Gabe J. Murphy

5.6k total citations
19 papers, 1.5k citations indexed

About

Gabe J. Murphy is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Gabe J. Murphy has authored 19 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cellular and Molecular Neuroscience, 12 papers in Molecular Biology and 11 papers in Cognitive Neuroscience. Recurrent topics in Gabe J. Murphy's work include Neural dynamics and brain function (10 papers), Photoreceptor and optogenetics research (10 papers) and Retinal Development and Disorders (8 papers). Gabe J. Murphy is often cited by papers focused on Neural dynamics and brain function (10 papers), Photoreceptor and optogenetics research (10 papers) and Retinal Development and Disorders (8 papers). Gabe J. Murphy collaborates with scholars based in United States, Australia and China. Gabe J. Murphy's co-authors include Jeffry S. Isaacson, Fred Rieke, Samuel D. Gale, Daniel P. Darcy, Grégory Gauvain, Benjamin Sivyer, Lindsey L. Glickfeld, Sascha du, Corbett Bennett and Shawn R. Olsen and has published in prestigious journals such as Neuron, Journal of Neuroscience and Nature Neuroscience.

In The Last Decade

Gabe J. Murphy

19 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gabe J. Murphy United States 18 1.0k 672 653 365 157 19 1.5k
Jason M. Christie United States 21 897 0.9× 461 0.7× 459 0.7× 306 0.8× 139 0.9× 26 1.4k
Norimitsu Suzuki Australia 13 926 0.9× 281 0.4× 348 0.5× 461 1.3× 206 1.3× 16 1.1k
Conny Kopp‐Scheinpflug Germany 25 951 0.9× 572 0.9× 1.1k 1.7× 972 2.7× 126 0.8× 45 2.2k
Michael N. Economo United States 18 750 0.7× 299 0.4× 727 1.1× 190 0.5× 79 0.5× 28 1.6k
Jens Midtgaard Denmark 15 838 0.8× 279 0.4× 491 0.8× 335 0.9× 94 0.6× 22 1.1k
Veronica Egger Germany 16 1.4k 1.4× 279 0.4× 889 1.4× 611 1.7× 229 1.5× 33 1.9k
Matthew A. Xu‐Friedman United States 21 972 0.9× 468 0.7× 834 1.3× 592 1.6× 66 0.4× 42 1.6k
Lindsey L. Glickfeld United States 17 1.6k 1.5× 423 0.6× 1.5k 2.3× 199 0.5× 56 0.4× 23 2.1k
Hisayuki Ojima Japan 19 818 0.8× 208 0.3× 1.2k 1.9× 699 1.9× 252 1.6× 44 2.0k
Ryohei Tomioka Japan 14 1.5k 1.5× 578 0.9× 901 1.4× 153 0.4× 92 0.6× 26 2.1k

Countries citing papers authored by Gabe J. Murphy

Since Specialization
Citations

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

Fields of papers citing papers by Gabe J. Murphy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gabe J. Murphy

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

All Works

19 of 19 papers shown
1.
Gala, Rohan, Agata Budzillo, Fahimeh Baftizadeh, et al.. (2021). Consistent cross-modal identification of cortical neurons with coupled autoencoders. Nature Computational Science. 1(2). 120–127. 23 indexed citations
2.
Huang, Lawrence, Peter Ledochowitsch, Ulf Knoblich, et al.. (2021). Relationship between simultaneously recorded spiking activity and fluorescence signal in GCaMP6 transgenic mice. eLife. 10. 88 indexed citations
3.
Bennett, Corbett, Samuel D. Gale, Marina Garrett, et al.. (2019). Higher-Order Thalamic Circuits Channel Parallel Streams of Visual Information in Mice. Neuron. 102(2). 477–492.e5. 107 indexed citations
4.
Gala, Rohan, Nathan W. Gouwens, Zizhen Yao, et al.. (2019). A coupled autoencoder approach for multi-modal analysis of cell types. arXiv (Cornell University). 32. 9263–9272. 6 indexed citations
5.
Gale, Samuel D. & Gabe J. Murphy. (2018). Distinct cell types in the superficial superior colliculus project to the dorsal lateral geniculate and lateral posterior thalamic nuclei. Journal of Neurophysiology. 120(3). 1286–1292. 47 indexed citations
6.
Gauvain, Grégory, et al.. (2016). Shared and distinct retinal input to the mouse superior colliculus and dorsal lateral geniculate nucleus. Journal of Neurophysiology. 116(2). 602–610. 128 indexed citations
7.
Murphy, Gabe J., et al.. (2016). Active Dendritic Properties and Local Inhibitory Input Enable Selectivity for Object Motion in Mouse Superior Colliculus Neurons. Journal of Neuroscience. 36(35). 9111–9123. 69 indexed citations
8.
Gauvain, Grégory & Gabe J. Murphy. (2015). Projection-Specific Characteristics of Retinal Input to the Brain. Journal of Neuroscience. 35(16). 6575–6583. 34 indexed citations
9.
Gale, Samuel D. & Gabe J. Murphy. (2014). Distinct Representation and Distribution of Visual Information by Specific Cell Types in Mouse Superficial Superior Colliculus. Journal of Neuroscience. 34(40). 13458–13471. 168 indexed citations
10.
Murphy, Gabe J. & Fred Rieke. (2011). Electrical Synaptic Input to Ganglion Cells Underlies Differences in the Output and Absolute Sensitivity of Parallel Retinal Circuits. Journal of Neuroscience. 31(34). 12218–12228. 28 indexed citations
11.
Tian, Miao, Tim Jarsky, Gabe J. Murphy, Fred Rieke, & Joshua H. Singer. (2010). Voltage-Gated Na Channels in AII Amacrine Cells Accelerate Scotopic Light Responses Mediated by the Rod Bipolar Cell Pathway. Journal of Neuroscience. 30(13). 4650–4659. 41 indexed citations
12.
Murphy, Gabe J. & Fred Rieke. (2008). Signals and noise in an inhibitory interneuron diverge to control activity in nearby retinal ganglion cells. Nature Neuroscience. 11(3). 318–326. 74 indexed citations
13.
Duncan, Jacque L., Haidong Yang, Thuy Doan, et al.. (2006). Scotopic Visual Signaling in the Mouse Retina Is Modulated by High-Affinity Plasma Membrane Calcium Extrusion. Journal of Neuroscience. 26(27). 7201–7211. 32 indexed citations
14.
Murphy, Gabe J. & Fred Rieke. (2006). Network Variability Limits Stimulus-Evoked Spike Timing Precision in Retinal Ganglion Cells. Neuron. 52(3). 511–524. 155 indexed citations
15.
Murphy, Gabe J., Daniel P. Darcy, & Jeffry S. Isaacson. (2005). Intraglomerular inhibition: signaling mechanisms of an olfactory microcircuit. Nature Neuroscience. 8(3). 354–364. 150 indexed citations
16.
Murphy, Gabe J., et al.. (2004). Sensory Neuron Signaling to the Brain: Properties of Transmitter Release from Olfactory Nerve Terminals. Journal of Neuroscience. 24(12). 3023–3030. 100 indexed citations
17.
Murphy, Gabe J. & Jeffry S. Isaacson. (2003). Presynaptic Cyclic Nucleotide-Gated Ion Channels Modulate Neurotransmission in the Mammalian Olfactory Bulb. Neuron. 37(4). 639–647. 40 indexed citations
18.
Isaacson, Jeffry S. & Gabe J. Murphy. (2001). Glutamate-Mediated Extrasynaptic Inhibition. Neuron. 31(6). 1027–1034. 118 indexed citations
19.
Murphy, Gabe J. & Sascha du. (2001). Postnatal Development of Spike Generation in Rat Medial Vestibular Nucleus Neurons. Journal of Neurophysiology. 85(5). 1899–1906. 43 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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