Gunsagar S. Gulati
- Molecular Biology top 10%
- Immunology top 5%
- Neurology top 1%
- Oncology top 10%
- Cancer Research top 10%
- Co-authors
- Aaron M. NewmanDaniel J. WescheStephen R. QuakeQingyun LiLu ZhouGuoqiang YuTony Wyss‐CorayMariko L. Bennett
- Topics
- Immune cells in cancer (6 papers)Single-cell and spatial transcriptomics (5 papers)Hematopoietic Stem Cell Transplantation (5 papers)
- Partner nations
- United StatesIndiaPoland
In The Last Decade
Gunsagar S. Gulati
22 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Molecular Biology 985
- Immunology 738
- Neurology 603
- Oncology 442
- Cancer Research 270
Countries citing papers authored by Gunsagar S. Gulati
This map shows the geographic impact of Gunsagar S. Gulati'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 Gunsagar S. Gulati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gunsagar S. Gulati more than expected).
Fields of papers citing papers by Gunsagar S. Gulati
This network shows the impact of papers produced by Gunsagar S. Gulati. 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 Gunsagar S. Gulati. The network helps show where Gunsagar S. Gulati may publish in the future.
Co-authorship network of co-authors of Gunsagar S. Gulati
This figure shows the co-authorship network connecting the top 25 collaborators of Gunsagar S. Gulati. A scholar is included among the top collaborators of Gunsagar S. Gulati based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gunsagar S. Gulati. Gunsagar S. Gulati is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | Profiling cell identity and tissue architecture with single-cell and spatial transcriptomicsbreakdown → | 89 |
| 5 | 3 | |
| 6 | T cell characteristics associated with toxicity to immune checkpoint blockade in patients with melanomabreakdown → | 180 |
| 7 | 0 | |
| 8 | 89 | |
| 9 | 12 | |
| 10 | Single-cell transcriptional diversity is a hallmark of developmental potentialbreakdown → | 712 |
| 11 | 30 | |
| 12 | 23 | |
| 13 | 41 | |
| 14 | 110 | |
| 15 | 45 | |
| 16 | Developmental Heterogeneity of Microglia and Brain Myeloid Cells Revealed by Deep Single-Cell RNA Sequencingbreakdown → | 697 |
| 17 | 52 | |
| 18 | 2 | |
| 19 | 95 | |
| 20 | 58 |
About Gunsagar S. Gulati
Gunsagar S. Gulati is a scholar working on Hematology, Immunology and Genetics, having authored 26 papers that have together received 2.3k indexed citations. Recurring topics across this work include Immune cells in cancer (6 papers), Single-cell and spatial transcriptomics (5 papers) and Hematopoietic Stem Cell Transplantation (5 papers). The work is most often cited by research in Neurology (603 citations), Immunology (738 citations) and Developmental Neuroscience (127 citations). Gunsagar S. Gulati has collaborated with scholars based in United States, India and Poland. Frequent co-authors include Aaron M. Newman, Daniel J. Wesche, Stephen R. Quake, Qingyun Li, Lu Zhou, Guoqiang Yu, Tony Wyss‐Coray, Mariko L. Bennett, Norma Neff and Jennifer Okamoto. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.
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.