Min Wu

17.3k total citations · 8 hit papers
450 papers, 9.7k citations indexed

About

Min Wu is a scholar working on Molecular Biology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Min Wu has authored 450 papers receiving a total of 9.7k indexed citations (citations by other indexed papers that have themselves been cited), including 114 papers in Molecular Biology, 105 papers in Artificial Intelligence and 61 papers in Computer Vision and Pattern Recognition. Recurrent topics in Min Wu's work include Bioinformatics and Genomic Networks (47 papers), Computational Drug Discovery Methods (33 papers) and Anomaly Detection Techniques and Applications (21 papers). Min Wu is often cited by papers focused on Bioinformatics and Genomic Networks (47 papers), Computational Drug Discovery Methods (33 papers) and Anomaly Detection Techniques and Applications (21 papers). Min Wu collaborates with scholars based in China, Singapore and United States. Min Wu's co-authors include Xiaoli Li, Zhenghua Chen, Chee Keong Kwoh, Chee-Keong Kwoh, Ruqiang Yan, Ali Ezzat, See-Kiong Ng, Emadeldeen Eldele, Mohamed Ragab and Peilin Zhao and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Genes & Development.

In The Last Decade

Min Wu

399 papers receiving 9.5k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Machine Remaining Useful Life Prediction via an Attention-Based Deep Learning Approach

2020 437 citations Min Wu, Xiaoli Li et al. profile →
An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG

2021 378 citations Chengyu Liu, Min Wu et al. profile →
Time-Series Representation Learning via Temporal and Contextual Contrasting

2021 289 citations Min Wu, Chee Keong Kwoh et al. profile →
A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability

2020 259 citations Min Wu et al. profile →
Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST

2023 230 citations Yahui Long, Min Wu et al. Nature Communications profile →
Self-Supervised Contrastive Representation Learning for Semi-Supervised Time-Series Classification

2023 89 citations Min Wu, Chee Keong Kwoh et al. profile →
Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data

2024 41 citations Min Wu, Xiaoli Li et al. profile →
Graph Neural Network-Based EEG Classification: A Survey

2024 39 citations Min Wu et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Min Wu	3.6k	1.9k	1.6k	1.1k	861	450	9.7k
Xiaoli Li	4.3k 1.2×	4.2k 2.2×	2.0k 1.3×	1.3k 1.1×	1.8k 2.1×	531	13.9k
Yi Pan	6.6k 1.9×	2.6k 1.4×	3.2k 2.0×	230 0.2×	1.6k 1.9×	615	16.9k
Fuhui Long	2.4k 0.7×	3.0k 1.6×	552 0.4×	441 0.4×	2.4k 2.8×	31	9.5k
Jianxin Wang	10.3k 2.9×	2.1k 1.1×	4.0k 2.6×	205 0.2×	1.4k 1.6×	1.1k	22.1k
Gunnar Rätsch	5.1k 1.4×	4.9k 2.6×	653 0.4×	975 0.8×	4.6k 5.3×	167	16.1k
Guoyin Wang	1.3k 0.4×	5.1k 2.7×	4.0k 2.5×	408 0.4×	2.3k 2.7×	629	12.2k
Hua Liu	3.4k 1.0×	1.8k 1.0×	447 0.3×	177 0.2×	884 1.0×	308	10.4k
Paolo Frasconi	1.4k 0.4×	4.2k 2.2×	493 0.3×	946 0.8×	1.6k 1.8×	130	10.0k
Lifeng Wang	4.2k 1.2×	1.5k 0.8×	324 0.2×	183 0.2×	555 0.6×	172	10.0k
Fang‐Xiang Wu	8.0k 2.2×	1.4k 0.8×	2.6k 1.6×	326 0.3×	878 1.0×	443	12.2k

Countries citing papers authored by Min Wu

Since Specialization

Citations

This map shows the geographic impact of Min Wu'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 Min Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min Wu more than expected).

Fields of papers citing papers by Min Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Min Wu. 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 Min Wu. The network helps show where Min Wu may publish in the future.

Co-authorship network of co-authors of Min Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Min Wu. A scholar is included among the top collaborators of Min Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Min Wu. Min Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Ducamp, Sarah, Min Wu, Juan Putra, et al.. (2025). The GLYT1 inhibitor bitopertin mitigates erythroid PPIX production and liver disease in erythroid protoporphyria. Journal of Clinical Investigation. 135(18). 1 indexed citations

Gao, Hongxiang, et al.. (2025). Multimodal Fusion of Behavioral and Physiological Signals for Enhanced Emotion Recognition via Feature Decoupling and Knowledge Transfer. IEEE Journal of Biomedical and Health Informatics. 30(1). 208–218. 2 indexed citations

Yang, Xiao, et al.. (2024). Mediating effects of social support and presenteeism on turnover intention and post-traumatic stress disorder among Chinese nurses in the post-pandemic era: a cross-sectional study. Frontiers in Public Health. 12. 1323126–1323126. 4 indexed citations

Wu, Min, et al.. (2024). Machine learning-based prediction of the risk of moderate-to-severe catheter-related bladder discomfort in general anaesthesia patients: a prospective cohort study. BMC Anesthesiology. 24(1). 334–334. 2 indexed citations

Ma, Xiaoding, Jianli Yin, Yang Zhou, et al.. (2024). A programmable targeted protein-degradation platform for versatile applications in mammalian cells and mice. Molecular Cell. 84(8). 1585–1600.e7. 15 indexed citations

Long, Yahui, et al.. (2024). Benchmarking machine learning methods for synthetic lethality prediction in cancer. Nature Communications. 15(1). 9058–9058. 12 indexed citations

Li, Weimin, Hao Yu, Yingzhi Wang, et al.. (2024). Physiological and transcriptome analyses reveal copper toxicity responses in tomato plants. Environmental and Experimental Botany. 224. 105819–105819. 6 indexed citations

Hassan, Hasyma Abu, et al.. (2024). The value of amide proton transfer imaging in predicting parametrial invasion and lymph-vascular space invasion of cervical cancer. Magnetic Resonance Imaging. 116. 110282–110282.

Hu, Zeqi, Yitong Wang, Zhili Hu, et al.. (2024). Real-time 3D temperature field reconstruction for aluminum alloy forging die using Swin Transformer integrated deep learning framework. Applied Thermal Engineering. 260. 125033–125033. 6 indexed citations

10.

Ren, Xiaodong, Yali Zhang, Ming Zhuo, et al.. (2024). Inhibitors and PROTACs of CDK2: challenges and opportunities. Expert Opinion on Drug Discovery. 19(9). 1125–1148. 10 indexed citations

11.

Wu, Min, et al.. (2023). The influence of challenge research stressors on research creativity among Chinese doctoral students: a mediated moderation model. Frontiers in Psychology. 14. 1290342–1290342. 5 indexed citations

12.

Wu, Min, et al.. (2023). ERO1α promotes the proliferation and inhibits apoptosis of colorectal cancer cells by regulating the PI3K/AKT pathway. Journal of Molecular Histology. 54(6). 621–631. 3 indexed citations

13.

Chen, Jianneng, et al.. (2023). Rapid development methodology of agricultural robot navigation system working in GNSS-denied environment. Advances in Manufacturing. 11(4). 601–617. 8 indexed citations

14.

Zhu, Xiaomei, et al.. (2023). Spinal muscular atrophy with hypoplasia of the corpus callosum: a case report. BMC Neurology. 23(1). 77–77. 1 indexed citations

15.

Wu, Min, et al.. (2023). CYP4FB1 and CYP301B1 mediate the cross‐resistance of Laodelphax striatellus (Hemiptera: Delphacidae) to three pyrethroids. Journal of Applied Entomology. 148(3). 304–311. 2 indexed citations

16.

Xiong, Xin, Min Wu, Hong Peng, et al.. (2023). Time series classification models based on nonlinear spiking neural P systems. Engineering Applications of Artificial Intelligence. 129. 107603–107603. 3 indexed citations

17.

Lei, Min, Min Wu, Xiaosong Yang, et al.. (2023). Tirzepatide ameliorates spatial learning and memory impairment through modulation of aberrant insulin resistance and inflammation response in diabetic rats. Frontiers in Pharmacology. 14. 1146960–1146960. 31 indexed citations

18.

Long, Yahui, Min Wu, Yong Liu, et al.. (2021). Graph contextualized attention network for predicting synthetic lethality in human cancers. Bioinformatics. 37(16). 2432–2440. 31 indexed citations

19.

Li, Xuejuan, et al.. (2014). Syn-Lethality: An Integrative Knowledge Base of Synthetic Lethality towards Discovery of Selective Anticancer Therapies. BioMed Research International. 2014. 1–7. 22 indexed citations

20.

Yang, Peng, Xiaoli Li, Min Wu, Chee-Keong Kwoh, & See-Kiong Ng. (2011). Inferring Gene-Phenotype Associations via Global Protein Complex Network Propagation. PLoS ONE. 6(7). e21502–e21502. 68 indexed citations

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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