Udit Sheth
Impact in
- Neurology top 10%
- Amyotrophic Lateral Sclerosis Research
- Neuroinflammation and Neurodegeneration Mechanisms
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- Genetic Neurodegenerative Diseases
Papers in
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- Amyotrophic Lateral Sclerosis Research 9
- Neuroinflammation and Neurodegeneration Mechanisms 1
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- Genetic Neurodegenerative Diseases 1
- Co-authors
- Tania F. Gendron (5 shared papers)Katherine E. Irwin (1 shared paper)Philip C. Wong (1 shared paper)Yuka A. Martens (1 shared paper)Manling Xie (1 shared paper)Dennis W. Dickson (2 shared papers)Lingxin Zhang (1 shared paper)Chia‐Chen Liu (1 shared paper)
- Journals
- Nature Neuroscience (2 papers)Molecular Neurodegeneration (2 papers)Clinical Chemistry and Laboratory Medicine (CCLM) (1 paper)Science Translational Medicine (1 paper)Cell (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Udit Sheth
10 papers receiving 281 citations
Peers
Comparison fields: 5 of 31
- Neurology 79
- Neurology 119
- Cellular and Molecular Neuroscience 21
- Aging 2
- Physiology 29
Countries citing papers authored by Udit Sheth
This map shows the geographic impact of Udit Sheth'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 Udit Sheth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Udit Sheth more than expected).
Fields of papers citing papers by Udit Sheth
This network shows the impact of papers produced by Udit Sheth. 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 Udit Sheth. The network helps show where Udit Sheth may publish in the future.
Co-authors
The 25 scholars most cited alongside Udit Sheth, 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 | 2021 | 117 | |
| 2 | 2024 | 55 | |
| 3 | 2019 | 37 | |
| 4 | 2023 | 24 | |
| 5 | 2022 | 19 | |
| 6 | 2025 | 11 | |
| 7 | 2025 | 6 | |
| 8 | 2025 | 6 | |
| 9 | 2025 | 5 | |
| 10 | 2024 | 4 | |
| 11 | 2025 | 0 |
About Udit Sheth
Udit Sheth is a scholar working on Neurology, Neurology, Cellular and Molecular Neuroscience, Pathology and Forensic Medicine and Psychiatry and Mental health, having authored 11 papers that have together received 284 indexed citations. Recurring topics across this work include Amyotrophic Lateral Sclerosis Research (9 papers), Genetics and Neurodevelopmental Disorders (1 paper), RNA and protein synthesis mechanisms (1 paper), Clinical Laboratory Practices and Quality Control (1 paper), Neuroinflammation and Neurodegeneration Mechanisms (1 paper), Dementia and Cognitive Impairment Research (1 paper), Genetic Neurodegenerative Diseases (1 paper) and Multiple Sclerosis Research Studies (1 paper). The work is most often cited by research in Neurology (79 citations), Neurology (119 citations), Cellular and Molecular Neuroscience (21 citations), Aging (2 citations) and Physiology (29 citations). Udit Sheth has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Tania F. Gendron, Katherine E. Irwin, Philip C. Wong, Yuka A. Martens, Manling Xie, Dennis W. Dickson, Lingxin Zhang, Chia‐Chen Liu, Long‐Jun Wu and Yuan‐Ping Pang. Their work appears in journals such as Nature Neuroscience, Molecular Neurodegeneration, Clinical Chemistry and Laboratory Medicine (CCLM), Science Translational Medicine and 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.