Kun Qu

14.8k citations
103 papers · 9.5k indexed · 6 hit papers · h-index 41
    • Cancer-related molecular mechanisms research 14
    • RNA Research and Splicing 21
    • RNA modifications and cancer 18
    • Single-cell and spatial transcriptomics 11
    • RNA and protein synthesis mechanisms 9
    • Genomics and Chromatin Dynamics 9
  • Immunology top 2%
    • Immune Cell Function and Interaction 12
    • T-cell and B-cell Immunology 9

Kun Qu

100 papers receiving 9.4k citations

Hit Papers

Benchmarking spatial ...2252011202620162021250500750

Peers

Kun Qu
Comparison fields: 5 of 156
  • Cancer Research 4.0k
  • Molecular Biology 7.4k
  • Immunology 1.2k
  • Endocrinology 280
  • Developmental Neuroscience 174
Replace Leonardo Salmena with:
Leonardo Salmena Canada
Sven Diederichs Germany
Sean M. Grimmond Australia
Yvonne Tay Singapore
Artemis G. Hatzigeorgiou Greece
Jin‐Wu Nam South Korea
Alistair R. R. Forrest Australia
Pieter Mestdagh Belgium
Maite Huarte Spain
Kun Qu relative to Leonardo Salmena Canada Leonardo Salmena's profile →
Citations per field
00.5×3.4×
Leonardo Salmena · 1×
Citations per year

Countries citing papers authored by Kun Qu

Since Specialization
Citations

This map shows the geographic impact of Kun Qu'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 Kun Qu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Qu more than expected).

Fields of papers citing papers by Kun Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kun Qu. 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 Kun Qu. The network helps show where Kun Qu may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Kun Qu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kun Qu Line = papers co-authored together Kun Qu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20242
4 20247
5 202313
6 202313
7 202349
8 202211
9 202121
10 202019
11 20202
12 202028
13 201972
14 20191
15 201842
16 201746
17 201638
18 201449
19 201254
20 201234

About Kun Qu

Kun Qu is a scholar working on Cancer Research, Immunology, Aging, Molecular Biology and Endocrinology, having authored 103 papers that have together received 9.5k indexed citations. Recurring topics across this work include RNA Research and Splicing (21 papers), RNA modifications and cancer (18 papers), Cancer-related molecular mechanisms research (14 papers), Immune Cell Function and Interaction (12 papers), Single-cell and spatial transcriptomics (11 papers), RNA and protein synthesis mechanisms (9 papers), Genomics and Chromatin Dynamics (9 papers) and T-cell and B-cell Immunology (9 papers). The work is most often cited by research in Cancer Research (4.0k citations), Molecular Biology (7.4k citations), Immunology (1.2k citations), Endocrinology (280 citations) and Developmental Neuroscience (174 citations). Kun Qu has collaborated with scholars based in China, United States and Poland. Frequent co-authors include Howard Y. Chang, Ci Chu, Jiajing Zhang, Franklin L. Zhong, Maja Artandi, Paul A. Khavari, Ryan A. Flynn, Dan E. Webster, Markus Kretz and Marius Wernig. Their work appears in journals such as Nature Communications, Cell Reports, Cell stem cell, Developmental Cell and Journal of Investigative Dermatology.

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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