Bo‐Syong Pan

1.6k total citations · 1 hit paper
21 papers, 488 citations indexed

About

Bo‐Syong Pan is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Bo‐Syong Pan has authored 21 papers receiving a total of 488 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 5 papers in Oncology and 4 papers in Cell Biology. Recurrent topics in Bo‐Syong Pan's work include Ubiquitin and proteasome pathways (5 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Epigenetics and DNA Methylation (3 papers). Bo‐Syong Pan is often cited by papers focused on Ubiquitin and proteasome pathways (5 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Epigenetics and DNA Methylation (3 papers). Bo‐Syong Pan collaborates with scholars based in United States, Taiwan and China. Bo‐Syong Pan's co-authors include Hui‐Kuan Lin, Hongyu Li, Che-Chia Hsu, Bu‐Miin Huang, Danni Peng, Rajesh Manne, Asad Moten, Zhen Cai, Tingjin Chen and Zheng‐Yu Wang and has published in prestigious journals such as Cell, Journal of Biological Chemistry and Nature Cell Biology.

In The Last Decade

Bo‐Syong Pan

21 papers receiving 482 citations

Hit Papers

NSUN2 is a glucose sensor suppressing cGAS/STING to maint... 2023 2026 2024 2025 2023 40 80 120

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bo‐Syong Pan United States 12 355 108 94 56 46 21 488
Xueyuan Wu China 10 264 0.7× 188 1.7× 74 0.8× 45 0.8× 45 1.0× 22 478
Ana C. Millena United States 8 267 0.8× 105 1.0× 89 0.9× 41 0.7× 87 1.9× 8 449
Chengpeng Yu China 14 318 0.9× 133 1.2× 107 1.1× 84 1.5× 67 1.5× 24 538
Jiali Shen United States 11 357 1.0× 59 0.5× 75 0.8× 29 0.5× 30 0.7× 14 493
Danilo Piobbico Italy 15 261 0.7× 98 0.9× 77 0.8× 41 0.7× 41 0.9× 26 439
Jean-Pierre Roperch France 9 335 0.9× 71 0.7× 164 1.7× 26 0.5× 48 1.0× 10 503
Zhen Cai China 7 475 1.3× 149 1.4× 81 0.9× 62 1.1× 48 1.0× 9 593
Jessica Charlet United States 10 543 1.5× 91 0.8× 86 0.9× 60 1.1× 44 1.0× 14 742

Countries citing papers authored by Bo‐Syong Pan

Since Specialization
Citations

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

Fields of papers citing papers by Bo‐Syong Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bo‐Syong Pan. 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 Bo‐Syong Pan. The network helps show where Bo‐Syong Pan may publish in the future.

Co-authorship network of co-authors of Bo‐Syong Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Bo‐Syong Pan. A scholar is included among the top collaborators of Bo‐Syong Pan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bo‐Syong Pan. Bo‐Syong Pan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Zheng‐Yu, Bo‐Syong Pan, Rajesh Manne, et al.. (2025). CD36-mediated endocytosis of proteolysis-targeting chimeras. Cell. 188(12). 3219–3237.e18. 15 indexed citations
2.
Pan, Bo‐Syong, Cheng‐Yu Lin, Gilbert Aaron Lee, & Hui‐Kuan Lin. (2025). Targeting SETDB1 in cancer and immune regulation: Potential therapeutic strategies in cancer. The Kaohsiung Journal of Medical Sciences. 41(3). e12933–e12933. 1 indexed citations
3.
Pan, Bo‐Syong, Che-Chia Hsu, Xiaobo Zhou, et al.. (2025). Glucose metabolism and its direct action in cancer and immune regulation: opportunities and challenges for metabolic targeting. Journal of Biomedical Science. 32(1). 71–71. 1 indexed citations
4.
Hsu, Che-Chia, Chi‐Yun Wang, Rajesh Manne, et al.. (2025). ALDH4A1 functions as an active component of the MPC complex maintaining mitochondrial pyruvate import for TCA cycle entry and tumour suppression. Nature Cell Biology. 27(5). 847–862. 2 indexed citations
6.
Su, Bor‐Chyuan, Chunming Yang, Pei‐Ling Hsu, et al.. (2024). Impacts of hyperthermic chemotherapeutic agent on cytotoxicity, chemoresistance-related proteins and PD-L1 expression in human gastric cancer cells. International Journal of Hyperthermia. 41(1). 2310017–2310017. 5 indexed citations
7.
Chen, Tingjin, Zhigang Xu, Rajesh Manne, et al.. (2023). NSUN2 is a glucose sensor suppressing cGAS/STING to maintain tumorigenesis and immunotherapy resistance. Cell Metabolism. 35(10). 1782–1798.e8. 121 indexed citations breakdown →
8.
Hu, Lanlin, Mingxin Liu, Bo Tang, et al.. (2023). Posttranslational regulation of liver kinase B1 in human cancer. Journal of Biological Chemistry. 299(4). 104570–104570. 9 indexed citations
9.
Manne, Rajesh, Mohammad Anas, Vasudevarao Penugurti, et al.. (2022). Deregulated transcription factors in cancer cell metabolisms and reprogramming. Seminars in Cancer Biology. 86(Pt 3). 1158–1174. 37 indexed citations
11.
Cai, Zhen, Asad Moten, Danni Peng, et al.. (2020). The Skp2 Pathway: A Critical Target for Cancer Therapy. Seminars in Cancer Biology. 67(Pt 2). 16–33. 118 indexed citations
12.
Chang, Ming‐Min, Bo‐Syong Pan, Chia‐Yih Wang, & Bu‐Miin Huang. (2019). Cordycepin‐induced unfolded protein response‐dependent cell death, and AKT/MAPK‐mediated drug resistance in mouse testicular tumor cells. Cancer Medicine. 8(8). 3949–3964. 15 indexed citations
13.
Liu, Chunfang, Zhen Cai, Guoxiang Jin, et al.. (2018). Abnormal gametogenesis induced by p53 deficiency promotes tumor progression and drug resistance. Cell Discovery. 4(1). 54–54. 15 indexed citations
14.
Chang, Ming‐Min, Bo‐Syong Pan, Shang‐Hsun Yang, et al.. (2018). FGF9/FGFR2 increase cell proliferation by activating ERK1/2, Rb/E2F1, and cell cycle pathways in mouse Leydig tumor cells. Cancer Science. 109(11). 3503–3518. 36 indexed citations
15.
Huang, Bu‐Miin, Edmund Cheung So, Yung‐Chia Chen, et al.. (2016). Midazolam regulated caspase pathway, endoplasmic reticulum stress, autophagy, and cell cycle to induce apoptosis in MA-10 mouse Leydig tumor cells. OncoTargets and Therapy. 9. 2519–2519. 15 indexed citations
16.
Chen, Pei‐Jung, et al.. (2015). Apoptotic effect of cordycepin combined with cisplatin and/or paclitaxel on MA-10 mouse Leydig tumor cells. OncoTargets and Therapy. 8. 2345–2345. 9 indexed citations
17.
Huang, Bu‐Miin, et al.. (2014). Midazolam induces apoptosis in MA-10 mouse Leydig tumor cells through caspase activation and the involvement of MAPK signaling pathway. OncoTargets and Therapy. 7. 211–211. 12 indexed citations
18.
Pan, Bo‐Syong, et al.. (2013). Cordycepin enhances cisplatin apoptotic effect through caspase/MAPK pathways in human head and neck tumor cells. OncoTargets and Therapy. 6. 983–983. 25 indexed citations
19.
Pan, Bo‐Syong, Chun‐Yu Lin, & Bu‐Miin Huang. (2011). The Effect of Cordycepin on Steroidogenesis and Apoptosis in MA‐10Mouse Leydig Tumor Cells. Evidence-based Complementary and Alternative Medicine. 2011(1). 750468–750468. 21 indexed citations
20.
Pan, Bo‐Syong, Chun‐Yu Lin, & Bu‐Miin Huang. (2011). The Effect of Cordycepin on Steroidogenesis and Apoptosis in MA-10 Mouse Leydig Tumor Cells.. Biology of Reproduction. 85(Suppl_1). 542–542. 4 indexed citations

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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