J. Marshall

625 total citations
17 papers, 453 citations indexed

About

J. Marshall is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Genetics. According to data from OpenAlex, J. Marshall has authored 17 papers receiving a total of 453 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cellular and Molecular Neuroscience, 5 papers in Molecular Biology and 4 papers in Genetics. Recurrent topics in J. Marshall's work include Neuroscience and Neuropharmacology Research (6 papers), Genetic Syndromes and Imprinting (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). J. Marshall is often cited by papers focused on Neuroscience and Neuropharmacology Research (6 papers), Genetic Syndromes and Imprinting (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). J. Marshall collaborates with scholars based in United States, India and Australia. J. Marshall's co-authors include Anis Contractor, Donna S. Dorow, Anneli Savinainen, Jian Xu, Ya Fang Liu, Elizabeth P. Garcia, Toshihiro Nomura, Christine Remmers, Eric R. Kandel and Eleanor H. Simpson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Neuroscience.

In The Last Decade

J. Marshall

15 papers receiving 443 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Marshall United States	13	256	240	94	51	39	17	453
Ádám Fekete Canada	9	237 0.9×	210 0.9×	106 1.1×	47 0.9×	43 1.1×	18	421
Sarah Luo United States	8	201 0.8×	204 0.8×	94 1.0×	44 0.9×	37 0.9×	9	486
Yuichiro Ishii Japan	7	274 1.1×	257 1.1×	115 1.2×	76 1.5×	39 1.0×	8	464
Hannah I. Bishop United States	7	277 1.1×	331 1.4×	108 1.1×	37 0.7×	33 0.8×	7	534
Annelies Laeremans Belgium	13	163 0.6×	252 1.1×	144 1.5×	51 1.0×	44 1.1×	20	475
Vedrana Cvetkovska Canada	8	142 0.6×	179 0.7×	60 0.6×	61 1.2×	34 0.9×	11	363
Joanna Giza United States	9	213 0.8×	394 1.6×	81 0.9×	93 1.8×	32 0.8×	10	648
Shuichi Takizawa Japan	9	227 0.9×	280 1.2×	124 1.3×	48 0.9×	27 0.7×	10	656
Diancai Cai United States	11	350 1.4×	199 0.8×	233 2.5×	32 0.6×	30 0.8×	12	524
Wen‐Chin Huang United States	6	102 0.4×	178 0.7×	91 1.0×	72 1.4×	34 0.9×	8	390

Countries citing papers authored by J. Marshall

Since Specialization

Citations

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

Fields of papers citing papers by J. Marshall

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Marshall

This figure shows the co-authorship network connecting the top 25 collaborators of J. Marshall. A scholar is included among the top collaborators of J. Marshall 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 J. Marshall. J. Marshall is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

17 of 17 papers shown

Yang, Xin, Yu‐Wen Alvin Huang, & J. Marshall. (2025). UBE3A stabilization of β-catenin preserves synaptic proteins essential for motor and cognitive functions in Angelman Syndrome. Molecular Autism. 16(1). 60–60.

Ünal, Alper, et al.. (2025). Machine learning-driven regional prediction of PM2.5 concentrations in the eastern mediterranean bridging spatial data gaps in air quality monitoring. Environmental Modelling & Software. 192. 106586–106586.

Yang, Xin, Mengia S. Rioult-Pedotti, Kim M. Hansen, et al.. (2024). Peptidomimetic inhibitors targeting TrkB/PSD-95 signaling improves cognition and seizure outcomes in an Angelman Syndrome mouse model. Neuropsychopharmacology. 50(5). 772–782. 2 indexed citations

Xu, Jian, Andrew Jo, J. Marshall, et al.. (2022). Intersectional mapping of multi-transmitter neurons and other cell types in the brain. Cell Reports. 40(1). 111036–111036. 17 indexed citations

Xu, Jian, et al.. (2021). Genetic disruption of Grm5 causes complex alterations in motor activity, anxiety and social behaviors. Behavioural Brain Research. 411. 113378–113378. 13 indexed citations

Marshall, J., Jian Xu, & Anis Contractor. (2018). Kainate Receptors Inhibit Glutamate Release Via Mobilization of Endocannabinoids in Striatal Direct Pathway Spiny Projection Neurons. Journal of Neuroscience. 38(16). 3901–3910. 16 indexed citations

Banala, Sambashiva, Nicholas M. Bannon, J. J. Macklin, et al.. (2018). Photoactivatable drugs for nicotinic optopharmacology. Nature Methods. 15(5). 347–350. 42 indexed citations

Xu, Jian, J. Marshall, Herman B. Fernandes, et al.. (2017). Complete Disruption of the Kainate Receptor Gene Family Results in Corticostriatal Dysfunction in Mice. Cell Reports. 18(8). 1848–1857. 24 indexed citations

Nomura, Toshihiro, Timothy F. Musial, J. Marshall, et al.. (2017). Delayed Maturation of Fast-Spiking Interneurons Is Rectified by Activation of the TrkB Receptor in the Mouse Model of Fragile X Syndrome. Journal of Neuroscience. 37(47). 11298–11310. 47 indexed citations

10.

Fernandes, Herman B., Sean M. Riordan, Toshihiro Nomura, et al.. (2015). Epac2 Mediates cAMP-Dependent Potentiation of Neurotransmission in the Hippocampus. Journal of Neuroscience. 35(16). 6544–6553. 54 indexed citations

11.

Xu, Jian, Yongling Zhu, Qionger He, et al.. (2013). Potentiating mGluR5 function with a positive allosteric modulator enhances adaptive learning. Learning & Memory. 20(8). 438–445. 30 indexed citations

12.

Marshall, J., Leslie A.C. Blair, & Jeffrey D. Singer. (2011). BTB-Kelch Proteins and Ubiquitination of Kainate Receptors. Advances in experimental medicine and biology. 717. 115–125. 15 indexed citations

13.

Simpson, Eleanor H., et al.. (2008). Transient and selective overexpression of D ₂ receptors in the striatum causes persistent deficits in conditional associative learning. Proceedings of the National Academy of Sciences. 105(41). 16027–16032. 54 indexed citations

14.

Christensen, Svend, César Fernández‐Quintanilla, A. Grundy, et al.. (2005). Proceedings, 13th European Weed Research Society Symposium. Female Pelvic Medicine & Reconstructive Surgery. 27(3). 186–194. 24 indexed citations

15.

Savinainen, Anneli, Elizabeth P. Garcia, Donna S. Dorow, J. Marshall, & Ya Fang Liu. (2001). Kainate Receptor Activation Induces Mixed Lineage Kinase-mediated Cellular Signaling Cascades via Post-synaptic Density Protein 95. Journal of Biological Chemistry. 276(14). 11382–11386. 100 indexed citations

16.

Marshall, J.. (1986). Molecular Mechanisms of Ischemic Brain Damage. Journal of Neurology Neurosurgery & Psychiatry. 49(8). 980–980. 1 indexed citations

17.

Keating, Norah & J. Marshall. (1980). The Process of Retirement: The Rural Self Employed. The Gerontologist. 20(4). 437–443. 14 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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