Jun Koseki

3.2k total citations
72 papers, 2.4k citations indexed

About

Jun Koseki is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Jun Koseki has authored 72 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Molecular Biology, 24 papers in Cancer Research and 17 papers in Oncology. Recurrent topics in Jun Koseki's work include Epigenetics and DNA Methylation (15 papers), Cancer, Hypoxia, and Metabolism (13 papers) and Cancer Cells and Metastasis (9 papers). Jun Koseki is often cited by papers focused on Epigenetics and DNA Methylation (15 papers), Cancer, Hypoxia, and Metabolism (13 papers) and Cancer Cells and Metastasis (9 papers). Jun Koseki collaborates with scholars based in Japan, United Kingdom and United States. Jun Koseki's co-authors include Masamitsu Konno, Yuichiro� Doki, Masaki Mori, Hideshi Ishii, Koichi Kawamoto, Naohiro Nishida, Ayumu Asai, Taroh Satoh, Tsunekazu Mizushima and Kazuhiko Ogawa and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

Jun Koseki

69 papers receiving 2.3k citations

Peers

Jun Koseki

ONCOL

EPIDE

PRM

Sejal Vyas United States

Masamitsu Konno Japan

Frédéric Dayan France

Jianwei Zhu China

Janice Tsang Hong Kong

Carolyn Cao United States

Raymond E. Moellering United States

Cyril Corbet Belgium

Maria Peiris‐Pagès United Kingdom

Paolo Ubezio Italy

Sejal Vyas United States

Jun Koseki

1.3k ×0.8

563 ×0.5

425 ×0.8

ONCOL

203 ×1.2

EPIDE

103 ×0.7

PRM

Citations per year, relative to Jun Koseki Jun Koseki (= 1×) peers Sejal Vyas

Countries citing papers authored by Jun Koseki

Since Specialization

Citations

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

Fields of papers citing papers by Jun Koseki

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Koseki

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Koseki. A scholar is included among the top collaborators of Jun Koseki 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 Jun Koseki. Jun Koseki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Sato, Takahiko, Daisuke Sugiyama, Jun Koseki, et al.. (2025). Sustained inhibition of CSF1R signaling augments antitumor immunity through inhibiting tumor-associated macrophages. JCI Insight. 10(1). 10 indexed citations

Koseki, Jun, Jun Yokoyama, Tomohiro Akashi, et al.. (2024). Survivability and life support in sealed mini-ecosystems with simulated planetary soils. Scientific Reports. 14(1). 26322–26322.

Koseki, Jun, Haruka Hirose, Masamitsu Konno, & Teppei Shimamura. (2022). Theoretical Computational Analysis Predicts Interaction Changes Due to Differences of a Single Molecule in DNA. Applied Sciences. 13(1). 510–510. 1 indexed citations

Koseki, Jun, Hidekazu Takahashi, Norikatsu Miyoshi, et al.. (2019). Disruption of Endolysosomal RAB5/7 Efficiently Eliminates Colorectal Cancer Stem Cells. Cancer Research. 79(7). 1426–1437. 51 indexed citations

Konno, Masamitsu, Jun Koseki, Ayumu Asai, et al.. (2019). Distinct methylation levels of mature microRNAs in gastrointestinal cancers. Nature Communications. 10(1). 3888–3888. 143 indexed citations

Asai, Ayumu, Masamitsu Konno, Jun Koseki, et al.. (2019). One-carbon metabolism for cancer diagnostic and therapeutic approaches. Cancer Letters. 470. 141–148. 32 indexed citations

Tsunekuni, Kenta, Masamitsu Konno, Naotsugu Haraguchi, et al.. (2019). CD44/CD133-Positive Colorectal Cancer Stem Cells are Sensitive to Trifluridine Exposure. Scientific Reports. 9(1). 14861–14861. 53 indexed citations

Ohshiro, Takahito, Masamitsu Konno, Jun Koseki, et al.. (2019). Direct Analysis of Incorporation of an Anticancer Drug into DNA at Single-Molecule Resolution. Scientific Reports. 9(1). 3886–3886. 17 indexed citations

Toratani, Masayasu, Masamitsu Konno, Ayumu Asai, et al.. (2018). A Convolutional Neural Network Uses Microscopic Images to Differentiate between Mouse and Human Cell Lines and Their Radioresistant Clones. Cancer Research. 78(23). 6703–6707. 22 indexed citations

10.

Konno, Masamitsu, Hidetoshi Matsui, Jun Koseki, et al.. (2018). Computational trans-omics approach characterised methylomic and transcriptomic involvements and identified novel therapeutic targets for chemoresistance in gastrointestinal cancer stem cells. Scientific Reports. 8(1). 899–899. 4 indexed citations

11.

Haraguchi, Naotsugu, Jun Koseki, Yujiro Nishizawa, et al.. (2017). Low expression of the GOPC is a poor prognostic marker in colorectal cancer. Oncology Letters. 14(4). 4483–4490. 5 indexed citations

12.

Sato, Katsutoshi, Naohiro Nishida, Jun Koseki, et al.. (2016). MicroRNA miR-374, a potential radiosensitizer for carbon ion beam radiotherapy. Oncology Reports. 36(5). 2946–2950. 15 indexed citations

13.

Sueda, Toshinori, Daisuke Sakai, Koichi Kawamoto, et al.. (2016). BRAFV600E inhibition stimulates AMP-activated protein kinase-mediated autophagy in colorectal cancer cells. Scientific Reports. 6(1). 18949–18949. 38 indexed citations

14.

Koseki, Jun, Hidetoshi Matsui, Masamitsu Konno, et al.. (2016). A Trans-omics Mathematical Analysis Reveals Novel Functions of the Ornithine Metabolic Pathway in Cancer Stem Cells. Scientific Reports. 6(1). 20726–20726. 11 indexed citations

15.

Miyo, Masaaki, Masamitsu Konno, Naohiro Nishida, et al.. (2016). Metabolic Adaptation to Nutritional Stress in Human Colorectal Cancer. Scientific Reports. 6(1). 38415–38415. 55 indexed citations

16.

Miyo, Masaaki, Masamitsu Konno, Hugh Shunsuke Colvin, et al.. (2016). The importance of mitochondrial folate enzymes in human colorectal cancer. Oncology Reports. 37(1). 417–425. 48 indexed citations

17.

Nishizawa, Yujiro, Naohiro Nishida, Masamitsu Konno, et al.. (2016). Clinical Significance of Histone Demethylase NO66 in Invasive Colorectal Cancer. Annals of Surgical Oncology. 24(3). 841–849. 16 indexed citations

18.

Konno, Masamitsu, Jun Koseki, Nobuhiro Tanuma, et al.. (2015). Pyruvate kinase M2, but not M1, allele maintains immature metabolic states of murine embryonic stem cells. Regenerative Therapy. 1. 63–71. 6 indexed citations

19.

Hasegawa, Shinichiro, Hiroaki Nagano, Masamitsu Konno, et al.. (2015). A crucial epithelial to mesenchymal transition regulator, Sox4/Ezh2 axis is closely related to the clinical outcome in pancreatic cancer patients. International Journal of Oncology. 48(1). 145–152. 31 indexed citations

20.

Koseki, Jun, Yukiumi Kita, & Masanori Tachikawa. (2010). Formation of Schiff-base for photoreaction mechanism of red shift of GFP spectra. Biophysical Chemistry. 147(3). 140–145. 5 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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