Runqing Lu

2.5k citations
36 papers · 2.0k · h-index 23

Impact in

    • Sirtuins and Resveratrol in Medicine
  • Immunology top 5%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • interferon and immune responses
    • Immune Response and Inflammation

Papers in

    • Immune Cell Function and Interaction 7
    • T-cell and B-cell Immunology 6
    • interferon and immune responses 5
    • Immunodeficiency and Autoimmune Disorders 4

Runqing Lu

36 papers receiving 1.9k citations

Peers

Runqing Lu
Comparison fields: 5 of 102
  • Geriatrics and Gerontology 187
  • Immunology 797
  • Genetics 206
  • Hematology 193
  • Oncology 444
Replace Keishi Fujiwara with:
Keishi Fujiwara Japan
Sophie Raynaud France
Sondra Goehle United States
Bo Tang China
Sathish Kumar Mungamuri India
Antônio Palumbo Brazil
Yongdong Feng China
Soheil Naderi Norway
Eliana Abdelhay Brazil
Daniela Senft United States
Runqing Lu relative to Keishi Fujiwara Japan Keishi Fujiwara's profile →
Citations per field
00.5×5.1×
Keishi Fujiwara · 1×
Citations per year

Countries citing papers authored by Runqing Lu

Since Specialization
Citations

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

Fields of papers citing papers by Runqing Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999286
2 2003202
3 2000138
4 2000125
5 2000120
6 201098
7 200886
8 200784
9 200180
10 201080
11 200674
12 200253
13 201452
14 199947
15 201646
16 201639
17 201136
18 201334
19 201433
20 200132

About Runqing Lu

Runqing Lu is a scholar working on Immunology, Molecular Biology, Oncology, Genetics and Hematology, having authored 36 papers that have together received 2.0k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (7 papers), Chronic Lymphocytic Leukemia Research (6 papers), T-cell and B-cell Immunology (6 papers), interferon and immune responses (5 papers), Acute Myeloid Leukemia Research (4 papers), Acute Lymphoblastic Leukemia research (4 papers), Immunodeficiency and Autoimmune Disorders (4 papers) and Cytokine Signaling Pathways and Interactions (3 papers). The work is most often cited by research in Geriatrics and Gerontology (187 citations), Immunology (797 citations), Genetics (206 citations), Hematology (193 citations) and Oncology (444 citations). Runqing Lu has collaborated with scholars based in United States, China and Israel. Frequent co-authors include Ginette Serrero, Paula M. Pitha, Shibin Ma, Long Trinh, Harinder Singh, Simanta Pathak, Kay L. Medina, D W Lancki, Vipul Shukla and Wen-Shuz Yeow. Their work appears in journals such as Journal of Biological Chemistry, Blood, Proceedings of the National Academy of Sciences, Molecular and Cellular Biology and British Journal of Haematology.

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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