Joost Snijder
- Infectious Diseases top 1%
- SARS-CoV-2 and COVID-19 Research 8
- Structural Biology top 2%
- Animal Science and Zoology top 1%
- Animal Virus Infections Studies 8
- Spectroscopy top 1%
- Mass Spectrometry Techniques and Applications 10
- Molecular Biology top 5%
- Glycosylation and Glycoproteins Research 10
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- Bacteriophages and microbial interactions 21
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- Monoclonal and Polyclonal Antibodies Research 11
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- Virus-based gene therapy research 9
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- Enzyme Structure and Function 7
- Co-authors
- Albert J. R. HeckDavid VeeslerAlexandra C. WallsF.A. ReyM. Alejandra TortoriciBerend‐Jan BoschXiaoli XiongTobias P. Wörner
- Partner nations
- NetherlandsUnited StatesGermany
In The Last Decade
Joost Snijder
64 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Infectious Diseases 1.4k
- Structural Biology 77
- Animal Science and Zoology 427
- Spectroscopy 684
- Molecular Biology 1.7k
Countries citing papers authored by Joost Snijder
This map shows the geographic impact of Joost Snijder'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 Joost Snijder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joost Snijder more than expected).
Fields of papers citing papers by Joost Snijder
This network shows the impact of papers produced by Joost Snijder. 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 Joost Snijder. The network helps show where Joost Snijder may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Joost Snijder, 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 | 2025 | 1 | |
| 3 | 2023 | 4 | |
| 4 | 2023 | 37 | |
| 5 | 2022 | 20 | |
| 6 | 2022 | 18 | |
| 7 | 2022 | 7 | |
| 8 | 2021 | 39 | |
| 9 | 2021 | 23 | |
| 10 | Adeno-associated virus capsid assembly is divergent and stochasticbreakdown → | 2021 | 151 |
| 11 | 2020 | 24 | |
| 12 | 2020 | 38 | |
| 13 | 2020 | 21 | |
| 14 | 2019 | 71 | |
| 15 | Unexpected Receptor Functional Mimicry Elucidates Activation of Coronavirus Fusionbreakdown → | 2019 | 370 |
| 16 | 2017 | 76 | |
| 17 | 2017 | 27 | |
| 18 | Glycan shield and epitope masking of a coronavirus spike protein observed by cryo-electron microscopybreakdown → | 2016 | 306 |
| 19 | 2013 | 49 | |
| 20 | 2013 | 30 |
About Joost Snijder
Joost Snijder is a scholar working on Structural Biology, Ecology and Animal Science and Zoology, having authored 67 papers that have together received 3.8k indexed citations. Recurring topics across this work include Bacteriophages and microbial interactions (21 papers), Monoclonal and Polyclonal Antibodies Research (11 papers), Glycosylation and Glycoproteins Research (10 papers), Mass Spectrometry Techniques and Applications (10 papers), Virus-based gene therapy research (9 papers), SARS-CoV-2 and COVID-19 Research (8 papers), Animal Virus Infections Studies (8 papers) and Enzyme Structure and Function (7 papers). The work is most often cited by research in Infectious Diseases (1.4k citations), Structural Biology (77 citations) and Animal Science and Zoology (427 citations). Joost Snijder has collaborated with scholars based in Netherlands, United States and Germany. Frequent co-authors include Albert J. R. Heck, David Veesler, Alexandra C. Walls, F.A. Rey, M. Alejandra Tortorici, Berend‐Jan Bosch, Xiaoli Xiong, Tobias P. Wörner, Antonette Bennett and Mavis Agbandje‐McKenna. Their work appears in journals such as Nature, Science and Cell.
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.