Jonathan I. Gent

4.7k total citations
33 papers, 1.6k citations indexed

About

Jonathan I. Gent is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, Jonathan I. Gent has authored 33 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Plant Science, 18 papers in Molecular Biology and 5 papers in Genetics. Recurrent topics in Jonathan I. Gent's work include Chromosomal and Genetic Variations (25 papers), Plant Molecular Biology Research (11 papers) and CRISPR and Genetic Engineering (8 papers). Jonathan I. Gent is often cited by papers focused on Chromosomal and Genetic Variations (25 papers), Plant Molecular Biology Research (11 papers) and CRISPR and Genetic Engineering (8 papers). Jonathan I. Gent collaborates with scholars based in United States, Netherlands and Germany. Jonathan I. Gent's co-authors include R. Kelly Dawe, Na Wang, Nathanael A. Ellis, Lin Guo, Alex Harkess, Andrew Fire, Xiaoyu Zhang, Yingyin Yao, Nathan M. Springer and Karen McGinnis and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Jonathan I. Gent

32 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan I. Gent United States 21 1.3k 1.0k 271 141 55 33 1.6k
Jonathan C. Lamb United States 23 1.7k 1.3× 1.1k 1.1× 342 1.3× 35 0.2× 8 0.1× 27 2.0k
Wojciech P. Pawlowski United States 26 1.5k 1.1× 1.5k 1.4× 258 1.0× 18 0.1× 17 0.3× 45 1.9k
Michael F. Portereiko United States 8 832 0.6× 871 0.8× 60 0.2× 112 0.8× 13 0.2× 8 1.1k
Qun Hu China 13 295 0.2× 513 0.5× 80 0.3× 43 0.3× 75 1.4× 27 743
K L Traverse United States 17 898 0.7× 1.1k 1.0× 117 0.4× 86 0.6× 28 0.5× 19 1.3k
Minhee Jung South Korea 7 495 0.4× 971 0.9× 121 0.4× 60 0.4× 5 0.1× 10 1.1k
Simon Schiml Germany 9 947 0.7× 1.2k 1.2× 87 0.3× 57 0.4× 4 0.1× 9 1.3k
Yanjun He China 17 881 0.7× 734 0.7× 48 0.2× 16 0.1× 24 0.4× 26 1.1k
Célia Payen United States 13 294 0.2× 710 0.7× 261 1.0× 11 0.1× 41 0.7× 18 849

Countries citing papers authored by Jonathan I. Gent

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan I. Gent

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan I. Gent. 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 Jonathan I. Gent. The network helps show where Jonathan I. Gent may publish in the future.

Co-authorship network of co-authors of Jonathan I. Gent

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan I. Gent. A scholar is included among the top collaborators of Jonathan I. Gent 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 Jonathan I. Gent. Jonathan I. Gent 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.
2.
Gent, Jonathan I., et al.. (2025). Conflicting Kinesin-14s in a single chromosomal drive haplotype. Genetics. 230(3). 1 indexed citations
3.
Bader, Rechien, et al.. (2024). RNA-directed DNA methylation mutants reduce histone methylation at the paramutated maize booster1 enhancer. PLANT PHYSIOLOGY. 195(2). 1161–1179. 4 indexed citations
4.
Gent, Jonathan I., et al.. (2024). The maize striate leaves2 (sr2) gene encodes a conserved DUF3732 domain and is homologous to the rice yss1 gene. Plant Direct. 8(2). e567–e567. 2 indexed citations
5.
Zeng, Yibing, R. Kelly Dawe, & Jonathan I. Gent. (2023). Natural methylation epialleles correlate with gene expression in maize. Genetics. 225(2). 3 indexed citations
6.
Gent, Jonathan I., Kyle W Swentowsky, Fangfang Fu, et al.. (2022). The maize gene maternal derepression of r1 encodes a DNA glycosylase that demethylates DNA and reduces siRNA expression in the endosperm. The Plant Cell. 34(10). 3685–3701. 19 indexed citations
7.
Wang, Na, Jianing Liu, William A. Ricci, Jonathan I. Gent, & R. Kelly Dawe. (2021). Maize centromeric chromatin scales with changes in genome size. Genetics. 217(4). 14 indexed citations
8.
Li, Chenxin, et al.. (2021). Resetting of the 24-nt siRNA landscape in rice zygotes. Genome Research. 32(2). 309–323. 14 indexed citations
9.
Liu, Jianing, Arun S. Seetharam, Kapeel Chougule, et al.. (2020). Gapless assembly of maize chromosomes using long-read technologies. Genome biology. 21(1). 121–121. 83 indexed citations
10.
Swentowsky, Kyle W, Jonathan I. Gent, Veit Schubert, et al.. (2020). Distinct kinesin motors drive two types of maize neocentromeres. Genes & Development. 34(17-18). 1239–1251. 27 indexed citations
11.
Li, Chenxin, et al.. (2020). Genome-wide redistribution of 24-nt siRNAs in rice gametes. Genome Research. 30(2). 173–184. 25 indexed citations
12.
Dawe, R. Kelly, Jonathan I. Gent, Michelle C. Stitzer, et al.. (2018). A Kinesin-14 Motor Activates Neocentromeres to Promote Meiotic Drive in Maize. Cell. 173(4). 839–850.e18. 82 indexed citations
13.
Gent, Jonathan I., Na Wang, & R. Kelly Dawe. (2017). Stable centromere positioning in diverse sequence contexts of complex and satellite centromeres of maize and wild relatives. Genome biology. 18(1). 121–121. 43 indexed citations
14.
Oka, Rurika, Johan Zicola, Sarah N. Anderson, et al.. (2017). Genome-wide mapping of transcriptional enhancer candidates using DNA and chromatin features in maize. Genome biology. 18(1). 137–137. 122 indexed citations
15.
Li, Qing, Jonathan I. Gent, Greg Zynda, et al.. (2015). RNA-directed DNA methylation enforces boundaries between heterochromatin and euchromatin in the maize genome. Proceedings of the National Academy of Sciences. 112(47). 14728–14733. 161 indexed citations
16.
Gent, Jonathan I., Nathanael A. Ellis, Lin Guo, et al.. (2012). CHH islands: de novo DNA methylation in near-gene chromatin regulation in maize. Genome Research. 23(4). 628–637. 243 indexed citations
17.
Parameswaran, Poornima, et al.. (2011). On the nature of in vivo requirements forrde-4in RNAi and developmental pathways inC. elegans. RNA Biology. 8(3). 458–467. 21 indexed citations
18.
Gent, Jonathan I., Yuzhu Dong, Jiming Jiang, & R. Kelly Dawe. (2011). Strong epigenetic similarity between maize centromeric and pericentromeric regions at the level of small RNAs, DNA methylation and H3 chromatin modifications. Nucleic Acids Research. 40(4). 1550–1560. 39 indexed citations
19.
Gent, Jonathan I., Ayelet T. Lamm, Derek M. Pavelec, et al.. (2010). Distinct Phases of siRNA Synthesis in an Endogenous RNAi Pathway in C. elegans Soma. Molecular Cell. 37(5). 679–689. 156 indexed citations
20.
Lamm, Ayelet T., Michael Stadler, Huibin Zhang, Jonathan I. Gent, & Andrew Fire. (2010). Multimodal RNA-seq using single-strand, double-strand, and CircLigase-based capture yields a refined and extended description of the C. elegans transcriptome. Genome Research. 21(2). 265–275. 34 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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