Yogesh Dhungana
- Immunology top 2%
- Immune Cell Function and Interaction 15
- T-cell and B-cell Immunology 11
- Immunotherapy and Immune Responses 4
- Cancer Research top 5%
- Oncology top 5%
- CAR-T cell therapy research 4
- Cancer Immunotherapy and Biomarkers 2
- Molecular Biology top 10%
- Single-cell and spatial transcriptomics 2
-
- Hippo pathway signaling and YAP/TAZ 3
-
- Acute Myeloid Leukemia Research 2
- Co-authors
- Hongbo ChiPeter VogelNicole M. ChapmanLingyun LongJordy SaraviaCliff GuyHao ShiGeoffrey Neale
- Cited by
- ImmunologyCancer ResearchOncology
- Journals
- Nature (5 papers)The Journal of Experimental Medicine (3 papers)Nature Communications (2 papers)
- Partner nations
- United StatesChinaRussia
In The Last Decade
Yogesh Dhungana
27 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Immunology 1.2k
- Cancer Research 357
- Oncology 584
- Molecular Biology 773
- Biological Psychiatry 23
Countries citing papers authored by Yogesh Dhungana
This map shows the geographic impact of Yogesh Dhungana'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 Yogesh Dhungana with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yogesh Dhungana more than expected).
Fields of papers citing papers by Yogesh Dhungana
This network shows the impact of papers produced by Yogesh Dhungana. 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 Yogesh Dhungana. The network helps show where Yogesh Dhungana may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yogesh Dhungana, 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 | 2025 | 2 | |
| 2 | 2024 | 8 | |
| 3 | SLC38A2 and glutamine signalling in cDC1s dictate anti-tumour immunitybreakdown → | 2023 | 154 |
| 4 | 2023 | 10 | |
| 5 | 2022 | 8 | |
| 6 | Lipid signalling enforces functional specialization of Treg cells in tumoursbreakdown → | 2021 | 286 |
| 7 | 2021 | 95 | |
| 8 | 2021 | 2 | |
| 9 | 2021 | 61 | |
| 10 | 2020 | 60 | |
| 11 | 2020 | 39 | |
| 12 | 2020 | 61 | |
| 13 | 2019 | 53 | |
| 14 | 2019 | 281 | |
| 15 | 2018 | 62 | |
| 16 | 2018 | 87 | |
| 17 | 2018 | 35 | |
| 18 | Metabolic signaling directs the reciprocal lineage decisions of αβ and γδ T cells | 2018 | 14 |
| 19 | 2018 | 146 | |
| 20 | 2018 | 132 |
About Yogesh Dhungana
Yogesh Dhungana is a scholar working on Immunology, Oncology and Cell Biology, having authored 27 papers that have together received 1.9k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (15 papers), T-cell and B-cell Immunology (11 papers), CAR-T cell therapy research (4 papers), Immunotherapy and Immune Responses (4 papers), Hippo pathway signaling and YAP/TAZ (3 papers), Acute Myeloid Leukemia Research (2 papers), Single-cell and spatial transcriptomics (2 papers) and Cancer Immunotherapy and Biomarkers (2 papers). The work is most often cited by research in Immunology (1.2k citations), Cancer Research (357 citations) and Oncology (584 citations). Yogesh Dhungana has collaborated with scholars based in United States, China and Russia. Frequent co-authors include Hongbo Chi, Peter Vogel, Nicole M. Chapman, Lingyun Long, Jordy Saravia, Cliff Guy, Hao Shi, Geoffrey Neale, Seon Ah Lim and Jun Wei. Their work appears in journals such as Nature, The Journal of Experimental Medicine, Nature Communications, Immunity and Science Advances.
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.