Dai Cui

848 citations
43 papers · 636 · h-index 18

Impact in

Papers in

Dai Cui

40 papers receiving 621 citations

Peers

Dai Cui
Comparison fields: 5 of 83
  • Endocrinology, Diabetes and Metabolism 271
  • Cancer Research 68
  • Health, Toxicology and Mutagenesis 57
  • Genetics 107
  • Oncology 100
Replace Patricia A. Smanik with:
Patricia A. Smanik United States
Shunhua Xing United States
Agnieszka Piekiełko‐Witkowska Poland
Karolina Zielińska United Kingdom
Malik Bisserier United States
Eric E. Niederkofler United States
Naohide Sato Japan
Daniel F. Freitag Germany
Alexander Hermani Germany
L. Demers United States
Dai Cui relative to Patricia A. Smanik United States Patricia A. Smanik's profile →
Citations per field
00.5×10×16×
Patricia A. Smanik · 1×
Citations per year

Countries citing papers authored by Dai Cui

Since Specialization
Citations

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

Fields of papers citing papers by Dai Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dai Cui, 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 Dai Cui Line = papers co-authored together Dai Cui links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200777
2 201362
3 202152
4 201133
5 199929
6 201525
7 200924
8 201923
9 201423
10 201322
11 201522
12 201621
13 202021
14 201320
15 201520
16 201818
17 201518
18 201517
19 201616
20 202015

About Dai Cui

Dai Cui is a scholar working on Endocrinology, Diabetes and Metabolism, Electrical and Electronic Engineering, Molecular Biology, Atomic and Molecular Physics, and Optics and Surgery, having authored 43 papers that have together received 636 indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (15 papers), Semiconductor Quantum Structures and Devices (6 papers), Thyroid Disorders and Treatments (6 papers), Radio Frequency Integrated Circuit Design (3 papers), Toxic Organic Pollutants Impact (3 papers), Diabetes and associated disorders (3 papers), S100 Proteins and Annexins (3 papers) and Advancements in Semiconductor Devices and Circuit Design (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (271 citations), Cancer Research (68 citations), Health, Toxicology and Mutagenesis (57 citations), Genetics (107 citations) and Oncology (100 citations). Dai Cui has collaborated with scholars based in China, United States and France. Frequent co-authors include Ling Lan, Lin Jiang, Xiaoyun Liu, Huanhuan Chen, Michael Derwahl, Yifang Hu, He Shi, Xuqin Zheng, Yong Luo and D. Pavlidis. Their work appears in journals such as Scientific Reports, PLoS ONE, European Archives of Oto-Rhino-Laryngology, Journal of Cellular and Molecular Medicine and Oncology Reports.

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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