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Junru Jin

Showing results (1-10 of 25) with videos related to

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Methods (San Diego, Calif.)|January 30, 2022
Mouse4mC-BGRU: Deep learning for predicting DNA N4-methylcytosine sites in mouse genomeJunru Jin, Yingying Yu, Leyi Wei
Computers in Biology and Medicine|November 13, 2023
MolCAP: Molecular Chemical reActivity Pretraining and prompted-finetuning enhanced molecular representation learningYu Wang, Jingjie Zhang, Junru Jin, et al.
Computers in Biology and Medicine|August 9, 2023
PLPMpro: Enhancing promoter sequence prediction with prompt-learning based pre-trained language modelZhongshen Li, Junru Jin, Wentao Long, et al.
Journal of Chemical Information and Modeling|July 16, 2024
Moss-m7G: A Motif-Based Interpretable Deep Learning Method for RNA N7-Methlguanosine Site PredictionYanxi Zhao, Junru Jin, Wenjia Gao, et al.
Bioinformatics (Oxford, England)|May 23, 2022
Predicting protein-peptide binding residues via interpretable deep learningRuheng Wang, Junru Jin, Quan Zou, et al.
Genomics, Proteomics & Bioinformatics|December 2, 2025
HGCPep: Hypergraph Deep Learning Identifies Cancer-associated Non-coding PeptidesWentao Long, Zhongshen Li, Junru Jin, et al.
Journal of Chemical Information and Modeling|May 30, 2023
CACPP: A Contrastive Learning-Based Siamese Network to Identify Anticancer Peptides Based on Sequence OnlyXuetong Yang, Junru Jin, Ruheng Wang, et al.
ACS Synthetic Biology|July 1, 2026
An Explainable Deep Learning Framework Integrating DNA Sequence and Transcription Initiation Signals for Gene Expression PredictionJianbo Qiao, Wenjia Gao, Ding Wang, et al.
Bioinformatics (Oxford, England)|March 10, 2023
ExamPle: explainable deep learning framework for the prediction of plant small secreted peptidesZhongshen Li, Junru Jin, Yu Wang, et al.
Bioinformatics (Oxford, England)|October 3, 2021
iDNA-ABT: advanced deep learning model for detecting DNA methylation with adaptive features and transductive information maximizationYingying Yu, Wenjia He, Junru Jin, et al.
Pageof 3

Showing results (1-10 of 25) with videos related to

Sort By:
Pageof 3
Methods (San Diego, Calif.)|January 30, 2022
Mouse4mC-BGRU: Deep learning for predicting DNA N4-methylcytosine sites in mouse genomeJunru Jin, Yingying Yu, Leyi Wei
Computers in Biology and Medicine|November 13, 2023
MolCAP: Molecular Chemical reActivity Pretraining and prompted-finetuning enhanced molecular representation learningYu Wang, Jingjie Zhang, Junru Jin, et al.
Computers in Biology and Medicine|August 9, 2023
PLPMpro: Enhancing promoter sequence prediction with prompt-learning based pre-trained language modelZhongshen Li, Junru Jin, Wentao Long, et al.
Journal of Chemical Information and Modeling|July 16, 2024
Moss-m7G: A Motif-Based Interpretable Deep Learning Method for RNA N7-Methlguanosine Site PredictionYanxi Zhao, Junru Jin, Wenjia Gao, et al.
Bioinformatics (Oxford, England)|May 23, 2022
Predicting protein-peptide binding residues via interpretable deep learningRuheng Wang, Junru Jin, Quan Zou, et al.
Genomics, Proteomics & Bioinformatics|December 2, 2025
HGCPep: Hypergraph Deep Learning Identifies Cancer-associated Non-coding PeptidesWentao Long, Zhongshen Li, Junru Jin, et al.
Journal of Chemical Information and Modeling|May 30, 2023
CACPP: A Contrastive Learning-Based Siamese Network to Identify Anticancer Peptides Based on Sequence OnlyXuetong Yang, Junru Jin, Ruheng Wang, et al.
ACS Synthetic Biology|July 1, 2026
An Explainable Deep Learning Framework Integrating DNA Sequence and Transcription Initiation Signals for Gene Expression PredictionJianbo Qiao, Wenjia Gao, Ding Wang, et al.
Bioinformatics (Oxford, England)|March 10, 2023
ExamPle: explainable deep learning framework for the prediction of plant small secreted peptidesZhongshen Li, Junru Jin, Yu Wang, et al.
Bioinformatics (Oxford, England)|October 3, 2021
iDNA-ABT: advanced deep learning model for detecting DNA methylation with adaptive features and transductive information maximizationYingying Yu, Wenjia He, Junru Jin, et al.
Pageof 3