Katsuhiro Yamano

462 total citations
17 papers, 391 citations indexed

About

Katsuhiro Yamano is a scholar working on Oncology, Pharmacology and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Katsuhiro Yamano has authored 17 papers receiving a total of 391 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Oncology, 12 papers in Pharmacology and 3 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Katsuhiro Yamano's work include Drug Transport and Resistance Mechanisms (12 papers), Pharmacogenetics and Drug Metabolism (12 papers) and Drug-Induced Hepatotoxicity and Protection (6 papers). Katsuhiro Yamano is often cited by papers focused on Drug Transport and Resistance Mechanisms (12 papers), Pharmacogenetics and Drug Metabolism (12 papers) and Drug-Induced Hepatotoxicity and Protection (6 papers). Katsuhiro Yamano collaborates with scholars based in Japan and United Kingdom. Katsuhiro Yamano's co-authors include Yasufumi Sawada, Koujirou Yamamoto, Hirotami Matsuo, Hajime Kotaki, Tatsuji Iga, Hisakazu Ohtani, Mikihiko Naito, Yukinori Kawahara, Hitomi Takanaga and Takashi Tsuruo and has published in prestigious journals such as Biochemistry, Antimicrobial Agents and Chemotherapy and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Katsuhiro Yamano

17 papers receiving 380 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Katsuhiro Yamano Japan 10 233 205 95 72 66 17 391
Kiran C. Patki United States 7 245 1.1× 137 0.7× 62 0.7× 43 0.6× 58 0.9× 13 435
Renato J. Scialis United States 15 232 1.0× 295 1.4× 144 1.5× 35 0.5× 98 1.5× 24 502
Kenji Tabata Japan 14 214 0.9× 212 1.0× 67 0.7× 86 1.2× 113 1.7× 29 561
Aaron M. Moss United States 7 117 0.5× 193 0.9× 85 0.9× 61 0.8× 114 1.7× 10 453
Naoe Yamane Japan 10 206 0.9× 212 1.0× 143 1.5× 51 0.7× 85 1.3× 15 451
Ian E. Templeton United States 9 212 0.9× 118 0.6× 80 0.8× 48 0.7× 102 1.5× 18 421
Anthony Harrison United Kingdom 10 259 1.1× 220 1.1× 95 1.0× 37 0.5× 101 1.5× 15 536
I. Gardner United Kingdom 10 195 0.8× 103 0.5× 60 0.6× 50 0.7× 133 2.0× 17 510
Angela Äbelö Sweden 12 195 0.8× 106 0.5× 46 0.5× 122 1.7× 123 1.9× 26 541
Johan Palm Sweden 8 150 0.6× 337 1.6× 193 2.0× 55 0.8× 77 1.2× 11 418

Countries citing papers authored by Katsuhiro Yamano

Since Specialization
Citations

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

Fields of papers citing papers by Katsuhiro Yamano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Katsuhiro Yamano

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

All Works

17 of 17 papers shown
1.
Ashizawa, Naoki, et al.. (2023). Uricosuric Agents Affect Plasma and Kidney Concentration of Adefovir <i>via</i> Inhibition of Oat1 and Mrp2 in Rats. Biological and Pharmaceutical Bulletin. 46(2). 170–176. 5 indexed citations
2.
3.
Yamano, Katsuhiro, et al.. (2015). In vitro–in vivoextrapolations to evaluate the effect of concomitant drugs on tacrolimus (FK506) exposure. Biopharmaceutics & Drug Disposition. 36(5). 265–274. 5 indexed citations
4.
Yamano, Katsuhiro, et al.. (2014). Effect of telaprevir on the metabolism and hepatic uptake of tacrolimus (FK506). Biopharmaceutics & Drug Disposition. 35(9). 501–512. 6 indexed citations
5.
Naritomi, Yoichi, Kazuhiro Tetsuka, Hiroyuki Moriguchi, et al.. (2013). Species differences in intestinal glucuronidation activities between humans, rats, dogs and monkeys. Xenobiotica. 44(3). 205–216. 22 indexed citations
6.
Yamano, Katsuhiro, et al.. (2012). Method for predicting human intestinal first-pass metabolism of UGT substrate compounds. Xenobiotica. 42(10). 980–988. 8 indexed citations
7.
Naritomi, Yoichi, Ken‐ichi Hosoya, Hiroyuki Moriguchi, et al.. (2012). Quantitative Prediction of Human Intestinal Glucuronidation Effects on Intestinal Availability of UDP-Glucuronosyltransferase Substrates Using In Vitro Data. Drug Metabolism and Disposition. 40(9). 1771–1777. 10 indexed citations
8.
Tetsuka, Kazuhiro, Yoichi Naritomi, Hiroyuki Moriguchi, et al.. (2011). Quantitative Prediction of Intestinal Glucuronidation of Drugs in Rats Using In Vitro Metabolic Clearance Data. Drug Metabolism and Pharmacokinetics. 27(2). 171–180. 18 indexed citations
9.
Sawada, Yasufumi, et al.. (2002). Effects of Single and Repeated Treatment with Itraconazole on the Pharmacokinetics of Midazolam in Rats. Drug Metabolism and Pharmacokinetics. 17(4). 275–283. 2 indexed citations
10.
Yamano, Katsuhiro, Koujirou Yamamoto, Masataka Katashima, et al.. (2001). Prediction of midazolam-CYP3A inhibitors interaction in the human liver from in vivo/in vitro absorption, distribution, and metabolism data.. PubMed. 29(4 Pt 1). 443–52. 66 indexed citations
11.
Matsuo, Hirotami, et al.. (2001). In-vivo kinetics of the interaction between midazolam and erythromycin in rats, taking account of metabolic intermediate complex formation. Journal of Pharmacy and Pharmacology. 53(5). 643–651. 9 indexed citations
12.
Yamano, Katsuhiro, Koujirou Yamamoto, Hajime Kotaki, et al.. (2000). Quantitative Prediction of Metabolic Inhibition of Midazolam by Erythromycin, Diltiazem, and Verapamil in Rats: Implication of Concentrative Uptake of Inhibitors into Liver. Journal of Pharmacology and Experimental Therapeutics. 292(3). 1118–1126. 32 indexed citations
13.
Yamano, Katsuhiro, et al.. (1999). Correlation between In Vivo and In Vitro Hepatic Uptake of Metabolic Inhibitors of Cytochrome P-450 in Rats. Drug Metabolism and Disposition. 27(11). 1225–1231. 28 indexed citations
14.
Yamano, Katsuhiro, et al.. (1999). Quantitative Prediction of Metabolic Inhibition of Midazolam by Itraconazole and Ketoconazole in Rats: Implication of Concentrative Uptake of Inhibitors into Liver. Drug Metabolism and Disposition. 27(3). 395–402. 59 indexed citations
15.
Takanaga, Hitomi, Hirotami Matsuo, Katsuhiro Yamano, et al.. (1998). P-Glycoprotein-Mediated Transport of Itraconazole across the Blood-Brain Barrier. Antimicrobial Agents and Chemotherapy. 42(7). 1738–1744. 87 indexed citations
16.
Matsuo, Hirotami, et al.. (1998). Quantitative prediction of the interaction of midazolam and histamine H2 receptor antagonists in rats.. PubMed. 26(4). 318–23. 15 indexed citations
17.
Tagaya, Mitsuo, et al.. (1989). Kinetic studies of the pyridoxal kinase from pig liver: slow-binding inhibition by adenosine tetraphosphopyridoxal. Biochemistry. 28(11). 4670–4675. 11 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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