Federico Gatto
- Endocrinology, Diabetes and Metabolism top 1%
- Epidemiology top 5%
- Surgery top 10%
- Molecular Biology
- Oncology
- Co-authors
- Diego FeroneLeo J. HoflandFrancesco MinutoMarica ArvigoSebastian NeggersLuiz Eduardo WildembergMônica R. GadelhaRichard A. Feelders
- Topics
- Pituitary Gland Disorders and Treatments (59 papers)Growth Hormone and Insulin-like Growth Factors (34 papers)Neuroendocrine Tumor Research Advances (27 papers)
- Journals
- The LancetSHILAP Revista de lepidopterologíaThe Journal of Clinical Endocrinology & Metabolism
- Partner nations
- ItalyNetherlandsUnited States
In The Last Decade
Federico Gatto
71 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 84
- Endocrinology, Diabetes and Metabolism 1.1k
- Epidemiology 631
- Surgery 431
- Molecular Biology 227
- Oncology 206
Countries citing papers authored by Federico Gatto
This map shows the geographic impact of Federico Gatto'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 Federico Gatto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federico Gatto more than expected).
Fields of papers citing papers by Federico Gatto
This network shows the impact of papers produced by Federico Gatto. 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 Federico Gatto. The network helps show where Federico Gatto may publish in the future.
Co-authorship network of co-authors of Federico Gatto
This figure shows the co-authorship network connecting the top 25 collaborators of Federico Gatto. A scholar is included among the top collaborators of Federico Gatto 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 Federico Gatto. Federico Gatto 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 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 1 | |
| 7 | 53 | |
| 8 | 7 | |
| 9 | 6 | |
| 10 | Octreotide-Resistant Acromegaly: Challenges and Solutions | 1 |
| 11 | 35 | |
| 12 | 42 | |
| 13 | 28 | |
| 14 | 84 | |
| 15 | 48 | |
| 16 | 32 | |
| 17 | 14 | |
| 18 | 16 | |
| 19 | 23 | |
| 20 | 10 |
About Federico Gatto
Federico Gatto is a scholar working on Endocrinology, Diabetes and Metabolism, Epidemiology and Neurology, having authored 78 papers that have together received 1.5k indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (59 papers), Growth Hormone and Insulin-like Growth Factors (34 papers) and Neuroendocrine Tumor Research Advances (27 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (1.1k citations), Epidemiology (631 citations) and Genetics (181 citations). Federico Gatto has collaborated with scholars based in Italy, Netherlands and United States. Frequent co-authors include Diego Ferone, Leo J. Hofland, Francesco Minuto, Marica Arvigo, Sebastian Neggers, Luiz Eduardo Wildemberg, Mônica R. Gadelha, Richard A. Feelders, Manuela Albertelli and Johan M. Kros. Their work appears in journals such as The Lancet, SHILAP Revista de lepidopterología and The Journal of Clinical Endocrinology & Metabolism.
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.