Maya U. Sheth
Impact in
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- Cancer Cells and Metastasis
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- Cancer Genomics and Diagnostics
- Cancer-related molecular mechanisms research
Papers in
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- Cancer Genomics and Diagnostics 3
- NF-κB Signaling Pathways 1
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- Ubiquitin and proteasome pathways 2
- Epigenetics and DNA Methylation 1
- Co-authors
- Jason A. Somarelli (9 shared papers)Andrew J. Armstrong (4 shared papers)Mohit Kumar Jolly (4 shared papers)Annapoorni Rangarajan (1 shared paper)Sharmila A. Bapat (1 shared paper)Herbert Levine (1 shared paper)Samir Hanash (1 shared paper)Adrian Biddle (1 shared paper)
- Journals
- Journal of Clinical Medicine (1 paper)Frontiers in Marine Science (1 paper)Frontiers in Oncology (1 paper)Molecular Biology and Evolution (1 paper)Pharmacology & Therapeutics (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Maya U. Sheth
11 papers receiving 389 citations
Peers
Comparison fields: 5 of 64
- Oncology 192
- Cancer Research 100
- Pollution 39
- Cell Biology 48
- Biotechnology 24
Countries citing papers authored by Maya U. Sheth
This map shows the geographic impact of Maya U. 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 Maya U. Sheth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya U. Sheth more than expected).
Fields of papers citing papers by Maya U. Sheth
This network shows the impact of papers produced by Maya U. 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 Maya U. Sheth. The network helps show where Maya U. Sheth may publish in the future.
Co-authors
The 25 scholars most cited alongside Maya U. 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 | 2018 | 247 | |
| 2 | 2019 | 43 | |
| 3 | 2019 | 21 | |
| 4 | 2022 | 20 | |
| 5 | 2020 | 16 | |
| 6 | 2020 | 15 | |
| 7 | 2019 | 13 | |
| 8 | 2021 | 6 | |
| 9 | 2023 | 6 | |
| 10 | 2025 | 3 | |
| 11 | 2020 | 2 |
About Maya U. Sheth
Maya U. Sheth is a scholar working on Cancer Research, Molecular Biology, Pulmonary and Respiratory Medicine, Oncology and Genetics, having authored 11 papers that have together received 392 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (3 papers), Ubiquitin and proteasome pathways (2 papers), Prostate Cancer Treatment and Research (2 papers), Hippo pathway signaling and YAP/TAZ (2 papers), Recycling and Waste Management Techniques (1 paper), Estrogen and related hormone effects (1 paper), NF-κB Signaling Pathways (1 paper) and Epigenetics and DNA Methylation (1 paper). The work is most often cited by research in Oncology (192 citations), Cancer Research (100 citations), Pollution (39 citations), Cell Biology (48 citations) and Biotechnology (24 citations). Maya U. Sheth has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Jason A. Somarelli, Andrew J. Armstrong, Mohit Kumar Jolly, Annapoorni Rangarajan, Sharmila A. Bapat, Herbert Levine, Samir Hanash, Adrian Biddle, S. C. Tripathi and William C. Eward. Their work appears in journals such as Journal of Clinical Medicine, Frontiers in Marine Science, Frontiers in Oncology, Molecular Biology and Evolution and Pharmacology & 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.