Lie Mao

936 citations
13 papers · 643 · h-index 10

Impact in

    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 detection and testing
    • Tuberculosis Research and Epidemiology
  • Immunology top 10%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology

Papers in

    • Immune Cell Function and Interaction 7
    • T-cell and B-cell Immunology 4
    • Reproductive System and Pregnancy 2
    • IL-33, ST2, and ILC Pathways 1
    • Tuberculosis Research and Epidemiology 3

Lie Mao

13 papers receiving 631 citations

Peers

Lie Mao
Comparison fields: 5 of 94
  • Infectious Diseases 327
  • Immunology 229
  • Endocrinology 53
  • Molecular Medicine 43
  • Oncology 96
Replace Clifford V. Harding with:
Clifford V. Harding United States
Molly A. Ingersoll France
Nguyễn Thụy Thương Thương Vietnam
Saskia Boisot United States
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Alicja Misiak Ireland
Friedemann Gebhardt Germany
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Citations per field
00.5×5.4×
Clifford V. Harding · 1×
Citations per year

Countries citing papers authored by Lie Mao

Since Specialization
Citations

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

Fields of papers citing papers by Lie Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lie Mao, 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 Lie Mao Line = papers co-authored together Lie Mao links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2020254
2 2015114
3 201886
4 201751
5 201837
6 201821
7 201719
8 201519
9 202211
10 201611
11 20167
12 20177
13 20226

About Lie Mao

Lie Mao is a scholar working on Immunology, Infectious Diseases, Epidemiology, Surgery and Pulmonary and Respiratory Medicine, having authored 13 papers that have together received 643 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (7 papers), T-cell and B-cell Immunology (4 papers), Tuberculosis Research and Epidemiology (3 papers), Reproductive System and Pregnancy (2 papers), Mycobacterium research and diagnosis (2 papers), Lung Cancer Diagnosis and Treatment (1 paper), Endometriosis Research and Treatment (1 paper) and IL-33, ST2, and ILC Pathways (1 paper). The work is most often cited by research in Infectious Diseases (327 citations), Immunology (229 citations), Endocrinology (53 citations), Molecular Medicine (43 citations) and Oncology (96 citations). Lie Mao has collaborated with scholars based in China and Macao. Frequent co-authors include Hongyan Hou, Shiji Wu, Ziyong Sun, Yanfang Lu, Ying Luo, Feng Wang, Bo Zhang, Ting Wang, Yu Zhou and Sun Ziyong. Their work appears in journals such as European Journal of Immunology, American Journal of Reproductive Immunology, Immunology, Human Immunology and BMC Infectious Diseases.

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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