Hatsune Chiba

3.5k total citations · 1 hit paper
17 papers, 2.7k citations indexed

About

Hatsune Chiba is a scholar working on Molecular Biology, Genetics and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Hatsune Chiba has authored 17 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 13 papers in Genetics and 11 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Hatsune Chiba's work include Genetic Syndromes and Imprinting (13 papers), Epigenetics and DNA Methylation (12 papers) and Prenatal Screening and Diagnostics (10 papers). Hatsune Chiba is often cited by papers focused on Genetic Syndromes and Imprinting (13 papers), Epigenetics and DNA Methylation (12 papers) and Prenatal Screening and Diagnostics (10 papers). Hatsune Chiba collaborates with scholars based in Japan, United Kingdom and France. Hatsune Chiba's co-authors include Masahiro Kaneda, Hiroyuki Sasaki, Tomohiro Kono, Ryutaro Hirasawa, Atsushi Toyoda, Yasushi Totoki, Toshiaki Watanabe, Yuji Kohara, Satomi Kuramochi‐Miyagawa and Toru Nakano and has published in prestigious journals such as Nature, Nature Genetics and Genes & Development.

In The Last Decade

Hatsune Chiba

17 papers receiving 2.6k citations

Hit Papers

Endogenous siRNAs from naturally formed dsRNAs regulate t... 2008 2026 2014 2020 2008 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hatsune Chiba Japan 15 2.3k 910 756 421 352 17 2.7k
Valérie Grandjean France 24 1.8k 0.8× 603 0.7× 605 0.8× 535 1.3× 294 0.8× 43 2.5k
Julia Arand Germany 16 3.1k 1.3× 860 0.9× 446 0.6× 160 0.4× 255 0.7× 23 3.4k
Takashi Sado Japan 28 3.5k 1.5× 2.1k 2.3× 633 0.8× 565 1.3× 348 1.0× 54 4.0k
Sylvia Erhardt Germany 18 3.4k 1.5× 987 1.1× 526 0.7× 214 0.5× 260 0.7× 31 3.7k
Daniel M. Messerschmidt Singapore 18 1.5k 0.6× 437 0.5× 341 0.5× 134 0.3× 237 0.7× 30 1.9k
Kenjiro Shirane Japan 18 1.9k 0.8× 544 0.6× 498 0.7× 104 0.2× 439 1.2× 33 2.4k
Yayoi Obata Japan 23 3.3k 1.4× 1.7k 1.8× 998 1.3× 490 1.2× 1.2k 3.5× 54 4.0k
Ryuichi Ono Japan 17 1.6k 0.7× 1.1k 1.2× 625 0.8× 155 0.4× 102 0.3× 31 2.0k
Canquan Zhou China 24 1.4k 0.6× 454 0.5× 635 0.8× 148 0.4× 614 1.7× 118 2.4k
Nathalie Beaujean France 28 2.6k 1.1× 749 0.8× 473 0.6× 70 0.2× 1.4k 3.9× 69 3.0k

Countries citing papers authored by Hatsune Chiba

Since Specialization
Citations

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

Fields of papers citing papers by Hatsune Chiba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hatsune Chiba

This figure shows the co-authorship network connecting the top 25 collaborators of Hatsune Chiba. A scholar is included among the top collaborators of Hatsune Chiba 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 Hatsune Chiba. Hatsune Chiba 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.
Yeung, Wan Kin Au, Motoko Unoki, Kenji Ichiyanagi, et al.. (2019). Characterization of genetic‐origin‐dependent monoallelic expression in mouse embryonic stem cells. Genes to Cells. 25(1). 54–64. 3 indexed citations
2.
Kitamura, Hiroshi, Hiroki Shima, Daisuke Saigusa, et al.. (2018). Lactate dehydrogenase C is required for the protein expression of a sperm-specific isoform of lactate dehydrogenase A. The Journal of Biochemistry. 165(4). 323–334. 18 indexed citations
3.
Hiura, Hitoshi, Hiromitsu Hattori, Norio Kobayashi, et al.. (2017). Genome-wide microRNA expression profiling in placentae from frozen-thawed blastocyst transfer. Clinical Epigenetics. 9(1). 79–79. 56 indexed citations
4.
Kobayashi, Norio, Hiroaki Okae, Hitoshi Hiura, et al.. (2016). Genome-Scale Assessment of Age-Related DNA Methylation Changes in Mouse Spermatozoa. PLoS ONE. 11(11). e0167127–e0167127. 11 indexed citations
5.
Hamada, Hirotaka, Hiroaki Okae, Hidehiro Toh, et al.. (2016). Allele-Specific Methylome and Transcriptome Analysis Reveals Widespread Imprinting in the Human Placenta. The American Journal of Human Genetics. 99(5). 1045–1058. 84 indexed citations
6.
Kitamura, Akane, Naoko Miyauchi, Hirotaka Hamada, et al.. (2015). Epigenetic alterations in sperm associated with male infertility. Congenital Anomalies. 55(3). 133–144. 45 indexed citations
7.
Okae, Hiroaki, Hatsune Chiba, Hitoshi Hiura, et al.. (2014). Genome-Wide Analysis of DNA Methylation Dynamics during Early Human Development. PLoS Genetics. 10(12). e1004868–e1004868. 183 indexed citations
8.
Hiura, Hitoshi, Hiroaki Okae, Hatsune Chiba, et al.. (2014). Imprinting methylation errors in ART. Reproductive Medicine and Biology. 13(4). 193–202. 65 indexed citations
9.
Shirane, Kenjiro, Hidehiro Toh, Hisato Kobayashi, et al.. (2013). Mouse Oocyte Methylomes at Base Resolution Reveal Genome-Wide Accumulation of Non-CpG Methylation and Role of DNA Methyltransferases. PLoS Genetics. 9(4). e1003439–e1003439. 236 indexed citations
10.
Okae, Hiroaki, Shogo Matoba, Takeshi Nagashima, et al.. (2013). RNA sequencing-based identification of aberrant imprinting in cloned mice. Human Molecular Genetics. 23(4). 992–1001. 56 indexed citations
11.
Chiba, Hatsune, Hitoshi Hiura, Hiroaki Okae, et al.. (2013). DNA methylation errors in imprinting disorders and assisted reproductive technology. Pediatrics International. 55(5). 542–549. 27 indexed citations
12.
Okae, Hiroaki, Hitoshi Hiura, Yuichiro Nishida, et al.. (2011). Re-investigation and RNA sequencing-based identification of genes with placenta-specific imprinted expression. Human Molecular Genetics. 21(3). 548–558. 91 indexed citations
13.
Borgel, Julie, Sylvain Guibert, Yufeng Li, et al.. (2010). Targets and dynamics of promoter DNA methylation during early mouse development. Nature Genetics. 42(12). 1093–1100. 456 indexed citations
14.
Kaneda, Masahiro, Ryutaro Hirasawa, Hatsune Chiba, et al.. (2010). Genetic evidence for Dnmt3a‐dependent imprinting during oocyte growth obtained by conditional knockout with Zp3‐Cre and complete exclusion of Dnmt3b by chimera formation. Genes to Cells. 15(3). 169–179. 79 indexed citations
15.
Chiba, Hatsune, Ryutaro Hirasawa, Masahiro Kaneda, et al.. (2008). De novo DNA methylation independent establishment of maternal imprint on X chromosome in mouse oocytes. genesis. 46(12). 768–774. 34 indexed citations
16.
Watanabe, Toshiaki, Yasushi Totoki, Atsushi Toyoda, et al.. (2008). Endogenous siRNAs from naturally formed dsRNAs regulate transcripts in mouse oocytes. Nature. 453(7194). 539–543. 861 indexed citations breakdown →
17.
Hirasawa, Ryutaro, Hatsune Chiba, Masahiro Kaneda, et al.. (2008). Maternal and zygotic Dnmt1 are necessary and sufficient for the maintenance of DNA methylation imprints during preimplantation development. Genes & Development. 22(12). 1607–1616. 359 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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