Deepa Ajit
Impact in
- Physiology top 1%
- Alzheimer's disease research and treatments
- Adenosine and Purinergic Signaling
- Biological Psychiatry top 5%
- Tryptophan and brain disorders
Papers in
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- Signaling Pathways in Disease 3
- S100 Proteins and Annexins 2
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- Neuroinflammation and Neurodegeneration Mechanisms 8
- Amyotrophic Lateral Sclerosis Research 2
- Co-authors
- Gary A. Weisman (10 shared papers)Laurie Erb (7 shared papers)Jean M. Camden (6 shared papers)Michael R. Nichols (4 shared papers)Lucas T. Woods (5 shared papers)Grace Y. Sun (6 shared papers)Troy S. Peterson (4 shared papers)Ágnes Simonyi (3 shared papers)
- Journals
- eLife (5 papers)Journal of Neurochemistry (3 papers)Molecular Neurobiology (2 papers)Nature Communications (1 paper)Cell Reports (1 paper)
- Partner nations
- United States
In The Last Decade
Deepa Ajit
22 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 91
- Physiology 272
- Biological Psychiatry 122
- Neurology 366
- Physiology 386
- Developmental Neuroscience 37
Countries citing papers authored by Deepa Ajit
This map shows the geographic impact of Deepa Ajit'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 Ajit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepa Ajit more than expected).
Fields of papers citing papers by Deepa Ajit
This network shows the impact of papers produced by Deepa Ajit. 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 Ajit. The network helps show where Deepa Ajit may publish in the future.
Co-authors
The 25 scholars most cited alongside Deepa Ajit, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 153 | |
| 2 | 2011 | 139 | |
| 3 | 2015 | 100 | |
| 4 | 2015 | 84 | |
| 5 | 2020 | 74 | |
| 6 | 2012 | 72 | |
| 7 | 2017 | 69 | |
| 8 | 2012 | 67 | |
| 9 | 2013 | 51 | |
| 10 | 2012 | 48 | |
| 11 | 2016 | 38 | |
| 12 | 2014 | 37 | |
| 13 | 2013 | 36 | |
| 14 | 2009 | 17 | |
| 15 | 2019 | 16 | |
| 16 | 2009 | 13 | |
| 17 | 2021 | 11 | |
| 18 | 2008 | 11 | |
| 19 | 2023 | 9 | |
| 20 | 2023 | 8 |
About Deepa Ajit
Deepa Ajit is a scholar working on Molecular Biology, Neurology, Physiology, Physiology and Immunology, having authored 23 papers that have together received 1.1k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (9 papers), Neuroinflammation and Neurodegeneration Mechanisms (8 papers), Adenosine and Purinergic Signaling (7 papers), Signaling Pathways in Disease (3 papers), Amyotrophic Lateral Sclerosis Research (2 papers), Tryptophan and brain disorders (2 papers), S100 Proteins and Annexins (2 papers) and Neurogenetic and Muscular Disorders Research (2 papers). The work is most often cited by research in Physiology (272 citations), Biological Psychiatry (122 citations), Neurology (366 citations), Physiology (386 citations) and Developmental Neuroscience (37 citations). Deepa Ajit has collaborated with scholars based in United States. Frequent co-authors include Gary A. Weisman, Laurie Erb, Jean M. Camden, Michael R. Nichols, Lucas T. Woods, Grace Y. Sun, Troy S. Peterson, Ágnes Simonyi, Jau‐Shyong Hong and W. Gibson Wood. Their work appears in journals such as eLife, Journal of Neurochemistry, Molecular Neurobiology, Nature Communications and Cell Reports.
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.