Ming‐Han Tong

2.5k total citations
34 papers, 1.8k citations indexed

About

Ming‐Han Tong is a scholar working on Molecular Biology, Genetics and Reproductive Medicine. According to data from OpenAlex, Ming‐Han Tong has authored 34 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 10 papers in Genetics and 10 papers in Reproductive Medicine. Recurrent topics in Ming‐Han Tong's work include Sperm and Testicular Function (10 papers), CRISPR and Genetic Engineering (7 papers) and DNA Repair Mechanisms (6 papers). Ming‐Han Tong is often cited by papers focused on Sperm and Testicular Function (10 papers), CRISPR and Genetic Engineering (7 papers) and DNA Repair Mechanisms (6 papers). Ming‐Han Tong collaborates with scholars based in China, United States and Ethiopia. Ming‐Han Tong's co-authors include Zhen Lin, Michael D. Griswold, Ryan Evanoff, Debra Mitchell, Ren‐Shan Ge, Matthew P. Hardy, Hui-Bao Gao, Michael D. Griswold, J. Larry Jameson and Yuchuan Zhou and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Ming‐Han Tong

33 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming‐Han Tong China 20 1.2k 532 451 405 317 34 1.8k
Antoine D. Rolland France 22 670 0.6× 566 1.1× 216 0.5× 608 1.5× 328 1.0× 44 1.5k
Sheng Cui China 19 546 0.5× 278 0.5× 339 0.8× 236 0.6× 185 0.6× 103 1.3k
Zi‐Jian Lan United States 18 1.2k 1.0× 835 1.6× 86 0.2× 439 1.1× 1.2k 3.8× 47 2.2k
Sara de Mateo Spain 15 456 0.4× 740 1.4× 64 0.1× 301 0.7× 530 1.7× 20 1.5k
Guylain Boissonneault Canada 19 776 0.7× 852 1.6× 105 0.2× 517 1.3× 637 2.0× 48 1.6k
Qifa Li China 26 1.2k 1.0× 193 0.4× 885 2.0× 483 1.2× 418 1.3× 104 2.1k
Dori C. Woods United States 28 1.3k 1.1× 695 1.3× 126 0.3× 456 1.1× 1.4k 4.4× 63 2.4k
Menghong Yan China 9 1.0k 0.9× 140 0.3× 450 1.0× 125 0.3× 133 0.4× 12 1.4k
Charles L. Chaffin United States 25 272 0.2× 565 1.1× 167 0.4× 361 0.9× 672 2.1× 50 1.6k
E. McGee United States 10 633 0.5× 481 0.9× 60 0.1× 204 0.5× 744 2.3× 14 1.4k

Countries citing papers authored by Ming‐Han Tong

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Han Tong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming‐Han Tong. 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 Ming‐Han Tong. The network helps show where Ming‐Han Tong may publish in the future.

Co-authorship network of co-authors of Ming‐Han Tong

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

All Works

20 of 20 papers shown
1.
Lin, Zhen, Bowen Rong, Ruitu Lyu, et al.. (2025). SETD1B-mediated broad H3K4me3 controls proper temporal patterns of gene expression critical for spermatid development. Cell Research. 35(5). 345–361. 10 indexed citations
2.
Zhang, Li, Jian‐Shu Wang, Zhidong Tang, et al.. (2025). The nuclear exosome co-factor MTR4 shapes the transcriptome for meiotic initiation. Nature Communications. 16(1). 2605–2605.
3.
Lin, Zhen, Bowen Rong, Meixia Wu, et al.. (2025). The KMT2 complex protein ASH2L is required for meiotic prophase progression but dispensable for mitosis in differentiated spermatogonia. Development. 152(6). 1 indexed citations
5.
Chen, Yao, et al.. (2024). Isolation of Homogeneous Sub-populations of Spermatocytes from Mouse Testis. Methods in molecular biology. 2818. 115–132. 1 indexed citations
6.
Jiang, Yu, Fei Huang, Lu Chen, et al.. (2022). Genome-wide map of R-loops reveals its interplay with transcription and genome integrity during germ cell meiosis. Journal of Advanced Research. 51. 45–57. 8 indexed citations
7.
Feng, Xiangling, Qian Ouyang, Qiaoli Chen, et al.. (2022). PGE 2 ‐EP3 axis promotes brown adipose tissue formation through stabilization of WTAP RNA methyltransferase. The EMBO Journal. 41(16). e110439–e110439. 19 indexed citations
8.
Yang, Ying, Jie Gao, Junhong Li, et al.. (2021). METTL3-mediated mRNA N6-methyladenosine is required for oocyte and follicle development in mice. Cell Death and Disease. 12(11). 989–989. 61 indexed citations
9.
Lin, Zhen, Yong Fan, Wenzhi Li, et al.. (2021). YTHDF2 is essential for spermatogenesis and fertility by mediating a wave of transcriptional transition in spermatogenic cells. Acta Biochimica et Biophysica Sinica. 53(12). 1702–1712. 10 indexed citations
10.
Wang, Yinghua, et al.. (2021). Rescue of male infertility through correcting a genetic mutation causing meiotic arrest in spermatogonial stem cells. Asian Journal of Andrology. 23(6). 590–599. 25 indexed citations
11.
Yao, Chen, Ruitu Lyu, Bowen Rong, et al.. (2020). Refined spatial temporal epigenomic profiling reveals intrinsic connection between PRDM9-mediated H3K4me3 and the fate of double-stranded breaks. Cell Research. 30(3). 256–268. 43 indexed citations
12.
Jia, Gongxue, Zhen Lin, Guowen Wang, et al.. (2020). WTAP Function in Sertoli Cells Is Essential for Sustaining the Spermatogonial Stem Cell Niche. Stem Cell Reports. 15(4). 968–982. 40 indexed citations
13.
Li, Yiping, et al.. (2019). Mechanistic target of rapamycin kinase (Mtor) is required for spermatogonial proliferation and differentiation in mice. Asian Journal of Andrology. 22(2). 169–169. 10 indexed citations
14.
Wang, Yiqin, Meng Ma, Wei Zhang, et al.. (2019). A new panel containing specific spermatogenesis markers to identify spermatogenic cells in nonobstructive azoospermia patients. Acta Biochimica et Biophysica Sinica. 51(6). 655–658. 3 indexed citations
15.
Zuo, Xiaoli, Bowen Rong, Li Li, et al.. (2018). The histone methyltransferase SETD2 is required for expression of acrosin-binding protein 1 and protamines and essential for spermiogenesis in mice. Journal of Biological Chemistry. 293(24). 9188–9197. 51 indexed citations
16.
Lin, Zhen, Phillip J. Hsu, Xudong Xing, et al.. (2017). Mettl3-/Mettl14-mediated mRNA N6-methyladenosine modulates murine spermatogenesis. Cell Research. 27(10). 1216–1230. 349 indexed citations
17.
Weiss, Jeffrey, Lisa Hurley, Rebecca M. Harris, et al.. (2012). ENU mutagenesis in mice identifies candidate genes for hypogonadism. Mammalian Genome. 23(5-6). 346–355. 16 indexed citations
18.
Tong, Ming‐Han, Debra Mitchell, Ryan Evanoff, & Michael D. Griswold. (2011). Expression of Mirlet7 Family MicroRNAs in Response to Retinoic Acid-Induced Spermatogonial Differentiation in Mice1. Biology of Reproduction. 85(1). 189–197. 97 indexed citations
19.
Tong, Ming‐Han, et al.. (2011). Two miRNA Clusters, Mir-17-92 (Mirc1) and Mir-106b-25 (Mirc3), Are Involved in the Regulation of Spermatogonial Differentiation in Mice1. Biology of Reproduction. 86(3). 72–72. 151 indexed citations
20.
Gao, Hui-Bao, et al.. (2002). Glucocorticoid Induces Apoptosis in Rat Leydig Cells. Endocrinology. 143(1). 130–138. 143 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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