Simone Marini
Impact in
- Health Information Management top 0.5%
- Artificial Intelligence in Healthcare
- Health Informatics top 5%
Papers in
-
- Genomics and Phylogenetic Studies 6
- Bioinformatics and Genomic Networks 5
- vaccines and immunoinformatics approaches 4
- Epidemiology 10
- Co-authors
- Riccardo Bellazzi (20 shared papers)Lucia Sacchi (4 shared papers)Valentina Tibollo (2 shared papers)Marsida Teliti (2 shared papers)Arianna Dagliati (3 shared papers)Pasquale De Cata (2 shared papers)Luca Chiovato (2 shared papers)Giulia Cogni (2 shared papers)
- Journals
- Bioinformatics (5 papers)Briefings in Bioinformatics (4 papers)PLoS ONE (3 papers)JCI Insight (2 papers)Bone (2 papers)
- Partner nations
- United StatesItalyJapan
In The Last Decade
Simone Marini
70 papers receiving 1.6k citations
Simone Marini's Hit Papers
Peers
Comparison fields: 5 of 143
- Health Information Management 169
- Health Informatics 27
- Reproductive Medicine 142
- Rheumatology 126
- Genetics 226
Countries citing papers authored by Simone Marini
This map shows the geographic impact of Simone Marini'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 Simone Marini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simone Marini more than expected).
Fields of papers citing papers by Simone Marini
This network shows the impact of papers produced by Simone Marini. 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 Simone Marini. The network helps show where Simone Marini may publish in the future.
Co-authors
The 25 scholars most cited alongside Simone Marini, 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 73 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 339 | |
| 2 | Machine Learning Methods to Predict Diabetes Complications Hit paper breakdown → | 2017 | 269 |
| 3 | 2022 | 108 | |
| 4 | 2018 | 106 | |
| 5 | 2018 | 97 | |
| 6 | 2019 | 46 | |
| 7 | 2015 | 45 | |
| 8 | 2020 | 43 | |
| 9 | 2015 | 42 | |
| 10 | 2013 | 36 | |
| 11 | 2018 | 34 | |
| 12 | 2022 | 33 | |
| 13 | 2020 | 31 | |
| 14 | 2020 | 30 | |
| 15 | 2019 | 29 | |
| 16 | 2020 | 27 | |
| 17 | 2020 | 25 | |
| 18 | 2020 | 23 | |
| 19 | 1997 | 22 | |
| 20 | 2015 | 19 |
About Simone Marini
Simone Marini is a scholar working on Molecular Biology, Epidemiology, Infectious Diseases, Molecular Medicine and Genetics, having authored 73 papers that have together received 1.7k indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (7 papers), Heterotopic Ossification and Related Conditions (6 papers), Genomics and Phylogenetic Studies (6 papers), Bacterial Identification and Susceptibility Testing (5 papers), Bioinformatics and Genomic Networks (5 papers), Machine Learning in Healthcare (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers) and vaccines and immunoinformatics approaches (4 papers). The work is most often cited by research in Health Information Management (169 citations), Health Informatics (27 citations), Reproductive Medicine (142 citations), Rheumatology (126 citations) and Genetics (226 citations). Simone Marini has collaborated with scholars based in United States, Italy and Japan. Frequent co-authors include Riccardo Bellazzi, Lucia Sacchi, Valentina Tibollo, Marsida Teliti, Arianna Dagliati, Pasquale De Cata, Luca Chiovato, Giulia Cogni, Mattia Prosperi and Jun Z. Li. Their work appears in journals such as Bioinformatics, Briefings in Bioinformatics, PLoS ONE, JCI Insight and Bone.
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.