Gary C. Hon

27.2k total citations · 5 hit papers
22 papers, 13.0k citations indexed

About

Gary C. Hon is a scholar working on Molecular Biology, Plant Science and Cancer Research. According to data from OpenAlex, Gary C. Hon has authored 22 papers receiving a total of 13.0k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 2 papers in Plant Science and 2 papers in Cancer Research. Recurrent topics in Gary C. Hon's work include Epigenetics and DNA Methylation (12 papers), Genomics and Chromatin Dynamics (11 papers) and RNA modifications and cancer (7 papers). Gary C. Hon is often cited by papers focused on Epigenetics and DNA Methylation (12 papers), Genomics and Chromatin Dynamics (11 papers) and RNA modifications and cancer (7 papers). Gary C. Hon collaborates with scholars based in United States, China and Canada. Gary C. Hon's co-authors include Bing Ren, R. David Hawkins, Chuan He, Qing Dai, Dali Han, Xiao Wang, Zhike Lu, Marc Parisien, Adrian Gomez-Nguyen and Tao Pan and has published in prestigious journals such as Nature, Cell and Nature Communications.

In The Last Decade

Gary C. Hon

21 papers receiving 12.9k citations

Hit Papers

Human DNA methylomes at base resolution show widespread e... 2007 2026 2013 2019 2009 2013 2007 2012 2013 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gary C. Hon United States 20 11.9k 2.4k 1.9k 1.0k 582 22 13.0k
Yujiang Geno Shi United States 43 11.1k 0.9× 1.9k 0.8× 1.8k 1.0× 486 0.5× 250 0.4× 73 12.4k
Naomi Habib United States 20 15.6k 1.3× 1.3k 0.6× 3.2k 1.7× 1.6k 1.6× 254 0.4× 34 18.0k
Neville E. Sanjana United States 35 10.3k 0.9× 1.6k 0.7× 1.7k 0.9× 470 0.5× 281 0.5× 74 12.5k
Riza M. Daza United States 26 6.6k 0.6× 2.2k 0.9× 1.1k 0.6× 733 0.7× 89 0.2× 35 8.6k
Fuchou Tang China 69 12.6k 1.1× 3.8k 1.6× 2.0k 1.1× 580 0.6× 104 0.2× 156 15.8k
Michiel Vermeulen Netherlands 53 10.5k 0.9× 1.0k 0.4× 1.3k 0.7× 583 0.6× 111 0.2× 182 12.2k
David S. Johnson United States 26 13.9k 1.2× 1.9k 0.8× 2.4k 1.3× 2.4k 2.4× 81 0.1× 48 17.0k
Andrew J. Bannister United Kingdom 52 20.1k 1.7× 2.3k 1.0× 2.8k 1.5× 2.1k 2.1× 162 0.3× 84 23.5k
Michael J. Hendzel Canada 64 11.8k 1.0× 1.0k 0.4× 1.2k 0.7× 937 0.9× 386 0.7× 160 14.2k
Andrew C. Adey United States 28 5.5k 0.5× 1.3k 0.5× 1000 0.5× 906 0.9× 97 0.2× 53 7.0k

Countries citing papers authored by Gary C. Hon

Since Specialization
Citations

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

Fields of papers citing papers by Gary C. Hon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gary C. Hon. 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 Gary C. Hon. The network helps show where Gary C. Hon may publish in the future.

Co-authorship network of co-authors of Gary C. Hon

This figure shows the co-authorship network connecting the top 25 collaborators of Gary C. Hon. A scholar is included among the top collaborators of Gary C. Hon 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 Gary C. Hon. Gary C. Hon 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.
Wang, Yihan, et al.. (2025). Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes. Genome biology. 26(1). 10–10.
2.
Xie, Shiqi & Gary C. Hon. (2019). Experimental and Computational Approaches for Single-Cell Enhancer Perturbation Assay. Methods in molecular biology. 1935. 203–221. 5 indexed citations
3.
Xie, Shiqi, et al.. (2018). Frequent sgRNA-barcode recombination in single-cell perturbation assays. PLoS ONE. 13(6). e0198635–e0198635. 36 indexed citations
4.
Liu, Xin, Yuannyu Zhang, Yong Chen, et al.. (2017). In Situ Capture of Chromatin Interactions by Biotinylated dCas9. Cell. 170(5). 1028–1043.e19. 208 indexed citations
5.
Yu, Miao, Dali Han, Gary C. Hon, & Chuan He. (2017). Tet-Assisted Bisulfite Sequencing (TAB-seq). Methods in molecular biology. 1708. 645–663. 22 indexed citations
6.
Hon, Gary C., Chun‐Xiao Song, Tingting Du, et al.. (2014). 5mC Oxidation by Tet2 Modulates Enhancer Activity and Timing of Transcriptome Reprogramming during Differentiation. Molecular Cell. 56(2). 286–297. 254 indexed citations
7.
Zhang, Liang, Keith E. Szulwach, Gary C. Hon, et al.. (2013). Tet-mediated covalent labelling of 5-methylcytosine for its genome-wide detection and sequencing. Nature Communications. 4(1). 1517–1517. 47 indexed citations
8.
Hon, Gary C., Nisha Rajagopal, Yin Shen, et al.. (2013). Epigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues. Nature Genetics. 45(10). 1198–1206. 352 indexed citations
9.
Wang, Xiao, Zhike Lu, Adrian Gomez-Nguyen, et al.. (2013). N6-methyladenosine-dependent regulation of messenger RNA stability. Nature. 505(7481). 117–120. 3320 indexed citations breakdown →
10.
Yu, Miao, Gary C. Hon, Keith E. Szulwach, et al.. (2012). Tet-assisted bisulfite sequencing of 5-hydroxymethylcytosine. Nature Protocols. 7(12). 2159–2170. 173 indexed citations
11.
Yu, Miao, Gary C. Hon, Keith E. Szulwach, et al.. (2012). Base-Resolution Analysis of 5-Hydroxymethylcytosine in the Mammalian Genome. Cell. 149(6). 1368–1380. 798 indexed citations breakdown →
12.
Smallwood, Andrea, Gary C. Hon, Fulai Jin, et al.. (2012). CBX3 regulates efficient RNA processing genome-wide. Genome Research. 22(8). 1426–1436. 82 indexed citations
13.
Hon, Gary C., R. David Hawkins, Otávia L. Caballero, et al.. (2011). Global DNA hypomethylation coupled to repressive chromatin domain formation and gene silencing in breast cancer. Genome Research. 22(2). 246–258. 410 indexed citations
14.
Hawkins, R. David, Gary C. Hon, Chuhu Yang, et al.. (2011). Dynamic chromatin states in human ES cells reveal potential regulatory sequences and genes involved in pluripotency. Cell Research. 21(10). 1393–1409. 72 indexed citations
15.
Hawkins, R. David, Gary C. Hon, & Bing Ren. (2010). Next-generation genomics: an integrative approach. Nature Reviews Genetics. 11(7). 476–486. 425 indexed citations
16.
Hon, Gary C., R. David Hawkins, & Bin Ren. (2009). Predictive chromatin signatures in the mammalian genome. Human Molecular Genetics. 18(R2). R195–R201. 158 indexed citations
17.
Lister, Ryan, Mattia Pelizzola, Robert H. Dowen, et al.. (2009). Human DNA methylomes at base resolution show widespread epigenomic differences. Nature. 462(7271). 315–322. 3371 indexed citations breakdown →
18.
Hon, Gary C., Bing Ren, & Wei Wang. (2008). ChromaSig: A Probabilistic Approach to Finding Common Chromatin Signatures in the Human Genome. PLoS Computational Biology. 4(10). e1000201–e1000201. 112 indexed citations
19.
Heintzman, Nathaniel D., Rhona Stuart, Gary C. Hon, et al.. (2007). Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome. Nature Genetics. 39(3). 311–318. 2463 indexed citations breakdown →
20.
Reguly, Teresa, Ashton Breitkreutz, Lorrie Boucher, et al.. (2006). Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae. Journal of Biology. 5(4). 11–11. 235 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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