Ping Gu

1.6k citations
48 papers · 1.2k indexed · h-index 18

Impact in

  • Physiology top 5%
    • Adipose Tissue and Metabolism
    • Diet and metabolism studies
    • Adipokines, Inflammation, and Metabolic Diseases

Papers in

    • Adipokines, Inflammation, and Metabolic Diseases 14
    • Adipose Tissue and Metabolism 13

Ping Gu

43 papers receiving 1.2k citations

Peers

Ping Gu
Comparison fields: 5 of 97
  • Physiology 533
  • Epidemiology 497
  • Rehabilitation 93
  • Endocrine and Autonomic Systems 85
  • Geriatrics and Gerontology 44
Replace Dawn K. Coletta with:
Dawn K. Coletta United States
Rocío Vila‐Bedmar Spain
Annie Durand France
Miroslav Baláž Slovakia
Paula M. Miotto Canada
Leire Méndez-Giménez Spain
Sanshiro Tateya United States
Silvia Gogg Sweden
Miki Okada‐Iwabu Japan
Kim A. Sjøberg Denmark
Ping Gu relative to Dawn K. Coletta United States Dawn K. Coletta's profile →
Citations per field
00.5×1.5×2.1×
Dawn K. Coletta · 1×
Citations per year

Countries citing papers authored by Ping Gu

Since Specialization
Citations

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

Fields of papers citing papers by Ping Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015280
2 2013116
3 2022104
4 201774
5 202060
6 201360
7 201753
8 202145
9 202139
10 201539
11 201339
12 201532
13 201923
14 201222
15 202322
16 201221
17 201919
18 201219
19 202017
20 201216

About Ping Gu

Ping Gu is a scholar working on Epidemiology, Physiology, Endocrinology, Diabetes and Metabolism, Cardiology and Cardiovascular Medicine and Molecular Biology, having authored 48 papers that have together received 1.2k indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (14 papers), Adipose Tissue and Metabolism (13 papers), Diabetes Management and Research (9 papers), Diabetes and associated disorders (7 papers), Pancreatic function and diabetes (5 papers), Cardiovascular Disease and Adiposity (5 papers), Apelin-related biomedical research (3 papers) and Sirtuins and Resveratrol in Medicine (3 papers). The work is most often cited by research in Physiology (533 citations), Epidemiology (497 citations), Rehabilitation (93 citations), Endocrine and Autonomic Systems (85 citations) and Geriatrics and Gerontology (44 citations). Ping Gu has collaborated with scholars based in China, Hong Kong and New Zealand. Frequent co-authors include Aimin Xu, Xiaoyan Hui, Bin Lü, Yu Wang, Donghai Wu, Tao Nie, Jiaqing Shao, Tianshi Feng, Jialiang Zhang and Karen S.L. Lam. Their work appears in journals such as Diabetology & Metabolic Syndrome, Clinical and Experimental Hypertension, Diabetes Research and Clinical Practice, Biochemical and Biophysical Research Communications and Cell 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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