Yogesh Dhungana

3.3k citations
27 papers · 1.9k indexed · 2 hit papers · h-index 18
Topics
Immune Cell Function and Interaction (15 papers)T-cell and B-cell Immunology (11 papers)CAR-T cell therapy research (4 papers)
Partner nations
United StatesChinaRussia

In The Last Decade

Yogesh Dhungana

27 papers receiving 1.9k citations

Hit Papers

Lipid signalling enforces functional specialization of Tr...20212026202220242021202350100150200250

Peers

Yogesh Dhungana
Comparison fields: 5 of 80
  • Immunology 1.2k
  • Molecular Biology 773
  • Oncology 584
  • Cancer Research 357
  • Genetics 143
Replace Mario Di Matteo with:
Mario Di Matteo Belgium
Yiyun Lin United States
Filip Bednar United States
Elena Jachetti Italy
Jimmy K. Stauffer United States
Ariadna Mendoza‐Naranjo United Kingdom
Sunila Pradeep United States
Dedeepya Vaka United States
Minu K. Srivastava United States
Leonardo Vargas Sweden
Yogesh Dhungana relative to Mario Di Matteo Belgium Mario Di Matteo's profile →
Citations per field
00.5×1.5×2.4×
Mario Di Matteo · 1×
Citations per year

Countries citing papers authored by Yogesh Dhungana

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Yogesh Dhungana

This figure shows the co-authorship network connecting the top 25 collaborators of Yogesh Dhungana. A scholar is included among the top collaborators of Yogesh Dhungana 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 Yogesh Dhungana. Yogesh Dhungana is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 8
3
SLC38A2 and glutamine signalling in cDC1s dictate anti-tumour immunitybreakdown →
154
4 10
5 8
6
Lipid signalling enforces functional specialization of Treg cells in tumoursbreakdown →
286
7 95
8 2
9 61
10 60
11 39
12 61
13 53
14 281
15 62
16 87
17 35
18
Metabolic signaling directs the reciprocal lineage decisions of αβ and γδ T cells
14
19 146
20 132

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) and CAR-T cell therapy research (4 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, Cell and Nature Communications.

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.

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