Shaohui Tang

1.3k citations
55 papers · 803 · h-index 18

Impact in

Papers in

Shaohui Tang

54 papers receiving 789 citations

Peers

Shaohui Tang
Comparison fields: 5 of 100
  • Cancer Research 172
  • Endocrinology, Diabetes and Metabolism 134
  • Hepatology 61
  • Epidemiology 230
  • Molecular Biology 365
Replace Chiara Gabbi with:
Chiara Gabbi United States
Kendal Jensen United States
Roland Köditz Germany
Wen Tang China
Froogh Darakhshan United Kingdom
Dov B. Ballak Netherlands
Stuart M. Raleigh United Kingdom
Hyun Jin Jung South Korea
Robert Kliček Croatia
Eva Serna Spain
Shaohui Tang relative to Chiara Gabbi United States Chiara Gabbi's profile →
Citations per field
00.5×4.0×
Chiara Gabbi · 1×
Citations per year

Countries citing papers authored by Shaohui Tang

Since Specialization
Citations

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

Fields of papers citing papers by Shaohui Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202079
2 200678
3 202147
4
A novel circular RNA hsa_circ_0008035 contributes to gastric cancer tumorigenesis through targeting the miR-375/YBX1 axis.
201943
5 201541
6 200933
7 201631
8
Induction of autophagy and apoptosis by miR-148a through the sonic hedgehog signaling pathway in hepatic stellate cells.
201529
9 201424
10 202322
11 201720
12 201919
13 202219
14 202118
15 202218
16 201918
17 202317
18 201917
19 202316
20 202116

About Shaohui Tang

Shaohui Tang is a scholar working on Molecular Biology, Epidemiology, Cancer Research, Oncology and Pathology and Forensic Medicine, having authored 55 papers that have together received 803 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (14 papers), Cancer-related molecular mechanisms research (8 papers), MicroRNA in disease regulation (7 papers), RNA modifications and cancer (5 papers), Diet and metabolism studies (5 papers), Diet, Metabolism, and Disease (5 papers), Alcohol Consumption and Health Effects (5 papers) and Gut microbiota and health (5 papers). The work is most often cited by research in Cancer Research (172 citations), Endocrinology, Diabetes and Metabolism (134 citations), Hepatology (61 citations), Epidemiology (230 citations) and Molecular Biology (365 citations). Shaohui Tang has collaborated with scholars based in China, Australia and Germany. Frequent co-authors include Kaiyin He, Lu Zhong, Yuting Li, Yuting Li, Liliangzi Guo, Xin Guo, Xiaojuan Peng, Tingzhuang Yi, Maohua Lai and Weiwei Chen. Their work appears in journals such as BMC Endocrine Disorders, Oncotarget, Frontiers in Public Health, Frontiers in Medicine and Oxidative Medicine and Cellular Longevity.

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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