Roberto Gianani
Impact in
Papers in
- Co-authors
- George S. Eisenbarth (26 shared papers)Liping Yu (14 shared papers)Charles F. Verge (9 shared papers)Eiji Kawasaki (4 shared papers)Richard A. Jackson (4 shared papers)Massimo Pietropaolo (7 shared papers)H. Peter Chase (2 shared papers)Alberto Pugliese (11 shared papers)
- Journals
- Diabetes (8 papers)Diabetologia (5 papers)The Journal of Clinical Endocrinology & Metabolism (4 papers)Proceedings of the National Academy of Sciences (3 papers)American Journal of Clinical Pathology (2 papers)
- Partner nations
- United StatesItalyJapan
In The Last Decade
Roberto Gianani
55 papers receiving 3.7k citations
Roberto Gianani's Hit Papers
Peers
Comparison fields: 5 of 98
- Genetics 2.3k
- Surgery 607
- Immunology 247
- Endocrinology, Diabetes and Metabolism 205
- Oncology 192
Countries citing papers authored by Roberto Gianani
This map shows the geographic impact of Roberto Gianani'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 Roberto Gianani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto Gianani more than expected).
Fields of papers citing papers by Roberto Gianani
This network shows the impact of papers produced by Roberto Gianani. 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 Roberto Gianani. The network helps show where Roberto Gianani may publish in the future.
Co-authors
The 25 scholars most cited alongside Roberto Gianani, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Prediction of Type I Diabetes in First-Degree Relatives Using a Combination of Insulin, GAD, and ICA512bdc/IA-2 Autoantibodies Hit paper breakdown → | 1996 | 698 |
| 2 | 2005 | 300 | |
| 3 | 1996 | 195 | |
| 4 | 2012 | 177 | |
| 5 | 2003 | 167 | |
| 6 | 1995 | 161 | |
| 7 | 2013 | 160 | |
| 8 | 2017 | 158 | |
| 9 | 2001 | 151 | |
| 10 | 1996 | 133 | |
| 11 | 2010 | 129 | |
| 12 | 2013 | 117 | |
| 13 | 2002 | 113 | |
| 14 | 1992 | 108 | |
| 15 | 2005 | 96 | |
| 16 | 2007 | 88 | |
| 17 | 1996 | 86 | |
| 18 | 1995 | 80 | |
| 19 | 1994 | 57 | |
| 20 | 2009 | 57 |
About Roberto Gianani
Roberto Gianani is a scholar working on Genetics, Surgery, Immunology, Oncology and Artificial Intelligence, having authored 56 papers that have together received 3.9k indexed citations. Recurring topics across this work include Diabetes and associated disorders (36 papers), Pancreatic function and diabetes (7 papers), AI in cancer detection (4 papers), Cancer Immunotherapy and Biomarkers (2 papers), T-cell and B-cell Immunology (2 papers), Cervical Cancer and HPV Research (1 paper), Cardiovascular Health and Disease Prevention (1 paper) and Molecular Biology Techniques and Applications (1 paper). The work is most often cited by research in Genetics (2.3k citations), Surgery (607 citations), Immunology (247 citations), Endocrinology, Diabetes and Metabolism (205 citations) and Oncology (192 citations). Roberto Gianani has collaborated with scholars based in United States, Italy and Japan. Frequent co-authors include George S. Eisenbarth, Liping Yu, Charles F. Verge, Eiji Kawasaki, Richard A. Jackson, Massimo Pietropaolo, H. Peter Chase, Alberto Pugliese, Mark A. Atkinson and Jan Nygaard Jensen. Their work appears in journals such as Diabetes, Diabetologia, The Journal of Clinical Endocrinology & Metabolism, Proceedings of the National Academy of Sciences and American Journal of Clinical Pathology.
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.