Shao-Nian Yang

1.9k total citations
19 papers, 1.4k citations indexed

About

Shao-Nian Yang is a scholar working on Surgery, Molecular Biology and Cell Biology. According to data from OpenAlex, Shao-Nian Yang has authored 19 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Surgery, 11 papers in Molecular Biology and 8 papers in Cell Biology. Recurrent topics in Shao-Nian Yang's work include Pancreatic function and diabetes (12 papers), Cellular transport and secretion (8 papers) and Ion channel regulation and function (5 papers). Shao-Nian Yang is often cited by papers focused on Pancreatic function and diabetes (12 papers), Cellular transport and secretion (8 papers) and Ion channel regulation and function (5 papers). Shao-Nian Yang collaborates with scholars based in Sweden, United States and China. Shao-Nian Yang's co-authors include Per‐Olof Berggren, Martin Köhler, Jia Yu, Barbara Leibiger, Björn Meister, Olof Larsson, Jesper Gromada, Ingo B. Leibiger, Alejandro M. Bertorello and Over Cabrera and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Shao-Nian Yang

19 papers receiving 1.4k citations

Peers

Shao-Nian Yang
Comparison fields: 5 of 80
  • Molecular Biology 793
  • Surgery 733
  • Cell Biology 375
  • Endocrinology, Diabetes and Metabolism 255
  • Genetics 252
Marianne Høy Denmark
Safia Costes France
M C Glennon United States
Stephan C. Collins United Kingdom
Cristina Alarcón United States
Laura Sheu Canada
Mark C. Harbeck United States
Judith A. Creba United Kingdom
Katsuya Tanabe Japan
Timothy Coskran United States
Marianne Høy Denmark View profile →
Citations per field, relative to Shao-Nian Yang
Shao-Nian Yang · 1×
Citations per year, relative to Shao-Nian Yang
Shao-Nian Yang · 1×

Countries citing papers authored by Shao-Nian Yang

Since Specialization
Citations

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

Fields of papers citing papers by Shao-Nian Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shao-Nian Yang. 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 Shao-Nian Yang. The network helps show where Shao-Nian Yang may publish in the future.

Co-authorship network of co-authors of Shao-Nian Yang

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

All Works

19 of 19 papers shown
# Work Indexed citations
1 1
2 23
3 18
4 170
5 157
6 33
7 198
8 80
9 89
10 20
11 70
12 123
13 24
14 83
15 70
16 38
17 78
18 118
19 9

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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