Tom G. Keulers
- Cell Biology top 2%
- Endoplasmic Reticulum Stress and Disease 4
- Epidemiology top 2%
- Autophagy in Disease and Therapy 12
- Physiology top 2%
- Cancer Research top 5%
- Cancer, Hypoxia, and Metabolism 7
- MicroRNA in disease regulation 3
- Geriatrics and Gerontology top 5%
-
- Extracellular vesicles in disease 6
- RNA modifications and cancer 3
- Epigenetics and DNA Methylation 2
-
- Nanoplatforms for cancer theranostics 4
- Co-authors
- Kasper M.A. RouschopMarco B.E. SchaafMarc VooijsBradly G. WoutersJohan BussinkMarianne KoritzinskyPhilippe LambinKim G.M. Savelkouls
- Cited by
- Cell BiologyEpidemiologyPhysiology
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Journal of Clinical Investigation (1 paper)PLoS ONE (1 paper)
- Partner nations
- NetherlandsCanadaUnited States
In The Last Decade
Tom G. Keulers
20 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Cell Biology 518
- Epidemiology 1.1k
- Physiology 134
- Cancer Research 442
- Geriatrics and Gerontology 96
Countries citing papers authored by Tom G. Keulers
This map shows the geographic impact of Tom G. Keulers'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 Tom G. Keulers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom G. Keulers more than expected).
Fields of papers citing papers by Tom G. Keulers
This network shows the impact of papers produced by Tom G. Keulers. 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 Tom G. Keulers. The network helps show where Tom G. Keulers may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tom G. Keulers, 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 | 0 | |
| 3 | 2025 | 3 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 4 | |
| 7 | 2021 | 24 | |
| 8 | 2021 | 27 | |
| 9 | 2019 | 52 | |
| 10 | 2018 | 37 | |
| 11 | 2017 | 5 | |
| 12 | 2016 | 35 | |
| 13 | 2015 | 20 | |
| 14 | 2015 | 20 | |
| 15 | 2013 | 38 | |
| 16 | 2013 | 36 | |
| 17 | 2013 | 177 | |
| 18 | 2011 | 20 | |
| 19 | 2009 | 113 | |
| 20 | The unfolded protein response protects human tumor cells during hypoxia through regulation of the autophagy genes MAP1LC3B and ATG5breakdown → | 2009 | 654 |
About Tom G. Keulers
Tom G. Keulers is a scholar working on Cancer Research, Family Practice and Epidemiology, having authored 22 papers that have together received 1.8k indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (12 papers), Cancer, Hypoxia, and Metabolism (7 papers), Extracellular vesicles in disease (6 papers), Endoplasmic Reticulum Stress and Disease (4 papers), Nanoplatforms for cancer theranostics (4 papers), MicroRNA in disease regulation (3 papers), RNA modifications and cancer (3 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Cell Biology (518 citations), Epidemiology (1.1k citations) and Physiology (134 citations). Tom G. Keulers has collaborated with scholars based in Netherlands, Canada and United States. Frequent co-authors include Kasper M.A. Rouschop, Marco B.E. Schaaf, Marc Vooijs, Bradly G. Wouters, Johan Bussink, Marianne Koritzinsky, Philippe Lambin, Kim G.M. Savelkouls, Ludwig J. Dubois and Twan van den Beucken. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and PLoS ONE.
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.