Jan Møller

760 total citations
8 papers, 401 citations indexed

About

Jan Møller is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jan Møller has authored 8 papers receiving a total of 401 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jan Møller's work include Receptor Mechanisms and Signaling (6 papers), Neuropeptides and Animal Physiology (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). Jan Møller is often cited by papers focused on Receptor Mechanisms and Signaling (6 papers), Neuropeptides and Animal Physiology (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). Jan Møller collaborates with scholars based in Germany, United States and Italy. Jan Møller's co-authors include Martin J. Lohse, Paolo Annibale, Andreas Böck, Martin Falcke, Andreas Koschinski, Manuela Zaccolo, Isabella Maiellaro, Mike Heilemann, Christof Schütte and Christos Karathanasis and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Scientific Reports.

In The Last Decade

Jan Møller

8 papers receiving 400 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jan Møller Germany	8	303	142	54	46	42	8	401
Bonnie J. Hanson United States	14	419 1.4×	148 1.0×	54 1.0×	15 0.3×	26 0.6×	20	557
Amanda J. Wheal United Kingdom	10	229 0.8×	108 0.8×	154 2.9×	21 0.5×	30 0.7×	10	429
Haibei Hu United States	9	323 1.1×	76 0.5×	14 0.3×	36 0.8×	22 0.5×	10	418
John Frazer United States	8	239 0.8×	99 0.7×	31 0.6×	14 0.3×	39 0.9×	15	361
Sara Marsango United Kingdom	14	370 1.2×	211 1.5×	17 0.3×	26 0.6×	60 1.4×	26	457
Elita Yuliantie Australia	6	381 1.3×	179 1.3×	24 0.4×	8 0.2×	52 1.2×	9	495
Jonas Kaindl Germany	12	528 1.7×	311 2.2×	23 0.4×	16 0.3×	88 2.1×	20	629
Heng B. See Australia	11	346 1.1×	139 1.0×	13 0.2×	20 0.4×	34 0.8×	14	410
Linshan Xie China	6	328 1.1×	159 1.1×	18 0.3×	7 0.2×	59 1.4×	8	471
Sébastien Blanc Belgium	6	190 0.6×	78 0.5×	29 0.5×	10 0.2×	24 0.6×	7	363

Countries citing papers authored by Jan Møller

Since Specialization

Citations

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

Fields of papers citing papers by Jan Møller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Møller

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

All Works

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8 of 8 papers shown

Maiellaro, Isabella, Jan Møller, Andreas Koschinski, et al.. (2022). Receptor-associated independent cAMP nanodomains mediate spatiotemporal specificity of GPCR signaling. Cell. 185(7). 1130–1142.e11. 109 indexed citations

Serfling, Robert, Jan Møller, Ulrike Zabel, et al.. (2021). Determination of G-protein–coupled receptor oligomerization by molecular brightness analyses in single cells. Nature Protocols. 16(3). 1419–1451. 24 indexed citations

Grätz, Lukas, et al.. (2021). A Versatile Sub-Nanomolar Fluorescent Ligand Enables NanoBRET Binding Studies and Single-Molecule Microscopy at the Histamine H₃ Receptor. Journal of Medicinal Chemistry. 64(15). 11695–11708. 24 indexed citations

Møller, Jan, Titiwat Sungkaworn, Christos Karathanasis, et al.. (2020). Single-molecule analysis reveals agonist-specific dimer formation of µ-opioid receptors. Nature Chemical Biology. 16(9). 946–954. 92 indexed citations

Møller, Jan, Marta Arimont, Vladimir Bobkov, et al.. (2020). Advanced fluorescence microscopy reveals disruption of dynamic CXCR4 dimerization by subpocket-specific inverse agonists. Proceedings of the National Academy of Sciences. 117(46). 29144–29154. 51 indexed citations

Huang, Jing, Anuradha Ramoji, Shuxia Guo, et al.. (2019). Vibrational spectroscopy as a powerful tool for follow-up immunoadsorption therapy treatment of dilated cardiomyopathy – a case report. The Analyst. 145(2). 486–496. 7 indexed citations

Provasi, Davide, Diego Prada‐Gracia, Jan Møller, et al.. (2018). Molecular details of dimerization kinetics reveal negligible populations of transient µ-opioid receptor homodimers at physiological concentrations. Scientific Reports. 8(1). 7705–7705. 39 indexed citations

Hoffmann, Matthias, Sandra Gunesch, Oliviero Marinelli, et al.. (2018). Structure–Activity Relationships and Computational Investigations into the Development of Potent and Balanced Dual-Acting Butyrylcholinesterase Inhibitors and Human Cannabinoid Receptor 2 Ligands with Pro-Cognitive in Vivo Profiles. Journal of Medicinal Chemistry. 61(4). 1646–1663. 55 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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