科研成果
1.Peng, H., Wang, H., Kong, W., Li, J., & Goh, W. W. B. (2024). Optimizing proteomics data differential expression analysis via High-Performing rules and ensemble inference. Nature Communications, 15(1), 3922.
2.Peng, H., Zhang, X., Liu, Y., Pan, Y., Goh, W. W. B. & Li, J. (2024). Optimal protospacer sequences recommended by ensemble deep learning for high-efficiency base editing. Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics.
3.Zhang, X., Peng, H.#, Tang, T., Liu, Y., Wang, Y., & Zhang, J. (2024). Knowledge-based Dual External Attention Network for peptide detectability prediction. Knowledge-Based Systems, 111378. (通讯作者)
4.Peng, H., Wong, L., & Goh, W. W. B. (2023). ProInfer: An interpretable protein inference tool leveraging on biological networks. PLOS Computational Biology, 19(3), e1010961.
5.Tang, T., Zhang, X., Liu, Y.#, Peng, H.#, Zheng, B., Yin, Y.#, & Zeng, X. (2023). Machine learning on protein–protein interaction prediction: models, challenges and trends. Briefings in Bioinformatics, 24(2), bbad076. (通讯作者)
6.Zhang, X., Peng, H.#, Zhang, J.#, & Wang, Y. (2023). A cost-sensitive attention temporal convolutional network based on adaptive top-k differential evolution for imbalanced time-series classification. Expert Systems with Applications, 213, 119073. (通讯作者)
7.Peng, H., Zheng, Y., Zhao, Z., & Li, J. (2021). Multigene editing: current methods and beyond. Briefings in Bioinformatics, bbaa396, https://doi.org/10.1093/bib/bbaa396.