David Chao

3.5k citations
72 papers · 2.3k · h-index 23

Impact in

  • Immunology top 5%
    • Immunotherapy and Immune Responses
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
  • Hepatology top 5%
    • Hepatitis C virus research

Papers in

David Chao

69 papers receiving 2.2k citations

Peers

David Chao
Comparison fields: 5 of 133
  • Immunology 638
  • Hepatology 171
  • Oncology 486
  • Neurology 119
  • Epidemiology 312
Replace Xin Geng with:
Xin Geng China
Naoko Watanabe Japan
Laurence Preisser France
Martina Fischer Germany
Ian P. Hayward Australia
Hidehiro Fukuyama Japan
R. A. Robins United Kingdom
R. Carlsson Sweden
Susan Kaufman Canada
Fernando López‐Casillas Mexico
David Chao relative to Xin Geng China Xin Geng's profile →
Citations per field
00.5×1.5×2×2.4×
Xin Geng · 1×
Citations per year

Countries citing papers authored by David Chao

Since Specialization
Citations

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

Fields of papers citing papers by David Chao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Rat macrophage lysosomal membrane antigen recognized by monoclonal antibody ED1.
1994483
2 2007205
3 2012138
4 2016124
5 2000123
6 2010112
7
Low-dose IFN-gamma induces tumor MHC expression in metastatic malignant melanoma.
200393
8 199981
9 201479
10 200060
11 201159
12 200943
13 201137
14 200331
15 201030
16 201328
17 201427
18 200727
19 198726
20 199925

About David Chao

David Chao is a scholar working on Molecular Biology, Oncology, Epidemiology, Immunology and Pathology and Forensic Medicine, having authored 72 papers that have together received 2.3k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (8 papers), Hepatitis C virus research (5 papers), Helminth infection and control (5 papers), Mollusks and Parasites Studies (5 papers), Trypanosoma species research and implications (5 papers), Cancer Immunotherapy and Biomarkers (5 papers), Melanoma and MAPK Pathways (4 papers) and Parasite Biology and Host Interactions (4 papers). The work is most often cited by research in Immunology (638 citations), Hepatology (171 citations), Oncology (486 citations), Neurology (119 citations) and Epidemiology (312 citations). David Chao has collaborated with scholars based in United Kingdom, Taiwan and United States. Frequent co-authors include Wim Calame, C Dijkstra, Ed A. Döpp, G. Gordon MacPherson, Jan Damoiseaux, Mindie H. Nguyen, Tim Eisen, Martin Gore, Adrian L. Harris and Joseph K. Lim. Their work appears in journals such as Journal of Clinical Oncology, British Journal of Cancer, Journal of Helminthology, Journal of Microbiology Immunology and Infection and The Lancet Oncology.

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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