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Abstract Accurate computational determination of RNA-protein interactions remains challenging, particularly when encountering unknown RNAs and proteins. The limited number of RNAs and their flexibility constrained the effectiveness of the deep-learning models for RNA-protein interaction prediction. Here, we introduce ZHMolGraph, which integrates graph neural network and unsupervised large language models to predict RNA-protein interaction.
Evaluation of DNA-protein complex structures using the deep learning method Biological processes such as transcription, repair, and regulation require the interactions between DNA and proteins. To unravel their functions, it is imperative to determine the high-resolution structures of DNA-protein complexes. However, experimental methods for this purpose are costly and technically demanding.
3 hours ago #TeacherQuittok is a window into the larger crisis in American education. When Nick Muniz came across a TikTok of a teacher sitting in her car, crying after quitting her job, he recognized her pain instantly. “You’re going to get there I promise!” Muniz, who goes by @TheTejanoTeacher on TikTok, said …
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