Jia‐Shing Chen

20 papers receiving 534 citations

Peers

Jia‐Shing Chen
Comparison fields: 5 of 82
  • Biological Psychiatry 19
  • Horticulture 8
  • Biochemistry 39
  • Cancer Research 69
  • Cellular and Molecular Neuroscience 70
Replace Leonardo Lisbôa da Motta with:
Leonardo Lisbôa da Motta Brazil
Saori Hata Japan
Deborah Pietrobono Italy
Zahra Ashkavand United States
Md. Shamim Hossain Japan
Jemma Gatliff United Kingdom
Xanthi Antoniou Italy
Shiyong Diao United States
Annapurna Chalasani United Kingdom
Jia‐Shing Chen relative to Leonardo Lisbôa da Motta Brazil Leonardo Lisbôa da Motta's profile →
Citations per field
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Leonardo Lisbôa da Motta · 1×
Citations per year

Countries citing papers authored by Jia‐Shing Chen

Since Specialization
Citations

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

Fields of papers citing papers by Jia‐Shing Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007100
2 201297
3 201167
4 201162
5 200342
6 201141
7 202119
8 201619
9 202015
10 202115
11 202113
12 202012
13 201411
14 20218
15 20225
16 20234
17 20234
18 20233
19 20251
20 20211

About Jia‐Shing Chen

Jia‐Shing Chen is a scholar working on Molecular Biology, Immunology, Neurology, Oncology and Genetics, having authored 22 papers that have together received 539 indexed citations. Recurring topics across this work include Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Cancer-related gene regulation (3 papers), Immune cells in cancer (3 papers), Traditional and Medicinal Uses of Annonaceae (2 papers), Genetics and Neurodevelopmental Disorders (2 papers), Congenital heart defects research (2 papers), Reproductive System and Pregnancy (2 papers) and Genomic variations and chromosomal abnormalities (2 papers). The work is most often cited by research in Biological Psychiatry (19 citations), Horticulture (8 citations), Biochemistry (39 citations), Cancer Research (69 citations) and Cellular and Molecular Neuroscience (70 citations). Jia‐Shing Chen has collaborated with scholars based in Taiwan, United States and India. Frequent co-authors include H. Sunny Sun, Shaw‐Jenq Tsai, Te-Jen Lai, Tsung-Ming Chen, Huimin Wang, Hsueh‐Wei Chang, Inn‐Wen Chong, Bing‐Hung Chen, Chung‐Yi Chen and Kung‐Chia Young. Their work appears in journals such as The FASEB Journal, Journal of Agricultural and Food Chemistry, Scientific Reports, Nutritional Neuroscience and Cancer Cell International.

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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