Deepti Abbey
Impact in
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- Liver physiology and pathology
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- Metabolism and Genetic Disorders
Papers in
- Surgery 6
- Pancreatic function and diabetes 3
- Tissue Engineering and Regenerative Medicine 2
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- Pluripotent Stem Cells Research 4
- CRISPR and Genetic Engineering 2
- Mitochondrial Function and Pathology 1
- Co-authors
- Polani B. Seshagiri (3 shared papers)Daniel J. Rader (4 shared papers)Christopher D. Brown (2 shared papers)Nicholas J. Hand (4 shared papers)Donna Conlon (2 shared papers)Katerina A.B. Gawronski (1 shared paper)Tobias Raabe (1 shared paper)Sarah L. McCarron (1 shared paper)
- Journals
- Gene (1 paper)Hepatology Communications (1 paper)Clinical and Translational Science (1 paper)Cellular Reprogramming (1 paper)Cell Biology International (1 paper)
- Partner nations
- United StatesIndiaGermany
In The Last Decade
Deepti Abbey
11 papers receiving 201 citations
Peers
Comparison fields: 5 of 52
- Hepatology 42
- Clinical Biochemistry 14
- Molecular Biology 92
- Biochemistry 9
- Oncology 31
Countries citing papers authored by Deepti Abbey
This map shows the geographic impact of Deepti Abbey'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 Deepti Abbey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepti Abbey more than expected).
Fields of papers citing papers by Deepti Abbey
This network shows the impact of papers produced by Deepti Abbey. 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 Deepti Abbey. The network helps show where Deepti Abbey may publish in the future.
Co-authors
The 25 scholars most cited alongside Deepti Abbey, 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 | 68 | |
| 2 | 2017 | 48 | |
| 3 | 2013 | 24 | |
| 4 | 2017 | 24 | |
| 5 | 2017 | 12 | |
| 6 | 2020 | 8 | |
| 7 | 2020 | 8 | |
| 8 | 2021 | 7 | |
| 9 | 2025 | 2 | |
| 10 | 2019 | 2 | |
| 11 | 2022 | 2 |
About Deepti Abbey
Deepti Abbey is a scholar working on Surgery, Molecular Biology, Biochemistry, Cellular and Molecular Neuroscience and Pulmonary and Respiratory Medicine, having authored 11 papers that have together received 205 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (4 papers), Pancreatic function and diabetes (3 papers), Lipid metabolism and biosynthesis (2 papers), Tissue Engineering and Regenerative Medicine (2 papers), CRISPR and Genetic Engineering (2 papers), Animal Genetics and Reproduction (1 paper), Mitochondrial Function and Pathology (1 paper) and Liver physiology and pathology (1 paper). The work is most often cited by research in Hepatology (42 citations), Clinical Biochemistry (14 citations), Molecular Biology (92 citations), Biochemistry (9 citations) and Oncology (31 citations). Deepti Abbey has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Polani B. Seshagiri, Daniel J. Rader, Christopher D. Brown, Nicholas J. Hand, Donna Conlon, Katerina A.B. Gawronski, Tobias Raabe, Sarah L. McCarron, Abraham Shaked and Kim M. Olthoff. Their work appears in journals such as Gene, Hepatology Communications, Clinical and Translational Science, Cellular Reprogramming and Cell Biology International.
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.