小肽识别与功能预测

zouquan

成员：
邹权
魏乐义
吕志彬
付祥政
过骁忆
焦仕虎
Shahid Akbar

承担项目：
面向治疗肽序列预测方法的鲁棒模型研究，青年，62302340，过骁忆主持
面向肿瘤生物治疗的大规模多肽功能预测研究，青年，62301368，焦仕虎主持

发表论文：

• Leyi Wei, Pengwei Xing, Ran Su, Gaotao Shi, Zhanshan (Sam) Ma*, Quan Zou*. CPPred-RF: a sequence-based predictor for identifying cell-penetrating peptides and their uptake efficiency. Journal of Proteome Research.2017, 16(5):2044-2053.
• Leyi Wei, Jijun Tang, Quan Zou*. SkipCPP-Pred: An Improved and Promising Sequence-based Predictor for Predicting Cell-Penetrating Peptides. BMC Genomics. 2017, 18 (Suppl 7): 742
• Leyi Wei, Jie Hu, Fuyi Li, Jiangning Song*, Ran Su*, Quan Zou*. Comparative analysis and prediction of quorum-sensing peptides using feature representation learning and machine learning algorithms. Briefings in Bioinformatics. 2020,21(1): 106-119
• Ran Su, Jie Hu, Quan Zou, Balachandran Manavalan, Leyi Wei. Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools. Briefings in Bioinformatics. 2020, 21(2): 408-420
• Leyi Wei*, Chen Zhou, Ran Su*, Quan Zou*. PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning. Bioinformatics. 2019, 35(21):4272-4280
• Chunyan Ao, Yu Zhang, Dapeng Li, Yuming Zhao*, Quan Zou*. Progress in the development of antimicrobial peptide prediction tools. Current protein & peptide science. 2021, 22(3): 211-216
• Xiangzheng Fu, Lijun Cai, Xiangxiang Zeng*, Quan Zou*. StackCPPred: A Stacking and Pairwise Energy Content based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency. Bioinformatics.2020, 36(10): 3028-3034
• Changli Feng, Quan Zou*, Donghua Wang*. Using a Low Correlation High Orthogonality Feature Set and Machine Learning Methods to Identify Plant Pentatricopeptide Repeat Coding Gene/Protein. Neurocomputing. 2021, 424: 246-254
• Jiawei Li, Yuqian Pu, Jijun Tang, Quan Zou*, Fei Guo*. DeepAVP: a dual-channel deep neural network for identifying variable-length antiviral peptides. IEEE Journal of Biomedical and Health Informatics. 2020, 24(10): 3012-3019
• Yu Zhang, Quan Zou*. PPTPP: A novel therapeutic peptide prediction method using physicochemical property encoding and adaptive feature representation learning. Bioinformatics. 2020, 36(13): 3982-3987
• Lijun Cai, Li Wang, Xiangzheng Fu*, Chenxing Xia, Xiangxiang Zeng, Quan Zou. ITP-Pred: An interpretable method for predicting therapeutic peptides with fused features low-dimension represention. Briefings in Bioinformatics. 2021, 22(4): bbaa367
• Zhibin Lv, Feifei Cui, Quan Zou*, Lichao Zhang*, Lei Xu*. Anti-Cancer Peptide Prediction with Deep Representation Learning Features. Briefings in Bioinformatics. 2021, 22(5): bbab008.
• Xiaoyi Guo, Yizhang Jiang*, Quan Zou*. Structured Sparse Regularized TSK Fuzzy System for predicting therapeutic peptides. Briefings in Bioinformatics. 2022, 23(3): bbac135
• Hongwu Lv, Ke Yan, Yichen Guo, Quan Zou, Abd EI-Latif Hesham, Bin Liu. AMPpred-EL: An effective antimicrobial peptide prediction model based on ensemble learning. Computers in Biology and Medicine. 2022, 146: 105577
• Ruheng Wang, Junru Jin, Quan Zou, Kenta Nakai*, Leyi Wei*. Predicting protein-peptide binding residues via interpretable deep learning. Bioinformatics. 2022, 38(13):3351-3360
• Peng Liu, Shulin Zhao, Quan Zou, Yijie Ding*. Prediction of Cell-Penetrating Peptides Using a Novel HSIC-Based Multiview TSK Fuzzy System. Applied Sciences. 2022, 12(11):5383.
• Xiaoyi Guo, Prayag Tiwari*, Quan Zou*, Yijie Ding*. Subspace projection-based weighted echo state networks for predicting therapeutic peptides. Knowledge Based Systems. 2023, 263:110307
• Yi Jiang, Ruheng Wang, Jiuxin Feng, Junru Jin, Sirui Liang, Zhongshen Li, Yingying Yu, Anjun Ma, Ran Su, Quan Zou, Qin Ma*, Leyi Wei*. Explainable Deep Hypergraph Learning Modeling the Peptide Secondary Structure Prediction. Advanced Science. 2023, 2206151.
• Jici Jiang, Jiayu Li, Junxian Li, Hongdi Pei, Mingxin Li, Quan Zou*, Zhibin Lv *. A robust machine learning method to identify umami peptides accurately with sequences embedded by multiplicative LSTM. Foods. 2023, 12(7): 1498
• Zhongsheng Li, Junru Jin, Wenjia He, Wentao Long, Haoqing Yu, Xin Gao, Kenta Nakai, Quan Zou*, Leyi Wei*. CoraL: Interpretable contrastive meta-learning for the prediction of cancer-associated ncRNA-encoded small peptides. Briefings in Bioinformatics. 2023, 24(6): bbad352
• Changjiang Li, Quan Zou, Cangzhi Jia*, Jia Zheng*. AMPpred-MFA: An Interpretable Antimicrobial Peptide Predictor with a Stacking Architecture, Multiple Features, and Multihead Attention. Journal of Chemical Information and Modeling. DOI:10.1021/acs.jcim.3c01017.
• Ali Raza, Jamal Uddin, Abdullah Almuhaimeed, Shahid Akbar*, Quan Zou*, Ashfaq Ahmad. AIPs-SnTCN: Predicting Anti-inflammatory Peptides Using Fast Text and Transformer Encoder-based Hybrid Word Embedding with Self-normalized Temporal Convolutional Networks. Journal of Chemical Information and Modeling. Doi: 10.1021/acs.jcim.3c01563
• Jici Jiang, Hongdi Pei, Jiayu Li, Mingxin Li, Quan Zou*, Zhibin Lv*. FEOpti-ACVP: Identification of novel anti-coronavirus peptide sequences based on feature engineering and optimization. Briefings in Bioinformatics. 2024,25(2): bbae037
• Ali Raza, Jamal Uddin, Shahid Akbar*, Fawaz Khaled Alarfaj, Quan Zou*, Ashfaq Ahmad. Comprehensive Analysis of Computational Methods for Predicting Anti-inflammatory Peptides. Archives of Computational Methods in Engineering. Doi: 10.1007/s11831-024-10078-7
• Shahid Akbar, Ali Raza, Quan Zou*. Deepstacked-AVPs: predicting antiviral peptides using tri-segment evolutionary profile and word embedding based multi-perspective features with deep stacking mode. BMC Bioinformatics. 2024, 25: 102
• Shahid Akbar, Quan Zou*, Ali Raza, Fawaz Khaled Alarfaj. iAFPs-Mv-BiTCN: Predicting antifungal peptides using self-attention transformer embedding and transform evolutionary based multi-view features with bidirectional temporal convolutional networks. Artificial Intelligence in Medicine. 2024, 151: 102860
• Rui Wang, Tao Wang, Linlin Zhuo*, Jinhang Wei, Xiangzheng Fu*, Quan Zou*, Xiaojun Yao*. Diff-AMP: Tailored Designed Antimicrobial Peptide Framework with All-in-One Generation, Identification, Prediction and Optimization. Briefings in Bioinformatics. 2024, 25(2): bbae078