Jay Z. Parrish

3.0k total citations
36 papers, 2.2k citations indexed

About

Jay Z. Parrish is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Immunology. According to data from OpenAlex, Jay Z. Parrish has authored 36 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cellular and Molecular Neuroscience, 19 papers in Molecular Biology and 10 papers in Immunology. Recurrent topics in Jay Z. Parrish's work include Neurobiology and Insect Physiology Research (19 papers), Invertebrate Immune Response Mechanisms (8 papers) and DNA Repair Mechanisms (5 papers). Jay Z. Parrish is often cited by papers focused on Neurobiology and Insect Physiology Research (19 papers), Invertebrate Immune Response Mechanisms (8 papers) and DNA Repair Mechanisms (5 papers). Jay Z. Parrish collaborates with scholars based in United States, Germany and Japan. Jay Z. Parrish's co-authors include Yuh Nung Jan, Ding Xue, Lily Yeh Jan, Kazuo Emoto, Michael D. Kim, Charles C. Kim, Claire Williams, Xiaodong Wang, Lily Li and Alyssa Baccarella and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Neuron.

In The Last Decade

Jay Z. Parrish

34 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jay Z. Parrish United States 24 1.4k 648 405 234 207 36 2.2k
Juan R. Riesgo‐Escovar Mexico 24 1.5k 1.1× 867 1.3× 510 1.3× 383 1.6× 245 1.2× 48 2.5k
Fillip Port Germany 16 1.8k 1.3× 428 0.7× 564 1.4× 207 0.9× 270 1.3× 23 2.3k
Jian‐Quan Ni China 23 1.5k 1.1× 354 0.5× 235 0.6× 201 0.9× 273 1.3× 44 1.9k
Matthew A. Booker United States 14 1.4k 1.0× 448 0.7× 259 0.6× 254 1.1× 281 1.4× 17 2.0k
James E. Wilhelm United States 21 2.3k 1.7× 267 0.4× 525 1.3× 161 0.7× 247 1.2× 33 2.7k
Michaela Fellner Austria 10 1.9k 1.4× 1.1k 1.7× 525 1.3× 416 1.8× 401 1.9× 16 2.8k
Michele Markstein United States 12 1.5k 1.1× 571 0.9× 220 0.5× 342 1.5× 359 1.7× 16 2.0k
Michael Hoch Germany 32 2.5k 1.8× 646 1.0× 601 1.5× 465 2.0× 360 1.7× 66 3.4k
Andrea Daga Italy 21 1.5k 1.0× 710 1.1× 741 1.8× 131 0.6× 154 0.7× 30 2.3k
Kuan-Chung Su United States 10 1.6k 1.2× 1.0k 1.6× 712 1.8× 369 1.6× 369 1.8× 14 2.6k

Countries citing papers authored by Jay Z. Parrish

Since Specialization
Citations

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

Fields of papers citing papers by Jay Z. Parrish

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay Z. Parrish. 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 Jay Z. Parrish. The network helps show where Jay Z. Parrish may publish in the future.

Co-authorship network of co-authors of Jay Z. Parrish

This figure shows the co-authorship network connecting the top 25 collaborators of Jay Z. Parrish. A scholar is included among the top collaborators of Jay Z. Parrish 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 Jay Z. Parrish. Jay Z. Parrish 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.
Mali, Sonali S., Claire Williams, Takeshi Morita, et al.. (2024). Drosophila epidermal cells are intrinsically mechanosensitive and modulate nociceptive behavioral outputs. eLife. 13.
2.
Morita, Takeshi, et al.. (2024). A cell atlas of the larval Aedes aegypti ventral nerve cord. Neural Development. 19(1). 2–2. 1 indexed citations
3.
Rasmussen, Jeffrey P., et al.. (2021). Transparent Touch: Insights From Model Systems on Epidermal Control of Somatosensory Innervation. Frontiers in Cellular Neuroscience. 15. 680345–680345. 7 indexed citations
4.
Hu, Chun, Alexandros K. Kanellopoulos, Melanie Richter, et al.. (2020). Conserved Tao Kinase Activity Regulates Dendritic Arborization, Cytoskeletal Dynamics, and Sensory Function inDrosophila. Journal of Neuroscience. 40(9). 1819–1833. 14 indexed citations
5.
Hasegawa, Eri, Kazuya Togashi, M. Tsuji, et al.. (2020). Drosophila miR-87 promotes dendrite regeneration by targeting the transcriptional repressor Tramtrack69. PLoS Genetics. 16(8). e1008942–e1008942. 19 indexed citations
6.
Coombes, Courtney, Dena M. Johnson-Schlitz, Mark McClellan, et al.. (2020). Non-enzymatic Activity of the α-Tubulin Acetyltransferase αTAT Limits Synaptic Bouton Growth in Neurons. Current Biology. 30(4). 610–623.e5. 3 indexed citations
7.
Vinauger, Clément, Chloé Lahondère, Gabriella H. Wolff, et al.. (2018). Modulation of Host Learning in Aedes aegypti Mosquitoes. Current Biology. 28(3). 333–344.e8. 63 indexed citations
8.
Jiang, Nan, Tyler J. Chozinski, Jorge Azpurua, et al.. (2018). Superresolution imaging of Drosophila tissues using expansion microscopy. Molecular Biology of the Cell. 29(12). 1413–1421. 40 indexed citations
9.
Hu, Chun, Meike Petersen, Kathrin Sauter, et al.. (2018). Ret and Substrate-Derived TGF-β Maverick Regulate Space-Filling Dendrite Growth in Drosophila Sensory Neurons. Cell Reports. 24(9). 2261–2272.e5. 14 indexed citations
10.
Williams, Claire, Alyssa Baccarella, Jay Z. Parrish, & Charles C. Kim. (2017). Empirical assessment of analysis workflows for differential expression analysis of human samples using RNA-Seq. BMC Bioinformatics. 18(1). 38–38. 50 indexed citations
11.
Meltzer, Shan, Smita Yadav, Peter Soba, et al.. (2016). Epidermis-Derived Semaphorin Promotes Dendrite Self-Avoidance by Regulating Dendrite-Substrate Adhesion in Drosophila Sensory Neurons. Neuron. 89(4). 741–755. 40 indexed citations
12.
Williams, Claire, Alyssa Baccarella, Jay Z. Parrish, & Charles C. Kim. (2016). Trimming of sequence reads alters RNA-Seq gene expression estimates. BMC Bioinformatics. 17(1). 103–103. 112 indexed citations
13.
Williams, Claire, et al.. (2015). Functions of the SLC36 transporter Pathetic in growth control. Fly. 9(3). 99–106. 6 indexed citations
14.
Parrish, Jay Z., et al.. (2011). Nmnat exerts neuroprotective effects in dendrites and axons. Molecular and Cellular Neuroscience. 48(1). 1–8. 40 indexed citations
15.
Parrish, Jay Z., Peizhang Xu, Charles C. Kim, Lily Yeh Jan, & Yuh Nung Jan. (2009). The microRNA bantam Functions in Epithelial Cells to Regulate Scaling Growth of Dendrite Arbors in Drosophila Sensory Neurons. Neuron. 63(6). 788–802. 135 indexed citations
16.
Parrish, Jay Z. & Ding Xue. (2006). Cuts can kill: the roles of apoptotic nucleases in cell death and animal development. Chromosoma. 115(2). 89–97. 39 indexed citations
17.
Emoto, Kazuo, Jay Z. Parrish, Lily Yeh Jan, & Yuh Nung Jan. (2006). The tumour suppressor Hippo acts with the NDR kinases in dendritic tiling and maintenance. Nature. 443(7108). 210–213. 160 indexed citations
18.
Parrish, Jay Z. & Ding Xue. (2003). Functional Genomic Analysis of Apoptotic DNA Degradation in C. elegans. Molecular Cell. 11(4). 987–996. 111 indexed citations
19.
Parrish, Jay Z.. (2003). CRN-1, a Caenorhabditis elegans FEN-1 homologue, cooperates with CPS-6/EndoG to promote apoptotic DNA degradation. The EMBO Journal. 22(13). 3451–3460. 107 indexed citations
20.
Parrish, Jay Z., et al.. (2001). Mitochondrial endonuclease G is important for apoptosis in C. elegans. Nature. 412(6842). 90–94. 333 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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