Masaaki Fujikawa

495 total citations
10 papers, 394 citations indexed

About

Masaaki Fujikawa is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Masaaki Fujikawa has authored 10 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Oncology and 4 papers in Computational Theory and Mathematics. Recurrent topics in Masaaki Fujikawa's work include Drug Transport and Resistance Mechanisms (4 papers), Computational Drug Discovery Methods (4 papers) and Pharmacogenetics and Drug Metabolism (3 papers). Masaaki Fujikawa is often cited by papers focused on Drug Transport and Resistance Mechanisms (4 papers), Computational Drug Discovery Methods (4 papers) and Pharmacogenetics and Drug Metabolism (3 papers). Masaaki Fujikawa collaborates with scholars based in Japan and United States. Masaaki Fujikawa's co-authors include Miki Akamatsu, Kazuya Nakao, Ryo Shimizu, Hiroshi Yamada, Ikuo Horii, Toshinori Yamamoto, Rie Kikkawa, Yoshimasa Hamada, Satomi Onoue and Yoshiki Seto and has published in prestigious journals such as Chemosphere, Bioorganic & Medicinal Chemistry and Journal of Pharmaceutical and Biomedical Analysis.

In The Last Decade

Masaaki Fujikawa

10 papers receiving 385 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Masaaki Fujikawa Japan 8 155 111 83 78 64 10 394
Yusuke Kamiya Japan 12 116 0.7× 111 1.0× 70 0.8× 79 1.0× 128 2.0× 33 405
Andrew P. Blanchard United States 6 140 0.9× 99 0.9× 144 1.7× 67 0.9× 351 5.5× 8 535
Andrés Olivares‐Morales Switzerland 11 137 0.9× 117 1.1× 87 1.0× 76 1.0× 125 2.0× 19 501
SR Walker United Kingdom 7 87 0.6× 130 1.2× 60 0.7× 76 1.0× 120 1.9× 14 440
Andre Dandeneau United States 5 103 0.7× 83 0.7× 141 1.7× 58 0.7× 304 4.8× 7 426
Petko Alov Bulgaria 12 138 0.9× 103 0.9× 28 0.3× 28 0.4× 45 0.7× 35 433
Luca A. Fenu Switzerland 5 76 0.5× 73 0.7× 141 1.7× 68 0.9× 192 3.0× 6 349
Manisha Iyer United States 12 215 1.4× 224 2.0× 99 1.2× 85 1.1× 193 3.0× 14 611
Chad Stoner United States 10 131 0.8× 121 1.1× 58 0.7× 44 0.6× 93 1.5× 10 333
Sunil Sarda United Kingdom 14 165 1.1× 41 0.4× 117 1.4× 51 0.7× 194 3.0× 24 513

Countries citing papers authored by Masaaki Fujikawa

Since Specialization
Citations

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

Fields of papers citing papers by Masaaki Fujikawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masaaki Fujikawa

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

All Works

10 of 10 papers shown
1.
Kimura, Yasuhisa, et al.. (2013). Substrate recognition by P-glycoprotein efflux transporters: Structure-ATPase activity relationship of diverse chemicals and agrochemicals. Journal of Pesticide Science. 38(3). 112–122. 5 indexed citations
2.
Nakao, Kazuya, Masaaki Fujikawa, Ryo Shimizu, & Miki Akamatsu. (2009). QSAR application for the prediction of compound permeability with in silico descriptors in practical use. Journal of Computer-Aided Molecular Design. 23(5). 309–319. 28 indexed citations
3.
Akamatsu, Miki, Masaaki Fujikawa, Kazuya Nakao, & Ryo Shimizu. (2009). In silico Prediction of Human Oral Absorption Based on QSAR Analyses of PAMPA Permeability. Chemistry & Biodiversity. 6(11). 1845–1866. 36 indexed citations
4.
Onoue, Satomi, Kiyoshi Kawamura, Naoko Igarashi, et al.. (2008). Reactive oxygen species assay-based risk assessment of drug-induced phototoxicity: Classification criteria and application to drug candidates. Journal of Pharmaceutical and Biomedical Analysis. 47(4-5). 967–972. 49 indexed citations
5.
Fujikawa, Masaaki, Kazuya Nakao, Ryo Shimizu, & Miki Akamatsu. (2008). The usefulness of an artificial membrane accumulation index for estimation of the bioconcentration factor of organophosphorus pesticides. Chemosphere. 74(6). 751–757. 16 indexed citations
6.
Fujikawa, Masaaki, Kazuya Nakao, Ryo Shimizu, & Miki Akamatsu. (2007). QSAR study on permeability of hydrophobic compounds with artificial membranes. Bioorganic & Medicinal Chemistry. 15(11). 3756–3767. 78 indexed citations
7.
8.
Kikkawa, Rie, Masaaki Fujikawa, Toshinori Yamamoto, et al.. (2006). IN VIVO HEPATOTOXICITY STUDY OF RATS IN COMPARISON WITH IN VITRO HEPATOTOXICITY SCREENING SYSTEM. The Journal of Toxicological Sciences. 31(1). 23–34. 63 indexed citations
9.
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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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