John Wade

896 total citations
28 papers, 605 citations indexed

About

John Wade is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, John Wade has authored 28 papers receiving a total of 605 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Cellular and Molecular Neuroscience, 17 papers in Cognitive Neuroscience and 11 papers in Electrical and Electronic Engineering. Recurrent topics in John Wade's work include Neural dynamics and brain function (16 papers), Neuroscience and Neuropharmacology Research (13 papers) and Advanced Memory and Neural Computing (11 papers). John Wade is often cited by papers focused on Neural dynamics and brain function (16 papers), Neuroscience and Neuropharmacology Research (13 papers) and Advanced Memory and Neural Computing (11 papers). John Wade collaborates with scholars based in United Kingdom, United States and Ireland. John Wade's co-authors include Liam McDaid, Jim Harkin, José Santos, Vincenzo Crunelli, J. A. Scott Kelso, Junxiu Liu, Liam Maguire, KongFatt Wong‐Lin, Alexei Verkhratsky and John Marsland and has published in prestigious journals such as PLoS ONE, Scientific Reports and PLoS Computational Biology.

In The Last Decade

John Wade

28 papers receiving 588 citations

Author Peers

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

Author Last Decade Papers Cites
John Wade 348 329 322 114 103 28 605
Vassilis Cutsuridis 403 1.2× 552 1.7× 82 0.3× 53 0.5× 65 0.6× 57 833
Henry Markram 404 1.2× 456 1.4× 165 0.5× 101 0.9× 34 0.3× 8 685
David Feng 240 0.7× 405 1.2× 100 0.3× 68 0.6× 29 0.3× 29 729
Timothy A. Zolnik 325 0.9× 348 1.1× 113 0.4× 71 0.6× 38 0.4× 12 641
Samuel A. Neymotin 708 2.0× 1.0k 3.2× 227 0.7× 65 0.6× 71 0.7× 60 1.3k
Robert A. McDougal 276 0.8× 367 1.1× 107 0.3× 38 0.3× 45 0.4× 40 702
Marcel Stimberg 433 1.2× 615 1.9× 417 1.3× 134 1.2× 22 0.2× 17 839
Michael Graupner 598 1.7× 483 1.5× 343 1.1× 37 0.3× 40 0.4× 19 791
Ľubica Beňušková 198 0.6× 417 1.3× 330 1.0× 250 2.2× 23 0.2× 47 743
Alexander Kaplan 346 1.0× 1.4k 4.1× 87 0.3× 69 0.6× 62 0.6× 122 1.6k

Countries citing papers authored by John Wade

Since Specialization
Citations

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

Fields of papers citing papers by John Wade

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Wade

This figure shows the co-authorship network connecting the top 25 collaborators of John Wade. A scholar is included among the top collaborators of John Wade 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 John Wade. John Wade 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.
Wade, John, et al.. (2024). Mathematical Modeling of PI3K/Akt Pathway in Microglia. Neural Computation. 36(4). 645–676. 3 indexed citations
2.
Wade, John, Alexei Verkhratsky, Mark Dallas, et al.. (2023). The influence of astrocytic leaflet motility on ionic signalling and homeostasis at active synapses. Scientific Reports. 13(1). 3050–3050. 7 indexed citations
3.
Wade, John, et al.. (2021). Mathematical modelling of human P2X-mediated plasma membrane electrophysiology and calcium dynamics in microglia. PLoS Computational Biology. 17(11). e1009520–e1009520. 5 indexed citations
4.
McDaid, Liam, et al.. (2021). A Computational Study of Astrocytic GABA Release at the Glutamatergic Synapse: EAAT-2 and GAT-3 Coupled Dynamics. Frontiers in Cellular Neuroscience. 15. 682460–682460. 7 indexed citations
5.
Wade, John, et al.. (2020). Computational Study of Astroglial Calcium Homeostasis in a Semi-isolated Synaptic Cleft. Ulster University Research Portal (Ulster University). 1–8. 1 indexed citations
6.
Liu, Junxiu, Liam McDaid, Alfonso Araque, et al.. (2019). GABA Regulation of Burst Firing in Hippocampal Astrocyte Neural Circuit: A Biophysical Model. Frontiers in Cellular Neuroscience. 13. 335–335. 7 indexed citations
7.
Wade, John, KongFatt Wong‐Lin, Jim Harkin, et al.. (2019). Calcium Microdomain Formation at the Perisynaptic Cradle Due to NCX Reversal: A Computational Study. Frontiers in Cellular Neuroscience. 13. 185–185. 14 indexed citations
8.
McDaid, Liam, et al.. (2018). A computational study of astrocytic glutamate influence on post-synaptic neuronal excitability. PLoS Computational Biology. 14(4). e1006040–e1006040. 27 indexed citations
9.
Wade, John, KongFatt Wong‐Lin, Jim Harkin, et al.. (2018). Potassium and sodium microdomains in thin astroglial processes: A computational model study. PLoS Computational Biology. 14(5). e1006151–e1006151. 48 indexed citations
10.
Liu, Junxiu, Jim Harkin, Liam Maguire, Liam McDaid, & John Wade. (2017). SPANNER: A Self-Repairing Spiking Neural Network Hardware Architecture. IEEE Transactions on Neural Networks and Learning Systems. 29(4). 1287–1300. 47 indexed citations
11.
Harkin, Jim, et al.. (2016). Astrocyte to spiking neuron communication using Networks-on-Chip ring topology. Ulster University Research Portal (Ulster University). 1–8. 5 indexed citations
12.
Machado, Pedro, Kofi Appiah, T.M. McGinnity, John Wade, & T.M. McGinnity. (2015). Si elegans: Hardware architecture and communications protocol. 1–8. 2 indexed citations
13.
Machado, Pedro, John Wade, & T.M. McGinnity. (2014). Si elegans - Computational Modelling of C. elegans Nematode Nervous System using FPGAs. 169–176. 2 indexed citations
14.
Wade, John, Liam McDaid, Jim Harkin, Vincenzo Crunelli, & Scott Kelso. (2013). Biophysically based computational models of astrocyte ~ neuron coupling and their functional significance. Frontiers in Computational Neuroscience. 7. 44–44. 11 indexed citations
15.
Wade, John. (2012). Self-repair in a bidirectionally coupled astrocyte-neuron (AN) system based on retrograde signaling. Frontiers in Computational Neuroscience. 6. 76–76. 47 indexed citations
16.
Glackin, Cornelius, Liam Maguire, Liam McDaid, & John Wade. (2012). Synchrony: A spiking-based mechanism for processing sensory stimuli. Neural Networks. 32. 26–34. 4 indexed citations
17.
Wade, John, Liam McDaid, Jim Harkin, Vincenzo Crunelli, & J. A. Scott Kelso. (2011). Bidirectional Coupling between Astrocytes and Neurons Mediates Learning and Dynamic Coordination in the Brain: A Multiple Modeling Approach. PLoS ONE. 6(12). e29445–e29445. 95 indexed citations
18.
Wade, John, Liam McDaid, Jim Harkin, et al.. (2011). Exploring retrograde signaling via astrocytes as a mechanism for self repair. ORCA Online Research @Cardiff. 3149–3155. 13 indexed citations
19.
Condell, Joan, et al.. (2010). Problem solving techniques in cognitive science. Artificial Intelligence Review. 34(3). 221–234. 8 indexed citations
20.
Wade, John, et al.. (2007). A Biologically Inspired Training Algorithm for Spiking Neural Networks. OpenGrey (Institut de l'Information Scientifique et Technique). 2020. 7–12. 7 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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