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Open Access

Peer-reviewed

Research Article

A KAN-based hybrid deep neural networks for accurate identification of transcription factor binding sites

Guodong He,

Roles Methodology, Validation, Visualization, Writing – original draft

Affiliation School of Information Engineering, Wenzhou Business College, Wenzhou, Zhejiang, PR China
⨯
Jiahao Ye,

Roles Validation, Visualization

Affiliation School of Information Engineering, Wenzhou Business College, Wenzhou, Zhejiang, PR China
⨯
Huijun Hao,

Roles Data curation

Affiliation School of Information Engineering, Wenzhou Business College, Wenzhou, Zhejiang, PR China
⨯
Wei Chen

Roles Project administration, Supervision, Writing – review & editing

* E-mail: chenw@wzbc.edu.cn

Affiliation School of Information Engineering, Wenzhou Business College, Wenzhou, Zhejiang, PR China

https://orcid.org/0000-0002-9942-2216

⨯

A KAN-based hybrid deep neural networks for accurate identification of transcription factor binding sites

Guodong He,
Jiahao Ye,
Huijun Hao,
Wei Chen

x

Published: May 7, 2025
https://doi.org/10.1371/journal.pone.0322978

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Transcription factors
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Neural networks
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Deep learning
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Convolution
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Genomics
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Bioinformatics
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Gene expression
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Transcriptional control
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