Hailin Chen

433 total citations
24 papers, 288 citations indexed

About

Hailin Chen is a scholar working on Pharmacology, Pathology and Forensic Medicine and Immunology. According to data from OpenAlex, Hailin Chen has authored 24 papers receiving a total of 288 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Pharmacology, 6 papers in Pathology and Forensic Medicine and 6 papers in Immunology. Recurrent topics in Hailin Chen's work include Multiple Myeloma Research and Treatments (4 papers), Cancer Mechanisms and Therapy (3 papers) and Cholinesterase and Neurodegenerative Diseases (3 papers). Hailin Chen is often cited by papers focused on Multiple Myeloma Research and Treatments (4 papers), Cancer Mechanisms and Therapy (3 papers) and Cholinesterase and Neurodegenerative Diseases (3 papers). Hailin Chen collaborates with scholars based in China, United States and Taiwan. Hailin Chen's co-authors include Kui Yang, Ning Liu, Youquan Gu, Jun Chen, Lijie Xing, Kenneth C. Anderson, Shih‐Feng Cho, Yu‐Tzu Tai, Nikhil C. Munshi and Jianxing Chen and has published in prestigious journals such as Blood, Clinical Cancer Research and Toxicology and Applied Pharmacology.

In The Last Decade

Hailin Chen

21 papers receiving 285 citations

Peers

Hailin Chen
Comparison fields: 5 of 72
  • Oncology 109
  • Molecular Biology 104
  • Hematology 60
  • Immunology 46
  • Rheumatology 38
Replace Hina Khan with:
Hina Khan United States
Jingjing Jiang China
Yunjie Chen China
Liwen Li China
Dean Messing United States
Sherri Smith United States
Mu-Peng Li China
Christoph Gerdes Germany
Yangmin Qiu China
Eva Brčáková Czechia
Hina Khan United States View profile →
Citations per field, relative to Hailin Chen
Hailin Chen · 1×
Citations per year, relative to Hailin Chen
Hailin Chen · 1×

Countries citing papers authored by Hailin Chen

Since Specialization
Citations

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

Fields of papers citing papers by Hailin Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hailin Chen

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 0
3 5
4 1
5 0
6 2
7 6
8 2
9 34
10 22
11 6
12 7
13 64
14 2
15 2
16 65
17 23
18 17
19 16
20
[Therapeutic effect of acupoint-injection combined with electroacupuncture on chronic pharyngitis].
1

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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