Fang Xia

10 papers receiving 402 citations

Peers

Fang Xia
Comparison fields: 5 of 71
  • Pharmacology 159
  • Endocrinology, Diabetes and Metabolism 109
  • Molecular Biology 101
  • Cardiology and Cardiovascular Medicine 76
  • Economics and Econometrics 52
Replace Yasuhisa Akaiwa with:
Yasuhisa Akaiwa Japan
Paulo Caleb Júnior Lima Santos Brazil
Eric A. Millican United States
Ben Burkley United States
Ming Ta Michael Lee United States
Marianne Kristiansen Kringen Norway
Kristen K. Reynolds United States
Sung Eun Sim South Korea
Simcha Blotnick Israel
Fang Xia relative to Yasuhisa Akaiwa Japan Yasuhisa Akaiwa's profile →
Citations per field
00.5×5.2×
Yasuhisa Akaiwa · 1×
Citations per year

Countries citing papers authored by Fang Xia

Since Specialization
Citations

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

Fields of papers citing papers by Fang Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fang Xia

This figure shows the co-authorship network connecting the top 25 collaborators of Fang Xia. A scholar is included among the top collaborators of Fang Xia based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fang Xia. Fang Xia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
#WorkIndexed citations
1 0
2 5
3 19
4 0
5 40
6 1
7 49
8
[Effect of Pinggan Qianyang Recipe Containing Serum on Angiotensin II Induced Vascular Smooth Muscle Cell Proliferation and Migration and DNA Methylation].
2
9 224
10
[Preventive and therapeutic effects of qiongyugao on hepatocellular carcinoma via inhibition of the expression of HBxAg in hepatic carcinoma cells].
1
11
Inhibitory effect of total flavonoids from mulberry tree leaf on small intestine disaccharidases in diabetic rats
4
12 75

About Fang Xia

Fang Xia is a scholar working on Geriatrics and Gerontology, Pharmacology and Endocrine and Autonomic Systems, having authored 12 papers that have together received 420 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (1 paper), Protein Structure and Dynamics (1 paper) and Ginger and Zingiberaceae research (1 paper). The work is most often cited by research in Pharmacology (159 citations), Endocrinology, Diabetes and Metabolism (109 citations) and Internal Medicine (14 citations). Fang Xia has collaborated with scholars based in China and United States. Frequent co-authors include Robert R. Verbrugge, J. Russell Teagarden, Brian F. Gage, Dennis J. O’Kane, Ronald E. Aubert, Robert S. Epstein, Thomas P. Moyer, Changyu Pan, Yating Zhu and J. Lu. Their work appears in journals such as Journal of the American College of Cardiology, Arteriosclerosis Thrombosis and Vascular Biology and Molecules.

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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