Tomohiko Yoshimi

458 total citations
11 papers, 341 citations indexed

About

Tomohiko Yoshimi is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Tomohiko Yoshimi has authored 11 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 2 papers in Cellular and Molecular Neuroscience and 1 paper in Physiology. Recurrent topics in Tomohiko Yoshimi's work include Genomics and Chromatin Dynamics (4 papers), RNA modifications and cancer (3 papers) and Signaling Pathways in Disease (2 papers). Tomohiko Yoshimi is often cited by papers focused on Genomics and Chromatin Dynamics (4 papers), RNA modifications and cancer (3 papers) and Signaling Pathways in Disease (2 papers). Tomohiko Yoshimi collaborates with scholars based in Japan, Switzerland and United States. Tomohiko Yoshimi's co-authors include Taro Tachibana, Yasuyuki Ohkawa, Akihito Harada, Jun Odawara, Koichi Akashi, Seiji Okada, Tomomi Tani, Hideo Yokota, Yasushi Sako and Takeharu Nagai and has published in prestigious journals such as Nucleic Acids Research, Journal of Neuroscience and The EMBO Journal.

In The Last Decade

Tomohiko Yoshimi

11 papers receiving 338 citations

Peers

Tomohiko Yoshimi

MB

GENET

PS

CR

BIOPH

Jeetayu Biswas United States

Joy N. Ismail United States

Frederik Ziebell Germany

Karen Tessmer Germany

Issam Aldiri United States

Susan M. Hiatt United States

Kathryn Weinand United States

Justyna Nitarska United Kingdom

Antonis Tatarakis United States

Emeline Coleno France

Jeetayu Biswas United States

Tomohiko Yoshimi

427 ×1.4

MB

32 ×0.7

GENET

19 ×0.6

PS

50 ×2.5

CR

38 ×2.2

BIOPH

Citations per year, relative to Tomohiko Yoshimi Tomohiko Yoshimi (= 1×) peers Jeetayu Biswas

Countries citing papers authored by Tomohiko Yoshimi

Since Specialization

Citations

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

Fields of papers citing papers by Tomohiko Yoshimi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomohiko Yoshimi

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

All Works

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11 of 11 papers shown

1.

Iguchi, Tokuichi, Tsuyoshi Hattori, Shinsuke Matsuzaki, et al.. (2015). DBZ Regulates Cortical Cell Positioning and Neurite Development by Sustaining the Anterograde Transport of Lis1 and DISC1 through Control of Ndel1 Dual-Phosphorylation. Journal of Neuroscience. 35(7). 2942–2958. 20 indexed citations

2.

Shimizu, Shoko, Yoshihisa Koyama, Tsuyoshi Hattori, et al.. (2014). DBZ, a CNS-specific DISC1 binding protein, positively regulates oligodendrocyte differentiation. Glia. 62(5). 709–724. 20 indexed citations

3.

Yoshimi, Tomohiko, et al.. (2013). Production of a Monoclonal Antibody Specific for Pou5f1/Oct4. Monoclonal Antibodies in Immunodiagnosis and Immunotherapy. 32(3). 229–231. 3 indexed citations

4.

Yoshimi, Tomohiko, Yasuyuki Ohkawa, Masayuki Azuma, & Taro Tachibana. (2013). A Panel of Specific Monoclonal Antibodies Directed Against Various Phosphorylated Histones H3. Monoclonal Antibodies in Immunodiagnosis and Immunotherapy. 32(2). 119–124. 1 indexed citations

5.

Hihara, Saera, Chan‐Gi Pack, Kazunari Kaizu, et al.. (2012). Local Nucleosome Dynamics Facilitate Chromatin Accessibility in Living Mammalian Cells. Cell Reports. 2(6). 1645–1656. 147 indexed citations

6.

Maehara, Kazumitsu, Jun Odawara, Akihito Harada, et al.. (2012). A co-localization model of paired ChIP-seq data using a large ENCODE data set enables comparison of multiple samples. Nucleic Acids Research. 41(1). 54–62. 7 indexed citations

7.

Harada, Akihito, Seiji Okada, Daijiro Konno, et al.. (2012). Chd2 interacts with H3.3 to determine myogenic cell fate. The EMBO Journal. 31(13). 2994–3007. 100 indexed citations

8.

Odawara, Jun, Akihito Harada, Tomohiko Yoshimi, et al.. (2011). The classification of mRNA expression levels by the phosphorylation state of RNAPII CTD based on a combined genome-wide approach. BMC Genomics. 12(1). 516–516. 29 indexed citations

9.

Yoshimi, Tomohiko, et al.. (2010). A Rat Monoclonal Antibody Against the Chromatin Remodeling Factor CHD5. Hybridoma. 29(1). 63–66. 6 indexed citations

10.

Tachibana, Taro, et al.. (2010). Rat Monoclonal Antibody Specific for Septin 9. Hybridoma. 29(2). 169–171. 2 indexed citations

11.

Yoshimi, Tomohiko, Chikako Yokoyama, Sumiko Kiryu‐Seo, et al.. (2009). Molecular characterization and expression of the low-density lipoprotein receptor-related protein-10, a new member of the LDLR gene family. Biochemical and Biophysical Research Communications. 391(1). 1110–1115. 6 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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