Deepa V. Dabir
Impact in
- Neurology top 5%
- Neuroinflammation and Neurodegeneration Mechanisms
- Clinical Biochemistry top 5%
- Metabolism and Genetic Disorders
Papers in
-
- Mitochondrial Function and Pathology 8
- ATP Synthase and ATPases Research 6
- Photosynthetic Processes and Mechanisms 4
- Prion Diseases and Protein Misfolding 2
-
- Alzheimer's disease research and treatments 4
- Co-authors
- Mark S. Forman (5 shared papers)Virginia M.‐Y. Lee (4 shared papers)John Q. Trojanowski (5 shared papers)Carla M. Koehler (9 shared papers)Bin Zhang (3 shared papers)Eric A. Swanson (2 shared papers)Christiane Richter‐Landsberg (2 shared papers)Sung‐Kun Kim (2 shared papers)
- Journals
- Journal of Biological Chemistry (3 papers)Journal of Neuroscience (3 papers)Molecular Biology of the Cell (2 papers)Developmental Cell (1 paper)Nature (1 paper)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Deepa V. Dabir
17 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 88
- Neurology 148
- Clinical Biochemistry 77
- Physiology 280
- Molecular Biology 657
- Aging 17
Countries citing papers authored by Deepa V. Dabir
This map shows the geographic impact of Deepa V. Dabir'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 Deepa V. Dabir with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepa V. Dabir more than expected).
Fields of papers citing papers by Deepa V. Dabir
This network shows the impact of papers produced by Deepa V. Dabir. 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 Deepa V. Dabir. The network helps show where Deepa V. Dabir may publish in the future.
Co-authors
The 25 scholars most cited alongside Deepa V. Dabir, 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 | 2019 | 163 | |
| 2 | 2005 | 149 | |
| 3 | 2007 | 136 | |
| 4 | 2006 | 108 | |
| 5 | 2004 | 104 | |
| 6 | 2013 | 75 | |
| 7 | 2003 | 64 | |
| 8 | 2009 | 60 | |
| 9 | 2010 | 35 | |
| 10 | 2012 | 27 | |
| 11 | 2017 | 27 | |
| 12 | 2012 | 24 | |
| 13 | 2020 | 17 | |
| 14 | 2015 | 13 | |
| 15 | 2017 | 8 | |
| 16 | 2021 | 7 | |
| 17 | 2004 | 1 |
About Deepa V. Dabir
Deepa V. Dabir is a scholar working on Molecular Biology, Physiology, Cell Biology, Cellular and Molecular Neuroscience and Neurology, having authored 17 papers that have together received 1.0k indexed citations. Recurring topics across this work include Mitochondrial Function and Pathology (8 papers), ATP Synthase and ATPases Research (6 papers), Alzheimer's disease research and treatments (4 papers), Photosynthetic Processes and Mechanisms (4 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Prion Diseases and Protein Misfolding (2 papers), Neuroscience and Neuropharmacology Research (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). The work is most often cited by research in Neurology (148 citations), Clinical Biochemistry (77 citations), Physiology (280 citations), Molecular Biology (657 citations) and Aging (17 citations). Deepa V. Dabir has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Mark S. Forman, Virginia M.‐Y. Lee, John Q. Trojanowski, Carla M. Koehler, Bin Zhang, Eric A. Swanson, Christiane Richter‐Landsberg, Sung‐Kun Kim, Samuel A. Hasson and Frederick D. Tsai. Their work appears in journals such as Journal of Biological Chemistry, Journal of Neuroscience, Molecular Biology of the Cell, Developmental Cell and Nature.
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.