Hai Chen

500 citations
21 papers · 299 · h-index 9

Impact in

Papers in

Hai Chen

20 papers receiving 293 citations

Peers

Hai Chen
Comparison fields: 5 of 79
  • Molecular Medicine 54
  • Critical Care and Intensive Care Medicine 22
  • Endocrinology 23
  • Developmental Neuroscience 15
  • Anesthesiology and Pain Medicine 14
Replace Dalia Ibrahim with:
Dalia Ibrahim Egypt
Jialing Hu China
Jinxing Feng China
Trung Le Tran South Korea
Lance Chou United States
Jennifer J. Brown United States
Luying Wang China
Yuzhen Huang China
Alex Von Schulze United States
Kelly Pertile Australia
Hai Chen relative to Dalia Ibrahim Egypt Dalia Ibrahim's profile →
Citations per field
00.5×11.5×
Dalia Ibrahim · 1×
Citations per year

Countries citing papers authored by Hai Chen

Since Specialization
Citations

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

Fields of papers citing papers by Hai Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202047
2 202442
3 202140
4 201739
5 201925
6 200620
7 201720
8 202216
9 202214
10 20207
11 20177
12 20215
13 20235
14 20193
15 20212
16 20162
17 20222
18 20251
19 20241
20 20171

About Hai Chen

Hai Chen is a scholar working on Molecular Biology, Organic Chemistry, Pharmacology, Pathology and Forensic Medicine and Developmental Neuroscience, having authored 21 papers that have together received 299 indexed citations. Recurring topics across this work include Circular RNAs in diseases (3 papers), Anesthesia and Neurotoxicity Research (3 papers), Antibiotic Resistance in Bacteria (2 papers), Cardiac Ischemia and Reperfusion (2 papers), Synthesis and biological activity (2 papers), Intensive Care Unit Cognitive Disorders (2 papers), Bacterial biofilms and quorum sensing (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Molecular Medicine (54 citations), Critical Care and Intensive Care Medicine (22 citations), Endocrinology (23 citations), Developmental Neuroscience (15 citations) and Anesthesiology and Pain Medicine (14 citations). Hai Chen has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Chan Chen, Tao Zhu, Rui Gao, Xueying Zhang, Qi Zhao, Xiong Zhu, Jinxing Lu, Min Yuan, Xia Chen and Nanxi Wang. Their work appears in journals such as Oncotarget, Signal Transduction and Targeted Therapy, Journal of Applied Microbiology, Journal of the American Heart Association and RSC Advances.

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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