Ken Iseki

6.6k total citations · 1 hit paper
273 papers, 5.4k citations indexed

About

Ken Iseki is a scholar working on Oncology, Molecular Biology and Pharmacology. According to data from OpenAlex, Ken Iseki has authored 273 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 117 papers in Oncology, 89 papers in Molecular Biology and 58 papers in Pharmacology. Recurrent topics in Ken Iseki's work include Drug Transport and Resistance Mechanisms (102 papers), Pharmacological Effects and Toxicity Studies (38 papers) and Antibiotics Pharmacokinetics and Efficacy (38 papers). Ken Iseki is often cited by papers focused on Drug Transport and Resistance Mechanisms (102 papers), Pharmacological Effects and Toxicity Studies (38 papers) and Antibiotics Pharmacokinetics and Efficacy (38 papers). Ken Iseki collaborates with scholars based in Japan, United States and United Kingdom. Ken Iseki's co-authors include Masaki Kobayashi, Takeshi Hirano, Shirou Itagaki, Mitsuru Sugawara, Jiro Ogura, Katsumi Miyazaki, Katsuya Narumi, Yuki Sato, Ayako Furugen and Michiya Kobayashi and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Journal of Agricultural and Food Chemistry.

In The Last Decade

Ken Iseki

265 papers receiving 5.3k citations

Hit Papers

In vitro and in vivo antioxidant properties of chlorogeni... 2010 2026 2015 2020 2010 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ken Iseki Japan 35 1.9k 1.5k 813 658 463 273 5.4k
Marilyn E. Morris United States 45 3.4k 1.9× 2.2k 1.5× 729 0.9× 715 1.1× 543 1.2× 189 7.8k
Su Zeng China 49 4.2k 2.3× 1.8k 1.2× 927 1.1× 447 0.7× 308 0.7× 392 9.7k
Walter Jäger Austria 39 1.9k 1.0× 1.4k 1.0× 680 0.8× 486 0.7× 358 0.8× 209 5.8k
Uwe Fuhr Germany 47 1.3k 0.7× 1.6k 1.1× 1.2k 1.5× 842 1.3× 152 0.3× 199 6.9k
Zhong Zuo Hong Kong 47 3.4k 1.8× 909 0.6× 1.7k 2.0× 394 0.6× 614 1.3× 247 8.5k
U. Kristina Walle United States 45 2.4k 1.3× 1.4k 0.9× 910 1.1× 318 0.5× 1.2k 2.6× 95 6.9k
Shu‐Feng Zhou China 55 4.1k 2.2× 2.1k 1.5× 1.5k 1.9× 673 1.0× 147 0.3× 340 11.7k
Mario Dicato Luxembourg 57 5.1k 2.8× 1.6k 1.1× 1.1k 1.4× 430 0.7× 546 1.2× 219 10.8k
Ismael J. Hidalgo United States 29 1.8k 1.0× 2.3k 1.5× 355 0.4× 783 1.2× 116 0.3× 70 5.6k
James W. Paxton New Zealand 35 1.7k 0.9× 1.4k 0.9× 574 0.7× 817 1.2× 136 0.3× 161 4.8k

Countries citing papers authored by Ken Iseki

Since Specialization
Citations

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

Fields of papers citing papers by Ken Iseki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ken Iseki

This figure shows the co-authorship network connecting the top 25 collaborators of Ken Iseki. A scholar is included among the top collaborators of Ken Iseki 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 Ken Iseki. Ken Iseki 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.
Yamamoto, Yuta, Katsuya Narumi, Naoko Yamagishi, et al.. (2025). HYA ameliorated postprandial hyperglycemia in type 1 diabetes model rats with bolus insulin treatment. Acta Diabetologica. 62(8). 1337–1345. 1 indexed citations
2.
Kobayashi, Masaki, et al.. (2023). Regulation of Chloride Channels by Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitor-Induced α-Defensin 5. Biological and Pharmaceutical Bulletin. 47(1). 159–165. 3 indexed citations
3.
Imai, Shungo, Yoh Takekuma, Hitoshi Kashiwagi, et al.. (2020). Validation of the usefulness of artificial neural networks for risk prediction of adverse drug reactions used for individual patients in clinical practice. PLoS ONE. 15(7). e0236789–e0236789. 31 indexed citations
4.
Imai, Shungo, et al.. (2019). Construction of a flow chart–like risk prediction model of ganciclovir‐induced neutropaenia including severity grade: A data mining approach using decision tree. Journal of Clinical Pharmacy and Therapeutics. 44(5). 726–734. 8 indexed citations
5.
Furugen, Ayako, Ayako Nishimura, Masaki Kobayashi, et al.. (2019). Quantification of eight benzodiazepines in human breastmilk and plasma by liquid-liquid extraction and liquid-chromatography tandem mass spectrometry: Application to evaluation of alprazolam transfer into breastmilk. Journal of Pharmaceutical and Biomedical Analysis. 168. 83–93. 29 indexed citations
6.
Furugen, Ayako, Katsuya Narumi, Ayako Nishimura, et al.. (2018). Valproic acid transport in the choriocarcinoma placenta cell line JEG-3 proceeds independently of the proton-dependent transporters MCT1 and MCT4. Drug Metabolism and Pharmacokinetics. 33(6). 270–274. 4 indexed citations
8.
Kimura, Yuki, Masaki Kobayashi, Masaru Asari, et al.. (2018). Genetic variations in the monocarboxylate transporter genes (SLC16A1, SLC16A3, and SLC16A11) in the Japanese population. Drug Metabolism and Pharmacokinetics. 33(5). 215–218. 7 indexed citations
10.
Kobayashi, Masaki, et al.. (2017). Identification of a selective inhibitor of human monocarboxylate transporter 4. Biochemical and Biophysical Research Communications. 495(1). 427–432. 34 indexed citations
11.
Imai, Shungo, et al.. (2015). Evaluation of Predictive Accuracy between Two Types of Vancomycin TDM Analysis Software. 16(4). 169–178. 1 indexed citations
12.
Sato, Yuki, Masaki Kobayashi, Shirou Itagaki, et al.. (2012). Involvement of Cholesterol Membrane Transporter Niemann-Pick C1-Like 1 in the Intestinal Absorption of Lutein. Journal of Pharmacy & Pharmaceutical Sciences. 15(2). 256–256. 44 indexed citations
13.
Yano, Ikuko, Ken Iseki, Takao Aoyama, et al.. (2009). Survey on Situation of Pharmacist Faculties in Japanese Pharmacy Schools. Iryo Yakugaku (Japanese Journal of Pharmaceutical Health Care and Sciences). 35(1). 43–49.
14.
Ogura, Jiro, Masaki Kobayashi, Shirou Itagaki, Takeshi Hirano, & Ken Iseki. (2008). Alteration of Mrp2 and P-gp expression, including expression in remote organs, after intestinal ischemia-reperfusion. Life Sciences. 82(25-26). 1242–1248. 18 indexed citations
15.
Fukuda, Yuko, Yoshinobu Hata, Takeshi Hirano, et al.. (2002). Absorption Profile in the Patients with Gatric Cancer after Gastrectomy.. Rinsho yakuri/Japanese Journal of Clinical Pharmacology and Therapeutics. 33(3). 67–72.
16.
Kobayashi, Michiya, et al.. (1995). Sodium‐dependent Putrescine Transport in Rat Intestinal Basolateral Membrane. Pharmacy and Pharmacology Communications. 1(7). 337–339. 2 indexed citations
17.
Iseki, Ken, et al.. (1995). Uptake of 6‐Mercaptopurine Riboside via the Nucleoside Transporter in the Human Intestinal Brush‐border Membrane. Pharmacy and Pharmacology Communications. 1(3). 127–129. 1 indexed citations
18.
Nomura, A, et al.. (1994). Altered Alpha-1-acid Glycoprotein Concentration and Free Fraction of Disopyramide in Patients with Heart Disease.. Rinsho yakuri/Japanese Journal of Clinical Pharmacology and Therapeutics. 25(2). 413–418. 1 indexed citations
20.
Saitoh, Hiroshi, et al.. (1989). TRANSPORT CHARACTERISTICS OF QUATERNARY AMMONIUM COMPOUNDS ACROSS RAT SMALL INTESTINAL BRUSH BORDER MEMBRANE. Journal of Pharmacobio-Dynamics. 12(5). 2 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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