Search research articles
Contact Us
Filters
Showing results (1-10 of 25) with videos related to
Page
of 3
Sort By:
Methods (San Diego, Calif.)
|
January 30, 2022
Mouse4mC-BGRU: Deep learning for predicting DNA N4-methylcytosine sites in mouse genome
Junru Jin, Yingying Yu, Leyi Wei
Computers in Biology and Medicine
|
November 13, 2023
MolCAP: Molecular Chemical reActivity Pretraining and prompted-finetuning enhanced molecular representation learning
Yu 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 model
Zhongshen 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 Prediction
Yanxi Zhao, Junru Jin, Wenjia Gao, et al.
Bioinformatics (Oxford, England)
|
May 23, 2022
Predicting protein-peptide binding residues via interpretable deep learning
Ruheng Wang, Junru Jin, Quan Zou, et al.
Genomics, Proteomics & Bioinformatics
|
December 2, 2025
HGCPep: Hypergraph Deep Learning Identifies Cancer-associated Non-coding Peptides
Wentao 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 Only
Xuetong 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 Prediction
Jianbo 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 peptides
Zhongshen 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 maximization
Yingying Yu, Wenjia He, Junru Jin, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 25) with videos related to
Sort By:
Page
of 3
Methods (San Diego, Calif.)
|
January 30, 2022
Mouse4mC-BGRU: Deep learning for predicting DNA N4-methylcytosine sites in mouse genome
Junru Jin, Yingying Yu, Leyi Wei
Computers in Biology and Medicine
|
November 13, 2023
MolCAP: Molecular Chemical reActivity Pretraining and prompted-finetuning enhanced molecular representation learning
Yu 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 model
Zhongshen 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 Prediction
Yanxi Zhao, Junru Jin, Wenjia Gao, et al.
Bioinformatics (Oxford, England)
|
May 23, 2022
Predicting protein-peptide binding residues via interpretable deep learning
Ruheng Wang, Junru Jin, Quan Zou, et al.
Genomics, Proteomics & Bioinformatics
|
December 2, 2025
HGCPep: Hypergraph Deep Learning Identifies Cancer-associated Non-coding Peptides
Wentao 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 Only
Xuetong 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 Prediction
Jianbo 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 peptides
Zhongshen 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 maximization
Yingying Yu, Wenjia He, Junru Jin, et al.
Page
of 3