Matteo De Chiara

2.4k total citations
27 papers, 612 citations indexed

About

Matteo De Chiara is a scholar working on Molecular Biology, Food Science and Plant Science. According to data from OpenAlex, Matteo De Chiara has authored 27 papers receiving a total of 612 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 11 papers in Food Science and 10 papers in Plant Science. Recurrent topics in Matteo De Chiara's work include Fermentation and Sensory Analysis (11 papers), Fungal and yeast genetics research (10 papers) and Pneumonia and Respiratory Infections (6 papers). Matteo De Chiara is often cited by papers focused on Fermentation and Sensory Analysis (11 papers), Fungal and yeast genetics research (10 papers) and Pneumonia and Respiratory Infections (6 papers). Matteo De Chiara collaborates with scholars based in France, Italy and Chile. Matteo De Chiara's co-authors include Gianni Liti, Alessandro Muzzi, Jia‐Xing Yue, Joseph Schacherer, Benjamin Barré, Mariagrazia Pizza, Rino Rappuoli, Claudio Donati, Anne Friedrich and Marco Soriani and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Genetics.

In The Last Decade

Matteo De Chiara

25 papers receiving 607 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matteo De Chiara France 13 322 198 152 149 137 27 612
Damaríz Rivero Italy 11 295 0.9× 70 0.4× 191 1.3× 50 0.3× 183 1.3× 13 524
Zongli Luo Canada 13 433 1.3× 126 0.6× 51 0.3× 208 1.4× 8 0.1× 16 723
Wen-Jen Yang Taiwan 15 184 0.6× 44 0.2× 61 0.4× 75 0.5× 77 0.6× 19 457
Jolanta Krzysztoń-Russjan Poland 11 284 0.9× 52 0.3× 75 0.5× 33 0.2× 33 0.2× 29 537
Stephanie R. Shames United States 14 292 0.9× 61 0.3× 77 0.5× 36 0.2× 25 0.2× 26 649
Sarah Redmond United States 9 138 0.4× 65 0.3× 73 0.5× 38 0.3× 42 0.3× 12 546
Hélène Gingras Canada 10 197 0.6× 42 0.2× 198 1.3× 20 0.1× 45 0.3× 20 479
Daniela Mailänder‐Sánchez Germany 11 180 0.6× 80 0.4× 89 0.6× 37 0.2× 142 1.0× 13 398
Bharat Rash United Kingdom 11 303 0.9× 40 0.2× 79 0.5× 103 0.7× 22 0.2× 14 474
Nirpendra Singh India 16 232 0.7× 19 0.1× 163 1.1× 61 0.4× 45 0.3× 29 574

Countries citing papers authored by Matteo De Chiara

Since Specialization
Citations

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

Fields of papers citing papers by Matteo De Chiara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matteo De Chiara. 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 Matteo De Chiara. The network helps show where Matteo De Chiara may publish in the future.

Co-authorship network of co-authors of Matteo De Chiara

This figure shows the co-authorship network connecting the top 25 collaborators of Matteo De Chiara. A scholar is included among the top collaborators of Matteo De Chiara 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 Matteo De Chiara. Matteo De Chiara 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.
Chiara, Matteo De, Benjamin Barré, Inigo Barrio‐Hernandez, et al.. (2025). Predicting natural variation in the yeast phenotypic landscape with machine learning. Molecular Systems Biology. 21(11). 1466–1489.
2.
Villarreal, Pablo, Nicolas Agier, Matteo De Chiara, et al.. (2024). An integrative taxonomy approach reveals Saccharomyces chiloensis sp. nov. as a newly discovered species from Coastal Patagonia. PLoS Genetics. 20(9). e1011396–e1011396. 7 indexed citations
3.
Chiara, Matteo De, Lorenzo Tattini, Е. С. Наумова, et al.. (2024). Ancient and recent origins of shared polymorphisms in yeast. Nature Ecology & Evolution. 8(4). 761–776. 8 indexed citations
4.
O’Donnell, Samuel, Jia‐Xing Yue, Nicolas Agier, et al.. (2023). Telomere-to-telomere assemblies of 142 strains characterize the genome structural landscape in Saccharomyces cerevisiae. Nature Genetics. 55(8). 1390–1399. 56 indexed citations
5.
6.
Yue, Jia‐Xing, Matteo De Chiara, Benjamin Barré, et al.. (2022). Telomeres are shorter in wild Saccharomyces cerevisiae isolates than in domesticated ones. Genetics. 223(3). 6 indexed citations
7.
Chiara, Matteo De, Benjamin Barré, Karl Persson, et al.. (2022). Domestication reprogrammed the budding yeast life cycle. Nature Ecology & Evolution. 6(4). 448–460. 44 indexed citations
8.
Chiara, Matteo De, et al.. (2022). miRNAs Copy Number Variations Repertoire as Hallmark Indicator of Cancer Species Predisposition. Genes. 13(6). 1046–1046. 6 indexed citations
9.
10.
Krogerus, Kristoffer, Frederico Magalhães, Sandra Castillo, et al.. (2021). Lager Yeast Design Through Meiotic Segregation of a Saccharomyces cerevisiae × Saccharomyces eubayanus Hybrid. SHILAP Revista de lepidopterología. 2. 733655–733655. 17 indexed citations
11.
Wrobel, Russell L., Michael Place, Michael E. Graham, et al.. (2020). CRISpy-Pop: A Web Tool for Designing CRISPR/Cas9-Driven Genetic Modifications in Diverse Populations. G3 Genes Genomes Genetics. 10(11). 4287–4294. 8 indexed citations
12.
Nespolo, Roberto F., Carlos A. Villarroel, Sebastián M. Tapia, et al.. (2020). An Out-of-Patagonia migration explains the worldwide diversity and distribution of Saccharomyces eubayanus lineages. PLoS Genetics. 16(5). e1008777–e1008777. 36 indexed citations
13.
Villarroel, Carlos A., Matteo De Chiara, Francisco A. Cubillos, et al.. (2020). Transcriptional Activity and Protein Levels of Horizontally Acquired Genes in Yeast Reveal Hallmarks of Adaptation to Fermentative Environments. Frontiers in Genetics. 11. 293–293. 14 indexed citations
14.
Laureau, Raphaëlle, Jia‐Xing Yue, Matteo De Chiara, et al.. (2020). Meiotic Cells Counteract Programmed Retrotransposon Activation via RNA-Binding Translational Repressor Assemblies. Developmental Cell. 56(1). 22–35.e7. 7 indexed citations
15.
Chiara, Matteo De, Jia‐Xing Yue, Simon Stenberg, et al.. (2020). A yeast living ancestor reveals the origin of genomic introgressions. Nature. 587(7834). 420–425. 36 indexed citations
16.
Chiara, Matteo De, Anne Friedrich, Benjamin Barré, et al.. (2020). Discordant evolution of mitochondrial and nuclear yeast genomes at population level. BMC Biology. 18(1). 49–49. 36 indexed citations
17.
18.
Krogerus, Kristoffer, Mikko Arvas, Matteo De Chiara, et al.. (2016). Ploidy influences the functional attributes of de novo lager yeast hybrids. Applied Microbiology and Biotechnology. 100(16). 7203–7222. 63 indexed citations
19.
Metruccio, Matteo M. E., Matteo De Chiara, Rong Mu, et al.. (2014). Analysis of Two-Component Systems in Group B Streptococcus Shows That RgfAC and the Novel FspSR Modulate Virulence and Bacterial Fitness. mBio. 5(3). e00870–14. 50 indexed citations
20.
Spiga, Ottavia, Domenico Summa, Andrea Bernini, et al.. (2010). A structurally driven analysis of thiol reactivity in mammalian albumins. Biopolymers. 95(4). 278–285. 14 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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