Lingxia Chen

889 citations
29 papers · 661 · h-index 15

Impact in

Papers in

    • Immunodeficiency and Autoimmune Disorders 3
    • Immune responses and vaccinations 3
    • Tuberculosis Research and Epidemiology 4

Lingxia Chen

27 papers receiving 644 citations

Peers

Lingxia Chen
Comparison fields: 5 of 70
  • Infectious Diseases 171
  • Genetics 240
  • Molecular Medicine 42
  • Immunology 117
  • Molecular Biology 320
Replace Jenna McCracken with:
Jenna McCracken United States
Farshid Yeganeh Iran
Jacob J. Baker United States
Robert A. Bonnah United States
Laura E. Gordy United States
Mabel M. Beitsma Netherlands
Ekaterina I. Mokhonova United States
Michelle Mintz United States
Sun Hwa Lee South Korea
Ji‐Hun Lim South Korea
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Citations per field
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Jenna McCracken · 1×
Citations per year

Countries citing papers authored by Lingxia Chen

Since Specialization
Citations

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

Fields of papers citing papers by Lingxia Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lingxia Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lingxia Chen Line = papers co-authored together Lingxia Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200779
2 201070
3 201152
4 200843
5 202138
6 201136
7 200736
8 202236
9 201431
10 201129
11 200927
12 201224
13 202120
14 201920
15 202318
16 202215
17 202212
18 202412
19 202311
20 201511

About Lingxia Chen

Lingxia Chen is a scholar working on Immunology, Infectious Diseases, Genetics, Molecular Medicine and Molecular Biology, having authored 29 papers that have together received 661 indexed citations. Recurring topics across this work include Virus-based gene therapy research (8 papers), Tuberculosis Research and Epidemiology (4 papers), Immunodeficiency and Autoimmune Disorders (3 papers), Viral Infectious Diseases and Gene Expression in Insects (3 papers), Immune responses and vaccinations (3 papers), Antibiotic Resistance in Bacteria (3 papers), RNA Interference and Gene Delivery (3 papers) and CRISPR and Genetic Engineering (2 papers). The work is most often cited by research in Infectious Diseases (171 citations), Genetics (240 citations), Molecular Medicine (42 citations), Immunology (117 citations) and Molecular Biology (320 citations). Lingxia Chen has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Weidong Xiao, Hui Lu, Jinhui Wang, Xionglin Fan, Zhenhua Chen, Chunwei Shi, Bernd Hauck, Ying Zhang, Jia Lu and Chun Wang. Their work appears in journals such as Molecular Therapy, Infection and Drug Resistance, Human Gene Therapy, Vaccine and Journal of Infection and Public Health.

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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