Xun Wang

4.1k total citations · 2 hit papers
98 papers, 2.8k citations indexed

About

Xun Wang is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Xun Wang has authored 98 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 32 papers in Computer Vision and Pattern Recognition and 29 papers in Artificial Intelligence. Recurrent topics in Xun Wang's work include Computational Drug Discovery Methods (13 papers), Machine Learning in Bioinformatics (12 papers) and Protein Structure and Dynamics (12 papers). Xun Wang is often cited by papers focused on Computational Drug Discovery Methods (13 papers), Machine Learning in Bioinformatics (12 papers) and Protein Structure and Dynamics (12 papers). Xun Wang collaborates with scholars based in China, United States and Spain. Xun Wang's co-authors include Matthew R. Scott, Weilin Huang, Ziyang Huo, Jinghui Zeng, Leyu Wang, Lun Wang, Jie Bao, Ruoxue Yan, Qing Peng and Yadong Li and has published in prestigious journals such as Journal of Biological Chemistry, Angewandte Chemie International Edition and PLoS ONE.

In The Last Decade

Xun Wang

87 papers receiving 2.7k citations

Hit Papers

align trajectories

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.

Fluorescence Resonant Energy Transfer Biosensor Based on Upconversion‐Luminescent Nanoparticles

2005 807 citations Xun Wang et al. profile →
Multi-Similarity Loss With General Pair Weighting for Deep Metric Learning

2019 493 citations Xun Wang et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Xun Wang China	20	889	827	703	603	460	98	2.8k
Yu Rong China	30	1.2k 1.4×	935 1.1×	627 0.9×	1.7k 2.9×	662 1.4×	110	4.2k
Fan Zhang China	25	459 0.5×	968 1.2×	415 0.6×	265 0.4×	162 0.4×	207	2.7k
Weijie Su United States	27	458 0.5×	283 0.3×	200 0.3×	405 0.7×	520 1.1×	126	2.8k
Yu-Xiong Wang China	28	923 1.0×	1.6k 1.9×	135 0.2×	1.4k 2.3×	175 0.4×	85	3.8k
Qian Xu China	30	729 0.8×	385 0.5×	132 0.2×	423 0.7×	519 1.1×	239	3.3k
Takashi Matsubara Japan	26	255 0.3×	377 0.5×	416 0.6×	394 0.7×	144 0.3×	197	2.7k
Tae‐Yeon Kim South Korea	24	272 0.3×	147 0.2×	150 0.2×	304 0.5×	381 0.8×	175	2.2k
Rainer Kümmerle Germany	30	291 0.3×	2.4k 2.8×	632 0.9×	330 0.5×	150 0.3×	64	4.9k
Yinhai Wang United Kingdom	13	651 0.7×	120 0.1×	669 1.0×	231 0.4×	207 0.5×	30	1.8k
Chenyang Zhang China	20	614 0.7×	644 0.8×	329 0.5×	267 0.4×	1.0k 2.3×	60	2.1k

Countries citing papers authored by Xun Wang

Since Specialization

Citations

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

Fields of papers citing papers by Xun Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xun Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Xun Wang. A scholar is included among the top collaborators of Xun Wang 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 Xun Wang. Xun Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Xun, Xiangyu Meng, Mingzhen Li, et al.. (2025). 29-Billion Atoms Molecular Dynamics Simulation With Ab Initio Accuracy on 35 Million Cores of New Sunway Supercomputer. IEEE Transactions on Computers. 74(5). 1634–1648. 1 indexed citations

Wang, Jianmin, Jiashun Mao, Chunyan Li, et al.. (2024). Interface-aware molecular generative framework for protein–protein interaction modulators. Journal of Cheminformatics. 16(1). 142–142. 5 indexed citations

Wang, Xun, et al.. (2024). Educational Practices and Algorithmic Framework for Promoting Sustainable Development in Education by Identifying Real-World Learning Paths. Sustainability. 16(16). 6871–6871. 3 indexed citations

Yang, Xibei, et al.. (2024). Sequential attention layer-wise fusion network for multi-view classification. International Journal of Machine Learning and Cybernetics. 15(12). 5549–5561. 4 indexed citations

Song, Tao, et al.. (2024). Attenphos: General Phosphorylation Site Prediction Model Based on Attention Mechanism. International Journal of Molecular Sciences. 25(3). 1526–1526. 3 indexed citations

Bao, W.Y., et al.. (2024). DockingGA: enhancing targeted molecule generation using transformer neural network and genetic algorithm with docking simulation. Briefings in Functional Genomics. 23(5). 595–606. 5 indexed citations

Song, Tao, et al.. (2024). DeepDualEnhancer: A Dual-Feature Input DNABert Based Deep Learning Method for Enhancer Recognition. International Journal of Molecular Sciences. 25(21). 11744–11744. 1 indexed citations

Wang, Xun, et al.. (2024). TBCA: Prediction of Transcription Factor Binding Sites Using a Deep Neural Network With Lightweight Attention Mechanism. IEEE Journal of Biomedical and Health Informatics. 28(4). 2397–2407. 5 indexed citations

Wang, Min, et al.. (2023). DMFF-Net: A dual encoding multiscale feature fusion network for ovarian tumor segmentation. Frontiers in Public Health. 10. 1054177–1054177. 3 indexed citations

10.

Wang, Xun, et al.. (2023). QuantumTox: Utilizing quantum chemistry with ensemble learning for molecular toxicity prediction. Computers in Biology and Medicine. 157. 106744–106744. 7 indexed citations

11.

Wang, Xun, et al.. (2023). Integrating Multiple Single-Cell RNA Sequencing Datasets Using Adversarial Autoencoders. International Journal of Molecular Sciences. 24(6). 5502–5502. 1 indexed citations

12.

Wang, Xun, Xudong Zhang, Ying Zhang, et al.. (2022). TransFusionNet: Semantic and Spatial Features Fusion Framework for Liver Tumor and Vessel Segmentation Under JetsonTX2. IEEE Journal of Biomedical and Health Informatics. 27(3). 1173–1184. 22 indexed citations

13.

Wang, Xun, et al.. (2022). IMGG: Integrating Multiple Single-Cell Datasets through Connected Graphs and Generative Adversarial Networks. International Journal of Molecular Sciences. 23(4). 2082–2082. 10 indexed citations

14.

Wang, Xun, et al.. (2022). TransPhos: A Deep-Learning Model for General Phosphorylation Site Prediction Based on Transformer-Encoder Architecture. International Journal of Molecular Sciences. 23(8). 4263–4263. 19 indexed citations

15.

Zhang, Xudong, Xiangyu Meng, Shuang Wang, et al.. (2022). Molormer: a lightweight self-attention-based method focused on spatial structure of molecular graph for drug–drug interactions prediction. Briefings in Bioinformatics. 23(5). 36 indexed citations

16.

Meng, Xiangyu, et al.. (2022). A Novel Attention-Mechanism Based Cox Survival Model by Exploiting Pan-Cancer Empirical Genomic Information. Cells. 11(9). 1421–1421. 10 indexed citations

17.

Pang, Shanchen, et al.. (2021). AMDE: a novel attention-mechanism-based multidimensional feature encoder for drug–drug interaction prediction. Briefings in Bioinformatics. 23(1). 59 indexed citations

18.

Meng, Xiangyu, et al.. (2021). A Computationally Virtual Histological Staining Method to Ovarian Cancer Tissue by Deep Generative Adversarial Networks. Computational and Mathematical Methods in Medicine. 2021. 1–12. 22 indexed citations

19.

Wang, Xun, et al.. (2021). DEMLP: DeepWalk Embedding in MLP for miRNA‐Disease Association Prediction. Journal of Sensors. 2021(1). 4 indexed citations

20.

Wang, Xun, et al.. (2017). A novel method for multifactorial bio-chemical experiments design based on combinational design theory. PLoS ONE. 12(11). e0186853–e0186853. 2 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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