Tom H. Cheung

6.9k total citations · 2 hit papers
53 papers, 4.5k citations indexed

About

Tom H. Cheung is a scholar working on Molecular Biology, Physiology and Genetics. According to data from OpenAlex, Tom H. Cheung has authored 53 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Molecular Biology, 15 papers in Physiology and 7 papers in Genetics. Recurrent topics in Tom H. Cheung's work include Muscle Physiology and Disorders (24 papers), Telomeres, Telomerase, and Senescence (12 papers) and RNA Research and Splicing (8 papers). Tom H. Cheung is often cited by papers focused on Muscle Physiology and Disorders (24 papers), Telomeres, Telomerase, and Senescence (12 papers) and RNA Research and Splicing (8 papers). Tom H. Cheung collaborates with scholars based in Hong Kong, United States and China. Tom H. Cheung's co-authors include Thomas A. Rando, Ling Liu, Gregory W. Charville, Bryan Yoo, Christopher R.R. Bjornson, Pinky Tripathi, Nancy Y. Ip, Anne Brunet, Johnathan Shih and Tripp Leavitt 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

Tom H. Cheung

53 papers receiving 4.5k citations

Hit Papers

Molecular regulation of stem cell quiescence 2013 2026 2017 2021 2013 2025 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
Tom H. Cheung Hong Kong 27 3.4k 974 727 575 563 53 4.5k
Shenghui He United States 14 2.4k 0.7× 973 1.0× 370 0.5× 361 0.6× 504 0.9× 20 4.1k
Simona Parrinello United Kingdom 26 2.7k 0.8× 1.8k 1.9× 452 0.6× 465 0.8× 744 1.3× 38 5.9k
Alison C. Lloyd United Kingdom 30 2.7k 0.8× 648 0.7× 625 0.9× 492 0.9× 381 0.7× 52 5.9k
Lynn A. Megeney Canada 33 3.6k 1.1× 684 0.7× 594 0.8× 389 0.7× 246 0.4× 66 4.4k
Manisha Sinha India 15 2.1k 0.6× 575 0.6× 492 0.7× 204 0.4× 411 0.7× 41 3.3k
Hitoshi Niwa Japan 24 5.9k 1.7× 491 0.5× 736 1.0× 298 0.5× 394 0.7× 36 7.3k
José M. Polo Australia 41 6.2k 1.9× 773 0.8× 717 1.0× 544 0.9× 605 1.1× 110 8.6k
Jay W. Schneider United States 29 4.4k 1.3× 403 0.4× 471 0.6× 324 0.6× 502 0.9× 52 5.7k
April D. Pyle United States 30 3.6k 1.1× 367 0.4× 590 0.8× 342 0.6× 238 0.4× 62 4.5k
Manching Ku United States 25 7.8k 2.3× 493 0.5× 633 0.9× 320 0.6× 704 1.3× 33 8.8k

Countries citing papers authored by Tom H. Cheung

Since Specialization
Citations

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

Fields of papers citing papers by Tom H. Cheung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom H. Cheung. 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 Tom H. Cheung. The network helps show where Tom H. Cheung may publish in the future.

Co-authorship network of co-authors of Tom H. Cheung

This figure shows the co-authorship network connecting the top 25 collaborators of Tom H. Cheung. A scholar is included among the top collaborators of Tom H. Cheung 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 Tom H. Cheung. Tom H. Cheung 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.
He, Gary J., et al.. (2024). Muscle stem cell niche dynamics during muscle homeostasis and regeneration. Current topics in developmental biology. 158. 151–177. 1 indexed citations
2.
Yu, Qing, Yujie Chen, Guangdun Peng, et al.. (2022). Activation of Wnt/β-catenin signaling by Zeb1 in endothelial progenitors induces vascular quiescence entry. Cell Reports. 41(8). 111694–111694. 10 indexed citations
3.
Cheung, Tom H., et al.. (2021). Deciphering the chromatin organization and dynamics for muscle stem cell function. Current Opinion in Cell Biology. 73. 124–132. 7 indexed citations
4.
So, Wai‐Kin, et al.. (2020). A long noncoding RNA, LncMyoD , modulates chromatin accessibility to regulate muscle stem cell myogenic lineage progression. Proceedings of the National Academy of Sciences. 117(51). 32464–32475. 32 indexed citations
5.
Lau, Shun‐Fat, Congping Chen, Wing‐Yu Fu, et al.. (2020). IL-33-PU.1 Transcriptome Reprogramming Drives Functional State Transition and Clearance Activity of Microglia in Alzheimer’s Disease. Cell Reports. 31(3). 107530–107530. 80 indexed citations
6.
Wan, Raymond, et al.. (2020). Dek Modulates Global Intron Retention during Muscle Stem Cells Quiescence Exit. Developmental Cell. 53(6). 661–676.e6. 68 indexed citations
7.
Liu, Ling, Gregory W. Charville, Tom H. Cheung, et al.. (2018). Impaired Notch Signaling Leads to a Decrease in p53 Activity and Mitotic Catastrophe in Aged Muscle Stem Cells. Cell stem cell. 23(4). 544–556.e4. 113 indexed citations
8.
Kong, Cihang, Xiaoming Wei, Tom H. Cheung, et al.. (2017). Compact fs ytterbium fiber laser at 1010 nm for biomedical applications. Biomedical Optics Express. 8(11). 4921–4921. 27 indexed citations
9.
So, Wai‐Kin & Tom H. Cheung. (2017). Molecular Regulation of Cellular Quiescence: A Perspective from Adult Stem Cells and Its Niches. Methods in molecular biology. 1686. 1–25. 34 indexed citations
10.
Wang, Gang, Yarui Diao, Xinrong Fu, et al.. (2017). A Molecular Switch Regulating Cell Fate Choice between Muscle Progenitor Cells and Brown Adipocytes. Developmental Cell. 41(4). 382–391.e5. 48 indexed citations
11.
Fu, Amy K.Y., Xiaopu Zhou, D.S.Y. Mak, et al.. (2016). IL-33 ameliorates Alzheimer’s disease-like pathology and cognitive decline. Proceedings of the National Academy of Sciences. 113(19). E2705–13. 294 indexed citations
12.
Mueller, Alisa A., et al.. (2016). Intronic polyadenylation of PDGFRα in resident stem cells attenuates muscle fibrosis. Nature. 540(7632). 276–279. 102 indexed citations
13.
Charville, Gregory W., Tom H. Cheung, Bryan Yoo, et al.. (2015). Ex Vivo Expansion and In Vivo Self-Renewal of Human Muscle Stem Cells. Stem Cell Reports. 5(4). 621–632. 156 indexed citations
14.
Liu, Ling, Tom H. Cheung, Gregory W. Charville, & Thomas A. Rando. (2015). Isolation of skeletal muscle stem cells by fluorescence-activated cell sorting. Nature Protocols. 10(10). 1612–1624. 267 indexed citations
15.
Cheung, Tom H. & Thomas A. Rando. (2013). Molecular regulation of stem cell quiescence. Nature Reviews Molecular Cell Biology. 14(6). 329–340. 810 indexed citations breakdown →
16.
Liu, Ling, Tom H. Cheung, Gregory W. Charville, et al.. (2013). Chromatin Modifications as Determinants of Muscle Stem Cell Quiescence and Chronological Aging. Cell Reports. 4(1). 189–204. 392 indexed citations
17.
Boutet, Stéphane C., Tom H. Cheung, Ling Liu, et al.. (2012). Alternative Polyadenylation Mediates MicroRNA Regulation of Muscle Stem Cell Function. Cell stem cell. 10(3). 327–336. 124 indexed citations
18.
Cheung, Tom H., Gregory W. Charville, Ling Liu, et al.. (2012). Maintenance of muscle stem-cell quiescence by microRNA-489. Nature. 482(7386). 524–528. 379 indexed citations
19.
Cheung, Tom H., et al.. (2006). Unraveling transcriptional control and cis-regulatory codes using the software suite GeneACT. Genome biology. 7(10). R97–R97. 12 indexed citations
20.
Macdonald, Mara, Yong Wan, Wei Wang, et al.. (2004). Control of cell cycle-dependent degradation of c-Ski proto-oncoprotein by Cdc34. Oncogene. 23(33). 5643–5653. 23 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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