Lucie Delemotte

3.9k total citations · 1 hit paper
84 papers, 2.3k citations indexed

About

Lucie Delemotte is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Lucie Delemotte has authored 84 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Molecular Biology, 31 papers in Cellular and Molecular Neuroscience and 22 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Lucie Delemotte's work include Ion channel regulation and function (44 papers), Cardiac electrophysiology and arrhythmias (22 papers) and Neuroscience and Neuropharmacology Research (20 papers). Lucie Delemotte is often cited by papers focused on Ion channel regulation and function (44 papers), Cardiac electrophysiology and arrhythmias (22 papers) and Neuroscience and Neuropharmacology Research (20 papers). Lucie Delemotte collaborates with scholars based in Sweden, United States and France. Lucie Delemotte's co-authors include Mounir Tarek, Michael L. Klein, Annie M. Westerlund, Marina A. Kasimova, Vincenzo Carnevale, Eugene Palovcak, Werner Treptow, Michael R. Shirts, Vincenzo Carnevale and Tony Lelièvre and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Lucie Delemotte

80 papers receiving 2.3k citations

Hit Papers

Enhanced Sampling Methods... 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lucie Delemotte Sweden 29 1.6k 600 409 330 268 84 2.3k
Atsuko Yamashita Japan 25 3.1k 1.9× 1.1k 1.8× 739 1.8× 201 0.6× 62 0.2× 69 5.0k
Elisabeth P. Carpenter United Kingdom 35 2.6k 1.6× 442 0.7× 180 0.4× 115 0.3× 51 0.2× 66 3.7k
J. B. C. Findlay United Kingdom 33 3.2k 2.0× 1.1k 1.8× 198 0.5× 97 0.3× 197 0.7× 90 4.4k
José M. González‐Ros Spain 32 2.3k 1.4× 652 1.1× 173 0.4× 101 0.3× 52 0.2× 114 3.2k
Seok‐Yong Lee United States 38 2.8k 1.7× 862 1.4× 439 1.1× 104 0.3× 60 0.2× 65 4.2k
Jian Payandeh United States 26 2.9k 1.8× 1.2k 2.1× 552 1.3× 203 0.6× 22 0.1× 45 4.0k
Csaba Hetényi Hungary 30 1.9k 1.2× 207 0.3× 252 0.6× 271 0.8× 44 0.2× 94 3.4k
Péter Várnai United Kingdom 23 3.8k 2.4× 396 0.7× 88 0.2× 138 0.4× 52 0.2× 44 4.7k
Philippe Champeil France 36 3.3k 2.1× 397 0.7× 431 1.1× 173 0.5× 35 0.1× 86 4.0k
Jong Cheol Jeong United States 9 2.4k 1.5× 299 0.5× 75 0.2× 221 0.7× 50 0.2× 19 3.3k

Countries citing papers authored by Lucie Delemotte

Since Specialization
Citations

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

Fields of papers citing papers by Lucie Delemotte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lucie Delemotte

This figure shows the co-authorship network connecting the top 25 collaborators of Lucie Delemotte. A scholar is included among the top collaborators of Lucie Delemotte 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 Lucie Delemotte. Lucie Delemotte 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.
Albano, Giuseppe, et al.. (2025). PIP2-mediated oligomerization of the endosomal sodium/proton exchanger NHE9. Nature Communications. 16(1). 3055–3055. 5 indexed citations
2.
Tiemann, Johanna K. S., Rebecca J. Howard, Lucie Delemotte, et al.. (2024). MDverse, shedding light on the dark matter of molecular dynamics simulations. eLife. 12. 11 indexed citations
3.
Clatot, Jérôme, Qiansheng Liang, Shavonne L. Massey, et al.. (2024). A structurally precise mechanism links an epilepsy-associated KCNC2 potassium channel mutation to interneuron dysfunction. Proceedings of the National Academy of Sciences. 121(3). e2307776121–e2307776121. 8 indexed citations
4.
Yee, Sook Wah, Christian B. Macdonald, Jia Yang, et al.. (2024). The full spectrum of SLC22 OCT1 mutations illuminates the bridge between drug transporter biophysics and pharmacogenomics. Molecular Cell. 84(10). 1932–1947.e10. 17 indexed citations
6.
Delemotte, Lucie, et al.. (2023). Determinants of sugar-induced influx in the mammalian fructose transporter GLUT5. eLife. 12. 9 indexed citations
7.
Panel, Nicolas, Duc Duy Vo, Harald Hübner, et al.. (2023). Design of Drug Efficacy Guided by Free Energy Simulations of the β 2 ‐Adrenoceptor. Angewandte Chemie International Edition. 62(22). e202218959–e202218959. 12 indexed citations
8.
Chen, Yue, et al.. (2023). Coevolution-Driven Method for Efficiently Simulating Conformational Changes in Proteins Reveals Molecular Details of Ligand Effects in the β2AR Receptor. The Journal of Physical Chemistry B. 127(46). 9891–9904. 3 indexed citations
9.
Howard, Rebecca J., et al.. (2022). An α–π transition in S6 shapes the conformational cycle of the bacterial sodium channel NavAb. The Journal of General Physiology. 155(2). 1 indexed citations
10.
Westerlund, Annie M., et al.. (2022). Markov state modelling reveals heterogeneous drug-inhibition mechanism of Calmodulin. PLoS Computational Biology. 18(10). e1010583–e1010583. 1 indexed citations
12.
Hénin, Jérôme, Tony Lelièvre, Michael R. Shirts, Ómar Valsson, & Lucie Delemotte. (2022). Enhanced Sampling Methods for Molecular Dynamics Simulations [Article v1.0]. arXiv (Cornell University). 4(1). 1583–1583. 185 indexed citations breakdown →
13.
Ejneby, Malin Silverå, et al.. (2021). Resin-acid derivatives bind to multiple sites on the voltage-sensor domain of the Shaker potassium channel. The Journal of General Physiology. 153(4). 4 indexed citations
14.
Ghovanloo, Mohammad‐Reza, Mohamed A. Fouda, Kaveh Rayani, et al.. (2021). Cannabidiol inhibits the skeletal muscle Nav1.4 by blocking its pore and by altering membrane elasticity. The Journal of General Physiology. 153(5). 41 indexed citations
15.
Harms, Hendrik J., et al.. (2021). Functional cross-talk between phosphorylation and disease-causing mutations in the cardiac sodium channel Na v 1.5. Proceedings of the National Academy of Sciences. 118(33). 13 indexed citations
16.
Keeler, Eric G., et al.. (2021). Informing NMR experiments with molecular dynamics simulations to characterize the dominant activated state of the KcsA ion channel. The Journal of Chemical Physics. 154(16). 165102–165102. 8 indexed citations
18.
Kang, Po Wei, Annie M. Westerlund, Jingyi Shi, et al.. (2020). Calmodulin acts as a state-dependent switch to control a cardiac potassium channel opening. Science Advances. 6(50). 39 indexed citations
19.
Matricon, Pierre, et al.. (2020). Energy Landscapes Reveal Agonist Control of G Protein-Coupled Receptor Activation via Microswitches. Biochemistry. 59(7). 880–891. 44 indexed citations
20.
Elokely, Khaled M., Phanindra Velisetty, Lucie Delemotte, et al.. (2015). Understanding TRPV1 activation by ligands: Insights from the binding modes of capsaicin and resiniferatoxin. Proceedings of the National Academy of Sciences. 113(2). E137–45. 127 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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