Tyler M. Levy
Impact in
- Neurology top 2%
- Neuroinflammation and Neurodegeneration Mechanisms
- Parkinson's Disease Mechanisms and Treatments
- Physiology top 10%
- Alzheimer's disease research and treatments
Papers in
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- Advanced Proteomics Techniques and Applications 3
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- Neuroinflammation and Neurodegeneration Mechanisms 1
- Co-authors
- Klarisa Rikova (2 shared papers)Mark L. Grimes (3 shared papers)Matthew P. Stokes (1 shared paper)Hongbo Gu (1 shared paper)Kimberly A. Lee (1 shared paper)Jeffrey C. Silva (1 shared paper)Jian Min Ren (1 shared paper)Xiaoying Jia (1 shared paper)
- Journals
- Science Signaling (2 papers)Nature Medicine (1 paper)Nature Methods (1 paper)Molecular & Cellular Proteomics (1 paper)Molecular Biology of the Cell (1 paper)
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Tyler M. Levy
8 papers receiving 1.0k citations
Tyler M. Levy's Hit Papers
Peers
Comparison fields: 5 of 51
- Neurology 298
- Physiology 183
- Spectroscopy 51
- Developmental Neuroscience 7
- Molecular Biology 123
Countries citing papers authored by Tyler M. Levy
This map shows the geographic impact of Tyler M. Levy'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 Tyler M. Levy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tyler M. Levy more than expected).
Fields of papers citing papers by Tyler M. Levy
This network shows the impact of papers produced by Tyler M. Levy. 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 Tyler M. Levy. The network helps show where Tyler M. Levy may publish in the future.
Co-authors
The 25 scholars most cited alongside Tyler M. Levy, 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 | Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease Hit paper breakdown → | 2020 | 829 |
| 2 | 2022 | 62 | |
| 3 | 2015 | 48 | |
| 4 | 2018 | 48 | |
| 5 | 2022 | 31 | |
| 6 | 2024 | 11 | |
| 7 | 2020 | 9 | |
| 8 | 2025 | 3 |
About Tyler M. Levy
Tyler M. Levy is a scholar working on Spectroscopy, Neurology, Infectious Diseases, Molecular Biology and Nuclear Energy and Engineering, having authored 8 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (3 papers), Protein Kinase Regulation and GTPase Signaling (1 paper), Single-cell and spatial transcriptomics (1 paper), Neuroinflammation and Neurodegeneration Mechanisms (1 paper) and SARS-CoV-2 and COVID-19 Research (1 paper). The work is most often cited by research in Neurology (298 citations), Physiology (183 citations), Spectroscopy (51 citations), Developmental Neuroscience (7 citations) and Molecular Biology (123 citations). Tyler M. Levy has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Klarisa Rikova, Mark L. Grimes, Matthew P. Stokes, Hongbo Gu, Kimberly A. Lee, Jeffrey C. Silva, Jian Min Ren, Xiaoying Jia, Brandon M. Gassaway and Alexander Lachmann. Their work appears in journals such as Science Signaling, Nature Medicine, Nature Methods, Molecular & Cellular Proteomics and Molecular Biology of the 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.