Sui‐Dan Chen

446 citations
26 papers · 301 · h-index 10

Impact in

  • Hepatology top 10%
    • Liver Disease and Transplantation
    • Liver Diseases and Immunity
    • Liver Disease Diagnosis and Treatment

Papers in

Sui‐Dan Chen

23 papers receiving 300 citations

Peers

Sui‐Dan Chen
Comparison fields: 5 of 52
  • Hepatology 50
  • Epidemiology 151
  • Cancer Research 31
  • Endocrinology, Diabetes and Metabolism 33
  • Cell Biology 27
Replace Seita Kataoka with:
Seita Kataoka Japan
Marcelle de Carvalho Ribeiro United States
Christina K. Cajigas‐Du Ross United States
Han-Chieh Lin Taiwan
Yasushi Okura Japan
Yanan Ming China
Kan Toriguchi Japan
Yusuke Tsuchimoto Japan
Antonina Giammanco Italy
Xiaobo Cai China
Sui‐Dan Chen relative to Seita Kataoka Japan Seita Kataoka's profile →
Citations per field
00.5×1.5×2.4×
Seita Kataoka · 1×
Citations per year

Countries citing papers authored by Sui‐Dan Chen

Since Specialization
Citations

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

Fields of papers citing papers by Sui‐Dan Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sui‐Dan Chen. 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 Sui‐Dan Chen. The network helps show where Sui‐Dan Chen may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202450
2 202241
3 202330
4 202128
5 202327
6 202118
7 202213
8 202112
9 202210
10 20229
11 20248
12 20238
13 20228
14 20217
15
Increased CDK4 protein expression predicts a poor prognosis in mucosal melanoma associated with the p16INK4a-CDK4-pRb pathway.
20197
16 20217
17 20245
18 20234
19 20233
20 20242

About Sui‐Dan Chen

Sui‐Dan Chen is a scholar working on Epidemiology, Endocrinology, Diabetes and Metabolism, Oncology, Surgery and Molecular Biology, having authored 26 papers that have together received 301 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (18 papers), Diet, Metabolism, and Disease (2 papers), Ferroptosis and cancer prognosis (1 paper), Cancer Immunotherapy and Biomarkers (1 paper), Trace Elements in Health (1 paper), Cutaneous Melanoma Detection and Management (1 paper), Thyroid Cancer Diagnosis and Treatment (1 paper) and Endoplasmic Reticulum Stress and Disease (1 paper). The work is most often cited by research in Hepatology (50 citations), Epidemiology (151 citations), Cancer Research (31 citations), Endocrinology, Diabetes and Metabolism (33 citations) and Cell Biology (27 citations). Sui‐Dan Chen has collaborated with scholars based in China, Italy and United Kingdom. Frequent co-authors include Ming‐Hua Zheng, Giovanni Targher, Christopher D. Byrne, Liang‐Jie Tang, Pei‐Wu Zhu, Huai Zhang, Hong‐Lei Ma, Gang Li, Vincent Wai‐Sun Wong and Xiaodong Wang. Their work appears in journals such as Liver International, JHEP Reports, Alimentary Pharmacology & Therapeutics, Journal of Hepatology and Nutrition Metabolism and Cardiovascular Diseases.

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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