Koji Maruyama

497 total citations
18 papers, 310 citations indexed

About

Koji Maruyama is a scholar working on Cancer Research, Pathology and Forensic Medicine and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Koji Maruyama has authored 18 papers receiving a total of 310 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cancer Research, 6 papers in Pathology and Forensic Medicine and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Koji Maruyama's work include Cancer Genomics and Diagnostics (9 papers), Genetic factors in colorectal cancer (6 papers) and Lung Cancer Treatments and Mutations (4 papers). Koji Maruyama is often cited by papers focused on Cancer Genomics and Diagnostics (9 papers), Genetic factors in colorectal cancer (6 papers) and Lung Cancer Treatments and Mutations (4 papers). Koji Maruyama collaborates with scholars based in Japan, Australia and France. Koji Maruyama's co-authors include Kazuo Yamaguchi, Naganari Ohkura, T. Tsukada, Shuji Bandoh, Tetsuji Hosono, Keiichi Hatakeyama, Keiichi Ohshima, Yuji Shimoda, Yasuto Akiyama and Sumiko Ohnami and has published in prestigious journals such as Journal of Biological Chemistry, Cancer Research and Scientific Reports.

In The Last Decade

Koji Maruyama

17 papers receiving 307 citations

Peers

Koji Maruyama

CMN

IMMUN

ONCOL

Xiu‐Ming Li China

Jaspreet Sharma United States

Hyun‐Jung Byun South Korea

Vanessa Nancy-Portebois France

Zhongmin Yuan China

Sam Wells United States

Gabriele Hübinger Germany

Katherine Amato United States

Jianbing Xiao China

Masayuki Komura Japan

Xiu‐Ming Li China

Koji Maruyama

252 ×2.3

70 ×0.6

CMN

115 ×1.1

IMMUN

98 ×1.5

87 ×1.4

ONCOL

Citations per year, relative to Koji Maruyama Koji Maruyama (= 1×) peers Xiu‐Ming Li

Countries citing papers authored by Koji Maruyama

Since Specialization

Citations

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

Fields of papers citing papers by Koji Maruyama

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Koji Maruyama

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

All Works

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18 of 18 papers shown

Hatakeyama, Keiichi, Koji Muramatsu, Takeshi Nagashima, et al.. (2024). Tumor cell enrichment by tissue suspension improves sensitivity to copy number variation in diffuse gastric cancer with low tumor content. Scientific Reports. 14(1). 13699–13699.

Nagashima, Takeshi, Kenichi Urakami, Yuji Shimoda, et al.. (2023). Comparative analysis of tumor content estimation methods based on simu- lated tumor samples identified their impact on somatic variant detection in cancer whole genome sequencing. Biomedical Research. 44(4). 161–171. 2 indexed citations

Hatakeyama, Keiichi, Takeshi Nagashima, Keiichi Ohshima, et al.. (2023). Impact of somatic mutations and transcriptomic alterations on cancer aneuploidy. Biomedical Research. 44(5). 187–197. 2 indexed citations

Hashimoto, Michio, Kentaro Matsuzaki, Koji Maruyama, et al.. (2022). Perilla seed oil in combination with nobiletin-rich ponkan powder enhances cognitive function in healthy elderly Japanese individuals: a possible supplement for brain health in the elderly. Food & Function. 13(5). 2768–2781. 15 indexed citations

Hatakeyama, Keiichi, Takeshi Nagashima, Akifumi Notsu, et al.. (2021). Mutational concordance analysis provides supportive information for double cancer diagnosis. BMC Cancer. 21(1). 181–181. 4 indexed citations

Serizawa, Masakuni, Kenichi Urakami, Takeshi Nagashima, et al.. (2021). JCGA: the Japanese version of the Cancer Genome Atlas and its contribution to the interpretation of gene alterations detected in clinical cancer genome sequencing. Human Genome Variation. 8(1). 38–38. 4 indexed citations

Hatakeyama, Keiichi, Takeshi Nagashima, Keiichi Ohshima, et al.. (2020). Characterization of tumors with ultralow tumor mutational burden in Japanese cancer patients. Cancer Science. 111(10). 3893–3901. 14 indexed citations

Hatakeyama, Keiichi, Takeshi Nagashima, Keiichi Ohshima, et al.. (2019). Mutational burden and signatures in 4000 Japanese cancers provide insights into tumorigenesis and response to therapy. Cancer Science. 110(8). 2620–2628. 22 indexed citations

Maruyama, Koji & Daisuke Chujo. (2019). Tacrolimus-induced diabetic ketoacidosis with subsequent rapid recovery of endogenous insulin secretion after cessation of tacrolimus. Medicine. 98(36). e16992–e16992. 3 indexed citations

10.

Hatakeyama, Keiichi, Keiichi Ohshima, Takeshi Nagashima, et al.. (2018). Molecular profiling and sequential somatic mutation shift in hypermutator tumours harbouring POLE mutations. Scientific Reports. 8(1). 8700–8700. 20 indexed citations

11.

Hatakeyama, Keiichi, Takeshi Nagashima, Kenichi Urakami, et al.. (2018). <b>Tumor mutational burden analysis of 2,000 Japanese cancer genomes using whole exome and targeted gene panel </b><b>sequencing </b>. Biomedical Research. 39(3). 159–167. 33 indexed citations

12.

Maruyama, Koji, Daisuke Chujo, Kôji Watanabe, et al.. (2018). Evaluation of cellular and humoral autoimmunity before the development of type 1 diabetes in a patient with idiopathic CD4 lymphocytopenia. Journal of Diabetes Investigation. 10(4). 1108–1111. 4 indexed citations

13.

Maruyama, Koji, Hidee Ishii, Koji Muramatsu, et al.. (2012). Investigation of proNT/NMN secretion from small cell lung carcinoma cells using a mouse xenograft model. Oncology Reports. 28(4). 1181–1186. 3 indexed citations

14.

Yoshida, Masanobu, Hiroaki Takagi, Koji Maruyama, et al.. (2006). Different Progression of Tumor Xenografts between Mucin-Producing and Mucin–Non-Producing Mammary Adenocarcinoma-Bearing Mice. Cancer Research. 66(12). 6175–6182. 8 indexed citations

15.

Tani‐ichi, Shizue, Koji Maruyama, Masakazu Nagafuku, et al.. (2005). Structure and function of lipid rafts in human activated T cells. International Immunology. 17(6). 749–758. 41 indexed citations

16.

Terme, Magali, Cédric Menard, Julien Taı̈eb, et al.. (2005). The dialogue between natural killer cells and dendritic cells. International Congress Series. 1285. 169–176. 2 indexed citations

17.

Okazawa, Hideki, Koji Maruyama, Sei‐ichiro Motegi, et al.. (2003). Interaction of SAP-1, a Transmembrane-type Protein-tyrosine Phosphatase, with the Tyrosine Kinase Lck. Journal of Biological Chemistry. 278(37). 34854–34863. 9 indexed citations

18.

Maruyama, Koji, T. Tsukada, Naganari Ohkura, et al.. (1998). The NGFI-B subfamily of the nuclear receptor superfamily (review).. International Journal of Oncology. 12(6). 1237–43. 124 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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