Koji Arikawa

425 total citations
20 papers, 222 citations indexed

About

Koji Arikawa is a scholar working on Molecular Biology, Ecology and Oncology. According to data from OpenAlex, Koji Arikawa has authored 20 papers receiving a total of 222 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 6 papers in Ecology and 2 papers in Oncology. Recurrent topics in Koji Arikawa's work include Genomics and Phylogenetic Studies (8 papers), Gut microbiota and health (5 papers) and Microbial Community Ecology and Physiology (4 papers). Koji Arikawa is often cited by papers focused on Genomics and Phylogenetic Studies (8 papers), Gut microbiota and health (5 papers) and Microbial Community Ecology and Physiology (4 papers). Koji Arikawa collaborates with scholars based in Japan, United States and Portugal. Koji Arikawa's co-authors include Masahito Hosokawa, Haruko Takeyama, Shigeru Miyagawa, Keigo Ide, Masato Kogawa, Hiroko Matsunaga, Miki Yamazaki, Yohei Nishikawa, Masato Saito and Taiki Aoshi and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Koji Arikawa

20 papers receiving 212 citations

Peers

Koji Arikawa

ECOLO

Rory Munro United Kingdom

Johnny Debebe United Kingdom

Ezekiel J. Maier United States

Mihails Delmans United Kingdom

Bohan Ni United States

Ce Zhang China

Todd T. Eckdahl United States

Ekaterina Orlova United States

Biyun Zhu China

Brian P. Landry United States

Rory Munro United Kingdom

Koji Arikawa

207 ×1.9

37 ×0.9

ECOLO

33 ×0.9

0 ×0.0

17 ×0.6

Citations per year, relative to Koji Arikawa Koji Arikawa (= 1×) peers Rory Munro

Countries citing papers authored by Koji Arikawa

Since Specialization

Citations

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

Fields of papers citing papers by Koji Arikawa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Koji Arikawa

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

All Works

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20 of 20 papers shown

Arikawa, Koji, et al.. (2024). A single amplified genome catalog reveals the dynamics of mobilome and resistome in the human microbiome. Microbiome. 12(1). 188–188. 6 indexed citations

Hosokawa, Masahito, et al.. (2023). Target enrichment of uncultured human oral bacteria with phage-derived molecules found by single-cell genomics. Journal of Bioscience and Bioengineering. 136(1). 58–66. 4 indexed citations

Arikawa, Koji & Masahito Hosokawa. (2023). Uncultured prokaryotic genomes in the spotlight: An examination of publicly available data from metagenomics and single-cell genomics. Computational and Structural Biotechnology Journal. 21. 4508–4518. 6 indexed citations

Kogawa, Masato, et al.. (2023). Revealing within-species diversity in uncultured human gut bacteria with single-cell long-read sequencing. Frontiers in Microbiology. 14. 1133917–1133917. 8 indexed citations

Ide, Hiroki, Taiki Aoshi, Masato Saito, et al.. (2023). Linking antigen specific T-cell dynamics in a microfluidic chip to single cell transcription patterns. Biochemical and Biophysical Research Communications. 657. 8–15. 6 indexed citations

Nakayama, Jun, Hiroko Matsunaga, Koji Arikawa, et al.. (2022). Identification of two cancer stem cell-like populations in triple-negative breast cancer xenografts. Disease Models & Mechanisms. 15(6). 9 indexed citations

Matsunaga, Hiroko, Koji Arikawa, Miki Yamazaki, et al.. (2022). Reproducible and sensitive micro-tissue RNA sequencing from formalin-fixed paraffin-embedded tissues for spatial gene expression analysis. Scientific Reports. 12(1). 19511–19511. 11 indexed citations

Yamazaki, Miki, Masahito Hosokawa, Hiroko Matsunaga, et al.. (2022). Integrated spatial analysis of gene mutation and gene expression for understanding tumor diversity in formalin-fixed paraffin-embedded lung adenocarcinoma. Frontiers in Oncology. 12. 936190–936190. 3 indexed citations

Hosokawa, Masahito, et al.. (2022). Strain-level profiling of viable microbial community by selective single-cell genome sequencing. Scientific Reports. 12(1). 4443–4443. 19 indexed citations

10.

Ide, Keigo, et al.. (2022). Exploring strain diversity of dominant human skin bacterial species using single-cell genome sequencing. Frontiers in Microbiology. 13. 955404–955404. 10 indexed citations

11.

Arikawa, Koji, et al.. (2021). Recovery of strain-resolved genomes from human microbiome through an integration framework of single-cell genomics and metagenomics. Microbiome. 9(1). 202–202. 34 indexed citations

12.

Ueda, Shuhei, Masahito Hosokawa, Koji Arikawa, et al.. (2021). Distinctive Regulation of Emotional Behaviors and Fear-Related Gene Expression Responses in Two Extended Amygdala Subnuclei With Similar Molecular Profiles. Frontiers in Molecular Neuroscience. 14. 741895–741895. 7 indexed citations

13.

Yamazaki, Miki, et al.. (2020). Effective microtissue RNA extraction coupled with Smart-seq2 for reproducible and robust spatial transcriptome analysis. Scientific Reports. 10(1). 7083–7083. 14 indexed citations

14.

Hosokawa, Masahito, et al.. (2020). Time-lapse single-cell transcriptomics reveals modulation of histone H3 for dormancy breaking in fission yeast. Nature Communications. 11(1). 1265–1265. 10 indexed citations

15.

Arikawa, Koji, et al.. (2020). Evaluation of the effects of cell-dispensing using an inkjet-based bioprinter on cell integrity by RNA-seq analysis. Scientific Reports. 10(1). 7158–7158. 22 indexed citations

16.

Arikawa, Koji, et al.. (2020). High-Quality Draft Single-Cell Genome Sequences of Two Gammaproteobacteria Strains Sampled from Soil in a Strawberry Farm. Microbiology Resource Announcements. 9(35). 3 indexed citations

17.

Matsumura, Takayuki, Tadayoshi Ikebe, Koji Arikawa, et al.. (2019). Sequential Sensing by TLR2 and Mincle Directs Immature Myeloid Cells to Protect against Invasive Group A Streptococcal Infection in Mice. Cell Reports. 27(2). 561–571.e6. 10 indexed citations

18.

Arikawa, Koji. (2019). Graph Theory Teaches Us Something About Grammaticality. SHILAP Revista de lepidopterología. 112(1). 55–82. 1 indexed citations

19.

Miyagawa, Shigeru & Koji Arikawa. (2007). Locality in Syntax and Floating Numeral Quantifiers. Linguistic Inquiry. 38(4). 645–670. 36 indexed citations

20.

Arikawa, Koji. (1992). Binding Domain and Modality: A Case Study of Tense Binding in Japanese. Journal of Japanese Linguistics. 14(1). 141–143. 3 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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