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RLSuccSite: succinylation sites prediction based on reinforcement learning dynamic with balanced reward mechanism and three-peaks enhanced method for physicochemical property scores

Crossref DOI link: https://doi.org/10.1186/s13321-025-01034-z

Published Online: 2025-06-02

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

Authors

Zhu, Lun

Zhang, Qingchao

Yang, Sen
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)

Open project of State Key Laboratory of Animal Biotech Breeding (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)

Development Project of Jilin Province of China (20220508125RC)
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Text and Data Mining valid from 2025-06-02

Version of Record valid from 2025-06-02
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Article History

Received: 5 October 2024

Accepted: 17 May 2025

First Online: 2 June 2025

Declarations

:

: The authors declare no competing interests.

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