Matthew Y. Pecot

786 total citations
10 papers, 432 citations indexed

About

Matthew Y. Pecot is a scholar working on Cellular and Molecular Neuroscience, Cell Biology and Molecular Biology. According to data from OpenAlex, Matthew Y. Pecot has authored 10 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cellular and Molecular Neuroscience, 4 papers in Cell Biology and 3 papers in Molecular Biology. Recurrent topics in Matthew Y. Pecot's work include Neurobiology and Insect Physiology Research (8 papers), Axon Guidance and Neuronal Signaling (4 papers) and Cellular transport and secretion (3 papers). Matthew Y. Pecot is often cited by papers focused on Neurobiology and Insect Physiology Research (8 papers), Axon Guidance and Neuronal Signaling (4 papers) and Cellular transport and secretion (3 papers). Matthew Y. Pecot collaborates with scholars based in United States, Canada and Australia. Matthew Y. Pecot's co-authors include S Lawrence Zipursky, Aljoscha Nern, C. Kimberly Tsui, Orkun Akin, Yi Chen, Wael Tadros, Vivek Malhotra, Zhenqing Chen, Liming Tan and Yi Chen and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Neuron.

In The Last Decade

Matthew Y. Pecot

10 papers receiving 430 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew Y. Pecot United States	9	366	232	114	51	47	10	432
Shuwa Xu United States	10	301 0.8×	253 1.1×	111 1.0×	34 0.7×	34 0.7×	12	436
Diana Shy United States	9	332 0.9×	393 1.7×	79 0.7×	64 1.3×	37 0.8×	9	628
David Gorczyca United States	7	311 0.8×	245 1.1×	130 1.1×	59 1.2×	50 1.1×	7	524
Yukinori Hirano Japan	14	218 0.6×	455 2.0×	81 0.7×	66 1.3×	31 0.7×	21	681
David J. Sandstrom United States	14	398 1.1×	241 1.0×	81 0.7×	44 0.9×	79 1.7×	19	575
Sudipta Saraswati United States	7	361 1.0×	220 0.9×	125 1.1×	29 0.6×	56 1.2×	7	506
Nadine Ehmann Germany	11	331 0.9×	203 0.9×	99 0.9×	33 0.6×	19 0.4×	15	504
Dmitrij Ljaschenko Germany	7	297 0.8×	250 1.1×	80 0.7×	30 0.6×	18 0.4×	13	509
Samuel Kunes United States	7	322 0.9×	401 1.7×	105 0.9×	48 0.9×	35 0.7×	9	550
Mehmet Neset Özel United States	8	266 0.7×	249 1.1×	136 1.2×	23 0.5×	38 0.8×	11	445

Countries citing papers authored by Matthew Y. Pecot

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Y. Pecot

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Y. Pecot. 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 Matthew Y. Pecot. The network helps show where Matthew Y. Pecot may publish in the future.

Co-authorship network of co-authors of Matthew Y. Pecot

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Y. Pecot. A scholar is included among the top collaborators of Matthew Y. Pecot 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 Matthew Y. Pecot. Matthew Y. Pecot 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

Zhang, Dawei, Arunesh Saras, Chundi Xu, et al.. (2021). Drosophila Fezf functions as a transcriptional repressor to direct layer-specific synaptic connectivity in the fly visual system. Proceedings of the National Academy of Sciences. 118(13). 8 indexed citations

Xu, Chundi, Jing Peng, Clarence Yapp, et al.. (2019). Control of Synaptic Specificity by Establishing a Relative Preference for Synaptic Partners. Neuron. 103(5). 865–877.e7. 39 indexed citations

Millard, S. Sean & Matthew Y. Pecot. (2018). Strategies for assembling columns and layers in the Drosophila visual system. Neural Development. 13(1). 11–11. 15 indexed citations

Peng, Jing, et al.. (2018). Drosophila Fezf coordinates laminar-specific connectivity through cell-intrinsic and cell-extrinsic mechanisms. eLife. 7. 23 indexed citations

Xu, Chundi, Jing Peng, Dorota Tarnogorska, et al.. (2018). Control of Synaptic Specificity by Limiting Promiscuous Synapse Formation. SSRN Electronic Journal. 1 indexed citations

Tan, Liming, Kelvin Xi Zhang, Matthew Y. Pecot, et al.. (2015). Ig Superfamily Ligand and Receptor Pairs Expressed in Synaptic Partners in Drosophila. Cell. 163(7). 1756–1769. 119 indexed citations

Chen, Yi, Orkun Akin, Aljoscha Nern, et al.. (2014). Cell-type-Specific Labeling of Synapses In Vivo through Synaptic Tagging with Recombination. Neuron. 81(2). 280–293. 123 indexed citations

Pecot, Matthew Y., Yi Chen, Orkun Akin, et al.. (2014). Sequential Axon-Derived Signals Couple Target Survival and Layer Specificity in the Drosophila Visual System. Neuron. 82(2). 320–333. 27 indexed citations

Pecot, Matthew Y., Wael Tadros, Aljoscha Nern, et al.. (2013). Multiple Interactions Control Synaptic Layer Specificity in the Drosophila Visual System. Neuron. 77(2). 299–310. 51 indexed citations

10.

Pecot, Matthew Y. & Vivek Malhotra. (2006). The Golgi Apparatus Maintains Its Organization Independent of the Endoplasmic Reticulum. Molecular Biology of the Cell. 17(12). 5372–5380. 26 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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