Xuemei Pu

2.7k total citations
136 papers, 2.2k citations indexed

About

Xuemei Pu is a scholar working on Molecular Biology, Materials Chemistry and Electrical and Electronic Engineering. According to data from OpenAlex, Xuemei Pu has authored 136 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Molecular Biology, 36 papers in Materials Chemistry and 30 papers in Electrical and Electronic Engineering. Recurrent topics in Xuemei Pu's work include Receptor Mechanisms and Signaling (20 papers), Computational Drug Discovery Methods (19 papers) and Luminescence and Fluorescent Materials (17 papers). Xuemei Pu is often cited by papers focused on Receptor Mechanisms and Signaling (20 papers), Computational Drug Discovery Methods (19 papers) and Luminescence and Fluorescent Materials (17 papers). Xuemei Pu collaborates with scholars based in China, Hong Kong and Poland. Xuemei Pu's co-authors include Yanzhi Guo, Menglong Li, Zhiyun Lu, Yan Huang, Anmin Tian, Ning‐Bew Wong, Yuan Yuan, Yan Jiao, Liang Zhou and Yihuan Zhao and has published in prestigious journals such as Advanced Materials, Angewandte Chemie International Edition and Nature Communications.

In The Last Decade

Xuemei Pu

130 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xuemei Pu China 25 819 652 651 310 281 136 2.2k
Martha A. Grover United States 33 1.0k 1.2× 570 0.9× 1.2k 1.8× 364 1.2× 302 1.1× 141 3.3k
Volker Settels Germany 15 1000 1.2× 400 0.6× 565 0.9× 136 0.4× 150 0.5× 22 1.8k
Takeshi Ishikawa Japan 30 621 0.8× 157 0.2× 876 1.3× 244 0.8× 324 1.2× 167 3.0k
Lin Shen China 22 659 0.8× 824 1.3× 329 0.5× 141 0.5× 141 0.5× 112 2.0k
Jens Niklas United States 39 1.3k 1.6× 1.3k 2.0× 1.4k 2.2× 375 1.2× 370 1.3× 145 4.8k
Thomas P. Stockfisch United States 9 468 0.6× 141 0.2× 422 0.6× 163 0.5× 255 0.9× 15 1.5k
Jens Smiatek Germany 32 489 0.6× 481 0.7× 783 1.2× 111 0.4× 366 1.3× 106 2.6k
Mary Jo Ondrechen United States 30 628 0.8× 324 0.5× 952 1.5× 73 0.2× 211 0.8× 102 2.8k
Jiyong Park South Korea 23 574 0.7× 258 0.4× 733 1.1× 100 0.3× 432 1.5× 74 2.1k
Xiyun Zhang China 28 423 0.5× 253 0.4× 1.2k 1.9× 70 0.2× 879 3.1× 96 3.3k

Countries citing papers authored by Xuemei Pu

Since Specialization
Citations

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

Fields of papers citing papers by Xuemei Pu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xuemei Pu

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

All Works

20 of 20 papers shown
1.
He, Jian, Yanling Wu, Li‐Lian Yuan, et al.. (2025). An inductive learning-based method for predicting drug-gene interactions using a multi-relational drug-disease-gene graph. Journal of Pharmaceutical Analysis. 15(8). 101347–101347.
2.
Qiao, Yong-Kang, et al.. (2025). Seismic evaluation of base-isolated nuclear power plants with various tuned inerter dampers. Soil Dynamics and Earthquake Engineering. 197. 109438–109438. 2 indexed citations
3.
4.
Li, Yuan, et al.. (2025). Deep Clustering-Based Immunotherapy Prediction for Gastric Cancer mRNA Vaccine Development. International Journal of Molecular Sciences. 26(6). 2453–2453.
5.
Liu, Chunhong, Xin Chen, Yanling Shen, et al.. (2024). Versatile chiroptical induction/manipulation through specific solvation of ion pairs by alcohols. Science China Chemistry. 68(2). 610–621. 4 indexed citations
6.
Sun, Ming, et al.. (2024). Enhancing chemistry-intuitive feature learning to improve prediction performance of optical properties. Chemical Science. 15(42). 17533–17546. 5 indexed citations
7.
Liu, Yiran, et al.. (2024). Data-Quality-Navigated Machine Learning Strategy with Chemical Intuition to Improve Generalization. Journal of Chemical Theory and Computation. 20(23). 10633–10648. 4 indexed citations
8.
9.
Chen, Jianfang, et al.. (2023). Multi-omics integration analysis of GPCRs in pan-cancer to uncover inter-omics relationships and potential driver genes. Computers in Biology and Medicine. 161. 106988–106988. 10 indexed citations
10.
Li, Chuan, Jianfang Chen, Yuan Yuan, et al.. (2022). An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors. Journal of Chemical Information and Modeling. 62(6). 1399–1410. 18 indexed citations
11.
Zhang, Haichuan, et al.. (2022). Analysis and Development Review of Metal and Metal/Ceramic Composite Coating Prepared on Magnesium Alloy Surface. Journal of Physics Conference Series. 2152(1). 12025–12025.
12.
Li, Shiqi, Jianfang Chen, Xin Chen, et al.. (2022). Therapeutic and prognostic potential of GPCRs in prostate cancer from multi-omics landscape. Frontiers in Pharmacology. 13. 997664–997664. 6 indexed citations
13.
Luo, Yanju, Kai Zhang, Xiaomei Peng, et al.. (2022). Ultra-fast triplet-triplet-annihilation-mediated high-lying reverse intersystem crossing triggered by participation of nπ*-featured excited states. Nature Communications. 13(1). 6892–6892. 41 indexed citations
14.
Xiao, Xiuchan, et al.. (2021). Prediction of Synergistic Drug Combinations for Prostate Cancer by Transcriptomic and Network Characteristics. Frontiers in Pharmacology. 12. 634097–634097. 11 indexed citations
15.
Yang, Zongwei, Jiali Guo, Hongzhen Li, et al.. (2021). Coupling complementary strategy to flexible graph neural network for quick discovery of coformer in diverse co-crystal materials. Nature Communications. 12(1). 5950–5950. 75 indexed citations
16.
Li, Chuan, et al.. (2019). A Novel Convolutional Neural Network Architecture for SAR Target Recognition. Journal of Sensors. 2019. 1–9. 30 indexed citations
17.
He, Xuan, Yu Liu, Shiliang Huang, et al.. (2018). Raman spectroscopy coupled with principal component analysis to quantitatively analyze four crystallographic phases of explosive CL-20. RSC Advances. 8(41). 23348–23352. 29 indexed citations
18.
Zhang, Liyun, Yuzhi Li, Yuan Yuan, et al.. (2016). Molecular mechanism of carbon nanotube to activate Subtilisin Carlsberg in polar and non-polar organic media. Scientific Reports. 6(1). 36838–36838. 11 indexed citations
19.
Dai, Xing, Runyu Jing, Yanzhi Guo, et al.. (2015). Predicting the Druggability of Protein-Protein Interactions Based on Sequence and Structure Features of Active Pockets. Current Pharmaceutical Design. 21(21). 3051–3061. 3 indexed citations
20.
Guo, Yanzhi, et al.. (2010). PRED_PPI: a server for predicting protein-protein interactions based on sequence data with probability assignment. BMC Research Notes. 3(1). 145–145. 48 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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