RLAnOxPeptide: an integrated framework combining transformer and reinforcement learning for efficient antioxidant peptide prediction and innovative design.
- DOI
- 10.1093/bioinformatics/btag504
- Published
- 2026 Jul 2
- Container
- Bioinformatics (Oxford, England)
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1093/bioinformatics/btag504,
title = {RLAnOxPeptide: an integrated framework combining transformer and reinforcement learning for efficient antioxidant peptide prediction and innovative design.},
author = {Han C and Yue J and Li Y and Li H and Tan H and Wang Z and Qi Z and Zhou J and Liu Z and Wang Y},
year = {2026},
journal = {Bioinformatics (Oxford, England)},
doi = {10.1093/bioinformatics/btag504},
url = {https://doi.org/10.1093/bioinformatics/btag504}
}RIS
TY - JOUR TI - RLAnOxPeptide: an integrated framework combining transformer and reinforcement learning for efficient antioxidant peptide prediction and innovative design. AU - Han C AU - Yue J AU - Li Y AU - Li H AU - Tan H AU - Wang Z AU - Qi Z AU - Zhou J AU - Liu Z AU - Wang Y PY - 2026 JO - Bioinformatics (Oxford, England) DO - 10.1093/bioinformatics/btag504 UR - https://doi.org/10.1093/bioinformatics/btag504 ER -
APA
C, H., J, Y., Y, L., H, L., H, T., Z, W., Z, Q., J, Z., Z, L., & Y, W. (2026). RLAnOxPeptide: an integrated framework combining transformer and reinforcement learning for efficient antioxidant peptide prediction and innovative design.. Bioinformatics (Oxford, England). https://doi.org/10.1093/bioinformatics/btag504
Source records
- pubmed · retrieved 2026-09-25T13:38:32.302Z