Junjeong Choi

1.9k total citations · 1 hit paper
42 papers, 1.4k citations indexed

About

Junjeong Choi is a scholar working on Oncology, Cancer Research and Molecular Biology. According to data from OpenAlex, Junjeong Choi has authored 42 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Oncology, 18 papers in Cancer Research and 13 papers in Molecular Biology. Recurrent topics in Junjeong Choi's work include Cancer, Hypoxia, and Metabolism (9 papers), Cancer Cells and Metastasis (6 papers) and Cancer-related Molecular Pathways (5 papers). Junjeong Choi is often cited by papers focused on Cancer, Hypoxia, and Metabolism (9 papers), Cancer Cells and Metastasis (6 papers) and Cancer-related Molecular Pathways (5 papers). Junjeong Choi collaborates with scholars based in South Korea, China and Japan. Junjeong Choi's co-authors include Ja Seung Koo, Yoon Jin, Jones Gyamfi, Woo-Hee Jung, Yun-Hee Lee, Minseob Eom, Jinu Lee, Joo Hye Yeo, Byung Soh Min and Jung Min Han and has published in prestigious journals such as Nature Communications, PLoS ONE and Cell Metabolism.

In The Last Decade

Junjeong Choi

39 papers receiving 1.4k citations

Hit Papers

A Variant of SLC1A5 Is a ... 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junjeong Choi South Korea 17 746 645 441 154 136 42 1.4k
Adriane Feijó Evangelista Brazil 22 834 1.1× 622 1.0× 265 0.6× 148 1.0× 128 0.9× 75 1.4k
Oona Delpuech United Kingdom 20 1.1k 1.4× 460 0.7× 433 1.0× 141 0.9× 243 1.8× 33 1.7k
Yanhua Zheng China 13 1.2k 1.6× 633 1.0× 231 0.5× 187 1.2× 82 0.6× 29 1.7k
Maria Chiara De Santis Italy 14 1.0k 1.4× 333 0.5× 287 0.7× 124 0.8× 139 1.0× 18 1.6k
Noa Rivlin Israel 14 982 1.3× 459 0.7× 719 1.6× 79 0.5× 133 1.0× 15 1.6k
Han Yang China 28 933 1.3× 571 0.9× 365 0.8× 300 1.9× 162 1.2× 71 1.7k
Xisong Ke China 20 1.3k 1.7× 503 0.8× 533 1.2× 247 1.6× 213 1.6× 54 2.0k
Yongdong Feng China 26 972 1.3× 397 0.6× 641 1.5× 326 2.1× 176 1.3× 64 1.7k
Cheng‐Chi Chang Taiwan 21 1.3k 1.8× 478 0.7× 502 1.1× 160 1.0× 110 0.8× 26 1.8k

Countries citing papers authored by Junjeong Choi

Since Specialization
Citations

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

Fields of papers citing papers by Junjeong Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junjeong Choi

This figure shows the co-authorship network connecting the top 25 collaborators of Junjeong Choi. A scholar is included among the top collaborators of Junjeong Choi 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 Junjeong Choi. Junjeong Choi 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.
Sung, Yulseung, Ya Chun Yu, Mirim Lee, et al.. (2025). Targeting cancer glutamine dependency with a first-in-class inhibitor of the mitochondrial glutamine transporter SLC1A5_var. Nature Communications. 16(1). 9690–9690.
2.
Choi, Junjeong, et al.. (2025). Absence of Cysteine and Iron Chelation Induces Ferroptosis in Triple-Negative Breast Cancer Cells. Breast Cancer Basic and Clinical Research. 19. 782049572–782049572. 2 indexed citations
3.
Lee, Seongmin, et al.. (2025). Targeting EPAS-1/HIF-2α Pathway to Address Endocrine Resistance in Luminal A Type Breast Cancer. Translational Oncology. 57. 102415–102415. 1 indexed citations
4.
Lee, Hyesung, Hyunji Lee, Kuglae Kim, et al.. (2024). PLD1 is a key player in cancer stemness and chemoresistance: Therapeutic targeting of cross-talk between the PI3K/Akt and Wnt/β-catenin pathways. Experimental & Molecular Medicine. 56(7). 1479–1487. 9 indexed citations
5.
Kim, Jinyoung, et al.. (2023). Moracin E and M isolated from Morus alba Linné induced the skeletal muscle cell proliferation via PI3K-Akt-mTOR signaling pathway. Scientific Reports. 13(1). 20570–20570. 6 indexed citations
7.
Park, Seung Joon, Hee Chan Yoo, Yulseung Sung, et al.. (2023). Enhanced Glutaminolysis Drives Hypoxia-Induced Chemoresistance in Pancreatic Cancer. Cancer Research. 83(5). 735–752. 34 indexed citations
9.
Gyamfi, Jones, Joo Hye Yeo, Byung Soh Min, et al.. (2021). Interaction between CD36 and FABP4 modulates adipocyte-induced fatty acid import and metabolism in breast cancer. npj Breast Cancer. 7(1). 129–129. 99 indexed citations
10.
Ahn, Yuri, Eun Jung Lee, Junjeong Choi, et al.. (2021). Particulate Matter Promotes Melanin Production through Endoplasmic Reticulum Stress‒Mediated IRE1α Signaling. Journal of Investigative Dermatology. 142(5). 1425–1434.e6. 12 indexed citations
11.
Kim, Honsoul, Junjeong Choi, Dae‐Yeul Yu, & Hye Jin Choi. (2021). Expression of Organic Anion Transporting Polypeptides in an H-Ras 12V Transgenic Mouse Model of Spontaneous Hepatocellular Carcinoma. Yonsei Medical Journal. 62(7). 622–622. 1 indexed citations
12.
Hwang, Ho Kyoung, Sung Hwan Lee, Hyoung‐Il Kim, et al.. (2020). Yonsei Criteria, a Potential Linkage to Intratumoral Foxp3+/CD8+ Ratio for the Prediction of Oncologic Outcomes in Resected Left-Sided Pancreatic Cancer. Yonsei Medical Journal. 61(4). 291–291. 2 indexed citations
13.
Lee, Won-Kyung, et al.. (2019). Intake of green tea products and obesity in nondiabetic overweight and obese females: A systematic review and meta-analysis. Journal of Functional Foods. 58. 330–337. 9 indexed citations
14.
Gyamfi, Jones, Yun-Hee Lee, Byung Soh Min, & Junjeong Choi. (2019). Niclosamide reverses adipocyte induced epithelial-mesenchymal transition in breast cancer cells via suppression of the interleukin-6/STAT3 signalling axis. Scientific Reports. 9(1). 11336–11336. 51 indexed citations
15.
Yoo, Hee Chan, Seung Joon Park, Miso Nam, et al.. (2019). A Variant of SLC1A5 Is a Mitochondrial Glutamine Transporter for Metabolic Reprogramming in Cancer Cells. Cell Metabolism. 31(2). 267–283.e12. 312 indexed citations breakdown →
16.
Choi, Junjeong, et al.. (2018). Expression of Pentose Phosphate Pathway-Related Proteins in Breast Cancer. Disease Markers. 2018. 1–9. 35 indexed citations
17.
Gyamfi, Jones, Yun-Hee Lee, Minseob Eom, & Junjeong Choi. (2018). Interleukin-6/STAT3 signalling regulates adipocyte induced epithelial-mesenchymal transition in breast cancer cells. Scientific Reports. 8(1). 8859–8859. 122 indexed citations
18.
Choi, Junjeong, Yoon Jin, & Ja Seung Koo. (2017). Adipocyte biology in breast cancer: From silent bystander to active facilitator. Progress in Lipid Research. 69. 11–20. 193 indexed citations
19.
Sun, Woo Young, Junjeong Choi, Yoon Jin, & Ja Seung Koo. (2017). Evaluation of the Expression of Amine Oxidase Proteins in Breast Cancer. International Journal of Molecular Sciences. 18(12). 2775–2775. 32 indexed citations
20.
Choi, Junjeong, Do Hee Kim, Woo Hee Jung, & Ja Seung Koo. (2012). Differential expression of immune-related markers in breast cancer by molecular phenotypes. Breast Cancer Research and Treatment. 137(2). 417–429. 9 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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