Sen Wang

1.3k total citations
43 papers, 834 citations indexed

About

Sen Wang is a scholar working on Infectious Diseases, Epidemiology and Surgery. According to data from OpenAlex, Sen Wang has authored 43 papers receiving a total of 834 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Infectious Diseases, 19 papers in Epidemiology and 12 papers in Surgery. Recurrent topics in Sen Wang's work include Tuberculosis Research and Epidemiology (21 papers), Mycobacterium research and diagnosis (17 papers) and Infectious Diseases and Tuberculosis (7 papers). Sen Wang is often cited by papers focused on Tuberculosis Research and Epidemiology (21 papers), Mycobacterium research and diagnosis (17 papers) and Infectious Diseases and Tuberculosis (7 papers). Sen Wang collaborates with scholars based in China, United States and South Korea. Sen Wang's co-authors include Lingyun Shao, Jing Wu, Yan Gao, Wenhong Zhang, Jiazhen Chen, Xinhua Weng, Chanyi Lu, Ni Diao, Ying Zhang and Feifei Wang and has published in prestigious journals such as Nature Communications, PLoS ONE and Biochemical and Biophysical Research Communications.

In The Last Decade

Sen Wang

42 papers receiving 826 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sen Wang China 16 515 378 242 216 126 43 834
Shuihua Lu China 18 591 1.1× 388 1.0× 269 1.1× 181 0.8× 280 2.2× 72 987
María Teresa Herrera Mexico 16 544 1.1× 460 1.2× 155 0.6× 218 1.0× 264 2.1× 29 870
Bishwa R. Sapkota United States 13 484 0.9× 416 1.1× 190 0.8× 249 1.2× 133 1.1× 24 951
Jessica A. Neil Australia 14 271 0.5× 159 0.4× 288 1.2× 74 0.3× 171 1.4× 22 743
Neven Papić Croatia 12 145 0.3× 343 0.9× 207 0.9× 157 0.7× 168 1.3× 47 776
Benjamin A. Miko United States 13 332 0.6× 254 0.7× 133 0.5× 44 0.2× 403 3.2× 30 982
Ching‐Fen Shen Taiwan 17 295 0.6× 278 0.7× 105 0.4× 51 0.2× 83 0.7× 61 673
Masaharu Shinkai Japan 13 263 0.5× 338 0.9× 214 0.9× 82 0.4× 158 1.3× 58 993

Countries citing papers authored by Sen Wang

Since Specialization
Citations

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

Fields of papers citing papers by Sen Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sen Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Sen Wang. A scholar is included among the top collaborators of Sen 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 Sen Wang. Sen Wang 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, Yuzhen, Jing Wu, Qianqian Liu, et al.. (2024). The diagnostic value and validation of IL-22 combined with sCD40L in tuberculosis pleural effusion. BMC Immunology. 25(1). 66–66.
2.
Zhang, Yi, et al.. (2023). Clinical and Microbiological Characteristics of Klebsiella pneumoniae Co-Infections in Pulmonary Tuberculosis: A Retrospective Study. Infection and Drug Resistance. Volume 16. 7175–7185. 6 indexed citations
3.
Cao, Guojun, Ke Lin, Jingwen Ai, et al.. (2022). A diagnostic accuracy study comparing RNA LAMP, direct LAMP, and rapid antigen testing from nasopharyngeal swabs. Frontiers in Microbiology. 13. 1063414–1063414. 7 indexed citations
4.
Shen, Yaojie, Jing Wu, Yan Gao, et al.. (2021). Effect of adjusted cut-offs of interferon-γ release assays on diagnosis of tuberculosis in patients with fever of unknown origin. Journal of Clinical Tuberculosis and Other Mycobacterial Diseases. 26. 100290–100290. 1 indexed citations
5.
Wang, Sen, Wenqing Gao, Rui Ge, et al.. (2021). E3 ligase TRIM25 ubiquitinates RIP3 to inhibit TNF induced cell necrosis. Cell Death and Differentiation. 28(10). 2888–2899. 41 indexed citations
6.
7.
Gao, Wenqing, Yuanyuan Li, Sen Wang, et al.. (2021). TRIM21 regulates pyroptotic cell death by promoting Gasdermin D oligomerization. Cell Death and Differentiation. 29(2). 439–450. 59 indexed citations
8.
9.
Wang, Sen, Xin Ma, Dahang Zhao, et al.. (2020). Finite element analysis of the initial stability of arthroscopic ankle arthrodesis with three-screw fixation: posteromedial versus posterolateral home-run screw. Journal of Orthopaedic Surgery and Research. 15(1). 252–252. 6 indexed citations
10.
Wang, Sen, Lei He, Jing Wu, et al.. (2019). Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis. Frontiers in Immunology. 10. 2948–2948. 27 indexed citations
11.
Li, Long, et al.. (2019). The Trp183 is essential in lactonohydrolase ZHD detoxifying zearalenone and zearalenols. Biochemical and Biophysical Research Communications. 522(4). 986–989. 4 indexed citations
12.
Wang, Sen, Yang Li, Yaojie Shen, et al.. (2018). Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB. Journal of Translational Medicine. 16(1). 206–206. 29 indexed citations
13.
Wang, Sen, Jing Wu, Jiazhen Chen, et al.. (2018). Evaluation of Mycobacterium tuberculosis-specific antibody responses for the discrimination of active and latent tuberculosis infection. International Journal of Infectious Diseases. 70. 1–9. 22 indexed citations
14.
Wu, Jing, Sen Wang, Chanyi Lu, et al.. (2016). Multiple cytokine responses in discriminating between active tuberculosis and latent tuberculosis infection. Tuberculosis. 102. 68–75. 42 indexed citations
15.
Han, Jian, Lili He, Wanliang Shi, et al.. (2014). Glycerol Uptake Is Important for L-Form Formation and Persistence in Staphylococcus aureus. PLoS ONE. 9(9). e108325–e108325. 28 indexed citations
16.
Jin, Jialin, Yaojie Shen, Xiaoping Fan, et al.. (2012). Underestimation of the Resistance of Mycobacterium tuberculosis to Second-Line Drugs by the New GenoType MTBDRsl Test. Journal of Molecular Diagnostics. 15(1). 44–50. 20 indexed citations
17.
Wang, Sen, Ni Diao, Chanyi Lu, et al.. (2012). Evaluation of the Diagnostic Potential of IP-10 and IL-2 as Biomarkers for the Diagnosis of Active and Latent Tuberculosis in a BCG-Vaccinated Population. PLoS ONE. 7(12). e51338–e51338. 77 indexed citations
18.
Lu, Chanyi, Jing Wu, Honghai Wang, et al.. (2011). Novel Biomarkers Distinguishing Active Tuberculosis from Latent Infection Identified by Gene Expression Profile of Peripheral Blood Mononuclear Cells. PLoS ONE. 6(8). e24290–e24290. 71 indexed citations
19.
Wu, Jing, Chanyi Lu, Ni Diao, et al.. (2011). Analysis of microRNA expression profiling identifies miR-155 and miR-155* as potential diagnostic markers for active tuberculosis: a preliminary study. Human Immunology. 73(1). 31–37. 96 indexed citations
20.
Chen, Jiazhen, Sen Wang, Ying Zhang, et al.. (2010). Rv1985c, a promising novel antigen for diagnosis of tuberculosis infection from BCG-vaccinated controls. BMC Infectious Diseases. 10(1). 273–273. 17 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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