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DeepSymmetry: using 3D convolutional networks for identification of tandem repeats and internal symmetries in protein structures

机译:DeepSymmetry:使用3D卷积网络识别蛋白质结构中的串联重复和内部对称性

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摘要

Motivation: Thanks to the recent advances in structural biology, nowadays 3D structures of various proteins are solved on a routine basis. A large portion of these structures contain structural repetitions or internal symmetries. To understand the evolution mechanisms of these proteins and how structural repetitions affect the protein function, we need to be able to detect such proteins very robustly. As deep learning is particularly suited to deal with spatially organized data, we applied it to the detection of proteins with structural repetitions.
机译:动机:由于近期结构生物学的进步,目前各种蛋白质的3D结构在常规基础上解决。 这些结构的大部分包含结构重复或内部对称性。 为了了解这些蛋白质的进化机制以及结构重复如何影响蛋白质功能,我们需要能够非常稳健地检测此类蛋白质。 由于深度学习特别适合处理空间组织的数据,我们将其应用于具有结构重复的蛋白质。

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