Proceedings of the
The Nineteenth International Conference on Computational Intelligence and Security (CIS 2023)
December 1 – 4, 2023, Haikou, China
Predicting Algorithms of Transcription Factor Binding Sites Based on Deep Learning
1College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China.
2School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, China.
ABSTRACT
The rate of transcription can control gene expression, DNA binding proteins could be classified a kind of special proteins. The sites on the DNA sequence that bind to transcription factors are called transcription factor binding sites(TFBS), the prediction of TFBSs is of great help to our comprehension of gene expression. The paper presents a few methods of transcription factor in binding site prediction, which can be split into three methods: method of machine learning based on feature, method of based on sequence, and method of machine learning based on deep learning. We have made comparisons, research directions,and made suggestions to the model, and given a good accuracy rate for our predicting model.
Keywords: Predicting algorithm, Deep learning, Binding sites, Weight matrix, Convolutional layer.
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1College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China.
2School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, China.
ABSTRACT
The rate of transcription can control gene expression, DNA binding proteins could be classified a kind of special proteins. The sites on the DNA sequence that bind to transcription factors are called transcription factor binding sites(TFBS), the prediction of TFBSs is of great help to our comprehension of gene expression. The paper presents a few methods of transcription factor in binding site prediction, which can be split into three methods: method of machine learning based on feature, method of based on sequence, and method of machine learning based on deep learning. We have made comparisons, research directions,and made suggestions to the model, and given a good accuracy rate for our predicting model.
Keywords: Predicting algorithm, Deep learning, Binding sites, Weight matrix, Convolutional layer.
Download PDF