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pathway. Additionally, finite element theoretical modelling and density functional theory calculations will be used to further increase our understanding of the photo-reduction mechanism. Correlating
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sequencing and transcriptomics, and iPSC-based disease modeling to better understand the genetic etiologies of intractable epilepsy. The team is part of the European STXBP1 consortium . About the project
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validate the identified key (epi)genetic molecular and explore their therapeutic potential in vitro and in vivo disease models. Profile The candidate should: have an MSc in Systems Biology, Molecular Biology
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, you will leverage the power of graph neural networks – a novel ML architecture, capable of learning fundamental physical behaviour by modeling systems as graphs and encoding nonlinearities in these. As
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from human genetics, genomics, protein biochemistry and neuronal and glial cell biology to integrative systems and computational biology. Models include yeast, fly, mouse, and pluripotent human cell
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include 1) a murine (diet-induced obesity) model, 2) acute and chronic exercise paradigms, 3) treatment with peripherally restricted enzyme-based eCB modulators, 4) multi-tissue molecular analyses and 5
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on cancer metastasis and novel metabolic pathways. We exploit mouse models, genetic engineering, metabolomics and single cell & spatial multi-omics analysis to gain groundbreaking insights into metabolism as
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on cancer metastasis and novel metabolic pathways. We exploit mouse models, genetic engineering, metabolomics and single cell & spatial multi-omics analysis to gain groundbreaking insights into metabolism as
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-causing mutations. Finally, we will validate the identified key (epi)genetic molecular and eplore their therapeutic potential in in vitro and in vivo disease models. Profile The candidate should: have an
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short and long-read sequencing and transcriptomics, and iPSC-based disease modeling to better understand the genetic etiologies of intractable epilepsy. The team is part of the European STXBP1 consortium