Shawn P. Driscoll

2.6k total citations · 1 hit paper
19 papers, 1.7k citations indexed

About

Shawn P. Driscoll is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cell Biology. According to data from OpenAlex, Shawn P. Driscoll has authored 19 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 6 papers in Cellular and Molecular Neuroscience and 5 papers in Cell Biology. Recurrent topics in Shawn P. Driscoll's work include Zebrafish Biomedical Research Applications (5 papers), Neurogenesis and neuroplasticity mechanisms (4 papers) and Pluripotent Stem Cells Research (3 papers). Shawn P. Driscoll is often cited by papers focused on Zebrafish Biomedical Research Applications (5 papers), Neurogenesis and neuroplasticity mechanisms (4 papers) and Pluripotent Stem Cells Research (3 papers). Shawn P. Driscoll collaborates with scholars based in United States, Czechia and Japan. Shawn P. Driscoll's co-authors include Samuel L. Pfaff, Wesley D. Gifford, Todd S. Macfarlan, Karen Lettieri, Dario Bonanomi, Oded Singer, Didier Trono, Amy L. Firth, Helen M. Rowe and Christopher A. Hinckley and has published in prestigious journals such as Nature, Science and Neuron.

In The Last Decade

Shawn P. Driscoll

19 papers receiving 1.7k citations

Hit Papers

Embryonic stem cell potency fluctuates with endogenous re... 2012 2026 2016 2021 2012 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shawn P. Driscoll United States 13 1.3k 306 178 176 168 19 1.7k
Alain Dabdoub United States 25 1.7k 1.4× 117 0.4× 215 1.2× 317 1.8× 230 1.4× 49 2.9k
Moritz Mall United States 17 1.6k 1.2× 81 0.3× 149 0.8× 294 1.7× 180 1.1× 23 1.8k
Benjamin K. August United States 19 717 0.6× 77 0.3× 164 0.9× 153 0.9× 138 0.8× 40 1.5k
Nasir Malik United States 23 1.3k 1.0× 77 0.3× 107 0.6× 510 2.9× 237 1.4× 32 1.9k
Luis A. Williams United States 16 1.6k 1.2× 397 1.3× 127 0.7× 467 2.7× 91 0.5× 20 2.4k
Angelika Doetzlhofer United States 18 1.1k 0.9× 97 0.3× 66 0.4× 91 0.5× 112 0.7× 24 1.9k
Anna Szekely United States 14 1.8k 1.4× 86 0.3× 97 0.5× 326 1.9× 470 2.8× 22 2.3k
Daniel Fuentes United States 7 1.6k 1.2× 125 0.4× 58 0.3× 381 2.2× 196 1.2× 7 1.8k
Livia Tomasini United States 12 1.5k 1.2× 50 0.2× 214 1.2× 332 1.9× 585 3.5× 16 2.1k
Stéphane Blanchard France 20 1.9k 1.4× 103 0.3× 449 2.5× 227 1.3× 370 2.2× 32 2.9k

Countries citing papers authored by Shawn P. Driscoll

Since Specialization
Citations

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

Fields of papers citing papers by Shawn P. Driscoll

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shawn P. Driscoll. 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 Shawn P. Driscoll. The network helps show where Shawn P. Driscoll may publish in the future.

Co-authorship network of co-authors of Shawn P. Driscoll

This figure shows the co-authorship network connecting the top 25 collaborators of Shawn P. Driscoll. A scholar is included among the top collaborators of Shawn P. Driscoll 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 Shawn P. Driscoll. Shawn P. Driscoll 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.
Brown, Colin D., et al.. (2024). IMPROVING CELL AND GENE THERAPY MANUFACTURING PROCESSES BY AUTOMATED ON-LINE AND IN-LINE BIOPROCESS ANALYTICAL TECHNOLOGIES. Cytotherapy. 26(6). S142–S142. 2 indexed citations
2.
Costaguta, Giancarlo, Miriam Gullo, Brendan M. O’Leary, et al.. (2023). Mitf is a Schwann cell sensor of axonal integrity that drives nerve repair. Cell Reports. 42(11). 113282–113282. 7 indexed citations
3.
Kobayashi, Yoshiomi, Oleksandr Platoshyn, Silvia Marsala, et al.. (2023). Expandable Sendai-Virus-Reprogrammed Human iPSC-Neuronal Precursors: In Vivo Post-Grafting Safety Characterization in Rats and Adult Pig. Cell Transplantation. 32. 4221164865–4221164865. 3 indexed citations
4.
Amin, Neal D., et al.. (2022). Detecting microRNA-mediated gene regulatory effects in murine neuronal subpopulations. STAR Protocols. 3(1). 101130–101130. 2 indexed citations
5.
Amin, Neal D., Jeffrey D. Moore, Lukas C. Bachmann, et al.. (2021). Conserved genetic signatures parcellate cardinal spinal neuron classes into local and projection subsets. Science. 372(6540). 385–393. 54 indexed citations
6.
Amin, Neal D., Giancarlo Costaguta, Shawn P. Driscoll, et al.. (2021). A hidden threshold in motor neuron gene networks revealed by modulation of miR-218 dose. Neuron. 109(20). 3252–3267.e6. 18 indexed citations
7.
Bonanomi, Dario, Onanong Chivatakarn, Shawn P. Driscoll, et al.. (2019). p190RhoGAP Filters Competing Signals to Resolve Axon Guidance Conflicts. Neuron. 102(3). 602–620.e9. 14 indexed citations
8.
Bohačiaková, Dáša, Marián Hruška-Plocháň, Wesley D. Gifford, et al.. (2019). A scalable solution for isolating human multipotent clinical-grade neural stem cells from ES precursors. Stem Cell Research & Therapy. 10(1). 83–83. 31 indexed citations
9.
Maršala, Martin, Takahiro Tadokoro, Michael Navarro, et al.. (2019). Spinal parenchymal occupation by neural stem cells after subpial delivery in adult immunodeficient rats. Stem Cells Translational Medicine. 9(2). 177–188. 8 indexed citations
10.
Hayashi, Marito, Christopher A. Hinckley, Shawn P. Driscoll, et al.. (2018). Graded Arrays of Spinal and Supraspinal V2a Interneuron Subtypes Underlie Forelimb and Hindlimb Motor Control. Neuron. 97(4). 869–884.e5. 113 indexed citations
11.
12.
Hilde, Kathryn L., Ariel J. Levine, Christopher A. Hinckley, et al.. (2016). Satb2 Is Required for the Development of a Spinal Exteroceptive Microcircuit that Modulates Limb Position. Neuron. 91(4). 763–776. 29 indexed citations
14.
Hinckley, Christopher A., William A. Alaynick, Marito Hayashi, et al.. (2015). Spinal Locomotor Circuits Develop Using Hierarchical Rules Based on Motorneuron Position and Identity. Neuron. 87(5). 1008–1021. 44 indexed citations
15.
Amin, Neal D., Ge Bai, Jason R. Klug, et al.. (2015). Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure. Science. 350(6267). 1525–1529. 113 indexed citations
16.
Levine, Ariel J., Christopher A. Hinckley, Kathryn L. Hilde, et al.. (2014). Identification of a cellular node for motor control pathways. Nature Neuroscience. 17(4). 586–593. 160 indexed citations
17.
Macfarlan, Todd S., Wesley D. Gifford, Shawn P. Driscoll, et al.. (2012). Embryonic stem cell potency fluctuates with endogenous retrovirus activity. Nature. 487(7405). 57–63. 807 indexed citations breakdown →
18.
Macfarlan, Todd S., Wesley D. Gifford, Saurabh Agarwal, et al.. (2011). Endogenous retroviruses and neighboring genes are coordinately repressed by LSD1/KDM1A. Genes & Development. 25(6). 594–607. 209 indexed citations
19.
Driscoll, Shawn P., et al.. (1998). <title>Machine vision algorithms for semiconductor wafer inspection: a project with Inspex</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3521. 221–228. 5 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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