Daniel Coombs
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies 10
- Virology top 2%
- HIV Research and Treatment 14
- Immunology top 5%
- T-cell and B-cell Immunology 22
- Immune Cell Function and Interaction 13
- Immunotherapy and Immune Responses 10
- Immunology and Allergy top 5%
- Cell Adhesion Molecules Research 11
- Oncology top 5%
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- Monoclonal and Polyclonal Antibodies Research 13
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- HIV/AIDS Research and Interventions 9
- Co-authors
- Michael A. GilchristByron GoldsteinOmer DushekRaibatak DasCarla WofsyMark D. PegramMark X. SliwkowskiD L Baly
- Journals
- PLoS Computational Biology (7 papers)Biophysical Journal (6 papers)Bulletin of Mathematical Biology (6 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Daniel Coombs
82 papers receiving 3.4k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Modeling and Simulation 349
- Virology 269
- Immunology 834
- Immunology and Allergy 176
- Oncology 749
Countries citing papers authored by Daniel Coombs
This map shows the geographic impact of Daniel Coombs'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 Daniel Coombs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Coombs more than expected).
Fields of papers citing papers by Daniel Coombs
This network shows the impact of papers produced by Daniel Coombs. 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 Daniel Coombs. The network helps show where Daniel Coombs may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel Coombs, 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 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2022 | 3 | |
| 4 | 2022 | 16 | |
| 5 | 2022 | 15 | |
| 6 | 2021 | 13 | |
| 7 | 2020 | 53 | |
| 8 | 2019 | 10 | |
| 9 | 2019 | 11 | |
| 10 | 2019 | 5 | |
| 11 | 2018 | 3 | |
| 12 | 2018 | 72 | |
| 13 | 2016 | 14 | |
| 14 | 2015 | 60 | |
| 15 | 2014 | 8 | |
| 16 | 2011 | 59 | |
| 17 | 2009 | 101 | |
| 18 | 2008 | 14 | |
| 19 | 2004 | 58 | |
| 20 | 1999 | 88 |
About Daniel Coombs
Daniel Coombs is a scholar working on Virology, Modeling and Simulation and Immunology and Allergy, having authored 85 papers that have together received 3.5k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (22 papers), HIV Research and Treatment (14 papers), Monoclonal and Polyclonal Antibodies Research (13 papers), Immune Cell Function and Interaction (13 papers), Cell Adhesion Molecules Research (11 papers), Immunotherapy and Immune Responses (10 papers), COVID-19 epidemiological studies (10 papers) and HIV/AIDS Research and Interventions (9 papers). The work is most often cited by research in Modeling and Simulation (349 citations), Virology (269 citations) and Immunology (834 citations). Daniel Coombs has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Michael A. Gilchrist, Byron Goldstein, Omer Dushek, Raibatak Das, Carla Wofsy, Mark D. Pegram, Mark X. Sliwkowski, D L Baly, Gail D. Lewis Phillips and Dennis J. Slamon. Their work appears in journals such as PLoS Computational Biology, Biophysical Journal, Bulletin of Mathematical Biology, Epidemics and SIAM Journal on Applied Mathematics.
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.