Michael Lückmann

548 total citations
16 papers, 403 citations indexed

About

Michael Lückmann is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Oncology. According to data from OpenAlex, Michael Lückmann has authored 16 papers receiving a total of 403 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 7 papers in Cellular and Molecular Neuroscience and 5 papers in Oncology. Recurrent topics in Michael Lückmann's work include Receptor Mechanisms and Signaling (14 papers), Neuropeptides and Animal Physiology (7 papers) and Chemokine receptors and signaling (5 papers). Michael Lückmann is often cited by papers focused on Receptor Mechanisms and Signaling (14 papers), Neuropeptides and Animal Physiology (7 papers) and Chemokine receptors and signaling (5 papers). Michael Lückmann collaborates with scholars based in Denmark, Iran and United States. Michael Lückmann's co-authors include Thomas M. Frimurer, Thue W. Schwartz, Birgitte Holst, Andreas Nygaard Madsen, Mette Trauelsen, Michael Wright, Maria E. Trujillo, Maja S. Engelstoft, Adam B. Weinglass and Jerry Di Salvo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Michael Lückmann

16 papers receiving 397 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 Lückmann Denmark 10 268 148 123 103 60 16 403
Christina Rye Underwood Denmark 11 497 1.9× 260 1.8× 154 1.3× 222 2.2× 36 0.6× 16 653
Rudi Prihandoko United Kingdom 11 549 2.0× 67 0.5× 87 0.7× 325 3.2× 62 1.0× 13 680
Kathy Nguyen United States 5 237 0.9× 204 1.4× 217 1.8× 70 0.7× 26 0.4× 5 366
Charles Xing United States 8 211 0.8× 185 1.3× 113 0.9× 98 1.0× 15 0.3× 20 424
Amy E. Monaghan United Kingdom 8 222 0.8× 34 0.2× 55 0.4× 83 0.8× 50 0.8× 12 361
Gerd Krause Germany 11 325 1.2× 120 0.8× 38 0.3× 155 1.5× 34 0.6× 13 463
Wen Chiy Liew Singapore 2 178 0.7× 33 0.2× 50 0.4× 78 0.8× 51 0.8× 2 294
Patricio Atanes United Kingdom 11 135 0.5× 91 0.6× 124 1.0× 42 0.4× 46 0.8× 19 286
Murthy S.R. Madiraju Canada 3 309 1.2× 169 1.1× 219 1.8× 21 0.2× 157 2.6× 5 533
Dennis Norman United Kingdom 10 142 0.5× 38 0.3× 53 0.4× 30 0.3× 67 1.1× 11 382

Countries citing papers authored by Michael Lückmann

Since Specialization
Citations

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

Fields of papers citing papers by Michael Lückmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Lückmann

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Lückmann. A scholar is included among the top collaborators of Michael Lückmann 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 Lückmann. Michael Lückmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Lückmann, Michael, et al.. (2024). Multiple recent HCAR2 structures demonstrate a highly dynamic ligand binding and G protein activation mode. Nature Communications. 15(1). 6 indexed citations
2.
Lückmann, Michael, Mette Trauelsen, Matteo Lambrughi, et al.. (2024). Molecular dynamics-based identification of binding pathways and two distinct high-affinity sites for succinate in succinate receptor 1/GPR91. Molecular Cell. 84(5). 955–966.e4. 9 indexed citations
3.
Lückmann, Michael, et al.. (2022). Optimization of First-in-Class Dual-Acting FFAR1/FFAR4 Allosteric Modulators with Novel Mode of Action. ACS Medicinal Chemistry Letters. 13(12). 1839–1847. 3 indexed citations
4.
Velden, Wijnand J. C. van der, Michael Lückmann, Tobias Hansen, et al.. (2021). Investigating GIPR (ant)agonism: A structural analysis of GIP and its receptor. Structure. 29(7). 679–693.e6. 19 indexed citations
5.
Lückmann, Michael, et al.. (2021). Discovery of GPR183 Agonists Based on an Antagonist Scaffold. ChemMedChem. 16(17). 2623–2627. 8 indexed citations
6.
Lückmann, Michael, Mette Trauelsen, Thomas M. Frimurer, & Thue W. Schwartz. (2020). Structural basis for GPCR signaling by small polar versus large lipid metabolites—discovery of non-metabolite ligands. Current Opinion in Cell Biology. 63. 38–48. 18 indexed citations
7.
Lückmann, Michael, Mette Trauelsen, João M. Martins, et al.. (2019). Molecular dynamics-guided discovery of an ago-allosteric modulator for GPR40/FFAR1. Proceedings of the National Academy of Sciences. 116(14). 7123–7128. 39 indexed citations
8.
Larsen, Olav, Edith Uetz‐von Allmen, Michael Lückmann, et al.. (2019). Biased Signaling of CCL21 and CCL19 Does Not Rely on N-Terminal Differences, but Markedly on the Chemokine Core Domains and Extracellular Loop 2 of CCR7. Frontiers in Immunology. 10. 2156–2156. 16 indexed citations
9.
Larsen, Olav, Michael Lückmann, Wijnand J. C. van der Velden, et al.. (2019). Selective Allosteric Modulation of N-Terminally Cleaved, but Not Full Length CCL3 in CCR1. ACS Pharmacology & Translational Science. 2(6). 429–441. 2 indexed citations
10.
Plouffe, Bianca, Louise J. Skov, Børge Sivertsen, et al.. (2018). Translating biased signaling in the ghrelin receptor system into differential in vivo functions. Proceedings of the National Academy of Sciences. 115(43). E10255–E10264. 47 indexed citations
11.
Trauelsen, Mette, et al.. (2018). Structure-Activity Investigations and Optimisations of Non-metabolite Agonists for the Succinate Receptor 1. Scientific Reports. 8(1). 10010–10010. 16 indexed citations
12.
Lückmann, Michael, Katja Spieß, Gertrud M. Hjortø, et al.. (2018). Ligand-selective small molecule modulators of the constitutively active vGPCR US28. European Journal of Medicinal Chemistry. 155. 244–254. 9 indexed citations
13.
Madsen, Christian M., Michael Lückmann, Andreas W. Sailer, et al.. (2017). Biased agonism and allosteric modulation of G protein‐coupled receptor 183 – a 7TM receptor also known as Epstein–Barr virus‐induced gene 2. British Journal of Pharmacology. 174(13). 2031–2042. 13 indexed citations
14.
Lückmann, Michael, et al.. (2016). Role of Conserved Disulfide Bridges and Aromatic Residues in Extracellular Loop 2 of Chemokine Receptor CCR8 for Chemokine and Small Molecule Binding. Journal of Biological Chemistry. 291(31). 16208–16220. 10 indexed citations
15.
Lückmann, Michael, Birgitte Holst, Thue W. Schwartz, & Thomas M. Frimurer. (2015). In Silico Investigation of the Neurotensin Receptor 1 Binding Site: Overlapping Binding Modes for Small Molecule Antagonists and the Endogenous Peptide Agonist. Molecular Informatics. 35(1). 19–24. 9 indexed citations
16.
Hauge, M., M. A. Vestmar, Anna Sofie Husted, et al.. (2014). GPR40 (FFAR1) – Combined Gs and Gq signaling in vitro is associated with robust incretin secretagogue action ex vivo and in vivo. Molecular Metabolism. 4(1). 3–14. 179 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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