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Scientific Reports
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November 5, 2017
A deep ensemble model to predict miRNA-disease association
Laiyi Fu, Qinke Peng
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|
April 6, 2019
Predicting DNA Methylation States with Hybrid Information Based Deep-Learning Model
Laiyi Fu, Qinke Peng, Ling Chai
Briefings in Bioinformatics
|
August 3, 2025
Dual balanced augmented topological noncoding RNA disease triplet association in heterogeneous graphs
Laiyi Fu, Yangyi Zhou, Hongqiang Lyu, et al.
Briefings in Bioinformatics
|
May 11, 2026
Biased multi-view contrastive learning with attentive masking for spatial transcriptomic analysis
Laiyi Fu, Wenkai Cui, Yifan Chen, et al.
Briefings in Bioinformatics
|
October 23, 2024
ACLNDA: an asymmetric graph contrastive learning framework for predicting noncoding RNA-disease associations in heterogeneous graphs
Laiyi Fu, ZhiYuan Yao, Yangyi Zhou, et al.
Science Advances
|
December 23, 2020
Predicting transcription factor binding in single cells through deep learning
Laiyi Fu, Lihua Zhang, Emmanuel Dollinger, et al.
Briefings in Bioinformatics
|
June 29, 2025
DeepExDC interprets genomic compartmentalization changes in single-cell Hi-C data
Hongqiang Lyu, Pei Cao, Wenyao Long, et al.
Briefings in Bioinformatics
|
August 17, 2023
KGETCDA: an efficient representation learning framework based on knowledge graph encoder from transformer for predicting circRNA-disease associations
Jinyang Wu, Zhiwei Ning, Yidong Ding, et al.
Bioinformatics (Oxford, England)
|
March 7, 2024
Identifying TAD-like domains on single-cell Hi-C data by graph embedding and changepoint detection
Erhu Liu, Hongqiang Lyu, Yuan Liu, et al.
Nucleic Acids Research
|
November 18, 2021
UFold: fast and accurate RNA secondary structure prediction with deep learning
Laiyi Fu, Yingxin Cao, Jie Wu, et al.
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Search research articles
Search
Showing results (1-10 of 19) with videos related to
Sort By:
Page
of 2
Scientific Reports
|
November 5, 2017
A deep ensemble model to predict miRNA-disease association
Laiyi Fu, Qinke Peng
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|
April 6, 2019
Predicting DNA Methylation States with Hybrid Information Based Deep-Learning Model
Laiyi Fu, Qinke Peng, Ling Chai
Briefings in Bioinformatics
|
August 3, 2025
Dual balanced augmented topological noncoding RNA disease triplet association in heterogeneous graphs
Laiyi Fu, Yangyi Zhou, Hongqiang Lyu, et al.
Briefings in Bioinformatics
|
May 11, 2026
Biased multi-view contrastive learning with attentive masking for spatial transcriptomic analysis
Laiyi Fu, Wenkai Cui, Yifan Chen, et al.
Briefings in Bioinformatics
|
October 23, 2024
ACLNDA: an asymmetric graph contrastive learning framework for predicting noncoding RNA-disease associations in heterogeneous graphs
Laiyi Fu, ZhiYuan Yao, Yangyi Zhou, et al.
Science Advances
|
December 23, 2020
Predicting transcription factor binding in single cells through deep learning
Laiyi Fu, Lihua Zhang, Emmanuel Dollinger, et al.
Briefings in Bioinformatics
|
June 29, 2025
DeepExDC interprets genomic compartmentalization changes in single-cell Hi-C data
Hongqiang Lyu, Pei Cao, Wenyao Long, et al.
Briefings in Bioinformatics
|
August 17, 2023
KGETCDA: an efficient representation learning framework based on knowledge graph encoder from transformer for predicting circRNA-disease associations
Jinyang Wu, Zhiwei Ning, Yidong Ding, et al.
Bioinformatics (Oxford, England)
|
March 7, 2024
Identifying TAD-like domains on single-cell Hi-C data by graph embedding and changepoint detection
Erhu Liu, Hongqiang Lyu, Yuan Liu, et al.
Nucleic Acids Research
|
November 18, 2021
UFold: fast and accurate RNA secondary structure prediction with deep learning
Laiyi Fu, Yingxin Cao, Jie Wu, et al.
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of 2