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.

Nadine’s paper on identification of new biomarkers for IBD published in Nature Microbiology

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Nadine’s work on identification of new biomarkers of Inflammatory Bowel Disease (IBD), under the direction of Ramnik Xavier in collaboration with the Broad Institute, Harvard School of Public Health, the University of North Carolina and Novartis has been published in Nature Microbiology. Fantastic work Nadine!

Find the digest here: https://naturemicrobiologycommunity.nature.com/users/346662-nadine-fornelos/posts/58611-gut-bugs-and-metabolites.

Find the article here: https://www.nature.com/articles/s41564-019-0655-7

Lage Lab hosts Stanley Center Program Meeting

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Kasper hosted the Stanley Center Program Meeting where he gave a talk titled “Functional interpretation of genetic data in psychiatric diseases using human neuronal protein-protein interaction networks.” In addition, Yu-Han Hsu and Greta Pintacuda, postdocs in the Lage Lab and Eggan Lab, presented their work titled “Combining proteomics with human genetics to study neuropsychiatric disease.” Great job everyone!

Kasper gives plenary talk at WCPG 2019

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Kasper gave a plenary talk at World Congress of Psychiatric Genetics 2019 where he discussed the functional interpretation of genetic data in psychiatric diseases and the insights from tissue specific protein-protein interaction networks for schizophrenia.