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Updated: May 29, 2025

An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA
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An Optimized Quantitative Pull-Down Analysis of RNA-Binding Proteins Using Short Biotinylated RNA

Published on: February 17, 2023

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一个深度学习模型,用于从单基分辨率的序列中描述蛋白质-RNA相互作用

Xilin Shen1,2,3, Yayan Hou4,3, Xueer Wang5

  • 1Tianjin Cancer Institute, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.

Patterns (New York, N.Y.)
|February 3, 2025
PubMed
概括

根据序列数据,深度学习模型Reformer准确地预测蛋白质-RNA结合亲和力. 它确定了新的结合动机,改善了对RNA调节和突变影响的理解.

关键词:
在RBP中使用RBP.RNA结合蛋白质是RNA结合的蛋白质.RNA与蛋白质的相互作用深度学习是一种深度学习.这就是eCLIP-seqq.发现动机 发现动机图案的丰富 图案的丰富突变效应是一种突变效应.病原性变体的病原性变体单一基准解决方案的解决方案变压器变压器变压器变压器

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