Kasper interviewed by Nature News about SARS-CoV-2 genomics

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Kasper was interviewed in a Nature News article that discussed the cluster of SARS-CoV-2 mutations found in farmed mink and people in Denmark. Current data suggest that the mink mutations do not allow the virus to spread more easily or make symptoms more severe in people. However, culling the animals is probably necessary as uncontrolled spread in mink could eventually lead to dangerous mutations.

Yu-Han’s paper on characterizing the obesity metabolome published in International Journal of Obesity

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Yu-Han and colleagues combined untargeted metabolomics with genetics to identify metabolites that may be causes or effects of obesity. They further grouped these metabolites into pathways to highlight how distinct biological mechanisms may be involved in obesity. Their findings demonstrate the strong potential of using untargeted metabolomics and genetically informed causal inference (Mendelian randomization) to uncover causal biological connections between metabolites and various human diseases, especially as larger datasets with both genotype and metabolite profiling data become available in the future. Congratulations on the great work, Yu-Han!

Genoppi is a preprint on bioRxiv

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Our study co-led by @gretapinta, @flassen_, @yuhanhsu and @mjapkim, ‘Genoppi: an open-source software for robust and standardized integration of proteomic and genetic data’, is now posted as a pre-print on bioRxiv. Genoppi allows the seamless integration of proteomic data with genetic information from a multitude of public or custom gene lists to maximize the interpretation of protein interaction datasets.

Cancer network algorithm led by Heiko Horn accepted to ISMB

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The cancer network algorithm paper titled “Prediction of cancer driver genes through network-based moment propagation of mutation scores” has been accepted for presentation at ISMB 2020 and for inclusion in the conference proceedings. This work is in collaboration with Karsten Borgwardt and led by Heiko Horn and Anja Gumpinger.