Simon J. Newkirk

429 total citations
10 papers, 278 citations indexed

About

Simon J. Newkirk is a scholar working on Molecular Biology, Plant Science and Epidemiology. According to data from OpenAlex, Simon J. Newkirk has authored 10 papers receiving a total of 278 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 7 papers in Plant Science and 2 papers in Epidemiology. Recurrent topics in Simon J. Newkirk's work include Chromosomal and Genetic Variations (7 papers), CRISPR and Genetic Engineering (5 papers) and Influenza Virus Research Studies (2 papers). Simon J. Newkirk is often cited by papers focused on Chromosomal and Genetic Variations (7 papers), CRISPR and Genetic Engineering (5 papers) and Influenza Virus Research Studies (2 papers). Simon J. Newkirk collaborates with scholars based in United States, Germany and China. Simon J. Newkirk's co-authors include Wenfeng An, Suman Lee, James M. Rosser, Fiorella C. Grandi, Michael D. Griswold, Jef D. Boeke, Alysson R. Muotri, Valeriya Gaysinskaya, Ping Ye and Maria C. Marchetto and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Genetics.

In The Last Decade

Simon J. Newkirk

10 papers receiving 276 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Simon J. Newkirk United States	7	210	126	45	35	30	10	278
Niveen Mulholland United States	7	238 1.1×	24 0.2×	18 0.4×	25 0.7×	33 1.1×	9	325
Raymond Camahort United States	7	440 2.1×	305 2.4×	14 0.3×	45 1.3×	30 1.0×	7	510
Ki Young Paek South Korea	9	343 1.6×	30 0.2×	40 0.9×	30 0.9×	18 0.6×	10	435
Y. Q. Shirleen Soh United States	4	275 1.3×	22 0.2×	38 0.8×	25 0.7×	105 3.5×	4	367
Lorane Texari Switzerland	6	345 1.6×	76 0.6×	30 0.7×	49 1.4×	27 0.9×	7	396
Sophia Groh Germany	4	251 1.2×	74 0.6×	15 0.3×	32 0.9×	48 1.6×	4	279
James A. Dutko United States	7	259 1.2×	99 0.8×	51 1.1×	30 0.9×	18 0.6×	7	338
Liqing Geng China	6	344 1.6×	27 0.2×	33 0.7×	24 0.7×	29 1.0×	9	436
Michelle Wu United States	5	550 2.6×	157 1.2×	8 0.2×	10 0.3×	38 1.3×	10	594
Andreas Hoffmann Germany	3	165 0.8×	158 1.3×	17 0.4×	31 0.9×	28 0.9×	3	219

Countries citing papers authored by Simon J. Newkirk

Since Specialization

Citations

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

Fields of papers citing papers by Simon J. Newkirk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Simon J. Newkirk. 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 Simon J. Newkirk. The network helps show where Simon J. Newkirk may publish in the future.

Co-authorship network of co-authors of Simon J. Newkirk

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

All Works

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10 of 10 papers shown

Kong, Lingqi, Leanne S. Whitmore, Xijin Ge, et al.. (2022). Subfamily-specific differential contribution of individual monomers and the tether sequence to mouse L1 promoter activity. Mobile DNA. 13(1). 13–13. 6 indexed citations

Gu, Zhimin, Yuxuan Liu, Yuannyu Zhang, et al.. (2021). Silencing of LINE-1 retrotransposons is a selective dependency of myeloid leukemia. Nature Genetics. 53(5). 672–682. 60 indexed citations

Newkirk, Simon J., et al.. (2020). Subfamily-specific quantification of endogenous mouse L1 retrotransposons by droplet digital PCR. Analytical Biochemistry. 601. 113779–113779. 3 indexed citations

Liu, Runxia, Chithra Sreenivasan, Hai Yu, et al.. (2020). Influenza D virus diverges from its related influenza C virus in the recognition of 9-O-acetylated N-acetyl- or N-glycolyl-neuraminic acid-containing glycan receptors. Virology. 545. 16–23. 27 indexed citations

Newkirk, Simon J. & Wenfeng An. (2020). UHRF1: a jack of all trades, and a master epigenetic regulator during spermatogenesis. Biology of Reproduction. 102(6). 1147–1152. 3 indexed citations

Vázquez, Berta N., Joshua K. Thackray, Nicolás G. Simonet, et al.. (2019). SIRT7 mediates L1 elements transcriptional repression and their association with the nuclear lamina. Nucleic Acids Research. 47(15). 7870–7885. 57 indexed citations

Wang, Zhuqing, Simon J. Newkirk, Daniel Oliver, et al.. (2019). Insertion of a chimeric retrotransposon sequence in mouse Axin1 locus causes metastable kinky tail phenotype. Mobile DNA. 10(1). 17–17. 8 indexed citations

Sheng, Zizhang, Runxia Liu, Jieshi Yu, et al.. (2018). Identification and characterization of viral defective RNA genomes in influenza B virus. Journal of General Virology. 99(4). 475–488. 12 indexed citations

Newkirk, Simon J., Suman Lee, Fiorella C. Grandi, et al.. (2017). Intact piRNA pathway prevents L1 mobilization in male meiosis. Proceedings of the National Academy of Sciences. 114(28). E5635–E5644. 68 indexed citations

10.

Grandi, Fiorella C., James M. Rosser, Simon J. Newkirk, et al.. (2015). Retrotransposition creates sloping shores: a graded influence of hypomethylated CpG islands on flanking CpG sites. Genome Research. 25(8). 1135–1146. 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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