Shanshan Sha

435 total citations
30 papers, 293 citations indexed

About

Shanshan Sha is a scholar working on Molecular Biology, Epidemiology and Infectious Diseases. According to data from OpenAlex, Shanshan Sha has authored 30 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 19 papers in Epidemiology and 17 papers in Infectious Diseases. Recurrent topics in Shanshan Sha's work include Tuberculosis Research and Epidemiology (16 papers), Mycobacterium research and diagnosis (14 papers) and Gut microbiota and health (6 papers). Shanshan Sha is often cited by papers focused on Tuberculosis Research and Epidemiology (16 papers), Mycobacterium research and diagnosis (14 papers) and Gut microbiota and health (6 papers). Shanshan Sha collaborates with scholars based in China, United States and Japan. Shanshan Sha's co-authors include Yufang Ma, Yi Xin, Yan Zhou, Xiaoxia Shi, Jian Kang, Guoying Deng, Xin Yi, Liqiu Jia, Xiaochi Ma and Jian Kang and has published in prestigious journals such as American Journal of Respiratory and Critical Care Medicine, Analytical Biochemistry and International Journal of Molecular Sciences.

In The Last Decade

Shanshan Sha

28 papers receiving 290 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shanshan Sha China 11 152 110 82 37 28 30 293
Amit Kumar Singh India 14 317 2.1× 146 1.3× 67 0.8× 25 0.7× 17 0.6× 26 551
Rinie van Beuningen United States 10 164 1.1× 124 1.1× 60 0.7× 26 0.7× 7 0.3× 19 502
Meera Gurumurthy Singapore 11 277 1.8× 185 1.7× 134 1.6× 33 0.9× 23 0.8× 21 426
Hirokazu Ohbayashi Japan 7 242 1.6× 42 0.4× 53 0.6× 122 3.3× 24 0.9× 15 434
Abramo C. Ottolenghi United States 10 190 1.3× 145 1.3× 135 1.6× 21 0.6× 27 1.0× 21 432
Mengxuan Wang China 11 132 0.9× 73 0.7× 33 0.4× 26 0.7× 34 1.2× 39 333
Jose C. Granados United States 9 129 0.8× 74 0.7× 68 0.8× 35 0.9× 58 2.1× 12 389
Monique J. Williams South Africa 13 227 1.5× 151 1.4× 157 1.9× 19 0.5× 30 1.1× 24 448
Deborah Mai United States 5 253 1.7× 382 3.5× 302 3.7× 31 0.8× 46 1.6× 5 593
Nida Jamil Khan India 10 99 0.7× 86 0.8× 18 0.2× 20 0.5× 8 0.3× 25 269

Countries citing papers authored by Shanshan Sha

Since Specialization
Citations

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

Fields of papers citing papers by Shanshan Sha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanshan Sha

This figure shows the co-authorship network connecting the top 25 collaborators of Shanshan Sha. A scholar is included among the top collaborators of Shanshan Sha 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 Shanshan Sha. Shanshan Sha 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.
Zheng, Ning, Shenghui Li, Jian Kang, et al.. (2025). Characterization of the gut mycobiome in patients with non-alcoholic fatty liver disease and correlations with serum metabolome. BMC Microbiology. 25(1). 660–660.
2.
Yang, Jing, Danping Liu, Yi Wang, et al.. (2024). Dupilumab therapy improves gut microbiome dysbiosis and tryptophan metabolism in Chinese patients with atopic dermatitis. International Immunopharmacology. 131. 111867–111867. 9 indexed citations
3.
4.
Tang, Zhenzhen, et al.. (2024). Novel metabolic biomarkers for the diagnosis of acute ischemic stroke. Biomarkers in Medicine. 18(17-18). 727–737.
5.
Sha, Shanshan, Changyan Liu, Lin Zhao, et al.. (2024). Multikingdom characterization of gut microbiota in patients with rheumatoid arthritis and rheumatoid arthritis‐associated interstitial lung disease. Journal of Medical Virology. 96(7). e29781–e29781. 12 indexed citations
6.
Zhang, Jiaqi, et al.. (2024). Cellulase Promotes Mycobacterial Biofilm Dispersal in Response to a Decrease in the Bacterial Metabolite Gamma-Aminobutyric Acid. International Journal of Molecular Sciences. 25(2). 1051–1051. 6 indexed citations
7.
Guo, Ruochun, Shanshan Sha, Changming Chen, et al.. (2024). A population-scale analysis of 36 gut microbiome studies reveals universal species signatures for common diseases. npj Biofilms and Microbiomes. 10(1). 96–96. 8 indexed citations
8.
Liu, Yingying, Jiaqi Zhang, Wenzhen Wang, et al.. (2023). Mycobacterium tuberculosis Rv1987 protein attenuates inflammatory response and consequently alters microbiota in mouse lung. Frontiers in Cellular and Infection Microbiology. 13. 1256866–1256866. 3 indexed citations
9.
Liu, Dongqi, Gang Liu, Yuqing Li, et al.. (2021). Rapid glycosylation analysis of mouse serum glycoproteins separated by supported molecular matrix electrophoresis. Journal of Proteomics. 234. 104098–104098. 2 indexed citations
10.
Qiu, Tianming, Jingyuan Zhang, Shanshan Sha, et al.. (2021). Perfluorooctane sulfonate induces autophagy-dependent lysosomal membrane permeabilization by weakened interaction between tyrosinated alpha-tubulin and spinster 1. Food and Chemical Toxicology. 157. 112540–112540. 8 indexed citations
12.
Jia, Liqiu, et al.. (2021). Functional analysis and enzyme characterization of mannose-1-phosphate guanylyl transferase (ManB) from Mycobacterium tuberculosis. Research in Microbiology. 173(1-2). 103884–103884. 7 indexed citations
13.
Jia, Liqiu, et al.. (2021). Effect of Protein O-Mannosyltransferase (MSMEG_5447) on M. smegmatis and Its Survival in Macrophages. Frontiers in Microbiology. 12. 657726–657726. 5 indexed citations
14.
Sha, Shanshan, et al.. (2018). An integrated course based on two dimensional‐electrophoresis and mass spectrometry analysis to teach proteomic techniques for undergraduate students. Biochemistry and Molecular Biology Education. 46(4). 354–360. 3 indexed citations
15.
Sha, Shanshan, Xiaoxia Shi, Guoying Deng, et al.. (2017). Mycobacterium tuberculosis Rv1987 induces Th2 immune responses and enhances Mycobacterium smegmatis survival in mice. Microbiological Research. 197. 74–80. 20 indexed citations
16.
Yan, Qiulong, Changming Chen, Shenghui Li, et al.. (2016). Metagenomic Analysis of Sputum Microbiome as a Tool toward Culture-Independent Pathogen Detection of Patients with Ventilator-associated Pneumonia. American Journal of Respiratory and Critical Care Medicine. 194(5). 636–639. 12 indexed citations
17.
Shi, Xiaoxia, Shanshan Sha, Likun Liu, Xin Li, & Yufang Ma. (2016). A 96-well microtiter plate assay for high-throughput screening of Mycobacterium tuberculosis dTDP-d-glucose 4,6-dehydratase inhibitors. Analytical Biochemistry. 498. 53–58. 15 indexed citations
19.
Xu, Liming, Dongting Wu, Liang Liu, et al.. (2014). Characterization of mycobacterial UDP-N-acetylglucosamine enolpyruvyle transferase (MurA). Research in Microbiology. 165(2). 91–101. 18 indexed citations
20.
Zhou, Yan, Yi Xin, Shanshan Sha, & Yufang Ma. (2011). Kinetic properties of Mycobacterium tuberculosis bifunctional GlmU. Archives of Microbiology. 193(10). 751–757. 27 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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