Deciphering the code of nuclear RNA degradation by deep learning and transcriptomics
Grant amount: DKK 9,995,004
Albin Sandelin says: “The most fundamental process in molecular biology is reading of genes in DNA into RNA (transcription), which is then translated into proteins. However, we also need systems to remove RNAs from cells – RNA degradation. Because RNA degradation rates vary between different RNAs, RNA transcription and degradation together shape the concentration of each RNA in the cell. Therefore, understanding RNA degradation systems is necessary to understand the cell. Our current understanding is not on the level where we can predict the RNA degradation rates of a specific RNA based on its sequence and chemical properties. In this project we will merge state of the art methods for profiling RNA properties with the latest development in computer science: deep learning. We will make methods that can predict RNA degradation rates and discover what biological signals that are important for RNA degradation. This will be important for cell biology, but also for RNA-based medicine and biotechnology.”
Professor, Department of Biology, University of Copenhagen
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