Akiko Murakami

2.1k total citations
65 papers, 1.6k citations indexed

About

Akiko Murakami is a scholar working on Molecular Biology, Physiology and Genetics. According to data from OpenAlex, Akiko Murakami has authored 65 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 13 papers in Physiology and 10 papers in Genetics. Recurrent topics in Akiko Murakami's work include Adipose Tissue and Metabolism (7 papers), Regulation of Appetite and Obesity (6 papers) and Adipokines, Inflammation, and Metabolic Diseases (6 papers). Akiko Murakami is often cited by papers focused on Adipose Tissue and Metabolism (7 papers), Regulation of Appetite and Obesity (6 papers) and Adipokines, Inflammation, and Metabolic Diseases (6 papers). Akiko Murakami collaborates with scholars based in Japan, United States and Switzerland. Akiko Murakami's co-authors include Hitoshi Nakatogawa, Koreaki Ito, Rudy Raymond, Haruhiko Osawa, Hideichi Makino, Masaaki Ochi, Hiroshi Onuma, Yasuhisa Fujii, Ikki Shimizu and Kazuhisa Takahashi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Genes & Development.

In The Last Decade

Akiko Murakami

62 papers receiving 1.6k citations

Peers

Akiko Murakami
Hua Dong China
Fabien Campagne United States
Matthias Großmann Germany
Johannes Freudenberg United States
Stephan Gebel Germany
Kristina Kirschner United Kingdom
Laura C. Huang United States
Zheng Yin United States
Changlin Zhang China
Hua Dong China
Akiko Murakami
Citations per year, relative to Akiko Murakami Akiko Murakami (= 1×) peers Hua Dong

Countries citing papers authored by Akiko Murakami

Since Specialization
Citations

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

Fields of papers citing papers by Akiko Murakami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akiko Murakami

This figure shows the co-authorship network connecting the top 25 collaborators of Akiko Murakami. A scholar is included among the top collaborators of Akiko Murakami 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 Akiko Murakami. Akiko Murakami 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
1.
Murakami, Akiko, et al.. (2020). Understanding requirements and issues in disaster area using geotemporal visualization of Twitter analysis. IBM Journal of Research and Development. 64(1/2). 10:1–10:8.
2.
Sekimata, Masayuki, et al.. (2019). Runx1 and RORγt Cooperate to Upregulate IL-22 Expression in Th Cells through Its Distal Enhancer. The Journal of Immunology. 202(11). 3198–3210. 15 indexed citations
3.
Murakami, Akiko, Peter Schraml, W. Kimryn Rathmell, et al.. (2017). Context-dependent role for chromatin remodeling component PBRM1/BAF180 in clear cell renal cell carcinoma. Oncogenesis. 6(1). e287–e287. 25 indexed citations
4.
Hashimoto, Yukiko, Rie Kawakita, Yuki Hosokawa, et al.. (2015). Focal form of congenital hyperinsulinism clearly detectable by contrast-enhanced computed tomography imaging. International Journal of Pediatric Endocrinology. 2015(1). 20–20. 2 indexed citations
5.
Takase, Sho, et al.. (2013). Detecting Chronic Critics Based on Sentiment Polarity and User’s Behavior in Social Media. Meeting of the Association for Computational Linguistics. 110–116. 1 indexed citations
6.
Sekimata, Masayuki, Akiko Murakami, & Yoshimi Homma. (2011). CpG methylation prevents YY1-mediated transcriptional activation of the vimentin promoter. Biochemical and Biophysical Research Communications. 414(4). 767–772. 8 indexed citations
7.
Murakami, Akiko & Rudy Raymond. (2010). Support or Oppose? Classifying Positions in Online Debates from Reply Activities and Opinion Expressions. International Conference on Computational Linguistics. 869–875. 75 indexed citations
8.
Murakami, Akiko, Dongqing Huang, Brian Piening, Chaitanya Bangur, & Amanda G. Paulovich. (2010). The Saccharomyces cerevisiae RAD9, RAD17 and RAD24 genes are required for suppression of mutagenic post-replicative repair during chronic DNA damage. DNA repair. 9(7). 824–834. 20 indexed citations
9.
Yamauchi, Junko, Haruhiko Osawa, Masaaki Ochi, et al.. (2008). Serum resistin is reduced by glucose and meal loading in healthy human subjects. Metabolism. 57(2). 149–156. 21 indexed citations
10.
Nakatogawa, Hitoshi, Akiko Murakami, Hiroyuki Mori, & Koreaki Ito. (2005). SecM facilitates translocase function of SecA by localizing its biosynthesis. Genes & Development. 19(4). 436–444. 27 indexed citations
11.
Osawa, Haruhiko, Kazuya Yamada, Hiroshi Onuma, et al.. (2004). The G/G Genotype of a Resistin Single-Nucleotide Polymorphism at −420 Increases Type 2 Diabetes Mellitus Susceptibility by Inducing Promoter Activity through Specific Binding of Sp1/3. The American Journal of Human Genetics. 75(4). 678–686. 199 indexed citations
12.
13.
Sekimata, Masayuki, Atsushi Takahashi, Akiko Murakami, & Yoshimi Homma. (2001). Involvement of a Novel Zinc Finger Protein, MIZF, in Transcriptional Repression by Interacting with a Methyl-CpG-binding Protein, MBD2. Journal of Biological Chemistry. 276(46). 42632–42638. 50 indexed citations
14.
Osawa, Haruhiko, Hiroshi Onuma, Akiko Murakami, et al.. (2001). Systematic Search for Single Nucleotide Polymorphisms in the Insulin Gene: Evidence for a High Frequency of −23T→A in Japanese Subjects. Biochemical and Biophysical Research Communications. 286(3). 451–455. 11 indexed citations
15.
Murakami, Akiko, Keitarou Kimura, & Akihiko Nakano. (1999). The Inactive Form of a Yeast Casein Kinase I Suppresses the Secretory Defect of the sec12 Mutant. Journal of Biological Chemistry. 274(6). 3804–3810. 62 indexed citations
16.
Matsumura, Yasuo, et al.. (1996). Plasmin stimulates expression of endothelin-1 mRNA and endothelin-1 release in vascular endothelial cells. Life Sciences. 58(13). 1067–1074. 6 indexed citations
17.
Murakami, Akiko, Kazuhiro Chida, Yasutoshi Suzuki, et al.. (1996). Absence of Down-Regulation and Translocation of The η Isoform of Protein Kinase C in Normal Human Keratinocytes. Journal of Investigative Dermatology. 106(4). 790–794. 13 indexed citations
18.
Tsukahara, Yaeko, Taro Kojima, Shunsuke Murata, et al.. (1995). Effects of Phosphoramidon on Endothelin-1 and Big Endothelin-1 Production in Human Aortic Endothelial Cells.. Biological and Pharmaceutical Bulletin. 18(3). 401–406. 4 indexed citations
19.
Nikawa, Jun‐ichi, et al.. (1995). Cloning and Sequence of the SCS2 Gene, Which Can Suppress the Defect of IN01 Expression in an Inositol Auxotrophic Mutant of Saccharomyces cerevisiae1. The Journal of Biochemistry. 118(1). 39–45. 48 indexed citations
20.
Chida, Kazuhiro, Hiroshi Sagara, Yasutoshi Suzuki, et al.. (1994). The η Isoform of Protein Kinase C Is Localized on Rough Endoplasmic Reticulum. Molecular and Cellular Biology. 14(6). 3782–3790. 48 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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