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perturbation-based GRN inference for single-cell and spatial multi-omics data, to boost GRN quality and add the cell type and tissue heterogeneity dimensions to causal regulatory analysis. A deep learning
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
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Umeå University, Faculty Office of Medicine Umeå University is one of Sweden’s largest higher education institutions with over 41,500 students and about 4,600 employees. The University offers a
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perturbation-based GRN inference for single-cell and spatial multi-omics data, to boost GRN quality and add the cell type and tissue heterogeneity dimensions to causal regulatory analysis. A deep learning