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OMetaNet: an efficient hybrid deep learning model based on multimodal data fusion and contrastive learning for predicting 2ʹ-O-methylation sites in human RNA

Crossref DOI link: https://doi.org/10.1186/s12859-025-06324-9

Published Online: 2025-11-24

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

Authors

Shen, Peng

Lin, Yiyu

Yang, Sen

Zhang, Ziding
Funding

Funding for this research was provided by:

Natural Science Foundation of Jiangsu Province of China (BK20230626)

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)

National Natural Science Foundation of China (62502053)
License Information

Text and Data Mining valid from 2025-11-24

Version of Record valid from 2025-11-24
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Article History

Received: 6 August 2025

Accepted: 10 November 2025

First Online: 24 November 2025

Declarations

:

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

: Not applicable.

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

: Not applicable.

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