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April 25, 2025 RNA-based therapeutic design has gained significant momentum over the past five years, largely due to the success of mRNA vaccines, which have opened avenues for targeting genes in cells to treat previously untreatable diseases. RNA processes, including splicing, degradation, and translation, underpin all cellular pathways in health and disease, coordinated by combinatorial interactions between RNA and approximately 2,000 proteins that bind RNA in a time- and tissue-specific manner. Understanding these interactions and unravelling the sequence and three-dimensional structural patterns leading to specific RNA cellular outcomes is foundational for RNA therapeutic design. In my talk, I will present sequence-based deep learning approaches developed in our lab, such as Pysster (Bubach et al. 2018), RBPNet (Horlacher et al. 2023), and panRBPNet (unpublished, a foundation model of protein-RNA interactions). I will highlight their applications in addressing specific biological questions and their role in AI-assisted RNA therapeutic design,with focus antisense oligonucleotide (ASO) design and RNA UTR optimization.
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