Lan Wu

7.1k citations
153 papers · 4.4k · h-index 34

Impact in

  • Immunology top 1%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses
    • IL-33, ST2, and ILC Pathways
  • Virology top 2%
    • HIV Research and Treatment

Papers in

    • Immune Cell Function and Interaction 36
    • T-cell and B-cell Immunology 20
    • IL-33, ST2, and ILC Pathways 7

Lan Wu

140 papers receiving 4.3k citations

Peers

Lan Wu
Comparison fields: 5 of 179
  • Immunology 2.3k
  • Virology 415
  • Epidemiology 880
  • Physiology 115
  • Organizational Behavior and Human Resource Management 211
Replace Song Gao with:
Song Gao China
Jong Kim South Korea
I‐Ming Wang United States
Hans van Vliet Netherlands
Charles Wood United States
Eric Claassen Netherlands
Patrick Walsh United States
Federica Cavallo Italy
Richard Wang United States
Atsuo Suzuki Japan
Lan Wu relative to Song Gao China Song Gao's profile →
Citations per field
00.5×5.6×
Song Gao · 1×
Citations per year

Countries citing papers authored by Lan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Lan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 153 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001460
2 2005253
3 2007204
4 2014169
5 2009164
6 2012151
7 2010142
8 2009133
9 2013127
10 2004123
11 2019108
12 200492
13 202085
14 201281
15 201477
16 201575
17 202062
18 200560
19 201460
20 201759

About Lan Wu

Lan Wu is a scholar working on Immunology, Molecular Biology, Epidemiology, Oncology and Biomedical Engineering, having authored 153 papers that have together received 4.4k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (36 papers), T-cell and B-cell Immunology (20 papers), CAR-T cell therapy research (13 papers), HIV Research and Treatment (10 papers), Autophagy in Disease and Therapy (7 papers), IL-33, ST2, and ILC Pathways (7 papers), Pancreatic function and diabetes (6 papers) and Parallel Computing and Optimization Techniques (6 papers). The work is most often cited by research in Immunology (2.3k citations), Virology (415 citations), Epidemiology (880 citations), Physiology (115 citations) and Organizational Behavior and Human Resource Management (211 citations). Lan Wu has collaborated with scholars based in United States, China and France. Frequent co-authors include Luc Van Kaer, Vrajesh V. Parekh, Gary J. Nabel, Naresh K. Malhotra, Wing-Pui Kong, Zhi-Yong Yang, James Agarwal, Francis M. Ulgado, G. Shainesh and J. Luke Postoak. Their work appears in journals such as Frontiers in Immunology, The Journal of Immunology, Proceedings of the National Academy of Sciences, Cancer Research and Endocrinology.

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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