Deep-m5U: a deep learning-based approach for RNA 5-methyluridine modification prediction using optimized feature integration

Authors: Sumaiya Noor, Afshan Naseem, Hamid Hussain Awan, Wasiq Aslam, Salman Khan, Salman A. AlQahtani, Nijad Ahmad

Source: BMC Bioinformatics, Vol 25, Iss 1, Pp 1-23 (2024)

Subject Terms: RNA 5-methyluridine, PseKNC, Deep learning, Sequence-derived features, SHAP, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5

File Description: electronic resource

Relation: https://doaj.org/toc/1471-2105

Access URL: https://doaj.org/article/bbd86304f976402dad67d3e405f43320

A robust deep learning approach for identification of RNA 5-methyluridine sites

Authors: Md. Shazzad Hossain Shaon, Tasmin Karim, Md. Mamun Ali, Kawsar Ahmed, Francis M. Bui, Li Chen, Mohammad Ali Moni

Source: Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)

Subject Terms: RNA 5-methyluridine, RNA modifications, Physicochemical properties, Deep-learning, Principal component analysis, Transcript RNA, Medicine, Science

File Description: electronic resource

Relation: https://doaj.org/toc/2045-2322

Access URL: https://doaj.org/article/ad2bfa5f02e6459585c35d5c975e5e6a

Evaluation and development of deep neural networks for RNA 5-Methyluridine classifications using autoBioSeqpy

Authors: Lezheng Yu, Yonglin Zhang, Li Xue, Fengjuan Liu, Runyu Jing, Jiesi Luo

Source: Frontiers in Microbiology, Vol 14 (2023)

Subject Terms: RNA 5-methyluridine, deep learning, autoBioSeqpy, UMAP, SHAP, Microbiology, QR1-502

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fmicb.2023.1175925/full; https://doaj.org/toc/1664-302X

Access URL: https://doaj.org/article/f4259417139148eab9743d2d66870551