Jun Ji

1.1k citations
42 papers · 833 · h-index 18

Impact in

    • Cancer, Hypoxia, and Metabolism
    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • RNA modifications and cancer
    • Epigenetics and DNA Methylation
    • Histone Deacetylase Inhibitors Research

Papers in

    • Cancer-related gene regulation 5
    • Histone Deacetylase Inhibitors Research 4
    • RNA modifications and cancer 4
    • Epigenetics and DNA Methylation 3
    • TGF-β signaling in diseases 3
    • Peptidase Inhibition and Analysis 4

Jun Ji

41 papers receiving 822 citations

Peers

Jun Ji
Comparison fields: 5 of 94
  • Cancer Research 203
  • Molecular Biology 487
  • Oncology 156
  • Pulmonary and Respiratory Medicine 92
  • Cell Biology 50
Replace Kuo Yang with:
Kuo Yang China
Sung Hee Hong South Korea
Jung‐Yu Kan Taiwan
Yi-Chieh Yang Taiwan
Neda Shajari Iran
Bixin Xi China
Ze Yu China
Yansu Chen China
Jun Ji relative to Kuo Yang China Kuo Yang's profile →
Citations per field
00.5×
Kuo Yang · 1×
Citations per year

Countries citing papers authored by Jun Ji

Since Specialization
Citations

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

Fields of papers citing papers by Jun Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201793
2 201363
3 200845
4 201642
5 201937
6 201836
7 202333
8 201432
9 201532
10 200432
11 201732
12 202030
13 202427
14 201626
15 201525
16 200523
17 201022
18 201421
19 201317
20 201416

About Jun Ji

Jun Ji is a scholar working on Molecular Biology, Oncology, Cancer Research, Pathology and Forensic Medicine and Health, Toxicology and Mutagenesis, having authored 42 papers that have together received 833 indexed citations. Recurring topics across this work include Cancer-related gene regulation (5 papers), Peptidase Inhibition and Analysis (4 papers), Histone Deacetylase Inhibitors Research (4 papers), RNA modifications and cancer (4 papers), Epigenetics and DNA Methylation (3 papers), TGF-β signaling in diseases (3 papers), MicroRNA in disease regulation (3 papers) and Galectins and Cancer Biology (2 papers). The work is most often cited by research in Cancer Research (203 citations), Molecular Biology (487 citations), Oncology (156 citations), Pulmonary and Respiratory Medicine (92 citations) and Cell Biology (50 citations). Jun Ji has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Yingyan Yu, Jun Zhang, Zhenggang Zhu, Qu Cai, Jinling Jiang, Bingya Liu, Xuehua Chen, Min Shi, Chenfei Zhou and Chao Wang. Their work appears in journals such as Cancer Letters, International Journal of Oncology, Gene, Free Radical Biology and Medicine and Journal of Toxicology and Environmental Health.

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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