Predicting transcription factor binding sites using DNA shape features based on shared hybrid deep learning architecture

Predicting transcription factor binding sites using DNA shape features based on shared hybrid deep learning architecture

The study of transcriptional regulation is still difficult yet fundamental in molecular biology research. Recent research has shown that the double helix structure of nucleotides plays an important role in improving the accuracy and interpretability of transcription factor binding sites (TFBSs). Alt...

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Bibliographic Details
Main Authors: Siguo Wang, Qinhu Zhang, Zhen Shen, Ying He, Zhen-Heng Chen, Jianqiang Li, De-Shuang Huang
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:Molecular Therapy: Nucleic Acids
Subjects:
transcription factor binding sites
DNA sequence
DNA shape features
hybrid convolutional neural network
recurrent neural network
Online Access:http://www.sciencedirect.com/science/article/pii/S2162253121000494

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http://www.sciencedirect.com/science/article/pii/S2162253121000494

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