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, Nature Comms, 2024). One of our aims is to integrate single-cell and spatial information from spatial metabolomics and transcriptomic data to understand the metabolism of intestinal stem cells and cancer
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responses in ovarian cancer. Our aim is to identify the spatial transcriptional regulation of tumor cell states that drive chemoresistance in ovarian cancer. In this project, we will integrate multiplexed
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biophysics. • Prior experience in protein biochemistry and expression and purification (FPLC) and molecular biology is essential • Expertise in some degree of cell culture work (e.g. insect cell
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biophysics. • Prior experience in protein biochemistry and expression and purification (FPLC) and molecular biology is essential • Expertise in some degree of cell culture work (e.g. insect cell
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complexes involved in mitochondrial energy conversion in malaria parasites using protein biochemistry, single-particle cryo-EM and in-situ cryo-electron tomography. Specifically, the project is aimed
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employ various model systems such as mammalian cell lines, 3D organoid cultures and stem cell-based methods as well as cutting-edge genome-wide approaches from ChIP-seq, CUT&RUN and HiChIP to single-nuclei
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’ transition, particularly within the forestry, mining, and wind energy sectors, attention is for example given to the impacts on Sami Indigenous communities, women, more than human groups, and the broader
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Professor Vivek Sharma. The focus of research is on the structure and mechanism of proteins involved in biological energy (ATP) generation and mitochondrial function and dysfunction. An ensemble of multi
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models to profile cell and tissue samples imaged using 2/3D microscopy. The group is specifically focused on applying self-supervised representation learning and generative AI in computer vision to improve