Matteo Da Ros

12 papers and 473 indexed citations i.

About

Matteo Da Ros is a scholar working on Molecular Biology, Plant Science and Reproductive Medicine. According to data from OpenAlex, Matteo Da Ros has authored 12 papers receiving a total of 473 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Plant Science and 3 papers in Reproductive Medicine. Recurrent topics in Matteo Da Ros’s work include Chromosomal and Genetic Variations (6 papers), CRISPR and Genetic Engineering (5 papers) and Sperm and Testicular Function (3 papers). Matteo Da Ros is often cited by papers focused on Chromosomal and Genetic Variations (6 papers), CRISPR and Genetic Engineering (5 papers) and Sperm and Testicular Function (3 papers). Matteo Da Ros collaborates with scholars based in Finland, Switzerland and France. Matteo Da Ros's co-authors include Noora Kotaja, Oliver Meikar, Hanna Korhonen, Jorma Toppari, Serge Nef, Pedro L. Herrera, Yannick Romero, Marilena D. Papaioannou, Frédéric Chalmel and Kaja A. Wasik and has published in prestigious journals such as PLoS ONE, Journal of Neurochemistry and Experimental Cell Research.

In The Last Decade

Co-authorship network of co-authors of Matteo Da Ros i

Fields of papers citing papers by Matteo Da Ros

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Matteo Da Ros

Since Specialization
Citations

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

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2025