Anna Maria Sutera
- Genetics top 10%
- Cancer Research
- Agronomy and Crop Science top 10%
- Molecular Biology
- Animal Science and Zoology top 10%
- Co-authors
- Baldassare PortolanoMaria Teresa SardinaSalvatore MastrangeloMarco ToloneRosalia Di GerlandoGianluca SottileAlessandro ZumboGiuseppe Tardiolo
- Topics
- Genetic and phenotypic traits in livestock (15 papers)Genetic Mapping and Diversity in Plants and Animals (9 papers)Milk Quality and Mastitis in Dairy Cows (5 papers)
- Partner nations
- ItalyUnited KingdomCuba
In The Last Decade
Anna Maria Sutera
29 papers receiving 432 citations
Peers
Comparison fields: 5 of 49
- Genetics 325
- Cancer Research 91
- Agronomy and Crop Science 85
- Molecular Biology 82
- Animal Science and Zoology 68
Countries citing papers authored by Anna Maria Sutera
This map shows the geographic impact of Anna Maria Sutera'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 Anna Maria Sutera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna Maria Sutera more than expected).
Fields of papers citing papers by Anna Maria Sutera
This network shows the impact of papers produced by Anna Maria Sutera. 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 Anna Maria Sutera. The network helps show where Anna Maria Sutera may publish in the future.
Co-authorship network of co-authors of Anna Maria Sutera
This figure shows the co-authorship network connecting the top 25 collaborators of Anna Maria Sutera. A scholar is included among the top collaborators of Anna Maria Sutera 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 Anna Maria Sutera. Anna Maria Sutera is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 11 | |
| 7 | 13 | |
| 8 | 12 | |
| 9 | 7 | |
| 10 | 13 | |
| 11 | 21 | |
| 12 | The SNPs discovery in RRLs from DNA pools of Nero Siciliano pigs with extreme and divergent phenotypes for the Back Fat Thickness (BFT) tract | 1 |
| 13 | 14 | |
| 14 | 35 | |
| 15 | 10 | |
| 16 | 15 | |
| 17 | 51 | |
| 18 | 12 | |
| 19 | 109 | |
| 20 | 5 |
About Anna Maria Sutera
Anna Maria Sutera is a scholar working on Agronomy and Crop Science, Genetics and Animal Science and Zoology, having authored 32 papers that have together received 436 indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (15 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and Milk Quality and Mastitis in Dairy Cows (5 papers). The work is most often cited by research in Genetics (325 citations), Agronomy and Crop Science (85 citations) and Animal Science and Zoology (68 citations). Anna Maria Sutera has collaborated with scholars based in Italy, United Kingdom and Cuba. Frequent co-authors include Baldassare Portolano, Maria Teresa Sardina, Salvatore Mastrangelo, Marco Tolone, Rosalia Di Gerlando, Gianluca Sottile, Alessandro Zumbo, Giuseppe Tardiolo, Enrico D’Alessandro and Luca Fontanesi. Their work appears in journals such as PLoS ONE, Scientific Reports and Frontiers in Genetics.
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.