Unveiling the Potential Pattern Representation of RNA 5-Methyluridine Modification Sites Through a Novel Feature Fusion Model Leveraging Convolutional Neural Network and Tetranucleotide Composition-Reference-Cited by-同舟云学术

Unveiling the Potential Pattern Representation of RNA 5-Methyluridine Modification Sites Through a Novel Feature Fusion Model Leveraging Convolutional Neural Network and Tetranucleotide Composition

Published:2024 Issue: Volume:12 Page:10023-10035
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Alam Waleed¹^ORCID,Tahir Muhammad²^ORCID,Hussain Shahid³^ORCID,Gul Sarah⁴,Hayat Maqsood²^ORCID,Irshad Reyazur Rashid⁵,Pallonetto Fabiano³^ORCID

Affiliation:

1. Department of Electronics and Information Engineering, Jeonbuk National University, Jeonju, South Korea

2. Department of Computer Science, Abdul Wali Khan University, Mardan, Khyber Pakhtunkhwa, Pakistan

3. Innovation Value Institue (IVI), School of Business, National University of Ireland Maynooth (NUIM), Maynooth, Ireland

4. Department of Biological Sciences, Faculty of Basic and Applied Sciences, International Islamic University Islamabad, Islamabad, Pakistan

5. Department of Computer Science, College of Science and Arts, Najran University, Sharurah, Najran, Saudi Arabia

Funder

Deanship of Scientific Research and under the supervision of the Science and Engineering Research Centre at Najran University for funding this work under the Research Centers Funding program

Science Foundation Ireland

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10388321.pdf?arnumber=10388321

Reference71 articles.

1. iRNA-m5U: A sequence based predictor for identifying 5-methyluridine modification sites in Saccharomyces cerevisiae

2. Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely occurring RNA modifications

3. Identification of differential RNA modifications from nanopore direct RNA sequencing with xPore

4. The role of m6A, m5C and Ψ RNA modifications in cancer: Novel therapeutic opportunities

5. kDeepBind: Prediction of RNA-Proteins binding sites using convolution neural network and k-gram features

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