Jay E. Johnson
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
- Cell Biology top 10%
- Plant Pathogens and Fungal Diseases
Papers in
-
- DNA Repair Mechanisms 2
- Fungal and yeast genetics research 2
-
- Telomeres, Telomerase, and Senescence 4
- Co-authors
- F. Brad Johnson (3 shared papers)V. N. Njiti (5 shared papers)David A. Lightfoot (5 shared papers)Gene P. Ables (1 shared paper)Laura L. Lackner (2 shared papers)Piet A. J. de Boer (2 shared papers)Jason D. Plummer (5 shared papers)Jessica K. Tyler (3 shared papers)
- Journals
- Crop Science (3 papers)Journal of Bacteriology (2 papers)Aging Cell (2 papers)Theoretical and Applied Genetics (2 papers)Molecular Cancer Therapeutics (1 paper)
- Partner nations
- United StatesUnited KingdomGreece
In The Last Decade
Jay E. Johnson
27 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 76
- Aging 134
- Cell Biology 174
- Plant Science 360
- Physiology 226
- Molecular Biology 584
Countries citing papers authored by Jay E. Johnson
This map shows the geographic impact of Jay E. Johnson'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 Jay E. Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay E. Johnson more than expected).
Fields of papers citing papers by Jay E. Johnson
This network shows the impact of papers produced by Jay E. Johnson. 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 Jay E. Johnson. The network helps show where Jay E. Johnson may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay E. Johnson, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 129 | |
| 2 | 2014 | 118 | |
| 3 | 2002 | 96 | |
| 4 | 2017 | 85 | |
| 5 | 1999 | 80 | |
| 6 | 2002 | 80 | |
| 7 | 2008 | 74 | |
| 8 | 2008 | 73 | |
| 9 | 2004 | 59 | |
| 10 | 2001 | 59 | |
| 11 | 2005 | 55 | |
| 12 | 2019 | 42 | |
| 13 | 2017 | 40 | |
| 14 | 2018 | 36 | |
| 15 | 1964 | 33 | |
| 16 | 2021 | 27 | |
| 17 | 2021 | 19 | |
| 18 | 2022 | 18 | |
| 19 | 2007 | 17 | |
| 20 | 2007 | 14 |
About Jay E. Johnson
Jay E. Johnson is a scholar working on Molecular Biology, Physiology, Aging, Plant Science and Pediatrics, Perinatology and Child Health, having authored 28 papers that have together received 1.2k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (7 papers), Telomeres, Telomerase, and Senescence (4 papers), Soybean genetics and cultivation (4 papers), Birth, Development, and Health (4 papers), Nematode management and characterization studies (3 papers), DNA Repair Mechanisms (2 papers), Fungal and yeast genetics research (2 papers) and Plant pathogens and resistance mechanisms (2 papers). The work is most often cited by research in Aging (134 citations), Cell Biology (174 citations), Plant Science (360 citations), Physiology (226 citations) and Molecular Biology (584 citations). Jay E. Johnson has collaborated with scholars based in United States, United Kingdom and Greece. Frequent co-authors include F. Brad Johnson, V. N. Njiti, David A. Lightfoot, Gene P. Ables, Laura L. Lackner, Piet A. J. de Boer, Jason D. Plummer, Jessica K. Tyler, Kajia Cao and Li‐San Wang. Their work appears in journals such as Crop Science, Journal of Bacteriology, Aging Cell, Theoretical and Applied Genetics and Molecular Cancer Therapeutics.
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.