Michael Kunst

3.2k total citations
19 papers, 767 citations indexed

About

Michael Kunst is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Michael Kunst has authored 19 papers receiving a total of 767 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cellular and Molecular Neuroscience, 5 papers in Molecular Biology and 5 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Michael Kunst's work include Neurobiology and Insect Physiology Research (12 papers), Circadian rhythm and melatonin (4 papers) and Zebrafish Biomedical Research Applications (4 papers). Michael Kunst is often cited by papers focused on Neurobiology and Insect Physiology Research (12 papers), Circadian rhythm and melatonin (4 papers) and Zebrafish Biomedical Research Applications (4 papers). Michael Kunst collaborates with scholars based in United States, Germany and France. Michael Kunst's co-authors include Michael N. Nitabach, Davide Raccuglia, Guan Cao, Vincent A. Pieribone, Jelena Platiša, Herwig Baier, Eva Laurell, Ralf Heinrich, Michael E. Hughes and Gregory V. Barnett and has published in prestigious journals such as Cell, Nature Communications and Neuron.

In The Last Decade

Michael Kunst

18 papers receiving 760 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Kunst United States 14 527 212 190 155 140 19 767
Miri K. VanHoven United States 9 620 1.2× 346 1.6× 110 0.6× 509 3.3× 110 0.8× 13 1.3k
Tod R. Thiele United States 16 543 1.0× 545 2.6× 234 1.2× 392 2.5× 305 2.2× 20 1.5k
Johannes Larsch Germany 12 239 0.5× 247 1.2× 152 0.8× 206 1.3× 162 1.2× 14 860
Serge Faumont United States 18 496 0.9× 652 3.1× 139 0.7× 206 1.3× 58 0.4× 23 1.3k
Karen Erbguth Germany 8 644 1.2× 176 0.8× 85 0.4× 191 1.2× 33 0.2× 8 831
Alex S. Mauss Germany 14 834 1.6× 85 0.4× 184 1.0× 310 2.0× 100 0.7× 17 954
Christopher J. Tabone United States 8 476 0.9× 99 0.5× 80 0.4× 335 2.2× 98 0.7× 12 953
Anita Dittrich Denmark 7 697 1.3× 72 0.3× 104 0.5× 399 2.6× 78 0.6× 14 874
Sunhoe Bang South Korea 11 582 1.1× 285 1.3× 48 0.3× 170 1.1× 48 0.3× 13 813
Martin Schwärzel Germany 13 746 1.4× 90 0.4× 59 0.3× 521 3.4× 158 1.1× 20 1.0k

Countries citing papers authored by Michael Kunst

Since Specialization
Citations

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

Fields of papers citing papers by Michael Kunst

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Kunst

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Kunst. A scholar is included among the top collaborators of Michael Kunst 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 Michael Kunst. Michael Kunst 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.
Kunst, Michael, Shenqin Yao, Nicholas A. Lusk, et al.. (2025). Data-driven fine-grained region discovery in the mouse brain with transformers. Nature Communications. 16(1). 8536–8536.
2.
Trouvé, Alain, Laurent Younès, Michael Kunst, et al.. (2024). Cross-modality mapping using image varifolds to align tissue-scale atlases to molecular-scale measures with application to 2D brain sections. Nature Communications. 15(1). 3530–3530. 3 indexed citations
3.
Shainer, Inbal, Eva Laurell, Shachar Sherman, et al.. (2023). A single-cell resolution gene expression atlas of the larval zebrafish brain. Science Advances. 9(8). eade9909–eade9909. 34 indexed citations
4.
Tubiana, Jérôme, Michael Kunst, Herwig Baier, et al.. (2023). Neural assemblies uncovered by generative modeling explain whole-brain activity statistics and reflect structural connectivity. eLife. 12. 14 indexed citations
5.
Pantoja, Carlos, Johannes Larsch, Eva Laurell, et al.. (2020). Rapid Effects of Selection on Brain-wide Activity and Behavior. Current Biology. 30(18). 3647–3656.e3. 21 indexed citations
6.
Kunst, Michael, Eva Laurell, Fumi Kubo, et al.. (2019). A Cellular-Resolution Atlas of the Larval Zebrafish Brain. Neuron. 103(1). 21–38.e5. 149 indexed citations
7.
Kunst, Michael, Eva Laurell, Fumi Kubo, et al.. (2018). A Cellular-Resolution Atlas of the Larval Zebrafish Brain. SSRN Electronic Journal. 6 indexed citations
8.
Goda, Tadahiro, Yujiro Umezaki, Michelle Chu, et al.. (2016). DrosophilaDH31 Neuropeptide and PDF Receptor Regulate Night-Onset Temperature Preference. Journal of Neuroscience. 36(46). 11739–11754. 45 indexed citations
9.
Raccuglia, Davide, Li Yan McCurdy, Mahmut Demir, et al.. (2016). Presynaptic GABA Receptors Mediate Temporal Contrast Enhancement inDrosophilaOlfactory Sensory Neurons and Modulate Odor-Driven Behavioral Kinetics. eNeuro. 3(4). ENEURO.0080–16.2016. 18 indexed citations
10.
Li, Jiajia, et al.. (2016). Achilles is a circadian clock-controlled gene that regulates immune function in Drosophila. Brain Behavior and Immunity. 61. 127–136. 18 indexed citations
11.
Kunst, Michael, et al.. (2014). Rhythmic control of activity and sleep by class B1 GPCRs. Critical Reviews in Biochemistry and Molecular Biology. 50(1). 18–30. 15 indexed citations
12.
Kunst, Michael, Michael E. Hughes, Davide Raccuglia, et al.. (2014). Calcitonin Gene-Related Peptide Neurons Mediate Sleep-Specific Circadian Output in Drosophila. Current Biology. 24(22). 2652–2664. 147 indexed citations
13.
Cao, Guan, Jelena Platiša, Vincent A. Pieribone, et al.. (2013). Genetically Targeted Optical Electrophysiology in Intact Neural Circuits. Cell. 154(4). 904–913. 194 indexed citations
14.
Heinrich, Ralf, et al.. (2012). Reproduction-Related Sound Production of Grasshoppers Regulated by Internal State and Actual Sensory Environment. Frontiers in Neuroscience. 6. 89–89. 7 indexed citations
15.
Kunst, Michael, et al.. (2011). Neurochemical Architecture of the Central Complex Related to Its Function in the Control of Grasshopper Acoustic Communication. PLoS ONE. 6(9). e25613–e25613. 19 indexed citations
16.
Kunst, Michael, et al.. (2009). In vivo labeling and in vitro characterisation of central complex neurons involved in the control of sound production. Journal of Neuroscience Methods. 183(2). 202–212. 6 indexed citations
17.
Kunst, Michael, et al.. (2008). Suppression of grasshopper sound production by nitric oxide-releasing neurons of the central complex. Journal of Comparative Physiology A. 194(8). 763–776. 19 indexed citations
18.
Hoffmann, Kirsten, et al.. (2007). Muscarinic Excitation in Grasshopper Song Control Circuits Is Limited by Acetylcholinesterase Activity. ZOOLOGICAL SCIENCE. 24(10). 1028–1035. 22 indexed citations
19.
Wenzel, Beate, et al.. (2005). Nitric oxide/cyclic guanosine monophosphate signaling in the central complex of the grasshopper brain inhibits singing behavior. The Journal of Comparative Neurology. 488(2). 129–139. 30 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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