Ling Shen

10.9k citations
133 papers · 3.8k · h-index 34

Impact in

Papers in

Ling Shen

126 papers receiving 3.8k citations

Peers

Ling Shen
Comparison fields: 5 of 130
  • Biological Psychiatry 220
  • Endocrine and Autonomic Systems 298
  • Behavioral Neuroscience 98
  • Pathology and Forensic Medicine 430
  • Ophthalmology 198
Replace Feng He with:
Feng He United States
Arnold Y. Seo United States
Hiroshi Okamoto Japan
Elena Grossini Italy
Alberto Rícci Italy
Pierluigi Navarra Italy
Servio H. Ramirez United States
Masahiro Nishibori Japan
Jun Tang China
Huan Yang China
Ling Shen relative to Feng He United States Feng He's profile →
Citations per field
00.5×1.5×1.9×
Feng He · 1×
Citations per year

Countries citing papers authored by Ling Shen

Since Specialization
Citations

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

Fields of papers citing papers by Ling Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 133 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013168
2 2015158
3 2010151
4 2016146
5 2015135
6 2012130
7 2013115
8 2014111
9 199993
10 201492
11 202380
12 201573
13 200171
14 202271
15 201264
16 200658
17 200657
18 200556
19 201555
20 202153

About Ling Shen

Ling Shen is a scholar working on Molecular Biology, Endocrine and Autonomic Systems, Epidemiology, Surgery and Oncology, having authored 133 papers that have together received 3.8k indexed citations. Recurring topics across this work include Regulation of Appetite and Obesity (17 papers), Cancer-related molecular mechanisms research (8 papers), Multiple Sclerosis Research Studies (8 papers), Cholesterol and Lipid Metabolism (7 papers), Immune Cell Function and Interaction (6 papers), Tuberculosis Research and Epidemiology (6 papers), Cytokine Signaling Pathways and Interactions (5 papers) and RNA modifications and cancer (5 papers). The work is most often cited by research in Biological Psychiatry (220 citations), Endocrine and Autonomic Systems (298 citations), Behavioral Neuroscience (98 citations), Pathology and Forensic Medicine (430 citations) and Ophthalmology (198 citations). Ling Shen has collaborated with scholars based in United States, China and Sweden. Frequent co-authors include Catherine Schaefer, Stephen C. Woods, Alan S. Brown, Min Liu, Patrick Tso, David Q.‐H. Wang, Yuanyuan Bao, Lisa F. Barcellos, Zheng W. Chen and Ye Xiong. Their work appears in journals such as Oncotarget, Physiology & Behavior, Endocrinology, Frontiers in Immunology and Nature Communications.

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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