Reto Stöcklin

5.0k total citations · 1 hit paper
73 papers, 3.9k citations indexed

About

Reto Stöcklin is a scholar working on Molecular Biology, Genetics and Microbiology. According to data from OpenAlex, Reto Stöcklin has authored 73 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Molecular Biology, 28 papers in Genetics and 15 papers in Microbiology. Recurrent topics in Reto Stöcklin's work include Venomous Animal Envenomation and Studies (27 papers), Nicotinic Acetylcholine Receptors Study (27 papers) and Antimicrobial Peptides and Activities (15 papers). Reto Stöcklin is often cited by papers focused on Venomous Animal Envenomation and Studies (27 papers), Nicotinic Acetylcholine Receptors Study (27 papers) and Antimicrobial Peptides and Activities (15 papers). Reto Stöcklin collaborates with scholars based in Switzerland, France and Germany. Reto Stöcklin's co-authors include Philippe Bulet, Laure Menin, Philippe Favreau, Daniel Biass, Sébastien Dutertre, Roberto Montesano, Lelio Orci, J D Vassalli, Michael S. Pepper and Robin E. Offord and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Reto Stöcklin

71 papers receiving 3.7k citations

Hit Papers

Anti‐microbial peptides: ... 2004 2026 2011 2018 2004 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Reto Stöcklin Switzerland 30 2.3k 1.1k 1.0k 711 595 73 3.9k
Quentin Kaas Australia 41 4.8k 2.0× 595 0.5× 610 0.6× 1.3k 1.8× 280 0.5× 105 5.9k
Daniel C. Pimenta Brazil 32 1.6k 0.7× 580 0.5× 1.1k 1.1× 235 0.3× 356 0.6× 192 3.4k
Maria Elena de Lima Brazil 30 1.8k 0.7× 553 0.5× 1.7k 1.6× 173 0.2× 442 0.7× 131 2.7k
Günther Kreil Austria 34 2.3k 1.0× 687 0.6× 572 0.6× 305 0.4× 429 0.7× 63 3.9k
Antônio Carlos Martins de Camargo Brazil 39 2.4k 1.0× 477 0.4× 1.9k 1.8× 148 0.2× 187 0.3× 137 4.4k
Marcelo Valle de Sousa Brazil 31 1.3k 0.6× 230 0.2× 696 0.7× 237 0.3× 374 0.6× 145 3.0k
Adriano M.C. Pimenta Brazil 29 1.4k 0.6× 384 0.3× 1.3k 1.3× 103 0.1× 248 0.4× 98 2.4k
José G. Gavilanes Spain 36 2.5k 1.1× 277 0.2× 461 0.4× 1.6k 2.2× 264 0.4× 194 4.5k
Fernando Z. Zamudio Mexico 33 2.4k 1.0× 581 0.5× 2.3k 2.2× 243 0.3× 391 0.7× 110 3.1k
Erich M. Schwarz United States 33 3.2k 1.4× 227 0.2× 836 0.8× 319 0.4× 161 0.3× 61 5.1k

Countries citing papers authored by Reto Stöcklin

Since Specialization
Citations

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

Fields of papers citing papers by Reto Stöcklin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Reto Stöcklin

This figure shows the co-authorship network connecting the top 25 collaborators of Reto Stöcklin. A scholar is included among the top collaborators of Reto Stöcklin 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 Reto Stöcklin. Reto Stöcklin 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.
Violette, Aude, et al.. (2016). Advances in venomics. Molecular BioSystems. 12(12). 3530–3543. 46 indexed citations
3.
Puillandre, Nicolas, et al.. (2014). When everything converges: Integrative taxonomy with shell, DNA and venomic data reveals Conus conco, a new species of cone snails (Gastropoda: Conoidea). Molecular Phylogenetics and Evolution. 80. 186–192. 19 indexed citations
4.
Rödel, Mark‐Oliver, Christian Brede, Mareike Hirschfeld, et al.. (2013). Chemical Camouflage– A Frog's Strategy to Co-Exist with Aggressive Ants. PLoS ONE. 8(12). e81950–e81950. 15 indexed citations
5.
Koua, Dominique, Lauris Kaplinski, Reto Stöcklin, et al.. (2013). Position-specific scoring matrix and hidden Markov model complement each other for the prediction of conopeptide superfamilies. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1834(4). 717–724. 14 indexed citations
6.
Koua, Dominique, Age Brauer, Lauris Kaplinski, et al.. (2012). ConoDictor: a tool for prediction of conopeptide superfamilies. Nucleic Acids Research. 40(W1). W238–W241. 28 indexed citations
7.
Harvey, Alan L. & Reto Stöcklin. (2011). From venoms to drugs: Introduction. Toxicon. 59(4). 433–433. 2 indexed citations
8.
Dutertre, Sébastien, Daniel Biass, Reto Stöcklin, & Philippe Favreau. (2010). Dramatic intraspecimen variations within the injected venom of Conus consors: An unsuspected contribution to venom diversity. Toxicon. 55(8). 1453–1462. 61 indexed citations
9.
Biass, Daniel, Sébastien Dutertre, Jean‐Louis Menou, et al.. (2009). Comparative proteomic study of the venom of the piscivorous cone snail Conus consors. Journal of Proteomics. 72(2). 210–218. 67 indexed citations
11.
Fogli, Anne, Lynne Thadikkaran, Patricia Combes, et al.. (2006). Peptidomics and proteomics studies of transformed lymphocytes from patients mutated for the eukaryotic initiation factor 2B☆. Journal of Chromatography B. 840(1). 20–28. 3 indexed citations
12.
Monod, Michel, Barbara Léchenne, Olivier Jousson, et al.. (2005). Aminopeptidases and dipeptidyl-peptidases secreted by the dermatophyte Trichophyton rubrum. Microbiology. 151(1). 145–155. 69 indexed citations
13.
Menin, Laure, et al.. (2005). The Potential of <i>Bothrops moojeni</i> Venom in the Field of Hemostasis. Pathophysiology of Haemostasis and Thrombosis. 34(4-5). 241–245. 18 indexed citations
15.
Bulet, Philippe, Reto Stöcklin, & Laure Menin. (2004). Anti‐microbial peptides: from invertebrates to vertebrates. Immunological Reviews. 198(1). 169–184. 879 indexed citations breakdown →
16.
Favreau, Philippe, et al.. (2003). Profiling and in vivo Quantification of Proteins by High Resolution Mass Spectrometry: The Example of Goserelin, an Analogue of Luteinizing Hormone-Releasing Hormone. Clinical Chemistry and Laboratory Medicine (CCLM). 41(12). 1589–98. 10 indexed citations
17.
Urvoas, Agathe, Badia Amekraz, Christophe Moulin, et al.. (2003). Analysis of the metal‐binding selectivity of the metallochaperone CopZ from Enterococcus hirae by electrospray ionization mass spectrometry. Rapid Communications in Mass Spectrometry. 17(16). 1889–1896. 31 indexed citations
18.
Stöcklin, Reto, et al.. (2003). Identification of Snake Species by Toxin Mass Fingerprinting of Their Venoms. Humana Press eBooks. 146. 317–335. 20 indexed citations
19.
Castañeda, Olga, Ana Marı́a Amor, Reto Stöcklin, et al.. (1995). Characterization of a potassium channel toxin from the Caribbean sea anemone Stichodactyla helianthus. Toxicon. 33(5). 603–613. 231 indexed citations
20.
Vu, Lan Phuong, Reto Stöcklin, Keith Rose, & Robin E. Offord. (1993). Facile identification by electrospray mass spectrometry of the insulin fragment A14–21‐B17–30 produced by insulin proteinase. Rapid Communications in Mass Spectrometry. 7(11). 1048–1050. 3 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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