Xiaoling Cai

4.2k citations
187 papers · 2.8k · h-index 27

Impact in

Papers in

Xiaoling Cai

177 papers receiving 2.7k citations

Peers

Xiaoling Cai
Comparison fields: 5 of 137
  • Endocrinology, Diabetes and Metabolism 839
  • Pharmacology 488
  • Biotechnology 206
  • Nephrology 79
  • Toxicology 39
Replace Hirotoshi Utsunomiya with:
Hirotoshi Utsunomiya Japan
Cheng Zhang China
Eric A.G. Blomme United States
Veronika A. Myasoedova Italy
Yuanyuan Shi China
Maria Gabriella Caruso Italy
Sung‐Koo Kang South Korea
Maria Notarnicola Italy
Jing Gong China
Xianglu Rong China
Xiaoling Cai relative to Hirotoshi Utsunomiya Japan Hirotoshi Utsunomiya's profile →
Citations per field
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Hirotoshi Utsunomiya · 1×
Citations per year

Countries citing papers authored by Xiaoling Cai

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoling Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 187 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017139
2 2008122
3 201883
4 200982
5 201981
6 201979
7 202072
8 200869
9 201555
10 200754
11 201750
12 202148
13 201747
14 201745
15 201444
16 201744
17 200644
18 200743
19 201938
20 201438

About Xiaoling Cai

Xiaoling Cai is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology, Surgery, Pharmacology and Epidemiology, having authored 187 papers that have together received 2.8k indexed citations. Recurring topics across this work include Diabetes Treatment and Management (46 papers), Pancreatic function and diabetes (15 papers), Microbial Natural Products and Biosynthesis (12 papers), Diabetes Management and Research (12 papers), Metabolism, Diabetes, and Cancer (11 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (9 papers), Diabetes and associated disorders (7 papers) and Marine Sponges and Natural Products (6 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (839 citations), Pharmacology (488 citations), Biotechnology (206 citations), Nephrology (79 citations) and Toxicology (39 citations). Xiaoling Cai has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Linong Ji, Wenjia Yang, Xueyao Han, Linong Ji, Xueying Gao, Fang Lv, Chu Lin, Yifei Chen, Yongcheng Lin and Zhigang She. Their work appears in journals such as Frontiers in Endocrinology, Diabetes Obesity and Metabolism, Magnetic Resonance in Chemistry, PLoS ONE and Journal of Diabetes.

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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