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DeepYY1:一种用于识别 YY1 介导的染色质环的深度学习方法。

DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops.

机构信息

Center for Informational Biology at the University of Electronic Science and Technology of China.

Laboratory of Theoretical Biophysics at the Inner Mongolia University.

出版信息

Brief Bioinform. 2021 Jul 20;22(4). doi: 10.1093/bib/bbaa356.

Abstract

The protein Yin Yang 1 (YY1) could form dimers that facilitate the interaction between active enhancers and promoter-proximal elements. YY1-mediated enhancer-promoter interaction is the general feature of mammalian gene control. Recently, some computational methods have been developed to characterize the interactions between DNA elements by elucidating important features of chromatin folding; however, no computational methods have been developed for identifying the YY1-mediated chromatin loops. In this study, we developed a deep learning algorithm named DeepYY1 based on word2vec to determine whether a pair of YY1 motifs would form a loop. The proposed models showed a high prediction performance (AUCs$\ge$0.93) on both training datasets and testing datasets in different cell types, demonstrating that DeepYY1 has an excellent performance in the identification of the YY1-mediated chromatin loops. Our study also suggested that sequences play an important role in the formation of YY1-mediated chromatin loops. Furthermore, we briefly discussed the distribution of the replication origin site in the loops. Finally, a user-friendly web server was established, and it can be freely accessed at http://lin-group.cn/server/DeepYY1.

摘要

蛋白质 Yin Yang 1(YY1)可以形成二聚体,促进活性增强子和启动子近端元件之间的相互作用。YY1 介导的增强子-启动子相互作用是哺乳动物基因控制的普遍特征。最近,一些计算方法已经被开发出来,通过阐明染色质折叠的重要特征来描述 DNA 元件之间的相互作用;然而,还没有开发出用于识别 YY1 介导的染色质环的计算方法。在这项研究中,我们开发了一种基于 word2vec 的深度学习算法,名为 DeepYY1,用于确定一对 YY1 基序是否会形成一个环。所提出的模型在不同细胞类型的训练数据集和测试数据集中均表现出较高的预测性能(AUCs$\ge$0.93),表明 DeepYY1 在识别 YY1 介导的染色质环方面具有优异的性能。我们的研究还表明,序列在 YY1 介导的染色质环的形成中起着重要作用。此外,我们简要讨论了复制起始位点在环中的分布。最后,建立了一个用户友好的网络服务器,可以在 http://lin-group.cn/server/DeepYY1 上免费访问。

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