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对 和人类 DPR 元件的分析揭示了一种独特的人类变体,其特异性可以通过机器学习来增强。

Analysis of the and human DPR elements reveals a distinct human variant whose specificity can be enhanced by machine learning.

机构信息

Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, USA.

Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, USA

出版信息

Genes Dev. 2023 May 1;37(9-10):377-382. doi: 10.1101/gad.350572.123. Epub 2023 Apr 25.

Abstract

The RNA polymerase II core promoter is the site of convergence of the signals that lead to the initiation of transcription. Here, we performed a comparative analysis of the downstream core promoter region (DPR) in and humans by using machine learning. These studies revealed a distinct human-specific version of the DPR and led to the use of machine learning models for the identification of synthetic extreme DPR motifs with specificity for human transcription factors relative to factors and vice versa. More generally, machine learning models could similarly be used to design synthetic DNA elements with customized functional properties.

摘要

RNA 聚合酶 II 核心启动子是导致转录起始的信号汇聚的位点。在这里,我们通过机器学习对 和人类的下游核心启动子区域(DPR)进行了比较分析。这些研究揭示了人类特有的 DPR 版本,并导致使用机器学习模型来识别相对于 因子具有人类转录因子特异性的合成极端 DPR 基序,反之亦然。更一般地说,机器学习模型也可以用于设计具有定制功能特性的合成 DNA 元件。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b588/10270198/3ca99e5bf589/377f01.jpg

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