Junling Fu

765 citations
45 papers · 576 · h-index 15

Impact in

Papers in

    • Pancreatic function and diabetes 9
    • Nutrition and Health in Aging 5
    • Adipose Tissue and Metabolism 3

Junling Fu

43 papers receiving 570 citations

Peers

Junling Fu
Comparison fields: 5 of 64
  • Physiology 143
  • Endocrinology, Diabetes and Metabolism 72
  • Endocrine and Autonomic Systems 27
  • Experimental and Cognitive Psychology 52
  • Epidemiology 93
Replace Jie Shi with:
Jie Shi China
Hassan Kahal United Kingdom
Christine Lord United States
Xiaoguang Yao China
Ioannis Lempesis Greece
Renee M. Ross Australia
Yavuz Şimşek Türkiye
Teruhisa Ueda Japan
Inha Jung South Korea
E. Anastasiou Greece
Junling Fu relative to Jie Shi China Jie Shi's profile →
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Citations per year

Countries citing papers authored by Junling Fu

Since Specialization
Citations

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

Fields of papers citing papers by Junling Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201848
2 201841
3 201740
4 201935
5 201831
6 201731
7 201629
8 201726
9 202324
10 202124
11 201823
12 201919
13 202218
14 202016
15 201915
16 202114
17 201613
18 201911
19 201811
20 202110

About Junling Fu

Junling Fu is a scholar working on Surgery, Physiology, Molecular Biology, Epidemiology and Endocrinology, Diabetes and Metabolism, having authored 45 papers that have together received 576 indexed citations. Recurring topics across this work include Pancreatic function and diabetes (9 papers), Adipokines, Inflammation, and Metabolic Diseases (7 papers), Nutrition and Health in Aging (5 papers), Diabetes and associated disorders (3 papers), Fibroblast Growth Factor Research (3 papers), Adipose Tissue and Metabolism (3 papers), Sleep and related disorders (3 papers) and Obesity, Physical Activity, Diet (2 papers). The work is most often cited by research in Physiology (143 citations), Endocrinology, Diabetes and Metabolism (72 citations), Endocrine and Autonomic Systems (27 citations), Experimental and Cognitive Psychology (52 citations) and Epidemiology (93 citations). Junling Fu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Shan Gao, Ming Li, Xinhua Xiao, Lujiao Li, Ge Li, Shuangling Xiu, Lina Sun, Mingyao Li, Steven M. Willi and Dan Feng. Their work appears in journals such as Frontiers in Endocrinology, Cardiovascular Diabetology, Oncotarget, Nutrition and Diabetes & Metabolism.

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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