Jun Deng

892 citations
30 papers · 597 · h-index 14

Impact in

    • Cancer, Hypoxia, and Metabolism
    • Cancer, Lipids, and Metabolism
    • Cancer-related molecular mechanisms research
    • Metabolism, Diabetes, and Cancer
    • Gut microbiota and health
    • RNA modifications and cancer
    • Epigenetics and DNA Methylation

Papers in

    • Metabolism, Diabetes, and Cancer 8
    • PI3K/AKT/mTOR signaling in cancer 6
    • RNA modifications and cancer 5
    • Gut microbiota and health 4
    • Epigenetics and DNA Methylation 3
    • Metabolomics and Mass Spectrometry Studies 3
    • Cancer-related Molecular Pathways 5

Jun Deng

27 papers receiving 588 citations

Peers

Jun Deng
Comparison fields: 5 of 82
  • Cancer Research 175
  • Molecular Biology 390
  • Neurology 35
  • Oncology 104
  • Pharmacology 30
Replace Ting Tao with:
Ting Tao China
Sheng Huang China
Sichun Zhou China
Jie Wei China
Mengmeng Dou China
Fukushi Abekura South Korea
Xinxing Li China
Veronica Cocetta Italy
Kwame Oteng Darko China
Jun Deng relative to Ting Tao China Ting Tao's profile →
Citations per field
00.5×1.5×
Ting Tao · 1×
Citations per year

Countries citing papers authored by Jun Deng

Since Specialization
Citations

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

Fields of papers citing papers by Jun Deng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019145
2 201868
3 201841
4 201939
5 201929
6 202228
7 201827
8 201826
9 202325
10 201521
11 201919
12 201716
13 202016
14 201915
15 202212
16 201910
17 20239
18 20199
19 20237
20 20197

About Jun Deng

Jun Deng is a scholar working on Molecular Biology, Oncology, Cancer Research, Neurology and Pulmonary and Respiratory Medicine, having authored 30 papers that have together received 597 indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (8 papers), PI3K/AKT/mTOR signaling in cancer (6 papers), Cancer-related Molecular Pathways (5 papers), RNA modifications and cancer (5 papers), Gut microbiota and health (4 papers), Cancer, Lipids, and Metabolism (3 papers), Epigenetics and DNA Methylation (3 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). The work is most often cited by research in Cancer Research (175 citations), Molecular Biology (390 citations), Neurology (35 citations), Oncology (104 citations) and Pharmacology (30 citations). Jun Deng has collaborated with scholars based in China, Macao and Germany. Frequent co-authors include Mei Peng, Sichun Zhou, Xiaoping Yang, Ting Tao, Caimei He, Yanjun Huang, Di Xiao, Qiongli Su, Kwame Oteng Darko and Zhiren Wang. Their work appears in journals such as Cancer Cell International, Food & Function, Food Science & Nutrition, Archiv der Pharmazie and Biomedical Chromatography.

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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