Serge Pelet

3.3k total citations · 1 hit paper
48 papers, 2.5k citations indexed

About

Serge Pelet is a scholar working on Molecular Biology, Biophysics and Cell Biology. According to data from OpenAlex, Serge Pelet has authored 48 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 18 papers in Biophysics and 6 papers in Cell Biology. Recurrent topics in Serge Pelet's work include Gene Regulatory Network Analysis (19 papers), Fungal and yeast genetics research (18 papers) and Advanced Fluorescence Microscopy Techniques (14 papers). Serge Pelet is often cited by papers focused on Gene Regulatory Network Analysis (19 papers), Fungal and yeast genetics research (18 papers) and Advanced Fluorescence Microscopy Techniques (14 papers). Serge Pelet collaborates with scholars based in Switzerland, United States and Germany. Serge Pelet's co-authors include Michaël Grätzel, Jacques‐E. Moser, Udo Bach, Jessica Krueger, Robert Plass, Matthias Peter, Peter T. C. So, Sung Sik Lee, Heinz Koeppl and Lily H. Laiho and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Serge Pelet

47 papers receiving 2.5k citations

Hit Papers

Quantum Dot Sensitization... 2002 2026 2010 2018 2002 200 400 600

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Serge Pelet 1.1k 854 764 388 377 48 2.5k
Rob B. M. Koehorst 850 0.8× 685 0.8× 232 0.3× 405 1.0× 77 0.2× 50 1.8k
Deirdre R. Meldrum 1.1k 1.0× 694 0.8× 230 0.3× 629 1.6× 145 0.4× 116 3.3k
Marisela Vélez 1.4k 1.3× 289 0.3× 258 0.3× 579 1.5× 87 0.2× 93 2.5k
An‐An Liu 653 0.6× 679 0.8× 243 0.3× 261 0.7× 70 0.2× 77 1.8k
Iddo Heller 945 0.9× 709 0.8× 75 0.1× 824 2.1× 164 0.4× 46 2.6k
Aryeh Weiss 1.0k 1.0× 364 0.4× 76 0.1× 204 0.5× 87 0.2× 74 2.2k
Thomas Ryll 1.8k 1.7× 444 0.5× 119 0.2× 210 0.5× 63 0.2× 64 2.6k
Alexandre A. Arnold 897 0.8× 279 0.3× 101 0.1× 153 0.4× 59 0.2× 59 1.7k
Gregory A. Weiss 2.2k 2.1× 544 0.6× 52 0.1× 614 1.6× 83 0.2× 112 3.6k
Horst Pick 2.8k 2.6× 267 0.3× 65 0.1× 128 0.3× 691 1.8× 57 4.2k

Countries citing papers authored by Serge Pelet

Since Specialization
Citations

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

Fields of papers citing papers by Serge Pelet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Serge Pelet

This figure shows the co-authorship network connecting the top 25 collaborators of Serge Pelet. A scholar is included among the top collaborators of Serge Pelet 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 Serge Pelet. Serge Pelet 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.
Nadal‐Ribelles, Mariona, Carme Solé, Vincent Vincenzetti, et al.. (2025). Basal association of a transcription factor favors early gene expression. PLoS Genetics. 21(6). e1011710–e1011710.
2.
Nadal‐Ribelles, Mariona, Carme Solé, Antonin Morillon, et al.. (2025). Transcriptional heterogeneity shapes stress-adaptive responses in yeast. Nature Communications. 16(1). 2631–2631. 2 indexed citations
3.
Dusserre, Yves, et al.. (2024). Implication of polymerase recycling for nascent transcript quantification by live cell imaging. Yeast. 41(4). 279–294. 1 indexed citations
4.
Ewald, Jennifer C., et al.. (2022). Live cell microscopy: From image to insight. PubMed. 3(2). 21302–21302. 24 indexed citations
5.
Durandau, Eric & Serge Pelet. (2021). Cross‐regulation between CDK and MAPK control cellular fate. Quantitative Biology. 9(3). 341–359. 5 indexed citations
6.
Pelet, Serge, et al.. (2021). Cellular heterogeneity: yeast-side story. Fungal Biology Reviews. 39. 34–45. 7 indexed citations
7.
Hadadi, Noushin, et al.. (2021). Environmental connectivity controls diversity in soil microbial communities. Communications Biology. 4(1). 492–492. 20 indexed citations
8.
Drogen, Frank van, Nicolas Dard, Serge Pelet, et al.. (2020). Crosstalk and spatiotemporal regulation between stress-induced MAP kinase pathways and pheromone signaling in budding yeast. Cell Cycle. 19(14). 1707–1715. 14 indexed citations
9.
Ma, Min, Pino Bordignon, G. Paolo Dotto, & Serge Pelet. (2020). Visualizing cellular heterogeneity by quantifying the dynamics of MAPK activity in live mammalian cells with synthetic fluorescent biosensors. Heliyon. 6(12). e05574–e05574. 11 indexed citations
10.
Pelet, Serge, et al.. (2020). Single-particle imaging of stress-promoters induction reveals the interplay between MAPK signaling, chromatin and transcription factors. Nature Communications. 11(1). 3171–3171. 12 indexed citations
11.
Drogen, Frank van, Ranjan Kumar Mishra, Fabian Rudolf, et al.. (2019). Mechanical stress impairs pheromone signaling via Pkc1-mediated regulation of the MAPK scaffold Ste5. The Journal of Cell Biology. 218(9). 3117–3133. 10 indexed citations
12.
Solé, Carme, et al.. (2018). Timing of gene expression in a cell‐fate decision system. Molecular Systems Biology. 14(4). e8024–e8024. 28 indexed citations
13.
Durandau, Eric, et al.. (2016). New families of single integration vectors and gene tagging plasmids for genetic manipulations in budding yeast. Molecular Genetics and Genomics. 291(6). 2231–2240. 25 indexed citations
14.
Durandau, Eric, et al.. (2016). Real-time quantification of protein expression at the single-cell level via dynamic protein synthesis translocation reporters. Nature Communications. 7(1). 11304–11304. 41 indexed citations
15.
Hegemann, Björn, M. Unger, Sung Sik Lee, et al.. (2015). A Cellular System for Spatial Signal Decoding in Chemical Gradients. Developmental Cell. 35(4). 458–470. 40 indexed citations
16.
Pelet, Serge, et al.. (2013). Temporal Quantification of MAPK Induced Expression in Single Yeast Cells. Journal of Visualized Experiments. 4 indexed citations
17.
Koeppl, Heinz, Christoph Zechner, Arnab Ganguly, Serge Pelet, & Matthias Peter. (2012). Accounting for extrinsic variability in the estimation of stochastic rate constants. International Journal of Robust and Nonlinear Control. 22(10). 1103–1119. 17 indexed citations
18.
Pelet, Serge & Matthias Peter. (2011). Dynamic processes at stress promoters regulate the bimodal expression of HOG response genes. Communicative & Integrative Biology. 4(6). 699–702. 2 indexed citations
19.
Bauer, Christophe, Joël Teuscher, Serge Pelet, et al.. (2010). Ultrafast charge transfer through p-oligo(phenylene) bridges: effect of nonequilibrium vibrations. Current Science. 99(3). 343–352. 7 indexed citations
20.
Pelet, Serge, Michael J. R. Previte, Lily H. Laiho, & Peter T. C. So. (2004). A Fast Global Fitting Algorithm for Fluorescence Lifetime Imaging Microscopy Based on Image Segmentation. Biophysical Journal. 87(4). 2807–2817. 95 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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