Ethan Perlstein

2.4k total citations
27 papers, 1.7k citations indexed

About

Ethan Perlstein is a scholar working on Molecular Biology, Genetics and Physiology. According to data from OpenAlex, Ethan Perlstein has authored 27 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 7 papers in Genetics and 5 papers in Physiology. Recurrent topics in Ethan Perlstein's work include Fungal and yeast genetics research (7 papers), Glycosylation and Glycoproteins Research (5 papers) and Bioinformatics and Genomic Networks (5 papers). Ethan Perlstein is often cited by papers focused on Fungal and yeast genetics research (7 papers), Glycosylation and Glycoproteins Research (5 papers) and Bioinformatics and Genomic Networks (5 papers). Ethan Perlstein collaborates with scholars based in United States, Hungary and United Kingdom. Ethan Perlstein's co-authors include Stuart L. Schreiber, David C. Rubinsztein, Sovan Sarkar, Chih Long Liu, B Bernstein, Satoshi Nagayama, Christopher S. Neumann, Michael M.‐C. Lo, Sara Imarisio and John Webster and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Neuron.

In The Last Decade

Ethan Perlstein

27 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ethan Perlstein United States 15 992 439 277 197 163 27 1.7k
Lihao Meng United States 10 1.3k 1.3× 176 0.4× 184 0.7× 203 1.0× 236 1.4× 12 1.7k
Peter Chase United States 24 1.2k 1.2× 166 0.4× 224 0.8× 280 1.4× 214 1.3× 68 2.0k
Brett Marshall United States 10 1.2k 1.2× 625 1.4× 130 0.5× 180 0.9× 110 0.7× 11 2.2k
Daniel Peisach United States 13 688 0.7× 279 0.6× 98 0.4× 361 1.8× 87 0.5× 15 1.2k
Kwan Yong Choi South Korea 23 1.0k 1.0× 212 0.5× 84 0.3× 161 0.8× 73 0.4× 56 1.8k
Dale D. O. Martin Canada 20 1.1k 1.1× 263 0.6× 96 0.3× 370 1.9× 364 2.2× 36 1.7k
Ewan M. Smith United Kingdom 15 1.3k 1.3× 131 0.3× 160 0.6× 374 1.9× 80 0.5× 16 1.6k
André S. Bachmann United States 28 1.9k 1.9× 106 0.2× 143 0.5× 440 2.2× 167 1.0× 82 2.4k
Ricardo Aparício Brazil 20 738 0.7× 160 0.4× 85 0.3× 98 0.5× 72 0.4× 61 1.3k
Junro Kuromitsu Japan 22 1.2k 1.2× 107 0.2× 134 0.5× 181 0.9× 113 0.7× 34 1.7k

Countries citing papers authored by Ethan Perlstein

Since Specialization
Citations

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

Fields of papers citing papers by Ethan Perlstein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ethan Perlstein

This figure shows the co-authorship network connecting the top 25 collaborators of Ethan Perlstein. A scholar is included among the top collaborators of Ethan Perlstein 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 Ethan Perlstein. Ethan Perlstein 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.
Kozicz, Tamás, et al.. (2025). The Therapeutic Future for Congenital Disorders of Glycosylation. Journal of Inherited Metabolic Disease. 48(2). e70011–e70011. 2 indexed citations
2.
Ranatunga, Wasantha, Graeme Preston, Ethan Perlstein, et al.. (2024). N-glycoproteomic and proteomic alterations in SRD5A3-deficient fibroblasts. Glycobiology. 34(11). 2 indexed citations
3.
Anreiter, Ina, Vera C. Mazurak, Joshua D. Mast, et al.. (2022). Glial control of sphingolipid levels sculpts diurnal remodeling in a circadian circuit. Neuron. 110(19). 3186–3205.e7. 24 indexed citations
4.
Allocca, Mariateresa, Maria Monticelli, Joy Norris, et al.. (2022). Evolutionary rescue of phosphomannomutase deficiency in yeast models of human disease. eLife. 11. 12 indexed citations
5.
Iyer, Sangeetha, Nina DiPrimio, Graeme Preston, et al.. (2019). Repurposing the aldose reductase inhibitor and diabetic neuropathy drug epalrestat for the congenital disorder of glycosylation PMM2-CDG. Disease Models & Mechanisms. 12(11). 44 indexed citations
6.
Lao, Jessica P., et al.. (2018). Yeast Models of Phosphomannomutase 2 Deficiency, a Congenital Disorder of Glycosylation. G3 Genes Genomes Genetics. 9(2). 413–423. 12 indexed citations
7.
Mast, Joshua D., et al.. (2018). Defects in the Neuroendocrine Axis Contribute to Global Development Delay in a Drosophila Model of NGLY1 Deficiency. G3 Genes Genomes Genetics. 8(7). 2193–2204. 23 indexed citations
8.
Ekins, Sean & Ethan Perlstein. (2018). Doing it All - How Families are Reshaping Rare Disease Research. Pharmaceutical Research. 35(10). 192–192. 6 indexed citations
9.
Perlstein, Ethan. (2013). Anatomy of the Crowd4Discovery crowdfunding campaign. SpringerPlus. 2(1). 560–560. 13 indexed citations
10.
Perlstein, Ethan, et al.. (2012). Accumulation of an Antidepressant in Vesiculogenic Membranes of Yeast Cells Triggers Autophagy. PLoS ONE. 7(4). e34024–e34024. 28 indexed citations
11.
Bivort, Benjamin de, Ethan Perlstein, Sam Kunes, & Stuart L. Schreiber. (2009). Amino Acid Metabolic Origin as an Evolutionary Influence on Protein Sequence in Yeast. Journal of Molecular Evolution. 68(5). 490–497. 12 indexed citations
12.
Ruderfer, Douglas M., David Roberts, Stuart L. Schreiber, Ethan Perlstein, & Leonid Kruglyak. (2009). Using Expression and Genotype to Predict Drug Response in Yeast. PLoS ONE. 4(9). e6907–e6907. 13 indexed citations
13.
Perlstein, Ethan, Douglas M. Ruderfer, David Roberts, Stuart L. Schreiber, & Leonid Kruglyak. (2007). Genetic basis of individual differences in the response to small-molecule drugs in yeast. Nature Genetics. 39(4). 496–502. 98 indexed citations
14.
15.
Sarkar, Sovan, Ethan Perlstein, Sara Imarisio, et al.. (2007). Small molecules enhance autophagy and reduce toxicity in Huntington's disease models. Nature Chemical Biology. 3(6). 331–338. 474 indexed citations
16.
Perlstein, Ethan, Benjamin de Bivort, Samuel Kunes, & Stuart L. Schreiber. (2007). Evolutionarily Conserved Optimization of Amino Acid Biosynthesis. Journal of Molecular Evolution. 65(2). 186–196. 12 indexed citations
17.
Butcher, Rebecca A., Bhupinder Bhullar, Ethan Perlstein, et al.. (2006). Microarray-based method for monitoring yeast overexpression strains reveals small-molecule targets in TOR pathway. Nature Chemical Biology. 2(2). 103–109. 77 indexed citations
18.
Perlstein, Ethan, et al.. (2006). Revealing Complex Traits with Small Molecules and Naturally Recombinant Yeast Strains. Chemistry & Biology. 13(3). 319–327. 31 indexed citations
19.
Bernstein, B, et al.. (2004). Global nucleosome occupancy in yeast. Genome biology. 5(9). R62–R62. 288 indexed citations
20.
Weidanz, Jon A., et al.. (1998). Display of functional αβ single-chain T-cell receptor molecules on the surface of bacteriophage. Journal of Immunological Methods. 221(1-2). 59–76. 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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