iDNA-ABT: advanced deep learning model for detecting DNA methylation with adaptive features and transductive information maximization. - Yingying Yu; Wenjia He; Junru Jin; Guobao Xiao; Lizhen Cui; Rao Zeng; Leyi Wei (Bioinform., 2021)

Accelerating bioactive peptide discovery via mutual information-based meta-learning. - Wenjia He; Yi Jiang; Junru Jin; Zhongshen Li; Jiaojiao Zhao; Balachandran Manavalan; Ran Su; Xin Gao 001; Leyi Wei (Briefings Bioinform., 2022)

Predicting protein-peptide binding residues via interpretable deep learning. - Ruheng Wang; Junru Jin; Quan Zou 001; Kenta Nakai; Leyi Wei (Bioinform., 2022)

MechRetro is a chemical-mechanism-driven graph learning framework for interpretable retrosynthesis prediction and pathway planning. - Yu Wang; Chao Pang; Yuzhe Wang; Yi Jiang; Junru Jin; Sirui Liang; Quan Zou 001; Leyi Wei (CoRR, 2022)

SiameseCPP: a sequence-based Siamese network to predict cell-penetrating peptides by contrastive learning. - Xin Zhang; Lesong Wei; Xiucai Ye; Kai Zhang; Saisai Teng; Zhongshen Li; Junru Jin; Min Jae Kim; Tetsuya Sakurai; Lizhen Cui; Balachandran Manavalan; Leyi Wei (Briefings Bioinform., 2023)

ExamPle: explainable deep learning framework for the prediction of plant small secreted peptides. - Zhongshen Li; Junru Jin; Yu Wang; Wentao Long; Yuanhao Ding; Haiyan Hu; Leyi Wei (Bioinform., 2023)

DrugormerDTI: Drug Graphormer for drug-target interaction prediction. - Jiayue Hu; Yu Wang; Chao Pang; Junru Jin; Nhat Truong Pham; Balachandran Manavalan; Leyi Wei (Comput. Biol. Medicine, 2023)

CoraL: interpretable contrastive meta-learning for the prediction of cancer-associated ncRNA-encoded small peptides. - Zhongshen Li; Junru Jin; Wenjia He; Wentao Long; Haoqing Yu; Xin Gao 001; Kenta Nakai; Quan Zou 001; Leyi Wei (Briefings Bioinform., 2023)

PLPMpro: Enhancing promoter sequence prediction with prompt-learning based pre-trained language model. - Zhongshen Li; Junru Jin; Wentao Long; Leyi Wei (Comput. Biol. Medicine, 2023)

Rm-LR: A long-range-based deep learning model for predicting multiple types of RNA modifications. - Sirui Liang; Yanxi Zhao; Junru Jin; Jianbo Qiao; Ding Wang; Yu Wang; Leyi Wei (Comput. Biol. Medicine, 2023)

MolCAP: Molecular Chemical reActivity Pretraining and prompted-finetuning enhanced molecular representation learning. - Yu Wang; Jingjie Zhang; Junru Jin; Leyi Wei (Comput. Biol. Medicine, 2023)

CACPP: A Contrastive Learning-Based Siamese Network to Identify Anticancer Peptides Based on Sequence Only. - Xuetong Yang; Junru Jin; Ruheng Wang; Zhongshen Li; Yu Wang; Leyi Wei (J. Chem. Inf. Model., 2024)

Moss-m7G: A Motif-Based Interpretable Deep Learning Method for RNA N7-Methlguanosine Site Prediction. - Yanxi Zhao; Junru Jin; Wenjia Gao; Jianbo Qiao; Leyi Wei (J. Chem. Inf. Model., 2024)

StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides. - Ding Wang; Junru Jin; Zhongshen Li; Yu Wang; Mushuang Fan; Sirui Liang; Ran Su; Leyi Wei (Bioinform., 2024)

Towards retraining-free RNA modification prediction with incremental learning. - Jianbo Qiao; Junru Jin; Haoqing Yu; Leyi Wei (Inf. Sci., 2024)

Taco-DDI: accurate prediction of drug-drug interaction events using graph transformer-based architecture and dynamic co-attention matrices. - Jianbo Qiao; Xu Guo; Junru Jin; Ding Wang; Kefei Li; Wenjia Gao; Feifei Cui; Zilong Zhang; Hua Shi; Leyi Wei (Neural Networks, 2025)