Dev Bhatt
Impact in
- Immunology top 5%
- Immune Cell Function and Interaction
- Immune Response and Inflammation
- T-cell and B-cell Immunology
- Cancer Research top 5%
- NF-κB Signaling Pathways
Papers in
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- interferon and immune responses 3
- Immune Cell Function and Interaction 3
- T-cell and B-cell Immunology 2
-
- RNA Research and Splicing 3
- RNA and protein synthesis mechanisms 3
- Single-cell and spatial transcriptomics 2
- Genomics and Chromatin Dynamics 2
- Co-authors
- Sankar Ghosh (5 shared papers)Stephen T. Smale (5 shared papers)Amy Pandya‐Jones (2 shared papers)Douglas L. Black (2 shared papers)Ann-Jay Tong (3 shared papers)Vladimir Ramirez-Carrozzi (3 shared papers)Christine S. Cheng (2 shared papers)Daniel Braas (2 shared papers)
- Journals
- Cell (3 papers)Cold Spring Harbor Symposia on Quantitative Biology (1 paper)The International Journal of Biochemistry & Cell Biology (1 paper)The Journal of Experimental Medicine (1 paper)BMC Genomics (1 paper)
- Partner nations
- United StatesGermanyChina
In The Last Decade
Dev Bhatt
14 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 99
- Immunology 749
- Cancer Research 407
- Molecular Biology 901
- Oncology 221
- Biological Psychiatry 11
Countries citing papers authored by Dev Bhatt
This map shows the geographic impact of Dev Bhatt'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 Dev Bhatt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dev Bhatt more than expected).
Fields of papers citing papers by Dev Bhatt
This network shows the impact of papers produced by Dev Bhatt. 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 Dev Bhatt. The network helps show where Dev Bhatt may publish in the future.
Co-authors
The 25 scholars most cited alongside Dev Bhatt, 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 | 2009 | 466 | |
| 2 | 2012 | 355 | |
| 3 | 2017 | 241 | |
| 4 | 2014 | 206 | |
| 5 | 2017 | 169 | |
| 6 | 2013 | 80 | |
| 7 | 2021 | 53 | |
| 8 | 2021 | 49 | |
| 9 | 2021 | 25 | |
| 10 | 2020 | 13 | |
| 11 | 2009 | 13 | |
| 12 | 2023 | 9 | |
| 13 | 2013 | 6 | |
| 14 | 2022 | 5 |
About Dev Bhatt
Dev Bhatt is a scholar working on Immunology, Molecular Biology, Cancer Research, Oncology and Epidemiology, having authored 14 papers that have together received 1.7k indexed citations. Recurring topics across this work include NF-κB Signaling Pathways (4 papers), interferon and immune responses (3 papers), Immune Cell Function and Interaction (3 papers), RNA Research and Splicing (3 papers), RNA and protein synthesis mechanisms (3 papers), T-cell and B-cell Immunology (2 papers), Single-cell and spatial transcriptomics (2 papers) and Genomics and Chromatin Dynamics (2 papers). The work is most often cited by research in Immunology (749 citations), Cancer Research (407 citations), Molecular Biology (901 citations), Oncology (221 citations) and Biological Psychiatry (11 citations). Dev Bhatt has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Sankar Ghosh, Stephen T. Smale, Amy Pandya‐Jones, Douglas L. Black, Ann-Jay Tong, Vladimir Ramirez-Carrozzi, Christine S. Cheng, Daniel Braas, Kevin R. Doty and Christine Hong. Their work appears in journals such as Cell, Cold Spring Harbor Symposia on Quantitative Biology, The International Journal of Biochemistry & Cell Biology, The Journal of Experimental Medicine and BMC Genomics.
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.