Mario de Bono

5.2k total citations · 1 hit paper
51 papers, 3.7k citations indexed

About

Mario de Bono is a scholar working on Aging, Endocrine and Autonomic Systems and Molecular Biology. According to data from OpenAlex, Mario de Bono has authored 51 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Aging, 30 papers in Endocrine and Autonomic Systems and 15 papers in Molecular Biology. Recurrent topics in Mario de Bono's work include Genetics, Aging, and Longevity in Model Organisms (45 papers), Circadian rhythm and melatonin (30 papers) and Neuroendocrine regulation and behavior (10 papers). Mario de Bono is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (45 papers), Circadian rhythm and melatonin (30 papers) and Neuroendocrine regulation and behavior (10 papers). Mario de Bono collaborates with scholars based in United Kingdom, United States and Austria. Mario de Bono's co-authors include Cornelia I. Bargmann, Andres V. Maricq, Karl Emanuel Busch, Lorenz A. Fenk, Candida Rogers, Juliet C. Coates, Changchun Chen, Patrick Laurent, Jonathan Hodgkin and Jan E. Kammenga and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Mario de Bono

50 papers receiving 3.7k citations

Hit Papers

Natural Variation in a Ne... 1998 2026 2007 2016 1998 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mario de Bono United Kingdom 29 2.5k 1.6k 955 781 544 51 3.7k
Scott W. Emmons United States 35 2.6k 1.0× 1.1k 0.7× 1.5k 1.6× 656 0.8× 390 0.7× 76 3.9k
David M. Raizen United States 31 1.8k 0.7× 1.8k 1.1× 529 0.6× 972 1.2× 664 1.2× 76 3.3k
David M. Miller United States 39 3.0k 1.2× 1.2k 0.8× 2.3k 2.4× 1.0k 1.3× 562 1.0× 84 4.6k
Jean‐Louis Bessereau France 34 2.5k 1.0× 850 0.5× 2.8k 3.0× 997 1.3× 389 0.7× 72 4.7k
Rebecca A. Butcher United States 29 1.6k 0.7× 943 0.6× 1.1k 1.2× 338 0.4× 199 0.4× 62 3.2k
Navin Pokala United States 17 1.2k 0.5× 853 0.5× 1.4k 1.5× 572 0.7× 242 0.4× 20 3.0k
Jesse Gray United States 21 1.3k 0.5× 991 0.6× 3.1k 3.2× 1.1k 1.4× 445 0.8× 35 5.4k
Anne C. Hart United States 40 2.4k 1.0× 1.3k 0.8× 3.0k 3.2× 1.7k 2.2× 722 1.3× 73 5.7k
Steven L. McIntire United States 21 1.3k 0.5× 774 0.5× 1.2k 1.2× 906 1.2× 399 0.7× 25 2.8k
Janet E. Richmond United States 40 2.0k 0.8× 884 0.6× 3.2k 3.4× 2.2k 2.9× 521 1.0× 96 5.5k

Countries citing papers authored by Mario de Bono

Since Specialization
Citations

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

Fields of papers citing papers by Mario de Bono

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mario de Bono. 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 Mario de Bono. The network helps show where Mario de Bono may publish in the future.

Co-authorship network of co-authors of Mario de Bono

This figure shows the co-authorship network connecting the top 25 collaborators of Mario de Bono. A scholar is included among the top collaborators of Mario de Bono 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 Mario de Bono. Mario de Bono 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.
Artan, Murat, Hanna Schoen, & Mario de Bono. (2025). Proximity labeling of DAF-16 FOXO highlights aging regulatory proteins. Nature Communications. 16(1). 11355–11355.
3.
Artan, Murat, Markus Hartl, Weiqiang Chen, & Mario de Bono. (2022). Depletion of endogenously biotinylated carboxylases enhances the sensitivity of TurboID-mediated proximity labeling in Caenorhabditis elegans. Journal of Biological Chemistry. 298(9). 102343–102343. 14 indexed citations
4.
Vallis, Yvonne, et al.. (2021). Neuronal calmodulin levels are controlled by CAMTA transcription factors. eLife. 10. 4 indexed citations
5.
Murdoch, Sharlene, Andrea F. Lopez‐Clavijo, Hanneke Okkenhaug, et al.. (2021). Neuronal HSF-1 coordinates the propagation of fat desaturation across tissues to enable adaptation to high temperatures in C. elegans. PLoS Biology. 19(11). e3001431–e3001431. 17 indexed citations
6.
Chen, Changchun, Murat Artan, Alastair Crisp, et al.. (2020). MALT-1 mediates IL-17 neural signaling to regulate C. elegans behavior, immunity and longevity. Nature Communications. 11(1). 2099–2099. 36 indexed citations
7.
Bono, Mario de, et al.. (2019). Activity-Dependent Regulation of the Proapoptotic BH3-Only Gene egl-1 in a Living Neuron Pair in Caenorhabditis elegans. G3 Genes Genomes Genetics. 9(11). 3703–3714. 3 indexed citations
8.
Sinnige, Tessa, et al.. (2019). Expression of the amyloid-β peptide in a single pair of C. elegans sensory neurons modulates the associated behavioural response. PLoS ONE. 14(5). e0217746–e0217746. 10 indexed citations
9.
Beets, Isabel, Gaotian Zhang, Lorenz A. Fenk, et al.. (2019). Natural Variation in a Dendritic Scaffold Protein Remodels Experience-Dependent Plasticity by Altering Neuropeptide Expression. Neuron. 105(1). 106–121.e10. 13 indexed citations
10.
McLachlan, Ian G., Isabel Beets, Mario de Bono, & Maxwell G. Heiman. (2018). A neuronal MAP kinase constrains growth of a Caenorhabditis elegans sensory dendrite throughout the life of the organism. PLoS Genetics. 14(6). e1007435–e1007435. 9 indexed citations
11.
Fenk, Lorenz A. & Mario de Bono. (2017). Memory of recent oxygen experience switches pheromone valence in Caenorhabditis elegans. Proceedings of the National Academy of Sciences. 114(16). 4195–4200. 27 indexed citations
12.
Itakura, Eisuke, Changchun Chen, & Mario de Bono. (2017). Purification of FLAG-tagged Secreted Proteins from Mammalian Cells. BIO-PROTOCOL. 7(15). 2 indexed citations
13.
Linneweber, Gerit Arne, Jake Jacobson, Karl Emanuel Busch, et al.. (2014). Neuronal Control of Metabolism through Nutrient-Dependent Modulation of Tracheal Branching. Cell. 156(1-2). 69–83. 58 indexed citations
14.
Fenk, Lorenz A., et al.. (2013). Cross-Modulation of Homeostatic Responses to Temperature, Oxygen and Carbon Dioxide in C. elegans. PLoS Genetics. 9(12). e1004011–e1004011. 24 indexed citations
15.
Busch, Karl Emanuel, et al.. (2011). Temperature, Oxygen, and Salt-Sensing Neurons in C. elegans Are Carbon Dioxide Sensors that Control Avoidance Behavior. Neuron. 69(6). 1099–1113. 110 indexed citations
16.
Cohen, Merav, Vincenzina Reale, Birgitta Olofsson, et al.. (2009). Coordinated Regulation of Foraging and Metabolism in C. elegans by RFamide Neuropeptide Signaling. Cell Metabolism. 9(4). 375–385. 89 indexed citations
17.
Olofsson, Birgitta & Mario de Bono. (2008). Sleep: Dozy Worms and Sleepy Flies. Current Biology. 18(5). R204–R206. 6 indexed citations
18.
Cohen, Merav, et al.. (2005). Experience-Dependent Modulation of C. elegans Behavior by Ambient Oxygen. Current Biology. 15(10). 905–917. 164 indexed citations
19.
Bono, Mario de. (2002). Molecular approaches to aggregation behavior and social attachment. Journal of Neurobiology. 54(1). 78–92. 25 indexed citations
20.
Coates, Juliet C. & Mario de Bono. (2002). Antagonistic pathways in neurons exposed to body fluid regulate social feeding in Caenorhabditis elegans. Nature. 419(6910). 925–929. 154 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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