Danilo Pietretti

912 total citations
18 papers, 656 citations indexed

About

Danilo Pietretti is a scholar working on Immunology, Molecular Biology and Ecology. According to data from OpenAlex, Danilo Pietretti has authored 18 papers receiving a total of 656 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 3 papers in Molecular Biology and 3 papers in Ecology. Recurrent topics in Danilo Pietretti's work include Aquaculture disease management and microbiota (11 papers), Immune Response and Inflammation (9 papers) and Immune Cell Function and Interaction (5 papers). Danilo Pietretti is often cited by papers focused on Aquaculture disease management and microbiota (11 papers), Immune Response and Inflammation (9 papers) and Immune Cell Function and Interaction (5 papers). Danilo Pietretti collaborates with scholars based in Netherlands, Belgium and United Kingdom. Danilo Pietretti's co-authors include Geert F. Wiegertjes, Maria Forlenza, Huub F. J. Savelkoul, M. Carla Piazzon, Alberto Falcó, D. Hoole, Inge R. Fink, Herman P. Spaink, Michael Engelbrecht Nielsen and Joanna J. Miest and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Immunology and Analytical and Bioanalytical Chemistry.

In The Last Decade

Danilo Pietretti

18 papers receiving 646 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Danilo Pietretti Netherlands 10 574 148 64 61 43 18 656
Taoshan Ai China 14 422 0.7× 127 0.9× 104 1.6× 38 0.6× 46 1.1× 18 507
Xiang-Yang Zhang China 13 402 0.7× 144 1.0× 124 1.9× 42 0.7× 41 1.0× 31 516
Eakapol Wangkahart Thailand 10 354 0.6× 108 0.7× 64 1.0× 33 0.5× 30 0.7× 19 475
Kai Luo China 17 392 0.7× 194 1.3× 115 1.8× 27 0.4× 27 0.6× 51 602
Liguo Ding China 11 595 1.0× 201 1.4× 145 2.3× 47 0.8× 90 2.1× 15 666
Madhubanti Basu India 20 870 1.5× 131 0.9× 139 2.2× 110 1.8× 69 1.6× 30 1.0k
Xiaojun Zhang China 13 322 0.6× 79 0.5× 98 1.5× 24 0.4× 44 1.0× 31 459
Houjun Pan China 10 330 0.6× 74 0.5× 83 1.3× 27 0.4× 87 2.0× 21 434
Ei Lin Ooi Japan 11 504 0.9× 232 1.6× 91 1.4× 30 0.5× 47 1.1× 12 586
Silas Fernandes Eto Brazil 12 253 0.4× 124 0.8× 76 1.2× 47 0.8× 42 1.0× 41 452

Countries citing papers authored by Danilo Pietretti

Since Specialization
Citations

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

Fields of papers citing papers by Danilo Pietretti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danilo Pietretti

This figure shows the co-authorship network connecting the top 25 collaborators of Danilo Pietretti. A scholar is included among the top collaborators of Danilo Pietretti 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 Danilo Pietretti. Danilo Pietretti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Ghidotti, Michele, Marc Behr, Danilo Pietretti, et al.. (2025). High rate of safety and fraud issues in commercially available cinnamon. npj Science of Food. 9(1). 125–125. 1 indexed citations
2.
Behr, Marc, Linda Garlant, Danilo Pietretti, et al.. (2024). A robust set of qPCR methods to evaluate adulteration in major spices and herbs. Food Control. 165. 110623–110623. 5 indexed citations
3.
Lievens, Antoon, Valentina Paracchini, Linda Garlant, et al.. (2023). Detection and Quantification of Botanical Impurities in Commercial Oregano (Origanum vulgare) Using Metabarcoding and Digital PCR. Foods. 12(16). 2998–2998. 3 indexed citations
4.
Ghidotti, Michele, et al.. (2023). Use of elemental profiles determined by energy-dispersive X-ray fluorescence and multivariate analyses to detect adulteration in Ceylon cinnamon. Analytical and Bioanalytical Chemistry. 415(22). 5437–5449. 13 indexed citations
5.
Lievens, Antoon, Valentina Paracchini, Danilo Pietretti, et al.. (2021). DNA Accounting: Tallying Genomes to Detect Adulterated Saffron. Foods. 10(11). 2670–2670. 3 indexed citations
6.
Mercier, Ingrid, Céline Cougoule, Danilo Pietretti, et al.. (2017). C-type lectin receptor DCIR modulates immunity to tuberculosis by sustaining type I interferon signaling in dendritic cells. Proceedings of the National Academy of Sciences. 114(4). E540–E549. 54 indexed citations
7.
Fink, Inge R., Danilo Pietretti, Adrie H. Westphal, et al.. (2016). Molecular and functional characterization of Toll-like receptor (Tlr)1 and Tlr2 in common carp ( Cyprinus carpio ). Fish & Shellfish Immunology. 56. 70–83. 45 indexed citations
8.
Fink, Inge R., Maria Forlenza, Danilo Pietretti, & Geert F. Wiegertjes. (2016). Facing the challenge of a functional characterization of toll-like receptor (TLR)1 and TLR2 in common carp. Fish & Shellfish Immunology. 53. 76–76. 5 indexed citations
9.
Piazzon, M. Carla, Huub F. J. Savelkoul, Danilo Pietretti, Geert F. Wiegertjes, & Maria Forlenza. (2014). Carp Il10 Has Anti-Inflammatory Activities on Phagocytes, Promotes Proliferation of Memory T Cells, and Regulates B Cell Differentiation and Antibody Secretion. The Journal of Immunology. 194(1). 187–199. 106 indexed citations
10.
11.
Pietretti, Danilo, Herman P. Spaink, Alberto Falcó, Maria Forlenza, & Geert F. Wiegertjes. (2013). Accessory molecules for Toll-like receptors in Teleost fish. Identification of TLR4 interactor with leucine-rich repeats (TRIL). Molecular Immunology. 56(4). 745–756. 41 indexed citations
12.
Pietretti, Danilo & Geert F. Wiegertjes. (2013). Ligand specificities of Toll-like receptors in fish: Indications from infection studies. Developmental & Comparative Immunology. 43(2). 205–222. 183 indexed citations
13.
Falcó, Alberto, Joanna J. Miest, Nicolas Pionnier, et al.. (2013). β-Glucan-supplemented diets increase poly(I:C)-induced gene expression of Mx, possibly via Tlr3-mediated recognition mechanism in common carp (Cyprinus carpio). Fish & Shellfish Immunology. 36(2). 494–502. 54 indexed citations
14.
Pietretti, Danilo, Maria Forlenza, Inge R. Fink, & Geert F. Wiegertjes. (2013). A closer look at Toll-like receptor 4 (TLR4) and toll-like receptor 20 (TLR20) of common carp (Cyprinus carpio). Fish & Shellfish Immunology. 34(6). 1673–1673. 4 indexed citations
15.
Pietretti, Danilo, Inge R. Fink, Nico Taverne, et al.. (2013). Identification and functional characterization of nonmammalian Toll-like receptor 20. Immunogenetics. 66(2). 123–141. 39 indexed citations
16.
17.
Fink, Inge R., Danilo Pietretti, Maria Forlenza, & Geert F. Wiegertjes. (2013). Toll-like receptor-1 and -2 in common carp. Fish & Shellfish Immunology. 34(6). 1706–1707. 1 indexed citations
18.
Falcó, Alberto, Joanna J. Miest, Nicolas Pionnier, et al.. (2013). β-glucan supplemented diets induce high and broad expression levels of TLR3 what explains protection conferred by these additives against viral infections in fish. Fish & Shellfish Immunology. 34(6). 1706–1706. 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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