Deep Learning in DNA- and RNA-sequence Analysis: Advances and New Challenges

Авторы: <a target="_blank" href="https://cardiosomatics.ru/1574-8936/search/authors/view?firstName=Xiangtao&amp;middleName=&amp;lastName=Li">Li X. 1
Учреждения: School of Artificial Intelligence, Jilin University
Выпуск: Том 19, № 9 (2024)
Страницы: 793-793
Раздел: <a href="https://cardiosomatics.ru/1574-8936/browseSearch/sections/view?sectionId=2687">Life Sciences
URL: https://cardiosomatics.ru/1574-8936/article/view/644056
DOI: https://doi.org/10.2174/157489361909240611150749
ID: 644056

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School of Artificial Intelligence, Jilin University

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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