Dario Copetti

7.9k total citations
34 papers, 1.2k citations indexed

About

Dario Copetti is a scholar working on Plant Science, Molecular Biology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Dario Copetti has authored 34 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Plant Science, 14 papers in Molecular Biology and 8 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Dario Copetti's work include Genomics and Phylogenetic Studies (9 papers), Chromosomal and Genetic Variations (7 papers) and Plant Disease Resistance and Genetics (6 papers). Dario Copetti is often cited by papers focused on Genomics and Phylogenetic Studies (9 papers), Chromosomal and Genetic Variations (7 papers) and Plant Disease Resistance and Genetics (6 papers). Dario Copetti collaborates with scholars based in United States, Switzerland and Philippines. Dario Copetti's co-authors include Rod A. Wing, Gabriele Di Gaspero, Michele Morgante, R. Testolin, Pál Kozma, Michael J. Sanderson, Simone Scalabrin, S. Hoffmann, László Kovács and Michelle M. McMahon and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Dario Copetti

31 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dario Copetti United States 15 907 456 262 244 206 34 1.2k
Graham Collins Australia 21 904 1.0× 726 1.6× 136 0.5× 195 0.8× 270 1.3× 55 1.3k
Jean‐Baptiste Leducq Canada 14 296 0.3× 474 1.0× 263 1.0× 128 0.5× 110 0.5× 23 667
D. Mendonça Portugal 13 489 0.5× 193 0.4× 165 0.6× 327 1.3× 89 0.4× 27 768
L. S. Lee Australia 6 651 0.7× 222 0.5× 133 0.5× 264 1.1× 98 0.5× 8 875
Thomas Rosleff Sörensen Germany 10 893 1.0× 625 1.4× 120 0.5× 216 0.9× 72 0.3× 11 1.2k
Véronique Decroocq France 22 1.3k 1.5× 662 1.5× 35 0.1× 180 0.7× 133 0.6× 41 1.5k
Gerhard Wenzel Germany 27 1.4k 1.6× 643 1.4× 85 0.3× 374 1.5× 70 0.3× 45 1.6k
Uri Lavi Israel 22 1.1k 1.2× 515 1.1× 102 0.4× 628 2.6× 97 0.5× 35 1.5k
Timothy A. Rinehart United States 20 586 0.6× 379 0.8× 37 0.1× 218 0.9× 188 0.9× 64 911
Gabriele Magris Italy 13 459 0.5× 166 0.4× 121 0.5× 193 0.8× 27 0.1× 20 565

Countries citing papers authored by Dario Copetti

Since Specialization
Citations

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

Fields of papers citing papers by Dario Copetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dario Copetti

This figure shows the co-authorship network connecting the top 25 collaborators of Dario Copetti. A scholar is included among the top collaborators of Dario Copetti 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 Dario Copetti. Dario Copetti 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.
Amaral, Danilo T., Cassandra N. Trier, Dario Copetti, Fernando Faria Franco, & Evandro M. Moraes. (2025). Chromosome-level genome assembly of the iconic South American mandacaru cactus (Cereus jamacaru DC, Tribe Cereeae, Cactaceae). Planta. 262(2). 42–42.
2.
Román‐Palacios, Cristian, et al.. (2025). Universal orthologs infer deep phylogenies and improve genome quality assessments. BMC Biology. 23(1). 224–224. 1 indexed citations
3.
Copetti, Dario, Roland Kölliker, Martin Mascher, et al.. (2025). Chromosome-level haplotype-resolved assembly of highly heterozygous grass genomes with PhaseGrass. Nature Communications. 17(1). 12–12.
4.
5.
6.
Kölliker, Roland, Martin Mascher, Dario Copetti, et al.. (2024). An improved chromosome-level genome assembly of perennial ryegrass (Lolium perenne L.). SHILAP Revista de lepidopterología. 2024. 1–11. 5 indexed citations
7.
8.
Manzanares, Chloé, Steven Yates, Daniel Thorogood, et al.. (2022). Fine-Mapping and Comparative Genomic Analysis Reveal the Gene Composition at the S and Z Self-incompatibility Loci in Grasses. Molecular Biology and Evolution. 40(1). 7 indexed citations
9.
Mayjonade, Baptiste, Daniel Frei, Giacomo Potente, et al.. (2022). Low-Input High-Molecular-Weight DNA Extraction for Long-Read Sequencing From Plants of Diverse Families. Frontiers in Plant Science. 13. 883897–883897. 31 indexed citations
10.
Halstead-Nussloch, Gwyneth, Tsuyoshi Tanaka, Dario Copetti, et al.. (2021). Multiple Wheat Genomes Reveal Novel Gli-2 Sublocus Location and Variation of Celiac Disease Epitopes in Duplicated α-Gliadin Genes. Frontiers in Plant Science. 12. 715985–715985. 7 indexed citations
11.
Manzanares, Chloé, Steven Yates, Dario Copetti, et al.. (2021). Identification of Candidate Genes for Self-Compatibility in Perennial Ryegrass (Lolium perenne L.). Frontiers in Plant Science. 12. 707901–707901. 14 indexed citations
12.
Paritosh, Kumar, Satish Kumar Yadava, Arundhati Mukhopadhyay, et al.. (2020). A chromosome‐scale assembly of allotetraploid Brassica juncea (AABB) elucidates comparative architecture of the A and B genomes. Plant Biotechnology Journal. 19(3). 602–614. 58 indexed citations
13.
Sheehan, Hester, Tao Feng, Nathanael Walker‐Hale, et al.. (2019). Evolution of l‐DOPA 4,5‐dioxygenase activity allows for recurrent specialisation to betalain pigmentation in Caryophyllales. New Phytologist. 227(3). 914–929. 48 indexed citations
14.
Andel, Tinde van, Rachel S. Meyer, Saulo Aflitos, et al.. (2016). Tracing ancestor rice of Suriname Maroons back to its African origin. Nature Plants. 2(10). 16149–16149. 24 indexed citations
15.
Mansueto, Locedie, Roven Rommel Fuentes, Frances Nikki Borja, et al.. (2016). Rice SNP-seek database update: new SNPs, indels, and queries. Nucleic Acids Research. 45(D1). D1075–D1081. 228 indexed citations
16.
Wang, Jun, Yeisoo Yu, Tao Feng, et al.. (2016). DNA methylation changes facilitated evolution of genes derived from Mutator-like transposable elements. Genome biology. 17(1). 92–92. 14 indexed citations
17.
Geering, Andrew D. W., Florian Maumus, Dario Copetti, et al.. (2014). Endogenous florendoviruses are major components of plant genomes and hallmarks of virus evolution. Nature Communications. 5(1). 5269–5269. 84 indexed citations
18.
Venuti, Silvia, Dario Copetti, Serena Foria, et al.. (2013). Historical Introgression of the Downy Mildew Resistance Gene Rpv12 from the Asian Species Vitis amurensis into Grapevine Varieties. PLoS ONE. 8(4). e61228–e61228. 110 indexed citations
19.
Gaspero, Gabriele Di, Dario Copetti, Simone D. Castellarin, et al.. (2011). Selective sweep at the Rpv3 locus during grapevine breeding for downy mildew resistance. Theoretical and Applied Genetics. 124(2). 277–286. 104 indexed citations
20.
Copetti, Dario, G. Cipriani, S. Hoffmann, et al.. (2009). The powdery mildew resistance gene REN1 co-segregates with an NBS-LRR gene cluster in two Central Asian grapevines. BMC Genetics. 10(1). 89–89. 72 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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