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RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design
March 8, 2024, 5:43 a.m. | Cheng Tan, Yijie Zhang, Zhangyang Gao, Bozhen Hu, Siyuan Li, Zicheng Liu, Stan Z. Li
cs.LG updates on arXiv.org arxiv.org
Abstract: While artificial intelligence has made remarkable strides in revealing the relationship between biological macromolecules' primary sequence and tertiary structure, designing RNA sequences based on specified tertiary structures remains challenging. Though existing approaches in protein design have thoroughly explored structure-to-sequence dependencies in proteins, RNA design still confronts difficulties due to structural complexity and data scarcity. Moreover, direct transplantation of protein design methodologies into RNA design fails to achieve satisfactory outcomes although sharing similar structural components. In …
arxiv cs.ai cs.lg data design hierarchical q-bio.bm representation representation learning rna type
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