Yukio Nakamura

20.7k total citations · 4 hit papers
482 papers, 11.1k citations indexed

About

Yukio Nakamura is a scholar working on Molecular Biology, Oncology and Organic Chemistry. According to data from OpenAlex, Yukio Nakamura has authored 482 papers receiving a total of 11.1k indexed citations (citations by other indexed papers that have themselves been cited), including 158 papers in Molecular Biology, 71 papers in Oncology and 65 papers in Organic Chemistry. Recurrent topics in Yukio Nakamura's work include Organometallic Complex Synthesis and Catalysis (48 papers), Metal complexes synthesis and properties (46 papers) and Erythrocyte Function and Pathophysiology (46 papers). Yukio Nakamura is often cited by papers focused on Organometallic Complex Synthesis and Catalysis (48 papers), Metal complexes synthesis and properties (46 papers) and Erythrocyte Function and Pathophysiology (46 papers). Yukio Nakamura collaborates with scholars based in Japan, United States and Taiwan. Yukio Nakamura's co-authors include Ryo Kurita, Shinichi Kawaguchi, Kazuhiro Sudo, Takashi Hiroyama, Kenichi Miharada, Hiromitsu Nakauchi, Seichi Okeya, Kiyoshi Isobe, Steve Gerondakis and Raelene J. Grumont and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Yukio Nakamura

466 papers receiving 10.8k citations

Hit Papers

align trajectories

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.

BCL11A enhancer dissection by Cas9-mediated in situ saturating mutagenesis

2015 612 citations Ryo Kurita, Yukio Nakamura et al. profile →
Direct Promoter Repression by BCL11A Controls the Fetal to Adult Hemoglobin Switch

2018 310 citations Ryo Kurita, Yukio Nakamura et al. profile →
Long-term ex vivo haematopoietic-stem-cell expansion allows nonconditioned transplantation

2019 271 citations Kazuhiro Sudo, Yukio Nakamura et al. profile →
Chemically defined cytokine-free expansion of human haematopoietic stem cells

2023 78 citations Kazuhiro Sudo, Yukio Nakamura et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yukio Nakamura Japan	52	4.8k	2.1k	1.4k	1.2k	1.2k	482	11.1k
Billy G. Hudson United States	65	4.6k 1.0×	2.1k 1.0×	1.4k 1.0×	1.3k 1.0×	612 0.5×	238	14.0k
Joe B. Harford United States	57	7.8k 1.6×	1.3k 0.6×	2.5k 1.8×	1.5k 1.2×	2.2k 1.8×	134	14.0k
Joel S. Greenberger United States	68	7.7k 1.6×	2.8k 1.3×	2.4k 1.7×	2.2k 1.8×	3.1k 2.5×	447	18.6k
C. Haanen Netherlands	36	4.0k 0.8×	700 0.3×	1.6k 1.1×	1.9k 1.5×	1.7k 1.4×	199	9.6k
Francis Castellino United States	59	6.3k 1.3×	1.3k 0.6×	4.3k 3.0×	1.4k 1.2×	1.0k 0.8×	418	15.0k
Takayuki Takahashi Japan	43	3.8k 0.8×	501 0.2×	829 0.6×	1.8k 1.4×	1.2k 1.0×	364	9.9k
Toshiyuki Miyata Japan	62	4.9k 1.0×	1.4k 0.7×	3.5k 2.5×	3.8k 3.1×	515 0.4×	330	13.4k
Suzy V. Torti United States	61	6.5k 1.4×	2.6k 1.2×	5.3k 3.8×	1.2k 0.9×	1.7k 1.4×	142	16.8k
Alice L. Yu United States	56	6.1k 1.3×	725 0.3×	590 0.4×	2.1k 1.7×	2.8k 2.3×	297	11.9k
Pierre J. Courtoy Belgium	60	5.2k 1.1×	782 0.4×	732 0.5×	1.9k 1.5×	1.1k 0.9×	224	10.9k

Countries citing papers authored by Yukio Nakamura

Since Specialization

Citations

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

Fields of papers citing papers by Yukio Nakamura

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yukio Nakamura

This figure shows the co-authorship network connecting the top 25 collaborators of Yukio Nakamura. A scholar is included among the top collaborators of Yukio Nakamura 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 Yukio Nakamura. Yukio Nakamura 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

Kasai, Fumio, Makoto Fukushima, Yohei Miyagi, & Yukio Nakamura. (2024). Genetic diversity among the present Japanese population: evidence from genotyping of human cell lines established in Japan. Human Cell. 37(4). 944–950.

Fujita, Hideaki, Kazuhiro Sudo, Yukio Nakamura, et al.. (2024). Yuragi biomarker concept for evaluating human induced pluripotent stem cells using heterogeneity-based Raman finger-printing. Biophysics and Physicobiology. 21(Supplemental). n/a–n/a. 2 indexed citations

Gillemans, Nynke, Kerstin Putzker, Annelies de Klein, et al.. (2024). A cellular reporter system to evaluate endogenous fetal hemoglobin induction and screen for therapeutic compounds. HemaSphere. 8(8). e139–e139.

Sudo, Kazuhiro, et al.. (2024). Ascorbic acid predominantly kills cancer stem cell-like cells in the hepatocellular carcinoma cell line Li-7 and is more effective at low cell density and in small spheroids. Biochemical and Biophysical Research Communications. 709. 149816–149816. 1 indexed citations

Nakamura, Yukio, Meng Ling Moi, Takashi Shiina, Tadasu Shin‐I, & Ryuji Suzuki. (2023). Idiotope-Driven T-Cell/B-Cell Collaboration-Based T-Cell Epitope Prediction Using B-Cell Receptor Repertoire Sequences in Infectious Diseases. Viruses. 15(5). 1186–1186. 4 indexed citations

Song, Dan, Gou Takahashi, Yun‐Wen Zheng, et al.. (2022). Retinoids rescue ceruloplasmin secretion and alleviate oxidative stress in Wilson’s disease-specific hepatocytes. Human Molecular Genetics. 31(21). 3652–3671. 10 indexed citations

Wang, Xue Qing David, Fan Feng, Yushuai Liu, et al.. (2021). 3′HS1 CTCF binding site in human β-globin locus regulates fetal hemoglobin expression. eLife. 10. 14 indexed citations

Ye, Lin, Isadora Asunis, Maria Franca Marongiu, et al.. (2020). Induction of therapeutic levels of HbF in genome‐edited primary β⁰39‐thalassaemia haematopoietic stem and progenitor cells. British Journal of Haematology. 192(2). 395–404. 13 indexed citations

Wienert, Beeke, Gabriella E. Martyn, Ryo Kurita, et al.. (2017). KLF1 drives the expression of fetal hemoglobin in British HPFH. Blood. 130(6). 803–807. 71 indexed citations

10.

Zhang, Yankai, Ryo Kurita, Yukio Nakamura, & Vivien Sheehan. (2017). Screening Fetal Hemoglobin Inducing Compounds in Human Umbilical Cord Blood-Derived Erythroid Progenitor Cells. Blood. 130. 2222–2222. 1 indexed citations

11.

Koike, Chika, Kaixuan Zhou, Yuji Takeda, et al.. (2014). Characterization of Amniotic Stem Cells. Cellular Reprogramming. 16(4). 298–305. 61 indexed citations

12.

Tanigawa, Shunsuke, Chih‐Hung Lee, Chang‐Shen Lin, et al.. (2013). Jun dimerization protein 2 is a critical component of the Nrf2/MafK complex regulating the response to ROS homeostasis. Cell Death and Disease. 4(11). e921–e921. 54 indexed citations

13.

Nagano, Yumiko, Hirofumi Matsui, Osamu Shimokawa, et al.. (2012). Rebamipide attenuates nonsteroidal anti-inflammatory drugs (NSAID) induced lipid peroxidation by the manganese superoxide dismutase (MnSOD) overexpression in gastrointestinal epithelial cells.. PubMed. 63(2). 137–42. 19 indexed citations

14.

Capes‐Davis, Amanda, Hans G. Drexler, Arihiro Kohara, et al.. (2010). Check your cultures! A list of cross‐contaminated or misidentified cell lines. International Journal of Cancer. 127(1). 1–8. 338 indexed citations

15.

Ishiwata, Isamu, et al.. (2008). Induced in vitro differentiation of neural-like cells from human amnion-derived fibroblast-like cells. Human Cell. 21(2). 38–45. 31 indexed citations

16.

Shimokawa, Osamu, Hirofumi Matsui, Yumiko Nagano, et al.. (2007). Neoplastic transformation and induction of H+,K+-adenosine triphosphatase by N-methyl-N′-nitro-N-nitrosoguanidine in the gastric epithelial RGM-1 cell line. In Vitro Cellular & Developmental Biology - Animal. 44(1-2). 26–30. 41 indexed citations

17.

Nakagawa, Tsutomu, Akio Ebihara, Atsushi Iwasawa, et al.. (2003). Human Prorenin Has “Gate and Handle” Regions for Its Non-proteolytic Activation. Journal of Biological Chemistry. 278(25). 22217–22222. 149 indexed citations

18.

Suzuki, Fumiaki, et al.. (1999). Non-proteolytic Activation of Human Prorenin by Anti-prorenin Prosegment (pf#1: 1P-15P) Antiserum. Bioscience Biotechnology and Biochemistry. 63(3). 550–554. 7 indexed citations

19.

Nishimori, Hiroyuki, et al.. (1998). Cloning of TCFL5 encoding a novel human basic helix-loop-helix motif protein that is specifically expressed in primary spermatocytes at the pachytene stage. Cytogenetic and Genome Research. 82(1-2). 41–45. 26 indexed citations

20.

Nakamura, Yukio, et al.. (1991). Effect of Ammonia on the Survival of Red Sea Bream, Pagrus major Eggs and Larvae. Aquaculture Science. 39(4). 353–362. 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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