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The University of Texas MD Anderson Cancer Center | Houston, Texas | United States | about 1 month ago
laboratory Our research focuses on large-scale pan-cancer genomics to gain insight into the genes, mutational processes and evolution of cancer. Our work is highly data-driven, with a focus on large-scale data
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methods are developed in parallel, the postdoc will develop systems and services that make biological data accessible to AI and computational tools, collaborating closely with the Human Protein Atlas (HPA
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) Bioinformatics and Statistics, and (3) Data Science Methods. The postdoc will be part of the Data Science Methods group, which has a strong research focus on privacy-preserving techniques. CLINDA includes 17 core
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innovative high-throughput sequencing technologies, bioinformatics approaches, and multi-scale models to elucidate RNA-mediated endothelial biology in the context of diabetes. In parallel, the lab emphasizes
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ecomorphological outcomes significantly parallel. As a next step, it is vital to dig more deeply into the molecular mechanisms driving these patterns. This project will examine replicate divergences into specialist
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process here . ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position Are you ready to take your research career to the next
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/or cells) for MS-based metabolomics and lipidomics. You have experience in bioinformatics to process HRMS data for statistical analyses and biomarker discovery. Your research qualities are in line with
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metabolic disease, including type 2 diabetes (T2D), Non-alcoholic fatty liver disease (NAFLD) and obesity, collectively referred to as metabolic syndrome (MetS), has occurred in parallel with a global decline
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controls almost every cellular process in humans, including targeting poorly folded proteins for destruction to prevent them harming the cell. When ubiquitin signalling goes wrong, many different disease