Ken Kurokawa

22.9k total citations · 5 hit papers
171 papers, 9.3k citations indexed

About

Ken Kurokawa is a scholar working on Molecular Biology, Ecology and Endocrinology. According to data from OpenAlex, Ken Kurokawa has authored 171 papers receiving a total of 9.3k indexed citations (citations by other indexed papers that have themselves been cited), including 108 papers in Molecular Biology, 41 papers in Ecology and 25 papers in Endocrinology. Recurrent topics in Ken Kurokawa's work include Genomics and Phylogenetic Studies (37 papers), RNA and protein synthesis mechanisms (23 papers) and Bacteriophages and microbial interactions (23 papers). Ken Kurokawa is often cited by papers focused on Genomics and Phylogenetic Studies (37 papers), RNA and protein synthesis mechanisms (23 papers) and Bacteriophages and microbial interactions (23 papers). Ken Kurokawa collaborates with scholars based in Japan, United States and France. Ken Kurokawa's co-authors include Tetsuya Hayashi, Hiroshi Mori, Masahira Hattori, Yoshitoshi Ogura, Kenshiro Oshima, Fumito Maruyama, Teruo Yasunaga, Makoto Ohnishi, Atsushi Toyoda and Shigehiko Kanaya and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and The Lancet.

In The Last Decade

Ken Kurokawa

164 papers receiving 9.2k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Genome sequence of Vibrio parahaemolyticus: a pathogenic mechanism distinct from that of V cholerae

2003 839 citations Ken Kurokawa, Teruo Yasunaga et al. profile →
Comparative Metagenomics Revealed Commonly Enriched Gene Sets in Human Gut Microbiomes

2007 627 citations Ken Kurokawa, Atsushi Toyoda et al. DNA Research profile →
Design and Experimental Application of a Novel Non-Degenerate Universal Primer Set that Amplifies Prokaryotic 16S rRNA Genes with a Low Possibility to Amplify Eukaryotic rRNA Genes

2013 455 citations Hiroshi Mori, Fumito Maruyama et al. DNA Research profile →
Meta‐Analysis of Gut Dysbiosis in Parkinson's Disease

2020 270 citations Hiroshi Nishiwaki, Mikako Ito et al. Movement Disorders profile →
Key bacterial taxa and metabolic pathways affecting gut short-chain fatty acid profiles in early life

2021 203 citations Naoki Tsukuda, T. Hara et al. The ISME Journal profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ken Kurokawa Japan	51	4.9k	2.4k	1.8k	1.5k	1.3k	171	9.3k
O. Colin Stine United States	57	4.3k 0.9×	1.6k 0.7×	921 0.5×	1.5k 1.0×	1.1k 0.9×	177	10.6k
Simon Rasmussen Denmark	38	4.2k 0.9×	2.1k 0.9×	1.9k 1.1×	980 0.7×	1.8k 1.4×	86	11.3k
Kenshiro Oshima Japan	46	6.7k 1.4×	1.4k 0.6×	1.3k 0.7×	1.3k 0.9×	1.5k 1.2×	159	12.5k
Lei Wang China	55	4.4k 0.9×	3.1k 1.3×	2.3k 1.3×	1.8k 1.2×	1.2k 1.0×	342	10.8k
Louise M. Judd Australia	46	5.7k 1.2×	2.1k 0.9×	2.5k 1.4×	835 0.6×	1.1k 0.9×	113	12.3k
Thomas Sicheritz‐Pontén Denmark	38	5.2k 1.1×	1.1k 0.5×	2.1k 1.2×	1.1k 0.8×	1.0k 0.8×	95	9.8k
Laurence G. Rahme United States	53	7.2k 1.5×	1.8k 0.8×	962 0.5×	2.5k 1.7×	798 0.6×	119	11.3k
Tetsuya Hayashi Japan	55	5.8k 1.2×	4.6k 2.0×	3.1k 1.7×	2.0k 1.4×	3.3k 2.6×	289	13.3k
Jason R. Grant Switzerland	26	4.4k 0.9×	882 0.4×	2.2k 1.2×	1.1k 0.7×	803 0.6×	89	8.8k
David W. Ussery Denmark	50	8.8k 1.8×	2.3k 1.0×	3.8k 2.1×	1.7k 1.2×	1.3k 1.0×	177	14.3k

Countries citing papers authored by Ken Kurokawa

Since Specialization

Citations

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

Fields of papers citing papers by Ken Kurokawa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ken Kurokawa

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Endo, Yukihiro, Atsushi Onodera, Seiji Mita, et al.. (2025). SLAMF6 regulates basal T cell receptor signaling and influences invariant natural killer T cell lineage diversity. International Immunology. 37(9). 567–581. 1 indexed citations

Ohkawara, Bisei, Akinori Kanai, Kiyomi Imamura, et al.. (2023). Transcriptome profile of subsynaptic myonuclei at the neuromuscular junction in embryogenesis. Journal of Neurochemistry. 168(4). 342–354. 5 indexed citations

Higashi, Koichi, Keisuke Yoshida, Tomohiko Sato, et al.. (2023). Metagenomic Thermometer. DNA Research. 30(6). 2 indexed citations

Tsukuda, Naoki, T. Hara, Y. Watanabe, et al.. (2021). Key bacterial taxa and metabolic pathways affecting gut short-chain fatty acid profiles in early life. The ISME Journal. 15(9). 2574–2590. 203 indexed citations breakdown →

Kobayashi, Maki, Wenjun Hu, Koichi Higashi, et al.. (2020). RNA-binding motifs of hnRNP K are critical for induction of antibody diversification by activation-induced cytidine deaminase. Proceedings of the National Academy of Sciences. 117(21). 11624–11635. 12 indexed citations

Nishiwaki, Hiroshi, Mikako Ito, Tomonari Hamaguchi, et al.. (2020). Meta‐Analysis of Gut Dysbiosis in Parkinson's Disease. Movement Disorders. 35(9). 1626–1635. 270 indexed citations breakdown →

Tajima, Naoyuki, Yu Kanesaki, Shusei Sato, et al.. (2018). Complete Genome Sequence of the Nonheterocystous Cyanobacterium Pseudanabaena sp. ABRG5-3. Genome Announcements. 6(6). 6 indexed citations

Tajima, Naoyuki, Kenji Saitoh, Shusei Sato, et al.. (2016). Sequencing and analysis of the complete organellar genomes of Parmales, a closely related group to Bacillariophyta (diatoms). Current Genetics. 62(4). 887–896. 19 indexed citations

Nakamura, Yuya, Nao Yamamoto, Nozomi Yamamoto, et al.. (2016). Establishment of a multi-species biofilm model and metatranscriptomic analysis of biofilm and planktonic cell communities. Applied Microbiology and Biotechnology. 100(16). 7263–7279. 29 indexed citations

10.

Yamaichi, Yoshiharu, Michael C. Chao, Jumpei Sasabe, et al.. (2014). High-resolution genetic analysis of the requirements for horizontal transmission of the ESBL plasmid from Escherichia coli O104:H4. Nucleic Acids Research. 43(1). 348–360. 51 indexed citations

11.

Sawabe, Tomoo, Tomoo Sawabe, Yoshitoshi Ogura, et al.. (2013). Updating the Vibrio clades defined by multilocus sequence phylogeny: proposal of eight new clades, and the description of Vibrio tritonius sp. nov.. Frontiers in Microbiology. 4. 583–583. 234 indexed citations

12.

Nozawa, Takashi, Chihiro Aikawa, Takayasu Watanabe, et al.. (2011). CRISPR Inhibition of Prophage Acquisition in Streptococcus pyogenes. PLoS ONE. 6(5). e19543–e19543. 79 indexed citations

13.

Kurokawa, Ken, Toshihito Tanahashi, A. Murata, et al.. (2011). Effects of chronic academic stress on mental state and expression ofglucocorticoid receptor αand β isoforms in healthy Japanese medical students. Stress. 14(4). 431–438. 21 indexed citations

14.

Goto, N., Ken Kurokawa, & Teruo Yasunaga. (2002). Finding Conserved Amino Acid Sequences among Prokaryotic Proteomes. Proceedings Genome Informatics Workshop/Genome informatics. 13. 443–444. 4 indexed citations

15.

Ohnishi, Makoto, Jun Terajima, Ken Kurokawa, et al.. (2002). Genomic diversity of enterohemorrhagic Escherichia coli O157 revealed by whole genome PCR scanning. Proceedings of the National Academy of Sciences. 99(26). 17043–17048. 139 indexed citations

16.

Yamazaki, Kiyoshi, Makoto Ohnishi, Ken Kurokawa, & Teruo Yasunaga. (2001). ParalogCluster: Classifying Paralogs in a Genome into Paralogous Groups. Proceedings Genome Informatics Workshop/Genome informatics. 12. 409–410. 1 indexed citations

17.

Kurokawa, Ken, N. Goto, & Teruo Yasunaga. (2000). Searching the Most Conserved Sequence in Bacterial Whole Genomes. Proceedings Genome Informatics Workshop/Genome informatics. 11. 309–310. 1 indexed citations

18.

Goto, N., Ken Kurokawa, & Teruo Yasunaga. (2000). CONSERV: A Tool for finding Exact Matching Conserved Sequences in Biological Sequences. Proceedings Genome Informatics Workshop/Genome informatics. 11. 307–308. 4 indexed citations

19.

Kurokawa, Ken, et al.. (1999). GeneAlign: Java Application Software for Multiple Sequence Alignment Editor. Proceedings Genome Informatics Workshop/Genome informatics. 10(10). 208–209. 1 indexed citations

20.

Kagawa, Shunsuke, et al.. (1987). Measurement of carbohydrate antigen ca19 9 levels in serum for urological malignancies. 49(5). 1395–1398. 1 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.

Explore authors with similar magnitude of impact