Le Ou-Yang

1.7k citations

95 papers · 1.1k indexed · h-index 20

Impact in

Computational Theory and Mathematics top 2%
- Computational Drug Discovery Methods
Molecular Biology top 10%
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Gene Regulatory Network Analysis
- Single-cell and spatial transcriptomics
- Machine Learning in Bioinformatics
- Microbial Metabolic Engineering and Bioproduction
- Protein Structure and Dynamics

Papers in ⓘ

Molecular Biology 70
- Bioinformatics and Genomic Networks 51
- Gene expression and cancer classification 37
- Gene Regulatory Network Analysis 21
- Single-cell and spatial transcriptomics 18
- Machine Learning in Bioinformatics 10
- Protein Structure and Dynamics 7
Computational Theory and Mathematics 19
- Computational Drug Discovery Methods 17

Co-authors: Xiao-Fei Zhang (41 shared papers)Hong Yan (30 shared papers)Dao‐Qing Dai (13 shared papers)Min Wu (10 shared papers)Xiaoli Li (7 shared papers)Xing‐Ming Zhao (5 shared papers)Xiaohua Hu (9 shared papers)Mengyun Wu (6 shared papers)
Journals: Bioinformatics (12 papers)IEEE/ACM Transactions on Computational Biology and Bioinformatics (12 papers)BMC Bioinformatics (9 papers)Briefings in Bioinformatics (5 papers)IEEE Journal of Biomedical and Health Informatics (4 papers)
Partner nations: China Hong Kong Singapore

In The Last Decade

Le Ou-Yang

87 papers receiving 1.1k citations

Peers

Countries citing papers authored by Le Ou-Yang

Since Specialization

Citations

This map shows the geographic impact of Le Ou-Yang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Le Ou-Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Le Ou-Yang more than expected).

Fields of papers citing papers by Le Ou-Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Le Ou-Yang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Le Ou-Yang. The network helps show where Le Ou-Yang may publish in the future.

Co-authors

The 25 scholars most cited alongside Le Ou-Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Le Ou-Yang Line = papers co-authored together Le Ou-Yang links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 95 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Detecting temporal protein complexes from dynamic protein-protein interaction networks BMC Bioinformatics ·Le Ou-Yang, Dao‐Qing Dai, Xiaoli Li, Min Wu, Xiao-Fei Zhang, Peng Yang	2014	57
2	Predicting the impacts of mutations on protein-ligand binding affinity based on molecular dynamics simulations and machine learning methods Computational and Structural Biotechnology Journal ·Debby D. Wang, Le Ou-Yang, Haoran Xie, Mengxu Zhu, Hong Yan	2020	57
3	A graph regularized generalized matrix factorization model for predicting links in biomedical bipartite networks Bioinformatics ·Zi-Chao Zhang, Xiao-Fei Zhang, Min Wu, Le Ou-Yang, Xing‐Ming Zhao, Xiaoli Li	2020	56
4	Determining minimum set of driver nodes in protein-protein interaction networks BMC Bioinformatics ·Xiao-Fei Zhang, Le Ou-Yang, Yuan Zhu, Mengyun Wu, Dao‐Qing Dai	2015	44
5	Detecting overlapping protein complexes based on a generative model with functional and topological properties BMC Bioinformatics ·Xiao-Fei Zhang, Dao‐Qing Dai, Le Ou-Yang, Hong Yan	2014	35
6	Incorporating prior information into differential network analysis using non-paranormal graphical models Bioinformatics ·Xiao-Fei Zhang, Le Ou-Yang, Hong Yan	2017	35
7	Detecting Protein Complexes from Signed Protein-Protein Interaction Networks IEEE/ACM Transactions on Computational Biology and Bioinformatics ·Le Ou-Yang, Dao‐Qing Dai, Xiao-Fei Zhang	2015	34
8	Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS Nature Biotechnology ·Zhen He, Shuofeng Hu, Yaowen Chen, Sijing An, Jiahao Zhou, Runyan Liu, Junfeng Shi, Jing Wang, Guohua Dong, Jinhui Shi, Jiaxin Zhao, Le Ou-Yang, Yuan Zhu, Xiaochen Bo, Xiaomin Ying	2024	32
9	Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization BMC Bioinformatics ·Jiang Huang, Min Wu, Fan Lü, Le Ou-Yang, Zexuan Zhu	2019	31
10	Self-weighted adaptive structure learning for ASD diagnosis via multi-template multi-center representation Medical Image Analysis ·Fanglin Huang, Ee-Leng Tan, Peng Yang, Shan Huang, Le Ou-Yang, Jiuwen Cao, Tianfu Wang, Baiying Lei	2020	29
11	Differential network analysis from cross-platform gene expression data Scientific Reports ·Xiao-Fei Zhang, Le Ou-Yang, Xing‐Ming Zhao, Hong Yan	2016	29
12	EnImpute: imputing dropout events in single-cell RNA-sequencing data via ensemble learning Bioinformatics ·Xiao-Fei Zhang, Le Ou-Yang, Shuo Yang, Xing‐Ming Zhao, Xiaohua Hu, Hong Yan	2019	27
13	Protein Complex Detection via Weighted Ensemble Clustering Based on Bayesian Nonnegative Matrix Factorization PLoS ONE ·Le Ou-Yang, Dao‐Qing Dai, Xiao-Fei Zhang	2013	26
14	scTSSR: gene expression recovery for single-cell RNA sequencing using two-side sparse self-representation Bioinformatics ·Ke Jin, Le Ou-Yang, Xing‐Ming Zhao, Hong Yan, Xiao-Fei Zhang	2020	25
15	T3SEpp: an Integrated Prediction Pipeline for Bacterial Type III Secreted Effectors mSystems ·Xinjie Hui, Zewei Chen, Mingxiong Lin, Junya Zhang, Yueming Hu, Yingying Zeng, Xi Cheng, Le Ou-Yang, Ming-an Sun, Aaron P. White, Wang Yejun	2020	23
16	Integrating node embeddings and biological annotations for genes to predict disease-gene associations BMC Systems Biology ·Sezin Kircali Ata, Le Ou-Yang, Yuan Fang, Chee-Keong Kwoh, Min Wu, Xiaoli Li	2018	22
17	Graph Convolutional Network Analysis for Mild Cognitive Impairment Prediction Xin Zhao, Feng Zhou, Le Ou-Yang, Tianfu Wang, Baiying Lei	2019	22
18	RepLong: de novo repeat identification using long read sequencing data Bioinformatics ·Rui Guo, Yan-Ran Li, Shan He, Le Ou-Yang, Yiwen Sun, Zexuan Zhu	2017	21
19	Identifying Gene Network Rewiring by Integrating Gene Expression and Gene Network Data IEEE/ACM Transactions on Computational Biology and Bioinformatics ·Ting Xu, Le Ou-Yang, Xiaohua Hu, Xiao-Fei Zhang	2018	20
20	Regularized logistic regression with network-based pairwise interaction for biomarker identification in breast cancer BMC Bioinformatics ·Mengyun Wu, Xiao-Fei Zhang, Dao‐Qing Dai, Le Ou-Yang, Yuan Zhu, Hong Yan	2016	19

About Le Ou-Yang

Le Ou-Yang is a scholar working on Molecular Biology, Computational Theory and Mathematics, Cancer Research, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 95 papers that have together received 1.1k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (51 papers), Gene expression and cancer classification (37 papers), Gene Regulatory Network Analysis (21 papers), Single-cell and spatial transcriptomics (18 papers), Computational Drug Discovery Methods (17 papers), Machine Learning in Bioinformatics (10 papers), Protein Structure and Dynamics (7 papers) and Cancer-related molecular mechanisms research (5 papers). The work is most often cited by research in Computational Theory and Mathematics (231 citations), Molecular Biology (840 citations), Computational Mathematics (6 citations), Cancer Research (102 citations) and Biophysics (26 citations). Le Ou-Yang has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Xiao-Fei Zhang, Hong Yan, Dao‐Qing Dai, Min Wu, Xiaoli Li, Xing‐Ming Zhao, Xiaohua Hu, Mengyun Wu, Yuan Zhu and Zexuan Zhu. Their work appears in journals such as Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, BMC Bioinformatics, Briefings in Bioinformatics and IEEE Journal of Biomedical and Health Informatics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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