Xinxia Chang

44 papers receiving 1.5k citations

Peers

Xinxia Chang
Comparison fields: 5 of 100
  • Endocrinology, Diabetes and Metabolism 384
  • Epidemiology 721
  • Pharmacology 341
  • Hepatology 147
  • Pharmacology 147
Replace Maren Carstensen with:
Maren Carstensen Germany
Anna Iacono Italy
Anita M. van den Hoek Netherlands
Lin Jia China
Tony Jourdan United States
Madhulika Tripathi Singapore
Michinaga Matsumoto Japan
Rosanna Tamborra Italy
Xinxia Chang relative to Maren Carstensen Germany Maren Carstensen's profile →
Citations per field
00.5×4.6×
Maren Carstensen · 1×
Citations per year

Countries citing papers authored by Xinxia Chang

Since Specialization
Citations

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

Fields of papers citing papers by Xinxia Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019197
2 2015180
3 2010136
4 200989
5 201184
6 201975
7 201671
8 201859
9 201754
10 201447
11 201644
12 201242
13 201737
14 202031
15 202029
16 201628
17 201526
18 202125
19 201525
20
Berberine reverses abnormal expression of L-type pyruvate kinase by DNA demethylation and histone acetylation in the livers of the non-alcoholic fatty disease rat.
201523

About Xinxia Chang

Xinxia Chang is a scholar working on Epidemiology, Endocrinology, Diabetes and Metabolism, Molecular Biology, Hepatology and Physiology, having authored 44 papers that have together received 1.5k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (25 papers), Diet, Metabolism, and Disease (12 papers), Berberine and alkaloids research (7 papers), Liver Diseases and Immunity (6 papers), Diet and metabolism studies (5 papers), Alcohol Consumption and Health Effects (5 papers), Bariatric Surgery and Outcomes (4 papers) and Retinoids in leukemia and cellular processes (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (384 citations), Epidemiology (721 citations), Pharmacology (341 citations), Hepatology (147 citations) and Pharmacology (147 citations). Xinxia Chang has collaborated with scholars based in China, Finland and Canada. Frequent co-authors include Xin Gao, Hongmei Yan, Mingfeng Xia, Hua Bian, Xiaopeng Zhu, Daru Lu, Xiaoyang Sun, Minghong Jiang, Xi Xu and Huandong Lin. Their work appears in journals such as Lipids in Health and Disease, PLoS ONE, Journal of Translational Medicine, Obesity Surgery and Scientific 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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