Peter J. Roy

3.5k total citations
51 papers, 2.4k citations indexed

About

Peter J. Roy is a scholar working on Aging, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Peter J. Roy has authored 51 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Aging, 22 papers in Molecular Biology and 9 papers in Cellular and Molecular Neuroscience. Recurrent topics in Peter J. Roy's work include Genetics, Aging, and Longevity in Model Organisms (36 papers), Axon Guidance and Neuronal Signaling (8 papers) and Circadian rhythm and melatonin (7 papers). Peter J. Roy is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (36 papers), Axon Guidance and Neuronal Signaling (8 papers) and Circadian rhythm and melatonin (7 papers). Peter J. Roy collaborates with scholars based in Canada, United States and Germany. Peter J. Roy's co-authors include Joshua M. Stuart, Jim Lund, Stuart K. Kim, Joseph G. Culotti, Andrew R. Burns, Scott J. Dixon, Sean R. Cutler, Sandra E. Black, Anthony Feinstein and Nancy J. Lobaugh and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Peter J. Roy

49 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter J. Roy Canada 24 1.1k 1.0k 352 273 203 51 2.4k
Julián Cerón Spain 19 1.2k 1.1× 962 0.9× 200 0.6× 213 0.8× 33 0.2× 41 1.9k
Alvaro Sagasti United States 28 974 0.9× 737 0.7× 1.0k 2.9× 505 1.8× 53 0.3× 48 2.7k
Linda Lee United States 25 1.7k 1.6× 1.2k 1.2× 155 0.4× 455 1.7× 55 0.3× 42 3.2k
Weiwei Zhong United States 25 908 0.8× 405 0.4× 245 0.7× 126 0.5× 35 0.2× 77 1.9k
Noelle D. Dwyer United States 18 1.8k 1.6× 559 0.5× 618 1.8× 333 1.2× 55 0.3× 24 2.9k
Dong Yan China 26 3.6k 3.2× 2.4k 2.3× 503 1.4× 487 1.8× 84 0.4× 73 5.1k
Carl D. Johnson United States 20 973 0.9× 853 0.8× 491 1.4× 326 1.2× 22 0.1× 23 2.4k
Michael A. Costa United States 24 2.2k 2.0× 803 0.8× 214 0.6× 338 1.2× 39 0.2× 41 3.3k
Kim D. Finley United States 27 1.4k 1.3× 301 0.3× 427 1.2× 119 0.4× 70 0.3× 42 3.2k

Countries citing papers authored by Peter J. Roy

Since Specialization
Citations

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

Fields of papers citing papers by Peter J. Roy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter J. Roy

This figure shows the co-authorship network connecting the top 25 collaborators of Peter J. Roy. A scholar is included among the top collaborators of Peter J. Roy 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 Peter J. Roy. Peter J. Roy 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.
Roy, Peter J., et al.. (2025). Line-scan imaging for real-time phenotypic screening of C. elegans. Review of Scientific Instruments. 96(6). 1 indexed citations
2.
Roy, Peter J.. (2025). Drug screens using the nematode Caenorhabditis elegans. Genetics. 231(1).
3.
Burns, Andrew R., Emily Puumala, Jamie Snider, et al.. (2024). Cyprocide selectively kills nematodes via cytochrome P450 bioactivation. Nature Communications. 15(1). 5529–5529. 6 indexed citations
4.
Harrington, Sean, Andrew R. Burns, Lucien Rufener, et al.. (2023). Nemacol is a small molecule inhibitor of C. elegans vesicular acetylcholine transporter with anthelmintic potential. Nature Communications. 14(1). 1816–1816. 11 indexed citations
5.
Magomedova, Lilia, Ken C. Q. Nguyen, Hong Zheng, et al.. (2023). PGP-14 establishes a polar lipid permeability barrier within the C. elegans pharyngeal cuticle. PLoS Genetics. 19(11). e1011008–e1011008. 4 indexed citations
6.
Mastrangelo, Peter, Hao Cai, Michael P. Hughes, et al.. (2022). A spatiotemporal reconstruction of the C. elegans pharyngeal cuticle reveals a structure rich in phase-separating proteins. eLife. 11. 13 indexed citations
7.
Roy, Peter J., et al.. (2022). Culturing and Screening the Plant Parasitic Nematode <em>Ditylenchus dipsaci</em>. Journal of Visualized Experiments. 1 indexed citations
8.
Joly, Nicolas, Edmond M. Linossi, Natalia Jura, et al.. (2021). A survey of the kinome pharmacopeia reveals multiple scaffolds and targets for the development of novel anthelmintics. Scientific Reports. 11(1). 9161–9161. 9 indexed citations
9.
Volpatti, Jonathan, Yukari Endo, Linda Groom, et al.. (2020). Identification of drug modifiers for RYR1-related myopathy using a multi-species discovery pipeline. eLife. 9. 18 indexed citations
10.
Rimann, Ivo, et al.. (2012). The Caenorhabditis elegans homolog of the Opitz syndrome gene, madd-2/Mid1, regulates anchor cell invasion during vulval development. Developmental Biology. 374(1). 108–114. 8 indexed citations
11.
Tharmalingam, Sujeenthar, Andrew R. Burns, Peter J. Roy, & David R. Hampson. (2012). Orthosteric and allosteric drug binding sites in the Caenorhabditis elegans mgl-2 metabotropic glutamate receptor. Neuropharmacology. 63(4). 667–674. 14 indexed citations
12.
Seetharaman, Ashwin, et al.. (2011). MADD-4 Is a Secreted Cue Required for Midline-Oriented Guidance in Caenorhabditis elegans. Developmental Cell. 21(4). 669–680. 39 indexed citations
13.
Burns, Andrew R., Iain M. Wallace, Jan Wildenhain, et al.. (2010). A predictive model for drug bioaccumulation and bioactivity in Caenorhabditis elegans. Nature Chemical Biology. 6(7). 549–557. 141 indexed citations
14.
Alexander, Mariam, Alexandra B. Byrne, Guillermo Selman, et al.. (2009). An UNC-40 pathway directs postsynaptic membrane extension in Caenorhabditis elegans. Development. 136(6). 911–922. 36 indexed citations
15.
Arnoldo, Anthony, Jasna Ćurak, Saranya Kittanakom, et al.. (2008). Identification of Small Molecule Inhibitors of Pseudomonas aeruginosa Exoenzyme S Using a Yeast Phenotypic Screen. PLoS Genetics. 4(2). e1000005–e1000005. 88 indexed citations
16.
Hui, Kwokyin, et al.. (2008). Differential sensitivities of CaV1.2 IIS5–S6 mutants to 1,4-dihydropyridine analogs. European Journal of Pharmacology. 602(2-3). 255–261. 8 indexed citations
17.
Hui, Kwokyin, et al.. (2008). A Genetic Screen for Dihydropyridine (DHP)-Resistant Worms Reveals New Residues Required for DHP-Blockage of Mammalian Calcium Channels. PLoS Genetics. 4(5). e1000067–e1000067. 23 indexed citations
18.
Dixon, Scott J. & Peter J. Roy. (2005). Muscle arm development in Caenorhabditis elegans. Development. 132(13). 3079–3092. 58 indexed citations
19.
Roy, Peter J. & Quaid Morris. (2005). Network News: Functional Modules Revealed during Early Embryogenesis in C. elegans. Developmental Cell. 9(3). 307–308. 2 indexed citations
20.
Dade, Lauren A., Fu‐Qiang Gao, Nataša Žunić Kovačević, et al.. (2004). Semiautomatic brain region extraction: a method of parcellating brain regions from structural magnetic resonance images. NeuroImage. 22(4). 1492–1502. 81 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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