Matteo Gianesella

121 total papers · 2.0k total citations
96 papers, 1.4k citations indexed

About

Matteo Gianesella is a scholar working on Agronomy and Crop Science, Animal Science and Zoology and Small Animals. According to data from OpenAlex, Matteo Gianesella has authored 96 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Agronomy and Crop Science, 34 papers in Animal Science and Zoology and 32 papers in Small Animals. Recurrent topics in Matteo Gianesella's work include Reproductive Physiology in Livestock (44 papers), Ruminant Nutrition and Digestive Physiology (34 papers) and Effects of Environmental Stressors on Livestock (30 papers). Matteo Gianesella is often cited by papers focused on Reproductive Physiology in Livestock (44 papers), Ruminant Nutrition and Digestive Physiology (34 papers) and Effects of Environmental Stressors on Livestock (30 papers). Matteo Gianesella collaborates with scholars based in Italy, United States and France. Matteo Gianesella's co-authors include M. Morgante, Enrico Fiore, Giuseppe Piccione, Elisabetta Giudice, C. Stelletta, Francesca Arfuso, Igino Andrighetto, Alessio Cecchinato, P.L. Ruegg and Giovanni Bittante and has published in prestigious journals such as PLoS ONE, Scientific Reports and Journal of Dairy Science.

In The Last Decade

Matteo Gianesella

94 papers receiving 1.4k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Matteo Gianesella 849 521 409 353 160 96 1.4k
M. Morgante 751 0.9× 448 0.9× 350 0.9× 313 0.9× 138 0.9× 84 1.3k
T. G. Martín 451 0.5× 422 0.8× 431 1.1× 239 0.7× 148 0.9× 71 1.2k
Martin Kaske 777 0.9× 298 0.6× 418 1.0× 323 0.9× 118 0.7× 82 1.3k
J. H. Eisemann 586 0.7× 572 1.1× 308 0.8× 241 0.7× 85 0.5× 58 1.5k
Michael Kreuzer 653 0.8× 745 1.4× 353 0.9× 325 0.9× 94 0.6× 59 1.5k
Nicole C Burdick Sanchez 569 0.7× 1.0k 1.9× 234 0.6× 724 2.1× 130 0.8× 113 1.6k
M. Wanner 528 0.6× 315 0.6× 218 0.5× 298 0.8× 93 0.6× 88 1.6k
C.S. Whisnant 632 0.7× 502 1.0× 346 0.8× 326 0.9× 43 0.3× 65 1.6k
K.A. Cummins 669 0.8× 463 0.9× 431 1.1× 342 1.0× 51 0.3× 63 1.5k
D. M. Hallford 1.1k 1.3× 452 0.9× 571 1.4× 233 0.7× 67 0.4× 124 1.8k

Countries citing papers authored by Matteo Gianesella

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Gianesella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Gianesella

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

All Works

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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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