Can Cui

823 citations
48 papers · 604 indexed · 1 hit paper · h-index 16
Topics
Amyotrophic Lateral Sclerosis Research (15 papers)Neurogenetic and Muscular Disorders Research (9 papers)Parkinson's Disease Mechanisms and Treatments (6 papers)
Journals
Nature CommunicationsSHILAP Revista de lepidopterologíaACS Nano
Partner nations
ChinaSwedenUnited States

In The Last Decade

Can Cui

43 papers receiving 599 citations

Hit Papers

Targeting tumor monocyte-intrinsic PD-L1 by rewiring STIN...2025202620255101520

Peers

Can Cui
Comparison fields: 5 of 87
  • Molecular Biology 222
  • Neurology 184
  • Neurology 93
  • Plant Science 86
  • Genetics 84
Replace Morgayn I. Read with:
Morgayn I. Read New Zealand
Junxia Xie China
Nemat Khan Australia
Chenxia Sheng China
Hyun‐Jeung Yu South Korea
Nobutaka Morimoto Japan
Qian-Hang Shao China
Ruixia Deng Hong Kong
Can Cui relative to Morgayn I. Read New Zealand Morgayn I. Read's profile →
Citations per field
00.5×10×15×18×
Morgayn I. Read · 1×
Citations per year

Countries citing papers authored by Can Cui

Since Specialization
Citations

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

Fields of papers citing papers by Can Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Can Cui

This figure shows the co-authorship network connecting the top 25 collaborators of Can Cui. A scholar is included among the top collaborators of Can Cui 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 Can Cui. Can Cui 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 1
2 0
3 0
4
Targeting tumor monocyte-intrinsic PD-L1 by rewiring STING signaling and enhancing STING agonist therapybreakdown →
20
5 3
6 0
7 1
8 8
9 1
10 51
11 6
12 11
13 22
14 32
15 34
16 46
17 39
18 1
19 1
20 28

About Can Cui

Can Cui is a scholar working on Neurology, Genetics and Neurology, having authored 48 papers that have together received 604 indexed citations. Recurring topics across this work include Amyotrophic Lateral Sclerosis Research (15 papers), Neurogenetic and Muscular Disorders Research (9 papers) and Parkinson's Disease Mechanisms and Treatments (6 papers). The work is most often cited by research in Neurology (184 citations), Neurology (93 citations) and Biological Psychiatry (23 citations). Can Cui has collaborated with scholars based in China, Sweden and United States. Frequent co-authors include Zhongyao Li, Weisong Duan, Chunyan Li, Yakun Liu, Di Wen, Xiaolong Hu, Ying Wang, Wan Wang, Qingchun Zhao and Weihong Meng. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and ACS Nano.

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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