Ying Ma

5.8k total citations · 1 hit paper
125 papers, 4.8k citations indexed

About

Ying Ma is a scholar working on Infectious Diseases, Parasitology and Immunology. According to data from OpenAlex, Ying Ma has authored 125 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Infectious Diseases, 36 papers in Parasitology and 33 papers in Immunology. Recurrent topics in Ying Ma's work include Viral Infections and Vectors (58 papers), Vector-borne infectious diseases (35 papers) and Viral Infections and Outbreaks Research (20 papers). Ying Ma is often cited by papers focused on Viral Infections and Vectors (58 papers), Vector-borne infectious diseases (35 papers) and Viral Infections and Outbreaks Research (20 papers). Ying Ma collaborates with scholars based in China, United States and Germany. Ying Ma's co-authors include Janis J. Weis, John H. Weis, Stefanie N. Vogel, Matthew Hirschfeld, James F. Zachary, Carsten J. Kirschning, Boquan Jin, Tom Morrison, Anne Sturrock and R. Mark Wooten and has published in prestigious journals such as Journal of Clinical Investigation, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Ying Ma

119 papers receiving 4.7k citations

Hit Papers

Cutting Edge: Repurification of Lipopolysaccharide Elimin... 2000 2026 2008 2017 2000 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ying Ma China 34 1.7k 1.7k 1.5k 848 663 125 4.8k
Hiroshi Suzuki Japan 46 1.6k 0.9× 1.3k 0.8× 1.7k 1.1× 1.6k 1.9× 888 1.3× 279 7.6k
Zhongdao Wu China 34 539 0.3× 453 0.3× 2.1k 1.4× 1.5k 1.7× 261 0.4× 256 5.1k
Emil Skamene Canada 49 3.1k 1.8× 2.6k 1.6× 620 0.4× 2.2k 2.6× 2.4k 3.7× 199 9.3k
Jonathan K. Stiles United States 34 1.2k 0.7× 379 0.2× 411 0.3× 994 1.2× 616 0.9× 116 5.3k
Ying Wu China 32 828 0.5× 2.3k 1.4× 171 0.1× 1.0k 1.2× 1.4k 2.1× 247 4.8k
Marije Oosting Netherlands 38 3.1k 1.8× 1.9k 1.2× 425 0.3× 2.8k 3.2× 1.4k 2.1× 75 7.2k
Andréa Teixeira‐Carvalho Brazil 37 1.5k 0.9× 548 0.3× 990 0.7× 717 0.8× 2.1k 3.2× 270 5.1k
Kris Chadee Canada 51 1.3k 0.7× 2.7k 1.6× 1.7k 1.1× 2.9k 3.4× 604 0.9× 158 7.8k
Masao Mitsuyama Japan 36 2.0k 1.1× 676 0.4× 344 0.2× 1.4k 1.7× 847 1.3× 154 4.6k
Amy G. Hise United States 30 1.3k 0.8× 1.2k 0.7× 270 0.2× 1.1k 1.3× 742 1.1× 41 3.5k

Countries citing papers authored by Ying Ma

Since Specialization
Citations

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

Fields of papers citing papers by Ying Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ying Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Ying Ma. A scholar is included among the top collaborators of Ying Ma 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 Ying Ma. Ying Ma 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.
Zhang, Yusi, He Liu, Huiyuan Zhang, et al.. (2025). Hantaan virus infection induces human mucosal-associated invariant T cell pyroptosis through IRE1α pathway. Communications Biology. 8(1). 538–538. 1 indexed citations
2.
Tang, Kang, Linfeng Cheng, Yusi Zhang, et al.. (2023). Increased blood CD226 - inflammatory monocytes with low antigen presenting potential correlate positively with severity of hemorrhagic fever with renal syndrome. Annals of Medicine. 55(2). 2247000–2247000. 2 indexed citations
4.
Zhang, Yusi, Meng Wang, Kang Tang, et al.. (2022). HTNV infection induces activation and deficiency of CD8+MAIT cells in HFRS patients. Clinical & Experimental Immunology. 211(1). 1–14. 3 indexed citations
5.
Zhang, Huiyuan, Yazhen Wang, Ying Ma, et al.. (2022). Increased CD4+CD8+ Double Positive T Cells during Hantaan Virus Infection. Viruses. 14(10). 2243–2243. 9 indexed citations
6.
Zhang, Chunmei, Ying Ma, Kang Tang, et al.. (2022). Anti‐platelet factor 4/heparin antibodies in patients with Hantaan virus infection. Research and Practice in Thrombosis and Haemostasis. 6(7). e12813–e12813. 1 indexed citations
7.
Li, Pengcheng, Chunmei Zhang, Yusi Zhang, et al.. (2022). Elevation of Myeloperoxidase Correlates with Disease Severity in Patients with Hantaan Virus Infection. Viral Immunology. 35(6). 418–424.
10.
Lochhead, Robert B., James F. Zachary, Ying Ma, et al.. (2015). Antagonistic Interplay between MicroRNA-155 and IL-10 during Lyme Carditis and Arthritis. PLoS ONE. 10(8). e0135142–e0135142. 24 indexed citations
11.
Zhang, Yusi, Bei Liu, Ying Ma, et al.. (2014). Hantaan Virus Infection Induces CXCL10 Expression through TLR3, RIG-I, and MDA-5 Pathways Correlated with the Disease Severity. Mediators of Inflammation. 2014. 1–11. 27 indexed citations
12.
Lochhead, Robert B., Ying Ma, James F. Zachary, et al.. (2014). MicroRNA-146a Provides Feedback Regulation of Lyme Arthritis but Not Carditis during Infection with Borrelia burgdorferi. PLoS Pathogens. 10(6). e1004212–e1004212. 33 indexed citations
13.
Liu, Bei, Ying Ma, Jing Yi, et al.. (2013). Elevated Plasma Soluble Sema4D/CD100 Levels Are Associated with Disease Severity in Patients of Hemorrhagic Fever with Renal Syndrome. PLoS ONE. 8(9). e73958–e73958. 24 indexed citations
14.
Aldape, Michael J., Amy E. Bryant, Eva J. Katahira, et al.. (2009). Innate immune recognition of, and response to, Clostridium sordellii. Anaerobe. 16(2). 125–130. 14 indexed citations
15.
Jacobson, Amanda, et al.. (2007). Mice Lacking CD21 and CD35 Proteins Mount Effective Immune Responses againstBorrelia burgdorferiInfection. Infection and Immunity. 75(4). 2075–2078. 2 indexed citations
16.
Crandall, Hillary, Diane M. Dunn, Ying Ma, et al.. (2006). Gene Expression Profiling Reveals Unique Pathways Associated with Differential Severity of Lyme Arthritis. The Journal of Immunology. 177(11). 7930–7942. 69 indexed citations
17.
Bolz, Devin D., Rhianna S. Sundsbak, Ying Ma, et al.. (2004). MyD88 Plays a Unique Role in Host Defense but Not Arthritis Development in Lyme Disease. The Journal of Immunology. 173(3). 2003–2010. 125 indexed citations
18.
Yoder, Alyson, Xiaohui Wang, Ying Ma, et al.. (2003). Tripalmitoyl-S-Glyceryl-Cysteine-Dependent OspA Vaccination of Toll-Like Receptor 2-Deficient Mice Results in Effective Protection fromBorrelia burgdorferiChallenge. Infection and Immunity. 71(7). 3894–3900. 26 indexed citations
19.
Wooten, R. Mark, Ying Ma, Jeanette P. Brown, et al.. (2002). Toll-Like Receptor 2 Is Required for Innate, But Not Acquired, Host Defense to Borrelia burgdorferi. The Journal of Immunology. 168(1). 348–355. 278 indexed citations
20.
Hirschfeld, Matthew, Ying Ma, John H. Weis, Stefanie N. Vogel, & Janis J. Weis. (2000). Cutting Edge: Repurification of Lipopolysaccharide Eliminates Signaling Through Both Human and Murine Toll-Like Receptor 2. The Journal of Immunology. 165(2). 618–622. 1031 indexed citations breakdown →

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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