Glenn Turner

7.4k total citations · 1 hit paper
38 papers, 3.5k citations indexed

About

Glenn Turner is a scholar working on Cellular and Molecular Neuroscience, Genetics and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Glenn Turner has authored 38 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Cellular and Molecular Neuroscience, 19 papers in Genetics and 11 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Glenn Turner's work include Neurobiology and Insect Physiology Research (25 papers), Insect and Arachnid Ecology and Behavior (18 papers) and Animal Behavior and Reproduction (10 papers). Glenn Turner is often cited by papers focused on Neurobiology and Insect Physiology Research (25 papers), Insect and Arachnid Ecology and Behavior (18 papers) and Animal Behavior and Reproduction (10 papers). Glenn Turner collaborates with scholars based in United States, United Kingdom and Italy. Glenn Turner's co-authors include Gilles Laurent, Rachel I. Wilson, Alexander Varshavsky, Robert A. A. Campbell, Stijn Cassenaer, Ofer Mazor, Javier Pérez-Orive, Maxim Bazhenov, Mehrab N Modi and Kyle S. Honegger and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Glenn Turner

34 papers receiving 3.4k citations

Hit Papers

Oscillations and Sparsening of Odor Representations in th... 2002 2026 2010 2018 2002 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Glenn Turner United States 22 2.4k 1.1k 805 666 608 38 3.5k
Jeremy E. Niven United Kingdom 28 1.6k 0.7× 915 0.8× 1.1k 1.4× 626 0.9× 114 0.2× 81 3.7k
Andreas Keller United States 29 1.3k 0.5× 505 0.4× 311 0.4× 342 0.5× 1.9k 3.1× 47 3.7k
Hanno Würbel Switzerland 43 745 0.3× 1.1k 0.9× 420 0.5× 610 0.9× 266 0.4× 129 6.1k
Joseph P. Garner United States 46 511 0.2× 1.1k 1.0× 442 0.5× 585 0.9× 150 0.2× 123 6.2k
Aubrey Manning United Kingdom 27 982 0.4× 1.3k 1.2× 1.5k 1.9× 403 0.6× 351 0.6× 53 3.2k
Brian H. Smith United States 46 2.5k 1.0× 2.5k 2.2× 2.9k 3.6× 260 0.4× 1.0k 1.7× 167 5.7k
Michael J. Sheehan United States 31 834 0.3× 558 0.5× 810 1.0× 783 1.2× 68 0.1× 119 2.8k
Björn Brembs Germany 24 1.0k 0.4× 565 0.5× 623 0.8× 332 0.5× 50 0.1× 64 2.4k
Jane L. Hurst United Kingdom 55 1.6k 0.7× 1.3k 1.1× 3.2k 3.9× 869 1.3× 2.3k 3.7× 157 8.7k
Alison R. Mercer New Zealand 37 2.1k 0.9× 2.1k 1.8× 1.9k 2.3× 253 0.4× 290 0.5× 80 3.9k

Countries citing papers authored by Glenn Turner

Since Specialization
Citations

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

Fields of papers citing papers by Glenn Turner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Glenn Turner

This figure shows the co-authorship network connecting the top 25 collaborators of Glenn Turner. A scholar is included among the top collaborators of Glenn Turner 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 Glenn Turner. Glenn Turner 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.
Shuai, Yichun, Megan Sammons, Gabriella R Sterne, et al.. (2025). Driver lines for studying associative learning in Drosophila. eLife. 13. 2 indexed citations
2.
Shuai, Yichun, Megan Sammons, Gabriella R Sterne, et al.. (2024). Driver lines for studying associative learning in Drosophila. eLife. 13.
3.
Hibbard, Karen L, et al.. (2023). Reward expectations direct learning and drive operant matching in Drosophila. Proceedings of the National Academy of Sciences. 120(39). e2221415120–e2221415120. 8 indexed citations
4.
Li, Ye, et al.. (2023). Input density tunes Kenyon cell sensory responses in the Drosophila mushroom body. Current Biology. 33(13). 2742–2760.e12. 8 indexed citations
5.
Srinivasan, Shyam, et al.. (2023). Effects of stochastic coding on olfactory discrimination in flies and mice. PLoS Biology. 21(10). e3002206–e3002206. 6 indexed citations
6.
Modi, Mehrab N, et al.. (2023). Flexible specificity of memory in Drosophila depends on a comparison between choices. eLife. 12. 2 indexed citations
7.
Smith, M. A., Kyle S. Honegger, Glenn Turner, & Benjamin de Bivort. (2022). Idiosyncratic learning performance in flies. Biology Letters. 18(2). 20210424–20210424. 15 indexed citations
8.
Honegger, Kyle S., M. A. Smith, Matthew A. Churgin, Glenn Turner, & Benjamin de Bivort. (2019). Idiosyncratic neural coding and neuromodulation of olfactory individuality in Drosophila. Proceedings of the National Academy of Sciences. 117(38). 23292–23297. 44 indexed citations
9.
Hige, Toshihide, Yoshinori Aso, Gerald M. Rubin, & Glenn Turner. (2015). Plasticity-driven individualization of olfactory coding in mushroom body output neurons. Nature. 526(7572). 258–262. 91 indexed citations
10.
Campbell, Robert A. A., et al.. (2014). Openstage: A Low-Cost Motorized Microscope Stage with Sub-Micron Positioning Accuracy. PLoS ONE. 9(2). e88977–e88977. 35 indexed citations
11.
Gruntman, Eyal & Glenn Turner. (2013). Integration of the olfactory code across dendritic claws of single mushroom body neurons. Nature Neuroscience. 16(12). 1821–1829. 105 indexed citations
12.
Murthy, Mala & Glenn Turner. (2013). Whole-Cell In Vivo Patch-Clamp Recordings in the Drosophila Brain. Cold Spring Harbor Protocols. 2013(2). pdb.prot071704–pdb.prot071704. 21 indexed citations
13.
Campbell, Robert A. A. & Glenn Turner. (2010). The mushroom body. Current Biology. 20(1). R11–R12. 26 indexed citations
14.
Masse, Nicolas Y., Glenn Turner, & Gregory S.X.E. Jefferis. (2009). Olfactory Information Processing in Drosophila. Current Biology. 19(16). R700–R713. 222 indexed citations
15.
Xia, Zanxian, et al.. (2008). Amino Acids Induce Peptide Uptake via Accelerated Degradation of CUP9, the Transcriptional Repressor of the PTR2 Peptide Transporter. Journal of Biological Chemistry. 283(43). 28958–28968. 39 indexed citations
16.
Turner, Glenn, Maxim Bazhenov, & Gilles Laurent. (2007). Olfactory Representations byDrosophilaMushroom Body Neurons. Journal of Neurophysiology. 99(2). 734–746. 289 indexed citations
17.
Wilson, Rachel I., Glenn Turner, & Gilles Laurent. (2003). Transformation of Olfactory Representations in the Drosophila Antennal Lobe. Science. 303(5656). 366–370. 422 indexed citations
18.
Varshavsky, Alexander, Glenn Turner, Fangyong Du, & Youming Xie. (2000). The Ubiquitin System and the N-End Rule Pathway. Biological Chemistry. 381(9-10). 779–89. 54 indexed citations
19.
Turner, Glenn. (1999). A method in search of a theory: peer education and health promotion. Health Education Research. 14(2). 235–247. 283 indexed citations
20.
Turner, Glenn, et al.. (1993). HIV/AIDS education in further education: a survey. Health Education Research. 8(2). 287–296. 1 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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