David L. Haviland
- Immunology top 5%
- Complement system in diseases 9
- Immune Cell Function and Interaction 4
- Immune Response and Inflammation 3
- Immune cells in cancer 3
- Genetics top 5%
- Microbiology top 5%
- Neurology top 5%
- Immunology and Allergy top 10%
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- Monoclonal and Polyclonal Antibodies Research 5
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- Blood Coagulation and Thrombosis Mechanisms 3
- Blood groups and transfusion 3
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- Single-cell and spatial transcriptomics 2
- Co-authors
- Rick A. WetselJoie C. HavilandDavid H. PerlmutterErnesto P. MolmentiDachun WangAlan R. BurnsEva ZsigmondScott R. Whittemore
- Cited by
- ImmunologyGeneticsMicrobiology
- Journals
- The Journal of Immunology (6 papers)Cytometry Part A (4 papers)Journal of Biological Chemistry (3 papers)
- Partner nations
- United StatesIndiaAustralia
In The Last Decade
David L. Haviland
30 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Immunology 838
- Genetics 203
- Microbiology 116
- Neurology 142
- Immunology and Allergy 69
Countries citing papers authored by David L. Haviland
This map shows the geographic impact of David L. Haviland'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 L. Haviland with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David L. Haviland more than expected).
Fields of papers citing papers by David L. Haviland
This network shows the impact of papers produced by David L. Haviland. 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 L. Haviland. The network helps show where David L. Haviland may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David L. Haviland, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Single-cell analysis of human glioma and immune cells identifies S100A4 as an immunotherapy targetbreakdown → | 2022 | 245 |
| 2 | 2020 | 5 | |
| 3 | 2019 | 13 | |
| 4 | 2018 | 5 | |
| 5 | 2014 | 13 | |
| 6 | 2011 | 37 | |
| 7 | 2007 | 25 | |
| 8 | 2006 | 17 | |
| 9 | 2005 | 4 | |
| 10 | 2004 | 104 | |
| 11 | 2002 | 45 | |
| 12 | 1998 | 25 | |
| 13 | 1995 | 95 | |
| 14 | 1995 | 168 | |
| 15 | 1993 | 22 | |
| 16 | 1991 | 16 | |
| 17 | 1990 | 161 | |
| 18 | 1989 | 1 | |
| 19 | 1989 | 10 | |
| 20 | 1987 | 39 |
About David L. Haviland
David L. Haviland is a scholar working on Immunology, General Dentistry and Hematology, having authored 30 papers that have together received 1.6k indexed citations. Recurring topics across this work include Complement system in diseases (9 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), Immune Cell Function and Interaction (4 papers), Blood Coagulation and Thrombosis Mechanisms (3 papers), Immune Response and Inflammation (3 papers), Immune cells in cancer (3 papers), Blood groups and transfusion (3 papers) and Single-cell and spatial transcriptomics (2 papers). The work is most often cited by research in Immunology (838 citations), Genetics (203 citations) and Microbiology (116 citations). David L. Haviland has collaborated with scholars based in United States, India and Australia. Frequent co-authors include Rick A. Wetsel, Joie C. Haviland, David H. Perlmutter, Ernesto P. Molmenti, Dachun Wang, Alan R. Burns, Eva Zsigmond, Scott R. Whittemore, Scott R. Barnum and Jennifer L. Jones. Their work appears in journals such as The Journal of Immunology, Cytometry Part A, Journal of Biological Chemistry, Molecular Immunology and Journal of Immunological Methods.
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.