Dan Long

6.0k citations
128 papers · 3.6k · h-index 33

Impact in

Papers in

    • Immune Cell Function and Interaction 10
    • T-cell and B-cell Immunology 9
    • Immunotherapy and Immune Responses 6

Dan Long

126 papers receiving 3.6k citations

Peers

Dan Long
Comparison fields: 5 of 141
  • Molecular Medicine 217
  • Infectious Diseases 649
  • Cancer Research 423
  • Genetics 252
  • Transplantation 55
Replace Pier Giulio Conaldi with:
Pier Giulio Conaldi Italy
Chuan‐Mu Chen Taiwan
David T. Harris United States
Gertrud Maria Hänsch Germany
Xiaoming Liu China
David M. Young United States
Franck Housseau United States
Kenji Okada Japan
Quan‐Zhen Li United States
Donald C. Anderson United States
Dan Long relative to Pier Giulio Conaldi Italy Pier Giulio Conaldi's profile →
Citations per field
00.5×1.7×
Pier Giulio Conaldi · 1×
Citations per year

Countries citing papers authored by Dan Long

Since Specialization
Citations

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

Fields of papers citing papers by Dan Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 128 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019308
2 2011209
3 2008182
4 2009113
5 2012106
6 201295
7 201094
8 201093
9 201187
10 201784
11 201980
12 201677
13 201975
14 201666
15 201159
16 201057
17 201355
18 201249
19 201248
20 201046

About Dan Long

Dan Long is a scholar working on Molecular Biology, Immunology, Cancer Research, Infectious Diseases and Epidemiology, having authored 128 papers that have together received 3.6k indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (10 papers), Immune Cell Function and Interaction (10 papers), T-cell and B-cell Immunology (9 papers), Viral Infections and Vectors (9 papers), Immunotherapy and Immune Responses (6 papers), Mesenchymal stem cell research (6 papers), Cancer-related molecular mechanisms research (6 papers) and Osteoarthritis Treatment and Mechanisms (5 papers). The work is most often cited by research in Molecular Medicine (217 citations), Infectious Diseases (649 citations), Cancer Research (423 citations), Genetics (252 citations) and Transplantation (55 citations). Dan Long has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Shengfu Li, Youping Li, Rebecca Rosenke, Xuechi Lin, Juan Shan, Donald J. Gardner, Xuelu Chen, Yanni Zhou, Ying Liao and Li Feng. Their work appears in journals such as Cellular Immunology, PLoS ONE, Journal of Virology, The Journal of Infectious Diseases and Journal of Surgical Research.

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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