David Hunt

2.8k total citations
52 papers, 1.1k citations indexed

About

David Hunt is a scholar working on Molecular Biology, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, David Hunt has authored 52 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 12 papers in Genetics and 10 papers in Cellular and Molecular Neuroscience. Recurrent topics in David Hunt's work include Structural Health Monitoring Techniques (8 papers), Genomics and Rare Diseases (7 papers) and Neural dynamics and brain function (6 papers). David Hunt is often cited by papers focused on Structural Health Monitoring Techniques (8 papers), Genomics and Rare Diseases (7 papers) and Neural dynamics and brain function (6 papers). David Hunt collaborates with scholars based in United States, United Kingdom and Australia. David Hunt's co-authors include Pablo E. Castillo, David Nixon, Nelson Spruston, Daniele Linaro, Kwang S. Kim, Michael B. Giles, Masahiko Watanabe, Christoph Straub, Susumu Tomita and Miwako Yamasaki and has published in prestigious journals such as Science, Nature Neuroscience and Scientific Reports.

In The Last Decade

David Hunt

44 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Hunt United States 17 437 375 223 153 87 52 1.1k
James E. Fitzgerald United States 24 684 1.6× 642 1.7× 608 2.7× 132 0.9× 13 0.1× 86 2.1k
Eunchai Kang United States 18 492 1.1× 725 1.9× 125 0.6× 262 1.7× 39 0.4× 28 1.6k
Malcolm Casale United States 13 537 1.2× 436 1.2× 156 0.7× 40 0.3× 92 1.1× 19 1.1k
Yiheng Xie United States 10 322 0.7× 310 0.8× 134 0.6× 16 0.1× 109 1.3× 11 1.2k
Hongbo Zhang China 21 67 0.2× 244 0.7× 104 0.5× 116 0.8× 17 0.2× 93 1.0k
David Schwarz United States 21 467 1.1× 529 1.4× 348 1.6× 211 1.4× 10 0.1× 40 1.8k
Akira Sato Japan 13 290 0.7× 649 1.7× 56 0.3× 59 0.4× 10 0.1× 80 1.3k
Hyoung Kim South Korea 19 405 0.9× 730 1.9× 252 1.1× 141 0.9× 4 0.0× 54 1.5k
Jean‐Christophe Roux France 26 193 0.4× 648 1.7× 536 2.4× 836 5.5× 9 0.1× 66 1.9k
Bo Shui United States 16 316 0.7× 697 1.9× 47 0.2× 40 0.3× 51 0.6× 35 1.3k

Countries citing papers authored by David Hunt

Since Specialization
Citations

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

Fields of papers citing papers by David Hunt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Hunt

This figure shows the co-authorship network connecting the top 25 collaborators of David Hunt. A scholar is included among the top collaborators of David Hunt 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 David Hunt. David Hunt 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.
Wai, Htoo A., David J. Bunyan, N. Simon Thomas, et al.. (2024). Identification of diagnostic candidates in Mendelian disorders using an RNA sequencing-centric approach. Genome Medicine. 16(1). 110–110. 3 indexed citations
2.
Soula, Marisol, et al.. (2024). NMDAR-mediated activation of pannexin1 channels contributes to the detonator properties of hippocampal mossy fiber synapses. iScience. 27(5). 109681–109681. 3 indexed citations
3.
Seaby, Eleanor G., N. Simon Thomas, David Hunt, et al.. (2023). A Panel-Agnostic Strategy ‘HiPPo’ Improves Diagnostic Efficiency in the UK Genomic Medicine Service. Healthcare. 11(24). 3179–3179.
4.
Makani, Sachin, et al.. (2021). Retrograde Suppression of Post-Tetanic Potentiation at the Mossy Fiber-CA3 Pyramidal Cell Synapse. eNeuro. 8(2). ENEURO.0450–20.2021. 5 indexed citations
5.
Wheway, Gabrielle, N. Simon Thomas, Mary Carroll, et al.. (2021). Whole genome sequencing in the diagnosis of primary ciliary dyskinesia. BMC Medical Genomics. 14(1). 234–234. 20 indexed citations
6.
Pengelly, Reuben J., Daniel Ward, David Hunt, C. Mattocks, & Sarah Ennis. (2020). Comparison of Mendeliome exome capture kits for use in clinical diagnostics. Scientific Reports. 10(1). 3235–3235. 9 indexed citations
7.
Kharbanda, Mira, Mark S. Bateman, David Hunt, et al.. (2020). Directly Transmitted 12.3-Mb Deletion with a Consistent Phenotype in the Variable 11q21q22.3 Region. Cytogenetic and Genome Research. 160(4). 185–192. 1 indexed citations
8.
Sugino, Ken, Erin Clark, Anton Schulmann, et al.. (2019). Mapping the transcriptional diversity of genetically and anatomically defined cell populations in the mouse brain. eLife. 8. 50 indexed citations
9.
Hunt, David, et al.. (2019). Multimodal in vivo brain electrophysiology with integrated glass microelectrodes. Nature Biomedical Engineering. 3(9). 741–753. 40 indexed citations
10.
Jin, Dezhe Z., et al.. (2019). ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology. Frontiers in Neuroinformatics. 13. 68–68. 11 indexed citations
11.
Hunt, David, Daniele Linaro, Bailu Si, Sandro Romani, & Nelson Spruston. (2018). A novel pyramidal cell type promotes sharp-wave synchronization in the hippocampus. Nature Neuroscience. 21(7). 985–995. 65 indexed citations
12.
Pengelly, Reuben J., et al.. (2017). Evaluating phenotype-driven approaches for genetic diagnoses from exomes in a clinical setting. Scientific Reports. 7(1). 13509–13509. 24 indexed citations
13.
Reijnders, Margot R.F., Richard J. Leventer, Bo Hoon Lee, et al.. (2017). PURA-Related Neurodevelopmental Disorders. ePrints Soton (University of Southampton). 6 indexed citations
14.
Seaby, Eleanor G., Rodney D. Gilbert, Gaia Andreoletti, et al.. (2017). Unexpected Findings in a Child with Atypical Hemolytic Uremic Syndrome: An Example of How Genomics Is Changing the Clinical Diagnostic Paradigm. Frontiers in Pediatrics. 5. 113–113. 8 indexed citations
15.
Hunt, David & Pablo E. Castillo. (2012). Synaptic plasticity of NMDA receptors: mechanisms and functional implications. Current Opinion in Neurobiology. 22(3). 496–508. 286 indexed citations
16.
Straub, Christoph, David Hunt, Miwako Yamasaki, et al.. (2011). Distinct functions of kainate receptors in the brain are determined by the auxiliary subunit Neto1. Nature Neuroscience. 14(7). 866–873. 98 indexed citations
17.
Lightbody, Kirsty L., Philip S. Renshaw, Matthew Collins, et al.. (2004). Characterisation of complex formation between members of the complex CFP-10/ESAT-6 protein family: towards an understanding of the rules governing complex formation and thereby functional flexibility. FEMS Microbiology Letters. 238(1). 255–262. 38 indexed citations
18.
Hunt, David, et al.. (2000). Generating rapid response NS 2-equation turbulence models. 2 indexed citations
19.
Hunt, David, et al.. (1985). A Normal Mode Identification Test Using Multiple Inputs. SAE technical papers on CD-ROM/SAE technical paper series. 1.
20.
Bruley, Duane F. & David Hunt. (1974). Theoretical studies of brain autoregulation: Oxygen transport to tissue. Microvascular Research. 8(3). 314–319. 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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