Email this article Deep Learning in DNA- and RNA-sequence Analysis: Advances and New Challenges
- Authors: Li X.1
-
Affiliations:
- School of Artificial Intelligence, Jilin University
- Issue: Vol 19, No 9 (2024)
- Pages: 793-793
- Section: Life Sciences
- URL: https://rjpbr.com/1574-8936/article/view/644056
- DOI: https://doi.org/10.2174/157489361909240611150749
- ID: 644056
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About the authors
Xiangtao Li
School of Artificial Intelligence, Jilin University
Email: info@benthamscience.net
References
- Das S, Pal S, Mahapatra S, et al. FMDVSerPred: A novel computational solution for foot-and-mouth disease virus classification and serotype prediction prevalent in Asia using VP1 nucleotide sequence data. Curr Bioinformat 2024; 19(9): 794-809.
- Soylu NN, Sefer E. DeepPTM: protein post-translational modification prediction from protein sequences by combining deep protein language model with vision transformers. Curr Bioinformat 2024; 19(9): 810-24.
- Chandrashekar K, Niranjan V, Vishal A, Setlur AS. Integration of artificial intelligence, machine learning and deep learning techniques in genomics: review on computational perspectives for NGS analysis of DNA and RNA seq data. Curr Bioinformat 2024; 19(9): 825-44.
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