Lai‐Chu Wu

5.1k citations
78 papers · 2.9k indexed · h-index 32

Impact in

  • Immunology top 5%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • NF-κB Signaling Pathways

Papers in

    • T-cell and B-cell Immunology 14
    • Immune Cell Function and Interaction 13
    • Immune Response and Inflammation 6
    • Complement system in diseases 5
    • NF-κB Signaling Pathways 14
    • MicroRNA in disease regulation 5

Lai‐Chu Wu

78 papers receiving 2.8k citations

Peers

Lai‐Chu Wu
Comparison fields: 5 of 117
  • Immunology 790
  • Cancer Research 367
  • Hematology 244
  • Molecular Medicine 104
  • Molecular Biology 1.4k
Replace Jeffrey R. Weidner with:
Jeffrey R. Weidner United States
Lily Huang United States
Brian K. Dieckgraefe United States
Sergio Catz United States
Eun Sook Hwang South Korea
Susan Kaufman Canada
Karen Sokol United States
Teruhiko Tamaya Japan
Matthew Mangan Germany
Douglas Lazarus United States
Lai‐Chu Wu relative to Jeffrey R. Weidner United States Jeffrey R. Weidner's profile →
Citations per field
00.5×4.9×
Jeffrey R. Weidner · 1×
Citations per year

Countries citing papers authored by Lai‐Chu Wu

Since Specialization
Citations

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

Fields of papers citing papers by Lai‐Chu Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20201
2 201859
3 201731
4
Mechanosignaling in bone health, trauma and inflammation
20141
5 201412
6 201421
7 201343
8 20131
9 20118
10 201154
11 201013
12 20105
13 20105
14 200687
15 200256
16 199918
17 199617
18 199567
19 1994165
20 199340

About Lai‐Chu Wu

Lai‐Chu Wu is a scholar working on Immunology, Cancer Research, Virology, Molecular Medicine and Rheumatology, having authored 78 papers that have together received 2.9k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (14 papers), NF-κB Signaling Pathways (14 papers), Immune Cell Function and Interaction (13 papers), Cytokine Signaling Pathways and Interactions (7 papers), Immune Response and Inflammation (6 papers), MicroRNA in disease regulation (5 papers), Complement system in diseases (5 papers) and Systemic Lupus Erythematosus Research (5 papers). The work is most often cited by research in Immunology (790 citations), Cancer Research (367 citations), Hematology (244 citations), Molecular Medicine (104 citations) and Molecular Biology (1.4k citations). Lai‐Chu Wu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include C. Yung Yu, Sondra G. Lazarowitz, Carl E. Allen, Philip W. Shaul, L B Wells, Bernard J. Morley, R. Duncan Campbell, Shujun Liu, Andrew W. Dangel and Zhongfa Liu. Their work appears in journals such as Journal of Biological Chemistry, The Journal of Immunology, Nucleic Acids Research, Blood and Immunogenetics.

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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