Wei Jin

2.8k citations
94 papers · 2.0k · h-index 24

Impact in

Papers in

    • Cell death mechanisms and regulation 6
    • RNA modifications and cancer 5
    • Ubiquitin and proteasome pathways 4
    • RNA Research and Splicing 3

Wei Jin

91 papers receiving 2.0k citations

Peers

Wei Jin
Comparison fields: 5 of 126
  • Rehabilitation 188
  • Cancer Research 233
  • Molecular Biology 846
  • Oncology 271
  • Neurology 66
Replace Xinyan Li with:
Xinyan Li China
Hiroyasu Sakai Japan
Carolyn Foster United States
Maria Graziella Catalano Italy
Yi‐Chao Lee Taiwan
Bhagirath Chaurasia United States
Klara Brixius Germany
Grace Kim United States
Ting Shen China
Keir J. Menzies Canada
Wei Jin relative to Xinyan Li China Xinyan Li's profile →
Citations per field
00.5×1.5×2.0×
Xinyan Li · 1×
Citations per year

Countries citing papers authored by Wei Jin

Since Specialization
Citations

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

Fields of papers citing papers by Wei Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 94 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015160
2 2007155
3 2016115
4 200695
5 200980
6 201568
7 201365
8 201963
9 201554
10 201153
11 200847
12 200747
13 201544
14 201840
15 200738
16 202038
17 201635
18 200734
19 201534
20 201233

About Wei Jin

Wei Jin is a scholar working on Molecular Biology, Oncology, Cancer Research, Surgery and Pathology and Forensic Medicine, having authored 94 papers that have together received 2.0k indexed citations. Recurring topics across this work include Cell death mechanisms and regulation (6 papers), RNA modifications and cancer (5 papers), Neuroinflammation and Neurodegeneration Mechanisms (5 papers), Ubiquitin and proteasome pathways (4 papers), Traumatic Brain Injury and Neurovascular Disturbances (4 papers), Thyroid Disorders and Treatments (4 papers), Phytochemistry and biological activity of medicinal plants (4 papers) and RNA Research and Splicing (3 papers). The work is most often cited by research in Rehabilitation (188 citations), Cancer Research (233 citations), Molecular Biology (846 citations), Oncology (271 citations) and Neurology (66 citations). Wei Jin has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Chuancheng Ren, Wei Xu, Xiaoxiao Zhang, Jiong Wu, Xiaonan Liu, Gen‐Hong Di, Jing Chen, Dayan B. Goodenowe, Zhi-Ming Shao and Zhongjie Zhou. Their work appears in journals such as Journal of Molecular Histology, Journal of Molecular Neuroscience, Scientific Reports, Acta Biochimica et Biophysica Sinica and Cellular and Molecular Neurobiology.

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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