Hitoshi Funabashi

724 total citations
28 papers, 588 citations indexed

About

Hitoshi Funabashi is a scholar working on Molecular Biology, Oncology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Hitoshi Funabashi has authored 28 papers receiving a total of 588 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Oncology and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Hitoshi Funabashi's work include Drug Transport and Resistance Mechanisms (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers) and Pharmacogenetics and Drug Metabolism (3 papers). Hitoshi Funabashi is often cited by papers focused on Drug Transport and Resistance Mechanisms (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers) and Pharmacogenetics and Drug Metabolism (3 papers). Hitoshi Funabashi collaborates with scholars based in Japan and United States. Hitoshi Funabashi's co-authors include Takeshi Kunimatsu, Juki Kimura, Takaki Seki, Izuru Miyawaki, Kiyoko Bando, Eiichiro Fukusaki, Jun Sakai, Takeshi Bamba, Hiroshi Inada and S Iwata and has published in prestigious journals such as Toxicology and Applied Pharmacology, Toxicology Letters and Mutation Research/Genetic Toxicology and Environmental Mutagenesis.

In The Last Decade

Hitoshi Funabashi

27 papers receiving 577 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hitoshi Funabashi Japan 12 279 84 70 53 53 28 588
Takaki Seki Japan 16 255 0.9× 172 2.0× 72 1.0× 29 0.5× 74 1.4× 36 713
Chandikumar S. Elangbam United States 15 224 0.8× 56 0.7× 64 0.9× 70 1.3× 26 0.5× 28 768
Anita Annas Sweden 13 152 0.5× 90 1.1× 28 0.4× 27 0.5× 34 0.6× 25 514
Takeshi Kunimatsu Japan 12 218 0.8× 166 2.0× 17 0.2× 87 1.6× 54 1.0× 23 524
Seiji Tsuboi Japan 18 354 1.3× 43 0.5× 72 1.0× 66 1.2× 9 0.2× 55 880
Erik Ullerås Sweden 16 236 0.8× 170 2.0× 38 0.5× 12 0.2× 139 2.6× 26 657
Alice Limonciel Austria 15 420 1.5× 108 1.3× 58 0.8× 13 0.2× 31 0.6× 19 739
Nils‐Erik Saris Finland 13 455 1.6× 77 0.9× 39 0.6× 97 1.8× 38 0.7× 44 779
Alessio Lepore Italy 9 315 1.1× 32 0.4× 36 0.5× 22 0.4× 15 0.3× 14 695
Naoya Masutomi Japan 13 237 0.8× 195 2.3× 93 1.3× 14 0.3× 92 1.7× 19 701

Countries citing papers authored by Hitoshi Funabashi

Since Specialization
Citations

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

Fields of papers citing papers by Hitoshi Funabashi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hitoshi Funabashi

This figure shows the co-authorship network connecting the top 25 collaborators of Hitoshi Funabashi. A scholar is included among the top collaborators of Hitoshi Funabashi 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 Hitoshi Funabashi. Hitoshi Funabashi 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
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Kitamoto, Sachiko, Tōru Yamada, Kaori Miyata, et al.. (2015). Genotoxicity evaluation of benzene, di(2-ethylhexyl) phthalate, and trisodium ethylenediamine tetraacetic acid monohydrate using a combined rat comet/micronucleus assays. Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 786-788. 137–143. 15 indexed citations
3.
Kitamoto, Sachiko, et al.. (2015). Optimal dose selection of N-methyl-N-nitrosourea for the rat comet assay to evaluate DNA damage in organs with different susceptibility to cytotoxicity. Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 786-788. 129–136. 6 indexed citations
4.
Honda, Yayoi, et al.. (2014). Availability of human induced pluripotent stem cell-derived cardiomyocytes in assessment of drug potential for QT prolongation. Toxicology and Applied Pharmacology. 278(1). 72–77. 44 indexed citations
5.
Miyawaki, Izuru, et al.. (2014). Establishment of a novel experimental protocol for drug-induced seizure liability screening based on a locomotor activity assay in zebrafish. The Journal of Toxicological Sciences. 39(4). 579–600. 22 indexed citations
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Matsumoto, Izumi, et al.. (2013). Spontaneous Rhabdomyosarcoma in a Common Marmoset (<i>Callithrix jacchus</i>). Journal of Toxicologic Pathology. 26(2). 187–191. 4 indexed citations
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Inada, Hiroshi, Izuru Miyawaki, Takeshi Kunimatsu, et al.. (2012). Evaluation of ovarian toxicity of mono-(2-ethylhexyl) phthalate (MEHP) using cultured rat ovarian follicles. The Journal of Toxicological Sciences. 37(3). 483–490. 55 indexed citations
11.
Inada, Hiroshi, Izuru Miyawaki, Takeshi Kunimatsu, et al.. (2012). Evaluation of ovarian toxicity of sodium valproate (VPA) using cultured rat ovarian follicles. The Journal of Toxicological Sciences. 37(3). 587–594. 5 indexed citations
12.
Toyosawa, Kaoru, et al.. (2011). Immunohistochemical and Ultrastructural Analyses of Cytoplasmic Blood Plasma Inclusions of Rat Hepatocytes. Journal of Toxicologic Pathology. 24(4). 245–249. 1 indexed citations
13.
Miyawaki, Izuru, Izumi Matsumoto, Hiroshi Horie, et al.. (2011). Toxicological approach for elucidation of clobazam-induced hepatomegaly in male rats. Regulatory Toxicology and Pharmacology. 60(3). 323–331. 4 indexed citations
14.
Bando, Kiyoko, Takeshi Kunimatsu, Jun Sakai, et al.. (2010). GC‐MS‐based metabolomics reveals mechanism of action for hydrazine induced hepatotoxicity in rats. Journal of Applied Toxicology. 31(6). 524–535. 86 indexed citations
15.
Bando, Kiyoko, Takeshi Kunimatsu, Jun Sakai, et al.. (2010). Influences of biofluid sample collection and handling procedures on GC–MS based metabolomic studies. Journal of Bioscience and Bioengineering. 110(4). 491–499. 47 indexed citations
16.
Kunimatsu, Takeshi, Juki Kimura, Hitoshi Funabashi, Tadashi Inoue, & Takaki Seki. (2010). The antipsychotics haloperidol and chlorpromazine increase bone metabolism and induce osteopenia in female rats. Regulatory Toxicology and Pharmacology. 58(3). 360–368. 24 indexed citations
17.
Bando, Kiyoko, et al.. (2010). Comparison of potential risks of lactic acidosis induction by biguanides in rats. Regulatory Toxicology and Pharmacology. 58(1). 155–160. 24 indexed citations
18.
Yamada, Tōru, et al.. (2010). Usefulness of field potential as a marker of embryonic stem cell-derived cardiomyocytes, and endpoint analysis of embryonic stem cell test. The Journal of Toxicological Sciences. 35(6). 899–909. 3 indexed citations
19.
Miyawaki, Izuru, et al.. (2003). Mechanism of clobazam-induced thyroidal oncogenesis in male rats. Toxicology Letters. 145(3). 291–301. 28 indexed citations
20.
Funabashi, Hitoshi, et al.. (2000). COLLABORATIVE WORK TO EVALUATE TOXICITY ON MALE REPRODUCTIVE ORGANS BY REPEATED DOSE STUDIES IN RATS : 22)EFFECTS OF 2-AND 4-WEEK ADMINISTRATION OF THEOBROMINE ON THE TESTIS. The Journal of Toxicological Sciences. 25(SpecialIssue). 211–221. 14 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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