Bertram Gerber

6.4k total citations · 1 hit paper
96 papers, 4.2k citations indexed

About

Bertram Gerber is a scholar working on Cellular and Molecular Neuroscience, Insect Science and Genetics. According to data from OpenAlex, Bertram Gerber has authored 96 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Cellular and Molecular Neuroscience, 49 papers in Insect Science and 33 papers in Genetics. Recurrent topics in Bertram Gerber's work include Neurobiology and Insect Physiology Research (84 papers), Insect Utilization and Effects (34 papers) and Insect and Arachnid Ecology and Behavior (33 papers). Bertram Gerber is often cited by papers focused on Neurobiology and Insect Physiology Research (84 papers), Insect Utilization and Effects (34 papers) and Insect and Arachnid Ecology and Behavior (33 papers). Bertram Gerber collaborates with scholars based in Germany, United States and Switzerland. Bertram Gerber's co-authors include Reinhard F. Stocker, Hiromu Tanimoto, Randolf Menzel, Martin Heisenberg, Thomas Hendel, Andreas S. Thum, Michael Schleyer, Ayse Yarali, Timo Saumweber and André Fiala and has published in prestigious journals such as Nature, Nature Communications and Journal of Neuroscience.

In The Last Decade

Bertram Gerber

93 papers receiving 4.1k citations

Hit Papers

The complete connectome of a learning and memory centre i... 2017 2026 2020 2023 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bertram Gerber Germany 39 3.4k 1.7k 1.3k 1.3k 543 96 4.2k
Allan M. Wong United States 26 4.3k 1.2× 1.8k 1.0× 941 0.7× 1.3k 1.0× 312 0.6× 33 5.5k
Hiromu Tanimoto Japan 39 5.0k 1.5× 2.3k 1.4× 1.1k 0.9× 1.5k 1.2× 717 1.3× 85 6.0k
Jing W. Wang United States 29 4.6k 1.3× 1.8k 1.1× 1.1k 0.9× 1.3k 1.0× 500 0.9× 56 5.3k
Gregory S.X.E. Jefferis United Kingdom 36 4.4k 1.3× 2.1k 1.3× 1.0k 0.8× 1.5k 1.2× 355 0.7× 64 5.4k
Scott Waddell United Kingdom 42 5.3k 1.5× 2.5k 1.5× 1.3k 1.0× 1.6k 1.3× 894 1.6× 77 6.8k
Joel D. Levine Canada 38 2.5k 0.7× 1.8k 1.1× 842 0.7× 1.5k 1.2× 223 0.4× 80 4.8k
Thomas Préat France 41 4.0k 1.2× 1.7k 1.0× 869 0.7× 1.1k 0.9× 648 1.2× 96 6.0k
Uwe Homberg Germany 54 7.8k 2.3× 3.6k 2.1× 1.5k 1.2× 2.6k 2.1× 604 1.1× 150 8.5k
Kristin Scott United States 32 4.1k 1.2× 1.4k 0.8× 1.2k 0.9× 1000 0.8× 525 1.0× 58 4.9k
Makoto Mizunami Japan 35 2.8k 0.8× 1.8k 1.1× 1.1k 0.8× 1.4k 1.1× 213 0.4× 117 3.4k

Countries citing papers authored by Bertram Gerber

Since Specialization
Citations

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

Fields of papers citing papers by Bertram Gerber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bertram Gerber

This figure shows the co-authorship network connecting the top 25 collaborators of Bertram Gerber. A scholar is included among the top collaborators of Bertram Gerber 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 Bertram Gerber. Bertram Gerber 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
2.
Pauls, Dennis, Oded Mayseless, Martin Strauch, et al.. (2023). Rewarding Capacity of Optogenetically Activating a Giant GABAergic Central-Brain Interneuron in Larval Drosophila. Journal of Neuroscience. 43(44). 7393–7428. 1 indexed citations
3.
König, Christian & Bertram Gerber. (2022). Age-related decrease in appetitive associative memory in fruit flies. Journal of Experimental Biology. 225(21). 3 indexed citations
4.
Gerber, Bertram, et al.. (2022). Optogenetically induced reward and ‘frustration’ memory in larval Drosophila melanogaster. Journal of Experimental Biology. 225(16). 4 indexed citations
5.
Kobler, Oliver, et al.. (2021). A quick and versatile protocol for the 3D visualization of transgene expression across the whole body of larval Drosophila. Journal of Neurogenetics. 35(3). 306–319. 4 indexed citations
6.
Eschbach, Claire, Akira Fushiki, Michael Winding, et al.. (2020). Recurrent architecture for adaptive regulation of learning in the insect brain. Nature Neuroscience. 23(4). 544–555. 89 indexed citations
7.
Schleyer, Michael, et al.. (2020). Aversive teaching signals from individual dopamine neurons in larval Drosophila show qualitative differences in their temporal “fingerprint”. The Journal of Comparative Neurology. 529(7). 1553–1570. 9 indexed citations
8.
Schleyer, Michael, Martin Strauch, Volker Hartenstein, et al.. (2020). Identification of Dopaminergic Neurons That Can Both Establish Associative Memory and Acutely Terminate Its Behavioral Expression. Journal of Neuroscience. 40(31). 5990–6006. 17 indexed citations
9.
Boetzl, Fabian A., et al.. (2019). An amino-acid mixture can be both rewarding and punishing to larval Drosophila. Journal of Experimental Biology. 6 indexed citations
10.
Croset, Vincent, Michael Schleyer, J. Roman Arguello, Bertram Gerber, & Richard Benton. (2016). A molecular and neuronal basis for amino acid sensing in the Drosophila larva. Scientific Reports. 6(1). 34871–34871. 94 indexed citations
11.
Chen, Yi‐Chun, Birgit Michels, Timo Saumweber, et al.. (2015). Synapsin is required to “boost” memory strength for highly salient events. Learning & Memory. 23(1). 9–20. 14 indexed citations
12.
Schleyer, Michael, Samuel F. Reid, Timo Saumweber, et al.. (2015). The impact of odor–reward memory on chemotaxis in larval Drosophila. Learning & Memory. 22(5). 267–277. 27 indexed citations
13.
Sadanandappa, Madhumala K., Beatriz Blanco-Redondo, Birgit Michels, et al.. (2013). Synapsin Function in GABA-ergic Interneurons Is Required for Short-Term Olfactory Habituation. Journal of Neuroscience. 33(42). 16576–16585. 29 indexed citations
14.
Eschbach, Claire, et al.. (2011). Associative learning between odorants and mechanosensory punishment in larval Drosophila. Journal of Experimental Biology. 214(23). 3897–3905. 20 indexed citations
15.
Yarali, Ayse, Markus Krischke, Birgit Michels, et al.. (2008). Genetic Distortion of the Balance between Punishment and Relief Learning in Drosophila. Journal of Neurogenetics. 23(1-2). 235–247. 36 indexed citations
16.
Niewalda, Thomas, Nidhi Singhal, André Fiala, et al.. (2008). Salt Processing in Larval Drosophila: Choice, Feeding, and Learning Shift from Appetitive to Aversive in a Concentration-Dependent Way. Chemical Senses. 33(8). 685–692. 60 indexed citations
17.
Gerber, Bertram, et al.. (2007). Ausblick/Impressum. e-Neuroforum. 13(2). 78–80.
18.
Schroll, Christian, Thomas Riemensperger, Daniel Bucher, et al.. (2006). Light-Induced Activation of Distinct Modulatory Neurons Triggers Appetitive or Aversive Learning in Drosophila Larvae. Current Biology. 16(17). 1741–1747. 436 indexed citations
19.
Tanimoto, Hiromu, Martin Heisenberg, & Bertram Gerber. (2004). Event timing turns punishment to reward. Nature. 430(7003). 983–983. 156 indexed citations
20.
Gerber, Bertram. (1990). Note on the occurrence of Paravespula germanica (Hymenoptera: Vespidae) in the Lower Fraser Valley of British Columbia. Biodiversity Heritage Library (Smithsonian Institution). 87(87). 73–74. 2 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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