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EnDM-CPP: A Multi-view Explainable Framework Based on Deep Learning and Machine Learning for Identifying Cell-Penetrating Peptides with Transformers and Analyzing Sequence Information

Crossref DOI link: https://doi.org/10.1007/s12539-024-00673-4

Published Online: 2024-12-23

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Zhu, Lun

Chen, Zehua

Yang, Sen https://orcid.org/0000-0003-4177-0653
Funding

Funding for this research was provided by:

Natural Science Foundation of Jiangsu Province of China (BK20230626)

State Key Laboratory of Plant Environmental Resilience (SKLPERKF2401)

National Key Laboratory of Animal Nutrition (2024SKLAB6-1)

Fourth Batch of Leading Innovative Talents Introduction and Training Projects under the Longcheng Talent Plan in Changzhou City (CQ20230086)

Changzhou Sci&Tech Program (CJ20241083)
License Information

Text and Data Mining valid from 2024-12-23

Version of Record valid from 2024-12-23
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Article History

Received: 4 June 2024

Revised: 28 October 2024

Accepted: 1 November 2024

First Online: 23 December 2024

Declarations

:

: On behalf of all authors, the corresponding author states that there is no conflict of interest.

: This article does not contain any studies with animals performed by any of the authors.

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