hydrogen in cyanobacteria led him to be a visiting researcher at Uppsal
 a University\, Denmark Technical University and EMBL Heidelberg. After gra
 duating\, he decided to apply modelling techniques to Cancer using logical
  models\, agent-based models and data deconvolution and integration.
LOCATION:\, 
SUMMARY:HPC boosts mathematical models’ promises of personalised medicine
URL;VALUE=URI:https://www.ebi.ac.uk/training/events/hpc-boosts-mathematical
 -models-promises-personalised-medicine
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