Liying Chen

146 papers receiving 2.9k citations

Peers

Liying Chen
Comparison fields: 5 of 180
  • Nephrology 248
  • Endocrinology, Diabetes and Metabolism 268
  • Cardiology and Cardiovascular Medicine 299
  • Cellular and Molecular Neuroscience 216
  • Epidemiology 406
Replace Chi‐Fai Ng with:
Chi‐Fai Ng Hong Kong
Yong Chul Kim South Korea
Soo‐Youn Lee South Korea
Jhi‐Joung Wang Taiwan
Xue Li China
Jun Lyu China
Yi Wang China
Brian R. Smith United States
Lei Liu China
Ralph Green United States
Liying Chen relative to Chi‐Fai Ng Hong Kong Chi‐Fai Ng's profile →
Citations per field
00.5×1.5×
Chi‐Fai Ng · 1×
Citations per year

Countries citing papers authored by Liying Chen

Since Specialization
Citations

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

Fields of papers citing papers by Liying Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 161 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005207
2 2008187
3 1997177
4 2017164
5 2012148
6 2010141
7 2007138
8 202199
9 201795
10 200887
11 199486
12 202085
13 201969
14 202165
15 199753
16 202152
17 200351
18 201850
19 199846
20 202045

About Liying Chen

Liying Chen is a scholar working on Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine, Surgery, Epidemiology and Molecular Biology, having authored 161 papers that have together received 2.9k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (8 papers), Liver Disease Diagnosis and Treatment (7 papers), Neonatal and fetal brain pathology (6 papers), Mobile Health and mHealth Applications (5 papers), Diabetes Treatment and Management (5 papers), Photoreceptor and optogenetics research (5 papers), Gout, Hyperuricemia, Uric Acid (5 papers) and Obesity, Physical Activity, Diet (4 papers). The work is most often cited by research in Nephrology (248 citations), Endocrinology, Diabetes and Metabolism (268 citations), Cardiology and Cardiovascular Medicine (299 citations), Cellular and Molecular Neuroscience (216 citations) and Epidemiology (406 citations). Liying Chen has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Lizheng Fang, Honglei Dai, Jawahar L. Mehta, Wenhua Zhu, Tom Saldeen, Feifei Huang, Bing Pan, Engeng Chen, Jun Wu and W. Herbert Haught. Their work appears in journals such as Journal of Zhejiang University SCIENCE B, Medicine, Blood, Journal of the American College of Cardiology and Neurobiology of Disease.

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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