Mixed-weight neural bagging for detecting m6A modifications in SARS-CoV-2 RNA sequencing

Liu, R., Ou, L., Qi, J. et al. (10 more authors) (2022) Mixed-weight neural bagging for detecting m6A modifications in SARS-CoV-2 RNA sequencing. IEEE Transactions on Biomedical Engineering. ISSN 1558-2531

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: RNA; Coronaviruses; COVID-19; Feature extraction; Sequential analysis; Hidden Markov models; Proteins
Dates:
  • Accepted: 1 February 2022
  • Published (online): 11 February 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 09 Feb 2022 14:37
Last Modified: 15 Feb 2022 12:38
Status: Published online
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
Identification Number: https://doi.org/10.1109/TBME.2022.3150420

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