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Applications of matrix-factorization approaches for multi-omics data integration

Thursday, May 27, 2021 - 11:00
Carl Hermann
Address: ID de réunion : 892 640 6558 Code secret : 7mdSKr
Health Data Science Unit - Biomedical Genomics Group Heidelberg

Dimensional reduction approaches are crucial to extract relevant information from high-dimensional datasets, such as clinical or omics data. We have developed a toolbox based onnon-negative matrix factorization, in order to extract relevant biological and clinicalsignatures from high-dimensional datasets and combine various modalities into molecularsignatures. I will present some recent applications of these approaches, fromneuroblastoma epigenomics to the study of comorbidities between mental and somaticdisorders and the application to transfer learning from single-cell to bulk datasets.

Interdisciplinary Seminar

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