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together with data from clinics, genomics, proteomics, and metabolomics. Our research group has developed several advanced methods for integrated analysis of the detailed image data and all other collected
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will be entirely computational, focusing on the large-scale bioinformatic analysis of proteome data from a wide range of existing species. The research will focus on understanding mutational robustness
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proteomic profiling of plaque tissue and plasma exist from over 1000 patients, together representing the world’s largest resource for molecular characterization of human atherosclerosis. The PhD student
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with documented experience in large-scale data analysis, is considered an asset. Experience working with various types of omics data (such as genomics, transcriptomics, proteomics, or metabolomics) is
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of cancer cells. The models are trained on high-throughput datasets, including metabolomics, proteomics, and transcriptomics, and constrained to align with the cell’s molecular networks. This allows us to