Yan Tang

3.5k citations
86 papers · 2.7k indexed · 2 hit papers · h-index 29
Topics
Adipose Tissue and Metabolism (18 papers)Adipokines, Inflammation, and Metabolic Diseases (12 papers)Ubiquitin and proteasome pathways (9 papers)

In The Last Decade

Yan Tang

84 papers receiving 2.7k citations

Hit Papers

Autophagy regulates adipose mass and differentiation in mice200920262014202020092024200400600

Peers

Yan Tang
Comparison fields: 5 of 126
  • Molecular Biology 1.1k
  • Epidemiology 994
  • Physiology 840
  • Cancer Research 337
  • Cell Biology 241
Replace Kalyankar Mahadev with:
Kalyankar Mahadev United States
Xiaoyan Hui China
Yuchang Fu United States
Kyu‐Sang Park South Korea
Zhenxiang Liu China
Ronni Nielsen Denmark
Kang Ho Kim United States
Eiji Warabi Japan
Haiyan Xu United States
Carolina E. Hagberg Sweden
Yan Tang relative to Kalyankar Mahadev United States Kalyankar Mahadev's profile →
Citations per field
00.5×3.8×
Kalyankar Mahadev · 1×
Citations per year

Countries citing papers authored by Yan Tang

Since Specialization
Citations

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

Fields of papers citing papers by Yan Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Yan Tang. A scholar is included among the top collaborators of Yan Tang 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 Yan Tang. Yan Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 2
3 6
4 1
5
Artemisinins ameliorate polycystic ovarian syndrome by mediating LONP1-CYP11A1 interactionbreakdown →
53
6 5
7 18
8 1
9 61
10 3
11 10
12 15
13 76
14 12
15 37
16 29
17 1
18 32
19
Autophagy regulates adipose mass and differentiation in micebreakdown →
623
20 48

About Yan Tang

Yan Tang is a scholar working on Cancer Research, Physiology and Epidemiology, having authored 86 papers that have together received 2.7k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (18 papers), Adipokines, Inflammation, and Metabolic Diseases (12 papers) and Ubiquitin and proteasome pathways (9 papers). The work is most often cited by research in Physiology (840 citations), Biochemistry (219 citations) and Epidemiology (994 citations). Yan Tang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Shuwen Qian, Gary J. Schwartz, Youqing Xiang, Yen Luu, Jeffrey E. Pessin, Mark J. Czaja, Rajat Singh, Qi‐Qun Tang, Yongjun Wang and Ana María Cuervo. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

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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