Jason E. Gestwicki
- Aging top 0.5%
- Molecular Biology top 0.2%
- Heat shock proteins research 110
- Protein Structure and Dynamics 58
- Ubiquitin and proteasome pathways 14
- Cell Biology top 0.2%
- Endoplasmic Reticulum Stress and Disease 35
- Physiology top 0.5%
- Alzheimer's disease research and treatments 27
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods 34
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- Enzyme Structure and Function 20
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- thermodynamics and calorimetric analyses 17
- Co-authors
- Laura L. KiesslingLaura E. StrongLyra ChangErik R. P. ZuiderwegChristopher G. EvansAshley A. ReinkeChristopher W. CairoDaniel J. Klionsky
- Cited by
- AgingMolecular BiologyCell Biology
- Journals
- Journal of Biological Chemistry (23 papers)ACS Chemical Biology (12 papers)Nature Communications (7 papers)
- Partner nations
- United StatesItalyChina
In The Last Decade
Jason E. Gestwicki
219 papers receiving 14.7k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Aging 338
- Molecular Biology 10.8k
- Cell Biology 2.5k
- Physiology 2.2k
- Computational Theory and Mathematics 1.3k
Countries citing papers authored by Jason E. Gestwicki
This map shows the geographic impact of Jason E. Gestwicki'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 Jason E. Gestwicki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason E. Gestwicki more than expected).
Fields of papers citing papers by Jason E. Gestwicki
This network shows the impact of papers produced by Jason E. Gestwicki. 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 Jason E. Gestwicki. The network helps show where Jason E. Gestwicki may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jason E. Gestwicki, 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 | 2024 | 0 | |
| 4 | 2024 | 3 | |
| 5 | 2022 | 6 | |
| 6 | Microglial NF-κB drives tau spreading and toxicity in a mouse model of tauopathybreakdown → | 2022 | 186 |
| 7 | 2021 | 10 | |
| 8 | 2020 | 28 | |
| 9 | 2020 | 4 | |
| 10 | 2019 | 18 | |
| 11 | 2018 | 97 | |
| 12 | 2018 | 108 | |
| 13 | 2016 | 28 | |
| 14 | 2015 | 101 | |
| 15 | 2015 | 189 | |
| 16 | 2014 | 137 | |
| 17 | 2012 | 28 | |
| 18 | 2012 | 25 | |
| 19 | 2009 | 362 | |
| 20 | 2008 | 5 |
About Jason E. Gestwicki
Jason E. Gestwicki is a scholar working on Molecular Biology, Cell Biology, Aging, Computational Theory and Mathematics and Physical and Theoretical Chemistry, having authored 226 papers that have together received 14.8k indexed citations. Recurring topics across this work include Heat shock proteins research (110 papers), Protein Structure and Dynamics (58 papers), Endoplasmic Reticulum Stress and Disease (35 papers), Computational Drug Discovery Methods (34 papers), Alzheimer's disease research and treatments (27 papers), Enzyme Structure and Function (20 papers), thermodynamics and calorimetric analyses (17 papers) and Ubiquitin and proteasome pathways (14 papers). The work is most often cited by research in Aging (338 citations), Molecular Biology (10.8k citations), Cell Biology (2.5k citations), Physiology (2.2k citations) and Computational Theory and Mathematics (1.3k citations). Jason E. Gestwicki has collaborated with scholars based in United States, Italy and China. Frequent co-authors include Laura L. Kiessling, Laura E. Strong, Lyra Chang, Erik R. P. Zuiderweg, Christopher G. Evans, Ashley A. Reinke, Christopher W. Cairo, Daniel J. Klionsky, David C. Rubinsztein and Leon O. Murphy. Their work appears in journals such as Journal of Biological Chemistry, ACS Chemical Biology, Nature Communications, Cell chemical biology and Cell Stress and Chaperones.
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.