Jayme Salsman

2.6k total citations
36 papers, 1.6k citations indexed

About

Jayme Salsman is a scholar working on Molecular Biology, Genetics and Cell Biology. According to data from OpenAlex, Jayme Salsman has authored 36 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 9 papers in Genetics and 6 papers in Cell Biology. Recurrent topics in Jayme Salsman's work include Virus-based gene therapy research (9 papers), CRISPR and Genetic Engineering (8 papers) and Retinoids in leukemia and cellular processes (6 papers). Jayme Salsman is often cited by papers focused on Virus-based gene therapy research (9 papers), CRISPR and Genetic Engineering (8 papers) and Retinoids in leukemia and cellular processes (6 papers). Jayme Salsman collaborates with scholars based in Canada, United States and China. Jayme Salsman's co-authors include Graham Dellaire, Roy Duncan, Jordan Pinder, David W. Hoskin, Jamie S. Mader, David Conrad, Deniz Top, Lori Frappier, Jennifer A. Corcoran and Roberto de Antueno and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Genes & Development.

In The Last Decade

Jayme Salsman

36 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jayme Salsman Canada 20 1.1k 349 216 197 191 36 1.6k
Yuji Hidaka Japan 26 1.1k 1.1× 300 0.9× 311 1.4× 223 1.1× 147 0.8× 79 1.8k
Hervé Le Moual Canada 23 1.0k 1.0× 598 1.7× 111 0.5× 188 1.0× 122 0.6× 36 2.1k
Tomoe Kitao Japan 23 1.1k 1.0× 225 0.6× 147 0.7× 145 0.7× 175 0.9× 38 1.7k
Wouter C. Puijk Netherlands 22 960 0.9× 271 0.8× 162 0.8× 252 1.3× 185 1.0× 45 1.7k
Na Dong China 21 1.0k 0.9× 277 0.8× 133 0.6× 307 1.6× 156 0.8× 56 1.8k
Yoshio Yamakawa Japan 26 1.3k 1.2× 324 0.9× 226 1.0× 323 1.6× 363 1.9× 91 2.3k
Zhao Bao United States 6 883 0.8× 318 0.9× 93 0.4× 285 1.4× 117 0.6× 6 1.6k
Mauricio R. Terebiznik Canada 24 880 0.8× 129 0.4× 261 1.2× 461 2.3× 116 0.6× 45 2.0k
Ian E. Gentle Germany 19 1.6k 1.5× 232 0.7× 272 1.3× 712 3.6× 147 0.8× 33 2.1k
S.D. Weeks Belgium 23 1.4k 1.3× 177 0.5× 94 0.4× 144 0.7× 118 0.6× 47 1.7k

Countries citing papers authored by Jayme Salsman

Since Specialization
Citations

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

Fields of papers citing papers by Jayme Salsman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jayme Salsman. 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 Jayme Salsman. The network helps show where Jayme Salsman may publish in the future.

Co-authorship network of co-authors of Jayme Salsman

This figure shows the co-authorship network connecting the top 25 collaborators of Jayme Salsman. A scholar is included among the top collaborators of Jayme Salsman 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 Jayme Salsman. Jayme Salsman 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.
Salsman, Jayme, et al.. (2024). Nuclear lipid droplets in Caco2 cells originate from nascent precursors and in situ at the nuclear envelope. Journal of Lipid Research. 65(5). 100540–100540. 2 indexed citations
2.
Xu, Meng, Xiaoyang Yu, Anne R. Wondisford, et al.. (2024). SUMO promotes DNA repair protein collaboration to support alternative telomere lengthening in the absence of PML. Genes & Development. 38(13-14). 614–630. 4 indexed citations
3.
Boisvert, François‐Michel, et al.. (2024). The proximity interactome of PML isoforms I and II under fatty acid stress. FEBS Letters. 599(5). 682–699. 2 indexed citations
4.
Mathavarajah, Sabateeshan, Jayme Salsman, Stéphane Roy, et al.. (2023). PML and PML-like exonucleases restrict retrotransposons in jawed vertebrates. Nucleic Acids Research. 51(7). 3185–3204. 10 indexed citations
5.
Salsman, Jayme, et al.. (2022). Running ‘LAPS’ Around nLD: Nuclear Lipid Droplet Form and Function. Frontiers in Cell and Developmental Biology. 10. 837406–837406. 15 indexed citations
6.
Martínez-Pastor, Bárbara, Giórgia Gobbi da Silveira, Thomas L. Clarke, et al.. (2021). Assessing kinetics and recruitment of DNA repair factors using high content screens. Cell Reports. 37(13). 110176–110176. 13 indexed citations
7.
Lee, Jong‐Hwa, et al.. (2020). Lipid-associated PML structures assemble nuclear lipid droplets containing CCTα and Lipin1. Life Science Alliance. 3(8). e202000751–e202000751. 34 indexed citations
8.
Mathavarajah, Sabateeshan, Jayme Salsman, & Graham Dellaire. (2019). An emerging role for calcium signalling in innate and autoimmunity via the cGAS-STING axis. Cytokine & Growth Factor Reviews. 50. 43–51. 40 indexed citations
9.
Nachtigal, Mark W., et al.. (2018). Bitter taste receptors are expressed in human epithelial ovarian and prostate cancers cells and noscapine stimulation impacts cell survival. Molecular and Cellular Biochemistry. 454(1-2). 203–214. 51 indexed citations
10.
Agudelo, Daniel, Lusiné Bozoyan, Caroline Huard, et al.. (2017). Marker-free coselection for CRISPR-driven genome editing in human cells. Nature Methods. 14(6). 615–620. 110 indexed citations
11.
Salsman, Jayme, et al.. (2017). Myogenic differentiation triggers PML nuclear body loss and DAXX relocalization to chromocentres. Cell Death and Disease. 8(3). e2724–e2724. 16 indexed citations
12.
Salsman, Jayme, Daniel Gaston, Kimberly R. Kukurba, et al.. (2017). PML nuclear bodies contribute to the basal expression of the mTOR inhibitor DDIT4. Scientific Reports. 7(1). 45038–45038. 17 indexed citations
13.
Corkery, Dale, Simon Gebremeskel, Jayme Salsman, et al.. (2017). Loss of PRP4K drives anoikis resistance in part by dysregulation of epidermal growth factor receptor endosomal trafficking. Oncogene. 37(2). 174–184. 21 indexed citations
14.
Salsman, Jayme & Graham Dellaire. (2016). Precision genome editing in the CRISPR era. Biochemistry and Cell Biology. 95(2). 187–201. 115 indexed citations
15.
Pinder, Jordan, Jayme Salsman, & Graham Dellaire. (2015). Nuclear domain ‘knock-in’ screen for the evaluation and identification of small molecule enhancers of CRISPR-based genome editing. Nucleic Acids Research. 43(19). 9379–9392. 212 indexed citations
16.
Salsman, Jayme, Xueqi Wang, & Lori Frappier. (2011). Nuclear body formation and PML body remodeling by the human cytomegalovirus protein UL35. Virology. 414(2). 119–129. 23 indexed citations
17.
Salsman, Jayme, Deniz Top, Christopher Barry, & Roy Duncan. (2008). A Virus-Encoded Cell–Cell Fusion Machine Dependent on Surrogate Adhesins. PLoS Pathogens. 4(3). e1000016–e1000016. 42 indexed citations
18.
Salsman, Jayme, et al.. (2008). Genome-Wide Screen of Three Herpesviruses for Protein Subcellular Localization and Alteration of PML Nuclear Bodies. PLoS Pathogens. 4(7). e1000100–e1000100. 88 indexed citations
19.
Mader, Jamie S., Angela M. Richardson, Jayme Salsman, et al.. (2007). Bovine lactoferricin causes apoptosis in Jurkat T-leukemia cells by sequential permeabilization of the cell membrane and targeting of mitochondria. Experimental Cell Research. 313(12). 2634–2650. 89 indexed citations
20.
Top, Deniz, Roberto de Antueno, Jayme Salsman, et al.. (2005). Liposome reconstitution of a minimal protein‐mediated membrane fusion machine. The EMBO Journal. 24(17). 2980–2988. 48 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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