John L. Kulp
Impact in
- Surfaces, Coatings and Films top 5%
- Polymer Surface Interaction Studies
- Biomaterials top 5%
- Supramolecular Self-Assembly in Materials
Papers in
-
- Computational Drug Discovery Methods 8
- Epidemiology 11
- Hepatitis B Virus Studies 9
- Co-authors
- John Spencer Evans (5 shared papers)Paramjit S. Arora (2 shared papers)Kang Chen (1 shared paper)Deyun Wang (1 shared paper)Daniel E. Barlow (2 shared papers)Kathryn J. Wahl (2 shared papers)Gary H. Dickinson (1 shared paper)Beatriz Orihuela (1 shared paper)
- Journals
- Antiviral Research (7 papers)Langmuir (4 papers)Bioorganic & Medicinal Chemistry Letters (2 papers)ACS Infectious Diseases (2 papers)Journal of the American Chemical Society (2 papers)
- Partner nations
- United StatesChinaJapan
In The Last Decade
John L. Kulp
43 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 88
- Surfaces, Coatings and Films 130
- Biomaterials 200
- Immunology 117
- Ocean Engineering 78
- Virology 23
Countries citing papers authored by John L. Kulp
This map shows the geographic impact of John L. Kulp'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 John L. Kulp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John L. Kulp more than expected).
Fields of papers citing papers by John L. Kulp
This network shows the impact of papers produced by John L. Kulp. 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 John L. Kulp. The network helps show where John L. Kulp may publish in the future.
Co-authors
The 25 scholars most cited alongside John L. Kulp, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 182 | |
| 2 | 2006 | 133 | |
| 3 | 2004 | 110 | |
| 4 | 2009 | 84 | |
| 5 | 2017 | 63 | |
| 6 | 2019 | 55 | |
| 7 | 2016 | 47 | |
| 8 | 2017 | 43 | |
| 9 | 2018 | 43 | |
| 10 | 2004 | 38 | |
| 11 | 2011 | 33 | |
| 12 | 2008 | 30 | |
| 13 | 2022 | 26 | |
| 14 | 2014 | 25 | |
| 15 | 2018 | 25 | |
| 16 | 2021 | 21 | |
| 17 | 2005 | 20 | |
| 18 | 2023 | 20 | |
| 19 | 2012 | 18 | |
| 20 | 2015 | 18 |
About John L. Kulp
John L. Kulp is a scholar working on Computational Theory and Mathematics, Epidemiology, Molecular Biology, Geriatrics and Gerontology and Virology, having authored 43 papers that have together received 1.2k indexed citations. Recurring topics across this work include Hepatitis B Virus Studies (9 papers), Computational Drug Discovery Methods (8 papers), Protein Structure and Dynamics (8 papers), Chemical Synthesis and Analysis (5 papers), Supramolecular Self-Assembly in Materials (3 papers), Poxvirus research and outbreaks (3 papers), Sirtuins and Resveratrol in Medicine (3 papers) and interferon and immune responses (2 papers). The work is most often cited by research in Surfaces, Coatings and Films (130 citations), Biomaterials (200 citations), Immunology (117 citations), Ocean Engineering (78 citations) and Virology (23 citations). John L. Kulp has collaborated with scholars based in United States, China and Japan. Frequent co-authors include John Spencer Evans, Paramjit S. Arora, Kang Chen, Deyun Wang, Daniel E. Barlow, Kathryn J. Wahl, Gary H. Dickinson, Beatriz Orihuela, Daniel Rittschof and Mehmet Sarıkaya. Their work appears in journals such as Antiviral Research, Langmuir, Bioorganic & Medicinal Chemistry Letters, ACS Infectious Diseases and Journal of the American Chemical Society.
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.