Stephen J. Moss

25.7k total citations · 4 hit papers
236 papers, 20.4k citations indexed

About

Stephen J. Moss is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Cell Biology. According to data from OpenAlex, Stephen J. Moss has authored 236 papers receiving a total of 20.4k indexed citations (citations by other indexed papers that have themselves been cited), including 187 papers in Cellular and Molecular Neuroscience, 178 papers in Molecular Biology and 20 papers in Cell Biology. Recurrent topics in Stephen J. Moss's work include Neuroscience and Neuropharmacology Research (180 papers), Ion channel regulation and function (73 papers) and Receptor Mechanisms and Signaling (61 papers). Stephen J. Moss is often cited by papers focused on Neuroscience and Neuropharmacology Research (180 papers), Ion channel regulation and function (73 papers) and Receptor Mechanisms and Signaling (61 papers). Stephen J. Moss collaborates with scholars based in United Kingdom, United States and Germany. Stephen J. Moss's co-authors include Trevor G. Smart, Josef T. Kittler, Nicholas J. Brandon, Richard L. Huganir, Menelas N. Pangalos, Tija C. Jacob, Bernard McDonald, Philip G. Haydon, Andrés Couve and Tarek Z. Deeb and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Stephen J. Moss

235 papers receiving 20.1k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Astrocytic Purinergic Signaling Coordinates Synaptic Networks

2005 993 citations Raquel Revilla-Sanchez, Stephen J. Moss et al. profile →
Antibodies to the GABAB receptor in limbic encephalitis with seizures: case series and characterisation of the antigen

2009 652 citations Eric Lancaster, Meizan Lai et al. The Lancet Neurology profile →
GABAA-receptor-associated protein links GABAA receptors and the cytoskeleton

1999 601 citations Nicholas J. Brandon, Stephen J. Moss et al. profile →
GABAA receptor trafficking and its role in the dynamic modulation of neuronal inhibition

2008 512 citations Tija C. Jacob, Stephen J. Moss et al. Nature reviews. Neuroscience profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Stephen J. Moss	14.1k	11.5k	2.5k	2.1k	1.7k	236	20.4k
Stephen F. Heinemann	16.7k 1.2×	15.2k 1.3×	3.0k 1.2×	2.6k 1.2×	1.3k 0.7×	147	23.4k
Masayoshi Mishina	13.5k 1.0×	12.9k 1.1×	2.6k 1.0×	2.4k 1.1×	2.0k 1.2×	267	20.8k
Kenji Sakimura	11.7k 0.8×	9.6k 0.8×	3.4k 1.4×	2.4k 1.1×	1.8k 1.0×	387	19.2k
Joël Bockaert	19.6k 1.4×	17.9k 1.6×	2.4k 1.0×	2.1k 1.0×	1.6k 0.9×	410	30.5k
John Roder	9.5k 0.7×	12.0k 1.0×	2.2k 0.9×	1.4k 0.6×	2.0k 1.1×	350	23.5k
Werner Sieghart	17.8k 1.3×	12.2k 1.1×	4.3k 1.7×	2.6k 1.2×	750 0.4×	317	23.6k
Randy Blakely	11.6k 0.8×	10.7k 0.9×	2.3k 0.9×	907 0.4×	1.3k 0.7×	326	22.7k
Keiji Wada	8.0k 0.6×	9.9k 0.9×	1.2k 0.5×	2.0k 0.9×	1.3k 0.7×	379	18.7k
Ronald S. Petralia	11.5k 0.8×	9.2k 0.8×	3.1k 1.2×	1.8k 0.8×	2.0k 1.2×	176	16.1k
Gary L. Westbrook	17.8k 1.3×	12.5k 1.1×	4.5k 1.8×	2.0k 0.9×	966 0.6×	129	22.2k

Countries citing papers authored by Stephen J. Moss

Since Specialization

Citations

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

Fields of papers citing papers by Stephen J. Moss

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen J. Moss

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

All Works

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20 of 20 papers shown

Blednov, Yuri A., William Shawlot, Gregg E. Homanics, et al.. (2024). The PDE4 inhibitor apremilast modulates ethanol responses in Gabrb1-S409A knock-in mice via PKA-dependent and independent mechanisms. Neuropharmacology. 257. 110035–110035.

Smalley, Joshua L., Josephine Ng, Catherine Choi, et al.. (2023). Spectrin-beta 2 facilitates the selective accumulation of GABAA receptors at somatodendritic synapses. Communications Biology. 6(1). 11–11. 4 indexed citations

Żukowska, Joanna, Stephen J. Moss, Vasanta Subramanian, & K. Ravi Acharya. (2023). Molecular basis of selective amyloid‐β degrading enzymes in Alzheimer's disease. FEBS Journal. 291(14). 2999–3029. 14 indexed citations

Hines, Dustin J., et al.. (2022). Human ARHGEF9 intellectual disability syndrome is phenocopied by a mutation that disrupts collybistin binding to the GABAA receptor α2 subunit. Molecular Psychiatry. 27(3). 1729–1741. 13 indexed citations

Palmos, Alish, Pooja Raval, Jayanta Mukherjee, et al.. (2020). Estradiol reverses excitatory synapse loss in a cellular model of neuropsychiatric disorders. Translational Psychiatry. 10(1). 16–16. 12 indexed citations

Modgil, Amit, Thuy N. Vien, Michael A. Ackley, et al.. (2019). Neuroactive Steroids Reverse Tonic Inhibitory Deficits in Fragile X Syndrome Mouse Model. Frontiers in Molecular Neuroscience. 12. 15–15. 9 indexed citations

Zhang, Yihui, Joshua L. Smalley, Peter M. Andrews, et al.. (2019). Identification of a Core Amino Acid Motif within the α Subunit of GABAARs that Promotes Inhibitory Synaptogenesis and Resilience to Seizures. Cell Reports. 28(3). 670–681.e8. 17 indexed citations

Vien, Thuy N., Thomas M. Hyde, Robert J. Mather, et al.. (2017). Deficits in the activity of presynaptic γ-aminobutyric acid type B receptors contribute to altered neuronal excitability in fragile X syndrome. Journal of Biological Chemistry. 292(16). 6621–6632. 42 indexed citations

Kelley, Matt R., Tarek Z. Deeb, Nicholas J. Brandon, et al.. (2016). Compromising KCC2 transporter activity enhances the development of continuous seizure activity. Neuropharmacology. 108. 103–110. 36 indexed citations

10.

Sivakumaran, Sudhir, Ross A. Cardarelli, Jamie Maguire, et al.. (2015). Selective Inhibition of KCC2 Leads to Hyperexcitability and Epileptiform Discharges in Hippocampal Slices andIn Vivo. Journal of Neuroscience. 35(21). 8291–8296. 77 indexed citations

11.

Kretschmannova, Karla, Rochelle M. Hines, Raquel Revilla-Sanchez, et al.. (2013). Enhanced Tonic Inhibition Influences the Hypnotic and Amnestic Actions of the Intravenous Anesthetics Etomidate and Propofol. Journal of Neuroscience. 33(17). 7264–7273. 30 indexed citations

12.

Porcher, Christophe, Rebecca Longbottom, Talvinder S. Sihra, et al.. (2011). Positive Feedback Regulation between γ-Aminobutyric Acid Type A (GABAA) Receptor Signaling and Brain-derived Neurotrophic Factor (BDNF) Release in Developing Neurons. Journal of Biological Chemistry. 286(24). 21667–21677. 72 indexed citations

13.

Dong, Jinghui, Raquel Revilla-Sanchez, Stephen J. Moss, & Philip G. Haydon. (2010). Multiphoton in vivo imaging of amyloid in animal models of Alzheimer’s disease. Neuropharmacology. 59(4-5). 268–275. 40 indexed citations

14.

Lancaster, Eric, Meizan Lai, Xiaoyu Peng, et al.. (2009). Antibodies to the GABAB receptor in limbic encephalitis with seizures: case series and characterisation of the antigen. The Lancet Neurology. 9(1). 67–76. 652 indexed citations breakdown →

15.

Terunuma, Miho, et al.. (2009). Direct Interaction of GABA_BReceptors with M₂Muscarinic Receptors Enhances Muscarinic Signaling. Journal of Neuroscience. 29(50). 15796–15809. 34 indexed citations

16.

Jacob, Tija C., Stephen J. Moss, & Rachel Jurd. (2008). GABAA receptor trafficking and its role in the dynamic modulation of neuronal inhibition. Nature reviews. Neuroscience. 9(5). 331–343. 512 indexed citations breakdown →

17.

Kuramoto, Nobuyuki, Megan E. Wilkins, Benjamin P. Fairfax, et al.. (2007). Phospho-Dependent Functional Modulation of GABAB Receptors by the Metabolic Sensor AMP-Dependent Protein Kinase. Neuron. 53(2). 233–247. 158 indexed citations

18.

Saliba, Richard S., Guido Michels, Tija C. Jacob, Menelas N. Pangalos, & Stephen J. Moss. (2007). Activity-Dependent Ubiquitination of GABA_AReceptors Regulates Their Accumulation at Synaptic Sites. Journal of Neuroscience. 27(48). 13341–13351. 106 indexed citations

19.

Brandon, Nicholas J., Patrick Delmas, Jason E. Hill, Trevor G. Smart, & Stephen J. Moss. (2001). Constitutive tyrosine phosphorylation of the GABAA receptor γ2 subunit in rat brain. Neuropharmacology. 41(6). 745–752. 49 indexed citations

20.

Valenzuela, C. Fernando, Andrius Kazlauskas, Susan J. Brozowski, et al.. (1995). Platelet-derived growth factor receptor is a novel modulator of type A gamma-aminobutyric acid-gated ion channels.. Molecular Pharmacology. 48(6). 1099–1107. 29 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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