Yoko Koseki

2.3k total citations · 1 hit paper
17 papers, 1.5k citations indexed

About

Yoko Koseki is a scholar working on Molecular Biology, Genetics and Immunology. According to data from OpenAlex, Yoko Koseki has authored 17 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 6 papers in Genetics and 2 papers in Immunology. Recurrent topics in Yoko Koseki's work include Epigenetics and DNA Methylation (12 papers), Genomics and Chromatin Dynamics (6 papers) and Cancer-related gene regulation (5 papers). Yoko Koseki is often cited by papers focused on Epigenetics and DNA Methylation (12 papers), Genomics and Chromatin Dynamics (6 papers) and Cancer-related gene regulation (5 papers). Yoko Koseki collaborates with scholars based in Japan, United Kingdom and Spain. Yoko Koseki's co-authors include Haruhiko Koseki, Robert J. Klose, Hamish W. King, Shinsuke Ito, Neil P. Blackledge, Anca M. Farcas, Manabu Nakayama, Neil Brockdorff, Takashi Kondo and Kaori Kondo and has published in prestigious journals such as Science, Cell and Nucleic Acids Research.

In The Last Decade

Yoko Koseki

17 papers receiving 1.5k citations

Hit Papers

Variant PRC1 Complex-Dependent H2A Ubiquitylation Drives ... 2014 2026 2018 2022 2014 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yoko Koseki Japan 15 1.3k 277 167 121 106 17 1.5k
Aditi K. Narayanan United States 5 1.2k 0.9× 237 0.9× 279 1.7× 98 0.8× 95 0.9× 6 1.4k
Roman Alpatov United States 8 1.1k 0.9× 275 1.0× 116 0.7× 74 0.6× 72 0.7× 13 1.3k
Eric M. Mendenhall United States 13 1.9k 1.5× 368 1.3× 177 1.1× 98 0.8× 140 1.3× 27 2.1k
Jennifer N. Cech United States 10 892 0.7× 201 0.7× 115 0.7× 95 0.8× 93 0.9× 13 1.2k
Anne Laugesen Denmark 8 1.1k 0.9× 161 0.6× 192 1.1× 72 0.6× 70 0.7× 9 1.3k
Pedro P. Rocha United States 19 1.3k 1.0× 195 0.7× 109 0.7× 136 1.1× 249 2.3× 29 1.5k
Hans-Martin Herz United States 15 1.9k 1.4× 244 0.9× 140 0.8× 93 0.8× 127 1.2× 15 2.0k
Daria Shlyueva United States 9 1.3k 1.0× 233 0.8× 150 0.9× 119 1.0× 166 1.6× 12 1.5k
Gilad Landan United States 9 875 0.7× 209 0.8× 257 1.5× 109 0.9× 107 1.0× 12 1.1k
Ramya Raviram United States 18 1.5k 1.1× 194 0.7× 175 1.0× 158 1.3× 282 2.7× 22 1.7k

Countries citing papers authored by Yoko Koseki

Since Specialization
Citations

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

Fields of papers citing papers by Yoko Koseki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yoko Koseki

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

All Works

17 of 17 papers shown
1.
Masui, Osamu, C. Corbel, Koji Nagao, et al.. (2023). Polycomb repressive complexes 1 and 2 are each essential for maintenance of X inactivation in extra-embryonic lineages. Nature Cell Biology. 25(1). 134–144. 14 indexed citations
2.
Ohinata, Yasuhide, Takaho A. Endo, Hiroki Sugishita, et al.. (2022). Establishment of mouse stem cells that can recapitulate the developmental potential of primitive endoderm. Science. 375(6580). 574–578. 30 indexed citations
3.
Shirakawa, Takayuki, Jafar Sharif, Shin-ichi Tomizawa, et al.. (2021). Maintenance DNA methylation in pre-meiotic germ cells regulates meiotic prophase by facilitating homologous chromosome pairing. Development. 148(10). 19 indexed citations
4.
Sugishita, Hiroki, Takashi Kondo, Shinsuke Ito, et al.. (2021). Variant PCGF1-PRC1 links PRC2 recruitment with differentiation-associated transcriptional inactivation at target genes. Nature Communications. 12(1). 5341–5341. 22 indexed citations
5.
Turberfield, Anne H., Takashi Kondo, Manabu Nakayama, et al.. (2019). KDM2 proteins constrain transcription from CpG island gene promoters independently of their histone demethylase activity. Nucleic Acids Research. 47(17). 9005–9023. 25 indexed citations
6.
Healy, Evan, Marlena Mucha, Eleanor Glancy, et al.. (2019). PRC2.1 and PRC2.2 Synergize to Coordinate H3K27 Trimethylation. Molecular Cell. 76(3). 437–452.e6. 125 indexed citations
7.
Fursova, Nadezda A., Neil P. Blackledge, Manabu Nakayama, et al.. (2019). Synergy between Variant PRC1 Complexes Defines Polycomb-Mediated Gene Repression. Molecular Cell. 74(5). 1020–1036.e8. 182 indexed citations
8.
Yakushiji‐Kaminatsui, Nayuta, Takashi Kondo, Ken‐ichi Hironaka, et al.. (2018). Variant PRC1 competes with retinoic acid-related signals to repress Meis2 in distal forelimb bud. Development. 145(19). 14 indexed citations
9.
Dimitrova, Emilia, Takashi Kondo, Angelika Feldmann, et al.. (2018). FBXL19 recruits CDK-Mediator to CpG islands of developmental genes priming them for activation during lineage commitment. eLife. 7. 21 indexed citations
10.
Almeida, Mafalda, Greta Pintacuda, Osamu Masui, et al.. (2017). PCGF3/5–PRC1 initiates Polycomb recruitment in X chromosome inactivation. Science. 356(6342). 1081–1084. 198 indexed citations
11.
Ikawa, Tomokatsu, Kyoko Masuda, Takaho A. Endo, et al.. (2016). Conversion of T cells to B cells by inactivation of polycomb-mediated epigenetic suppression of the B-lineage program. Genes & Development. 30(22). 2475–2485. 27 indexed citations
12.
Satoh, Rumi, Kiyokazu Kakugawa, Takuwa Yasuda, et al.. (2016). Requirement of Stat3 Signaling in the Postnatal Development of Thymic Medullary Epithelial Cells. PLoS Genetics. 12(1). e1005776–e1005776. 28 indexed citations
13.
Yakushiji‐Kaminatsui, Nayuta, Takashi Kondo, Takaho A. Endo, et al.. (2015). RING1 contributes to early proximal-distal specification of the forelimb bud by restricting Meis2 expression. Development. 143(2). 276–85. 12 indexed citations
14.
Blackledge, Neil P., Anca M. Farcas, Takashi Kondo, et al.. (2014). Variant PRC1 Complex-Dependent H2A Ubiquitylation Drives PRC2 Recruitment and Polycomb Domain Formation. Cell. 157(6). 1445–1459. 553 indexed citations breakdown →
15.
Higashimoto, Ken, Takaho A. Endo, Jafar Sharif, et al.. (2013). Ash1l Methylates Lys36 of Histone H3 Independently of Transcriptional Elongation to Counteract Polycomb Silencing. PLoS Genetics. 9(11). e1003897–e1003897. 66 indexed citations
16.
Zhang, Yan, Takashi Miki, Toshihiko Iwanaga, et al.. (2002). Identification, Tissue Expression, and Functional Characterization of Otx3, a Novel Member of the Otx Family. Journal of Biological Chemistry. 277(31). 28065–28069. 25 indexed citations
17.
Kimura, Motoko Y., Yoko Koseki, Masakatsu Yamashita, et al.. (2001). Regulation of Th2 Cell Differentiation by mel-18, a Mammalian Polycomb Group Gene. Immunity. 15(2). 275–287. 98 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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