Didier Cussac

5.8k total citations
99 papers, 4.8k citations indexed

About

Didier Cussac is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cell Biology. According to data from OpenAlex, Didier Cussac has authored 99 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Molecular Biology, 61 papers in Cellular and Molecular Neuroscience and 10 papers in Cell Biology. Recurrent topics in Didier Cussac's work include Receptor Mechanisms and Signaling (61 papers), Neurotransmitter Receptor Influence on Behavior (44 papers) and Neuroscience and Neuropharmacology Research (29 papers). Didier Cussac is often cited by papers focused on Receptor Mechanisms and Signaling (61 papers), Neurotransmitter Receptor Influence on Behavior (44 papers) and Neuroscience and Neuropharmacology Research (29 papers). Didier Cussac collaborates with scholars based in France, Germany and Poland. Didier Cussac's co-authors include Adrian Newman‐Tancredi, Mark J. Millan, Mark J. Millan, Valérie Pasteau, Valérie Audinot, Alain P. Gobert, Jean A. Boutin, Jean‐Michel Rivet, F. Lejeune and Pierre Teilhard de Chardin and has published in prestigious journals such as Journal of Biological Chemistry, The EMBO Journal and Journal of Molecular Biology.

In The Last Decade

Didier Cussac

99 papers receiving 4.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Didier Cussac France 37 2.4k 2.3k 480 465 444 99 4.8k
Aaron Janowsky United States 43 2.6k 1.0× 3.5k 1.5× 381 0.8× 649 1.4× 438 1.0× 129 5.5k
Valérie Audinot France 37 2.1k 0.9× 2.5k 1.0× 349 0.7× 359 0.8× 417 0.9× 98 4.7k
Carme Lluı́s Spain 52 4.4k 1.8× 4.2k 1.8× 676 1.4× 828 1.8× 283 0.6× 108 7.7k
Gonzalo E. Torres United States 33 2.3k 0.9× 2.5k 1.1× 523 1.1× 155 0.3× 321 0.7× 68 4.6k
Klaus Fink Germany 39 4.0k 1.6× 2.8k 1.2× 721 1.5× 364 0.8× 408 0.9× 82 7.4k
Sammanda Ramamoorthy United States 42 3.5k 1.4× 3.7k 1.6× 242 0.5× 422 0.9× 412 0.9× 96 6.9k
Tae‐Cheon Kang South Korea 38 2.5k 1.0× 1.9k 0.8× 271 0.6× 322 0.7× 671 1.5× 271 5.4k
Anthony S. Basile United States 45 2.4k 1.0× 2.8k 1.2× 364 0.8× 626 1.3× 386 0.9× 148 6.0k
Giambattista Bonanno Italy 45 3.1k 1.3× 3.4k 1.4× 836 1.7× 529 1.1× 260 0.6× 204 6.8k
Carmen Lluís Spain 45 3.3k 1.4× 2.8k 1.2× 221 0.5× 637 1.4× 201 0.5× 86 5.6k

Countries citing papers authored by Didier Cussac

Since Specialization
Citations

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

Fields of papers citing papers by Didier Cussac

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Didier Cussac

This figure shows the co-authorship network connecting the top 25 collaborators of Didier Cussac. A scholar is included among the top collaborators of Didier Cussac 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 Didier Cussac. Didier Cussac 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.
Heusler, Peter, et al.. (2017). Contribution of muscarinic receptors to in vitro and in vivo effects of Ruscus extract. Microvascular Research. 114. 1–11. 14 indexed citations
3.
Auclair, Agnès L., J.-C. Martel, M.B. Assié, et al.. (2013). Levomilnacipran (F2695), a norepinephrine-preferring SNRI: Profile in vitro and in models of depression and anxiety. Neuropharmacology. 70. 338–347. 84 indexed citations
4.
Vispé, Stéphane, Laurent Créancier, Jesper Q. Svejstrup, et al.. (2009). Triptolide is an inhibitor of RNA polymerase I and II–dependent transcription leading predominantly to down-regulation of short-lived mRNA. Molecular Cancer Therapeutics. 8(10). 2780–2790. 141 indexed citations
5.
Martel, Jean‐Claude, et al.. (2007). WAY-100635 has high selectivity for serotonin 5-HT1A versus dopamine D4 receptors. European Journal of Pharmacology. 574(1). 15–19. 41 indexed citations
6.
Boutet-Robinet, Élisa, et al.. (2007). Differential profile of typical, atypical and third generation antipsychotics at human 5-HT7a receptors coupled to adenylyl cyclase: detection of agonist and inverse agonist properties. Naunyn-Schmiedeberg s Archives of Pharmacology. 376(1-2). 93–105. 24 indexed citations
7.
Heusler, Peter, et al.. (2007). Antipsychotics differ in their ability to internalise human dopamine D2S and human serotonin 5-HT1A receptors in HEK293 cells. European Journal of Pharmacology. 581(1-2). 37–46. 24 indexed citations
8.
Martel, Jean‐Claude, et al.. (2006). Native Rat Hippocampal 5-HT1A Receptors Show Constitutive Activity. Molecular Pharmacology. 71(3). 638–643. 33 indexed citations
9.
Heusler, Peter, Petrus J. Pauwels, Thierry Wurch, et al.. (2005). Differential ion current activation by human 5-HT1A receptors in Xenopus oocytes: Evidence for agonist-directed trafficking of receptor signalling. Neuropharmacology. 49(7). 963–976. 18 indexed citations
10.
Newman‐Tancredi, Adrian, Jean‐Michel Rivet, Didier Cussac, et al.. (2003). Comparison of hippocampal G protein activation by 5-HT 1A receptor agonists and the atypical antipsychotics clozapine and S16924. Naunyn-Schmiedeberg s Archives of Pharmacology. 368(3). 188–199. 27 indexed citations
11.
12.
13.
Millan, Mark J., et al.. (2001). Agonist properties of pindolol at h5-HT1A receptors coupled to mitogen-activated protein kinase. European Journal of Pharmacology. 424(1). 13–17. 13 indexed citations
14.
Millan, Mark J., Alain P. Gobert, Jean‐Michel Rivet, et al.. (2000). Mirtazapine enhances frontocortical dopaminergic and corticolimbic adrenergic, but not serotonergic, transmission by blockade of α2‐adrenergic and serotonin2C receptors: a comparison with citalopram. European Journal of Neuroscience. 12(3). 1079–1095. 139 indexed citations
16.
Cussac, Didier, et al.. (2000). [ 3 H]S33084: a novel, selective and potent radioligand at cloned, human dopamine D 3 receptors. Naunyn-Schmiedeberg s Archives of Pharmacology. 361(5). 569–572. 15 indexed citations
17.
Newman‐Tancredi, Adrian, Didier Cussac, Valérie Audinot, & Mark J. Millan. (1999). Actions of roxindole at recombinant human dopamine D2, D3 and D4 and serotonin 5-HT1A, 5-HT1B and 5-HT1D receptors. Naunyn-Schmiedeberg s Archives of Pharmacology. 359(6). 447–453. 22 indexed citations
18.
Dubuffet, Thierry, Adrian Newman‐Tancredi, Didier Cussac, et al.. (1999). Novel benzopyrano[3,4-c]pyrrole derivatives as potent and selective dopamine D3 receptor antagonists. Bioorganic & Medicinal Chemistry Letters. 9(14). 2059–2064. 66 indexed citations
19.
Popoff, Michel R., Esteban Chaves‐Olarte, Emmanuel Lemichez, et al.. (1996). Ras, Rap, and Rac Small GTP-binding Proteins Are Targets for Clostridium sordellii Lethal Toxin Glucosylation. Journal of Biological Chemistry. 271(17). 10217–10224. 175 indexed citations
20.
Chardin, Pierre Teilhard de, Didier Cussac, S. Maignan, & A. Ducruix. (1995). The Grb2 adaptor. FEBS Letters. 369(1). 47–51. 115 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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