MLSNet:一种用于预测转录因子结合位点的深度学习模型

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Updated: Jun 11, 2025

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
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High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

Published on: February 7, 2019

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Yuchuan Zhang1, Zhikang Wang2, Fang Ge3

  • 1School of Computer Science and Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei, Nanjing 210094, China.

Briefings in bioinformatics
|October 1, 2024
PubMed
概括

我们开发了MLSNet,这是一种深度学习模型,通过整合序列和形状特征,准确预测转录因子结合位点 (TFBS). MLSNet的性能优于现有的方法,推进了基因调节研究.

关键词:
的 DNA 序列.形状 DNA 形状 DNA 的形状多大小的卷积融合融合.超级令牌注意力和Bi-LSTM转录因子的结合点是转录因子的结合点.

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