Mitsuru Inamura

831 total citations
10 papers, 653 citations indexed

About

Mitsuru Inamura is a scholar working on Molecular Biology, Surgery and Genetics. According to data from OpenAlex, Mitsuru Inamura has authored 10 papers receiving a total of 653 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 4 papers in Surgery and 2 papers in Genetics. Recurrent topics in Mitsuru Inamura's work include Pluripotent Stem Cells Research (8 papers), CRISPR and Genetic Engineering (8 papers) and Pancreatic function and diabetes (2 papers). Mitsuru Inamura is often cited by papers focused on Pluripotent Stem Cells Research (8 papers), CRISPR and Genetic Engineering (8 papers) and Pancreatic function and diabetes (2 papers). Mitsuru Inamura collaborates with scholars based in Japan. Mitsuru Inamura's co-authors include Kenji Kawabata, Hiroyuki Mizuguchi, Katsuhisa Tashiro, Fuminori Sakurai, Takao Hayakawa, Kazuo Takayama, Miho Furue, Kazufumi Katayama, Maiko Higuchi and Yasuhito Nagamoto and has published in prestigious journals such as PLoS ONE, Development and Journal of Hepatology.

In The Last Decade

Mitsuru Inamura

10 papers receiving 640 citations

Peers

Mitsuru Inamura

MB

HEPAT

SURGE

BE

GENET

Zoë Hewitt United Kingdom

Zhiying He China

Ronald Gallagher United Kingdom

Christoph Koehler Germany

Keiko Shimizu‐Saito Japan

Norihisa Ichinohe Japan

Katherine Holton United States

Adrián Álvarez-Varela Spain

Uyunbilig Borjigin China

Patricia Nohemí Olivares Ponce United States

Zoë Hewitt United Kingdom

Mitsuru Inamura

504 ×1.0

MB

156 ×0.6

HEPAT

210 ×0.8

SURGE

144 ×1.0

BE

33 ×0.6

GENET

Citations per year, relative to Mitsuru Inamura Mitsuru Inamura (= 1×) peers Zoë Hewitt

Countries citing papers authored by Mitsuru Inamura

Since Specialization

Citations

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

Fields of papers citing papers by Mitsuru Inamura

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mitsuru Inamura

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

All Works

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10 of 10 papers shown

1.

Gotoh, Yohko, et al.. (2020). Comparative study between lactose-silk fibroin conjugates and extracellular matrices as a substrate for the culture of human induced pluripotent stem cell-derived hepatocytes. Bio-Medical Materials and Engineering. 31(1). 35–45. 1 indexed citations

2.

Watanabe, Hitoshi, Kazuo Takayama, Mitsuru Inamura, et al.. (2014). HHEX Promotes Hepatic-Lineage Specification through the Negative Regulation of Eomesodermin. PLoS ONE. 9(3). e90791–e90791. 18 indexed citations

3.

Takayama, Kazuo, Kenji Kawabata, Yasuhito Nagamoto, et al.. (2013). CCAAT/enhancer binding protein-mediated regulation of TGFβ receptor 2 expression determines the hepatoblast fate decision. Development. 141(1). 91–100. 37 indexed citations

4.

Takayama, Kazuo, Mitsuru Inamura, Kenji Kawabata, et al.. (2012). Generation of metabolically functioning hepatocytes from human pluripotent stem cells by FOXA2 and HNF1α transduction. Journal of Hepatology. 57(3). 628–636. 132 indexed citations

5.

Takayama, Kazuo, Mitsuru Inamura, Kenji Kawabata, et al.. (2011). Efficient Generation of Functional Hepatocytes From Human Embryonic Stem Cells and Induced Pluripotent Stem Cells by HNF4α Transduction. Molecular Therapy. 20(1). 127–137. 196 indexed citations

6.

Kawabata, Kenji, Mitsuru Inamura, & Hiroyuki Mizuguchi. (2011). Efficient Hepatic Differentiation from Human iPS Cells by Gene Transfer. Methods in molecular biology. 826. 115–124. 5 indexed citations

7.

Takayama, Kazuo, Mitsuru Inamura, Kenji Kawabata, et al.. (2011). Efficient and Directive Generation of Two Distinct Endoderm Lineages from Human ESCs and iPSCs by Differentiation Stage-Specific SOX17 Transduction. PLoS ONE. 6(7). e21780–e21780. 45 indexed citations

8.

Tashiro, Katsuhisa, Kenji Kawabata, Mitsuru Inamura, et al.. (2010). Adenovirus Vector-Mediated Efficient Transduction into Human Embryonic and Induced Pluripotent Stem Cells. Cellular Reprogramming. 12(5). 501–507. 26 indexed citations

9.

Inamura, Mitsuru, Kenji Kawabata, Kazuo Takayama, et al.. (2010). Efficient Generation of Hepatoblasts From Human ES Cells and iPS Cells by Transient Overexpression of Homeobox Gene HEX. Molecular Therapy. 19(2). 400–407. 89 indexed citations

10.

Tashiro, Katsuhisa, Mitsuru Inamura, Kenji Kawabata, et al.. (2009). Efficient Adipocyte and Osteoblast Differentiation from Mouse Induced Pluripotent Stem Cells by Adenoviral Transduction. Stem Cells. 27(8). 1802–1811. 104 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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