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2025	iAMP-EmGCN: A new design for identifying antimicrobial peptides based on BERT and Graph Convolutional Network Expert Systems with Applications Wenxuan Xing, Jie Zhang, Chen Li, Gaifang Dong
2025	DeepPhoPred: Accurate Deep Learning Model to Predict Microbial Phosphorylation Proteins: Structure, Function, and Bioinformatics Faisal Ahmed, Alok Sharma, Swakkhar Shatabda, Iman Dehzangi
2025	AMPGP: Discovering Highly Effective Antimicrobial Peptides via Deep Learning Journal of Chemical Information and Modeling Jing Wang, Runze Wu, Xinran Zhang, Chengyao Jiang, Shishun Zhao, Qian Li, Nan Zhang
2025	Comprehensive Analysis of Computational Models for Prediction of Anticancer Peptides Using Machine Learning and Deep Learning Archives of Computational Methods in Engineering Farman Ali, Nouf Ibrahim, Raed Alsini, Atef Masmoudi, Wajdi Alghamdi, Tamim Alkhalifah, Fahad Alturise
2024	PLMACPred prediction of anticancer peptides based on protein language model and wavelet denoising transformation Scientific Reports Muhammad Arif, Saleh Musleh, Huma Fida, Tanvir Alam
2024	Chemical Strategies towards the Development of Effective Anticancer Peptides Current Medicinal Chemistry Cuicui Li, Kang Jin
2024	ACP-ESM2: The prediction of anticancer peptides based on pre-trained classifier Computational Biology and Chemistry Huijia Song, Xiaozhu Lin, Huainian Zhang, Huijuan Yin
2024	Advancing Peptide-Based Cancer Therapy with AI: In-Depth Analysis of State-of-the-Art AI Models Journal of Chemical Information and Modeling Sadik Bhattarai, Hilal Tayara, Kil To Chong
2024	ACP-PDAFF: Pretrained model and dual-channel attentional feature fusion for anticancer peptides prediction Computational Biology and Chemistry Xinyi Wang, Shunfang Wang
2024	2024 IEEE Congress on Evolutionary Computation (CEC) Elias A.D. Silva, Lucas S. Palmeira, Marcelo A. Garcia-Júnior, Luiz G.A. Martins, Yaochu Jin, Bruno S. Andrade, Robinson Sabino-Silva, Murillo G. Carneiro
2023	FFMAVP: a new classifier based on feature fusion and multitask learning for identifying antiviral peptides and their subclasses Briefings in Bioinformatics Ruifen Cao, Weiling Hu, Pijing Wei, Yun Ding, Yannan Bin, Chunhou Zheng
2023	Prediction of anticancer peptides based on an ensemble model of deep learning and machine learning using ordinal positional encoding Briefings in Bioinformatics Qitong Yuan, Keyi Chen, Yimin Yu, Nguyen Quoc Khanh Le, Matthew Chin Heng Chua
2023	ACP-BC: A Model for Accurate Identification of Anticancer Peptides Based on Fusion Features of Bidirectional Long Short-Term Memory and Chemically Derived Information International Journal of Molecular Sciences Mingwei Sun, Haoyuan Hu, Wei Pang, You Zhou
2022	Integrating multiple sequence features for identifying anticancer peptides Computational Biology and Chemistry Hongliang Zou, Fan Yang, Zhijian Yin
2022	PRIP: A Protein-RNA Interface Predictor Based on Semantics of Sequences Life You Li, Jianyi Lyu, Yaoqun Wu, Yuewu Liu, Guohua Huang
2022	ACP-check: An anticancer peptide prediction model based on bidirectional long short-term memory and multi-features fusion strategy Computers in Biology and Medicine Lun Zhu, Chenyang Ye, Xuemei Hu, Sen Yang, Chenyang Zhu
2022	Breast and Lung Anticancer Peptides Classification Using N-Grams and Ensemble Learning Techniques Big Data and Cognitive Computing Ayad Rodhan Abbas, Bashar Saadoon Mahdi, Osamah Younus Fadhil
2022	Recent Progress in the Discovery and Design of Antimicrobial Peptides Using Traditional Machine Learning and Deep Learning Antibiotics Jielu Yan, Jianxiu Cai, Bob Zhang, Yapeng Wang, Derek F. Wong, Shirley W. I. Siu
2022	DPProm: A Two-Layer Predictor for Identifying Promoters and Their Types on Phage Genome Using Deep Learning IEEE Journal of Biomedical and Health Informatics Chen Wang, Junyin Zhang, Li Cheng, Jiawei Wu, Minfeng Xiao, Junfeng Xia, Yannan Bin
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