Machine Learning Analysis of the Human Initiator Region Reveals Key Features of Different Types of Core Promoters

机器学习分析人类起始区揭示不同类型核心启动子的关键特征

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Abstract

The initiator (Inr) is the starting point for the transcription of many genes. Here, we generated highly predictive machine learning models of the human Inr region, and determined that the Inr is present in about 60% of natural promoters, identified a novel TATA-specific Inr, and detected the overlapping but functionally distinct TCT motif. Quantitative genome-wide analyses revealed a strict and synergistic interaction between the Inr and DPR, a duality between the TATA and DPR, a flexible and sometimes independent function of the TATA box in relation to the Inr, and different properties of the TCT motif in humans and Drosophila.

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