Jun Tan

639 citations
35 papers · 347 indexed · h-index 11

Impact in

Papers in

    • RNA modifications and cancer 4
    • Kruppel-like factors research 3
    • Hedgehog Signaling Pathway Studies 3
    • Phytochemical compounds biological activities 3
    • Bacterial biofilms and quorum sensing 2
    • Natural product bioactivities and synthesis 2
    • RNA Research and Splicing 2
    • Advanced biosensing and bioanalysis techniques 2

Jun Tan

31 papers receiving 344 citations

Peers

Jun Tan
Comparison fields: 5 of 93
  • Molecular Medicine 16
  • Reproductive Medicine 23
  • Biochemistry 16
  • Molecular Biology 181
  • Cancer Research 39
Replace Xiaozhen Zhao with:
Xiaozhen Zhao China
HyunJun Kang South Korea
Atefeh Araghi Iran
Chai-Ching Lin Taiwan
Lijun Ye China
Anatoly V. Kubyshkin Russia
Woo Young Choi South Korea
Metwally M. Montaser Saudi Arabia
Jun Tan relative to Xiaozhen Zhao China Xiaozhen Zhao's profile →
Citations per field
00.5×3.2×
Xiaozhen Zhao · 1×
Citations per year

Countries citing papers authored by Jun Tan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202382
2 202338
3 201920
4 201714
5 202413
6 201712
7 201911
8 202311
9 201911
10 202310
11 201910
12 202110
13 202110
14 20148
15
[Synonymous codon usage bias in the rice cultivar 93-11 (Oryza sativa L. ssp. indica)].
20038
16 20218
17 20238
18 20187
19 20217
20 20236

About Jun Tan

Jun Tan is a scholar working on Molecular Biology, Cancer Research, Reproductive Medicine, Molecular Medicine and Endocrinology, having authored 35 papers that have together received 347 indexed citations. Recurring topics across this work include RNA modifications and cancer (4 papers), Kruppel-like factors research (3 papers), Hedgehog Signaling Pathway Studies (3 papers), Phytochemical compounds biological activities (3 papers), Bacterial biofilms and quorum sensing (2 papers), Natural product bioactivities and synthesis (2 papers), RNA Research and Splicing (2 papers) and Advanced biosensing and bioanalysis techniques (2 papers). The work is most often cited by research in Molecular Medicine (16 citations), Reproductive Medicine (23 citations), Biochemistry (16 citations), Molecular Biology (181 citations) and Cancer Research (39 citations). Jun Tan has collaborated with scholars based in China, Singapore and Canada. Frequent co-authors include Jidong Zhang, Zhixu He, Shan Zeng, Dan Zhang, Hong Shen, Xianyao Wang, Chunyang Li, Ziqing Zhu, Jian-Jun Guo and Ying Tian. Their work appears in journals such as Evidence-based Complementary and Alternative Medicine, Asian Journal of Andrology, Movement Disorders, Journal of Cellular Physiology and ACS Omega.

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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