Gang Xu

7.6k total citations · 1 hit paper
72 papers, 3.7k citations indexed

About

Gang Xu is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Gang Xu has authored 72 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 22 papers in Immunology and 15 papers in Infectious Diseases. Recurrent topics in Gang Xu's work include Metabolism, Diabetes, and Cancer (13 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and Pancreatic function and diabetes (10 papers). Gang Xu is often cited by papers focused on Metabolism, Diabetes, and Cancer (13 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and Pancreatic function and diabetes (10 papers). Gang Xu collaborates with scholars based in China, Hong Kong and United States. Gang Xu's co-authors include Zheng Zhang, Shuye Zhang, Yang Liu, Juanjuan Zhao, Ido Amit, Mingfeng Liao, Yanling Wen, Jing Yuan, Lin Cheng and Fuxiang Wang and has published in prestigious journals such as Cell, Journal of Biological Chemistry and Nature Medicine.

In The Last Decade

Gang Xu

66 papers receiving 3.7k citations

Hit Papers

Single-cell landscape of bronchoalveolar immune cells in ... 2020 2026 2022 2024 2020 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gang Xu China 24 1.5k 1.3k 945 655 544 72 3.7k
Keiji Kuba Japan 29 2.3k 1.5× 1.3k 1.0× 487 0.5× 845 1.3× 676 1.2× 59 5.2k
Yingmei Feng China 26 1.3k 0.8× 834 0.7× 452 0.5× 427 0.7× 661 1.2× 99 3.3k
Heng Fan China 28 984 0.6× 1.1k 0.9× 518 0.5× 489 0.7× 327 0.6× 101 3.3k
Zili Zhang China 18 967 0.6× 447 0.4× 630 0.7× 445 0.7× 180 0.3× 49 2.4k
Jérôme C. Martin France 22 1.4k 0.9× 855 0.7× 1.2k 1.3× 671 1.0× 288 0.5× 49 3.5k
Qing Chang China 30 857 0.6× 1.3k 1.1× 418 0.4× 152 0.2× 321 0.6× 128 3.4k
Nicolas Vuilleumier Switzerland 35 651 0.4× 649 0.5× 1.1k 1.2× 135 0.2× 738 1.4× 172 3.8k
Qiu Zhao China 31 2.3k 1.5× 1.2k 1.0× 369 0.4× 1.2k 1.9× 957 1.8× 102 5.1k
Gilles Hayem France 35 465 0.3× 729 0.6× 696 0.7× 306 0.5× 1.8k 3.2× 98 4.8k
Michael Gosselin United States 6 902 0.6× 681 0.5× 563 0.6× 273 0.4× 412 0.8× 9 3.2k

Countries citing papers authored by Gang Xu

Since Specialization
Citations

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

Fields of papers citing papers by Gang Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gang Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Gang Xu. A scholar is included among the top collaborators of Gang Xu 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 Gang Xu. Gang Xu 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.
Xu, Zhihao, Yajie Wang, Xiaohan Liu, et al.. (2025). Genome-wide CRISPR screening identifies LRP1 as an entry factor for SFTSV. Nature Communications. 16(1). 4036–4036.
2.
Bao, Xinyu, Qingyuan Yang, Wei Zhang, et al.. (2025). 5-Methoxytryptophan attenuates hypobaric hypoxia induced acute lung injury by alleviating lipid peroxidation via targeting peroxiredoxin 6. Redox Biology. 88. 103922–103922.
3.
Zhou, Yuzheng, Taijie Guo, Xiao Zhang, et al.. (2025). Discovery of SARS-CoV-2 PLpro inhibitors and RIPK1 inhibitors with synergistic antiviral efficacy in a mouse COVID-19 model. Acta Pharmaceutica Sinica B. 16(1). 387–405.
5.
Zhou, Jian, Yuzheng Zhou, Xiang Gao, et al.. (2024). TRIM6 facilitates SARS‐CoV‐2 proliferation by catalyzing the K29‐typed ubiquitination of NP to enhance the ability to bind viral genomes. Journal of Medical Virology. 96(3). e29531–e29531. 6 indexed citations
6.
Liu, Wei, Yuling Li, Yanyun He, et al.. (2024). Preclinical characterization of a novel investigational monoclonal antibody CM313 with potent CD38-positive cell killing activity. Frontiers in Immunology. 15. 1410457–1410457. 1 indexed citations
7.
He, Xiaomeng, Yanmei Lu, Furong Qi, et al.. (2023). Breakthrough infection evokes the nasopharyngeal innate immune responses established by SARS-CoV-2–inactivated vaccine. Frontiers in Immunology. 14. 1181121–1181121.
8.
Qin, Tao, et al.. (2023). Melatonin attenuates lipopolysaccharide-induced immune dysfunction in dendritic cells. International Immunopharmacology. 120. 110282–110282. 7 indexed citations
9.
Qin, Ying, Dekang Li, Chunting Qi, et al.. (2023). Structure-based development of potent and selective type-II kinase inhibitors of RIPK1. Acta Pharmaceutica Sinica B. 14(1). 319–334. 7 indexed citations
10.
Qi, Furong, Gang Xu, Xuejiao Liao, et al.. (2021). ScRNA-seq revealed the kinetic of nasopharyngeal immune responses in asymptomatic COVID-19 carriers. Cell Discovery. 7(1). 56–56. 6 indexed citations
11.
Yang, Lingling, Sarah Webb, Nana Jin, et al.. (2021). Investigating the role of dachshund b in the development of the pancreatic islet in zebrafish. Journal of Diabetes Investigation. 12(5). 710–727. 2 indexed citations
12.
Liu, Jianping, Jiali Shen, Jialin Dai, et al.. (2021). Development of potent and selective inhibitors targeting the papain-like protease of SARS-CoV-2. Cell chemical biology. 28(6). 855–865.e9. 63 indexed citations
13.
Xu, Gang, Furong Qi, Hanjie Li, et al.. (2020). The differential immune responses to COVID-19 in peripheral and lung revealed by single-cell RNA sequencing. Cell Discovery. 6(1). 73–73. 150 indexed citations
14.
Liao, Mingfeng, Yang Liu, Jing Yuan, et al.. (2020). Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19. Nature Medicine. 26(6). 842–844. 1562 indexed citations breakdown →
15.
Chen, Dewei, Yuyu Yang, Xian Cheng, et al.. (2015). Megakaryocytic Leukemia 1 Directs a Histone H3 Lysine 4 Methyltransferase Complex to Regulate Hypoxic Pulmonary Hypertension. Hypertension. 65(4). 821–833. 41 indexed citations
16.
C.W., Ronald, Wing Yee So, Claudia H.T. Tam, et al.. (2014). Genetic variants for type 2 diabetes and new-onset cancer in Chinese with type 2 diabetes. Diabetes Research and Clinical Practice. 103(2). 328–337. 9 indexed citations
17.
Yang, Xilin, Wing‐Yee So, Ronald C.W., et al.. (2012). Diabetes and cancer: the mechanistic implications of epidemiological analyses from the Hong Kong Diabetes Registry. Diabetes/Metabolism Research and Reviews. 28(5). 379–387. 35 indexed citations
18.
Yang, Xilin, Wing‐Yee So, Ronald C.W., et al.. (2012). Use of thiazolidinedione and cancer risk in Type 2 diabetes: The Hong Kong diabetes registry. Diabetes Research and Clinical Practice. 97(1). e13–e17. 11 indexed citations
19.
Yang, Xilin, Ronald C.W., Wing Yee So, et al.. (2010). Low triglyceride and nonuse of statins is associated with cancer in type 2 diabetes mellitus. Cancer. 117(4). 862–871. 22 indexed citations
20.
Yang, Xilin, Ronald C.W., Wing Yee So, et al.. (2009). White blood cell count and renin–angiotensin system inhibitors for the risk of cancer in type 2 diabetes. Diabetes Research and Clinical Practice. 87(1). 117–125. 13 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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