Simone Marini
Impact in
- Health Information Management top 0.5%
- Artificial Intelligence in Healthcare
- Health Informatics top 5%
Papers in ⓘ
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- Antibiotic Resistance in Bacteria 8
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- Bacterial Identification and Susceptibility Testing 5
- Co-authors
- Riccardo Bellazzi (19 shared papers)Lucia Sacchi (4 shared papers)Arianna Dagliati (3 shared papers)Giulia Cogni (2 shared papers)Valentina Tibollo (2 shared papers)Marsida Teliti (2 shared papers)Luca Chiovato (2 shared papers)Pasquale De Cata (2 shared papers)
- Journals
- Bioinformatics (4 papers)Briefings in Bioinformatics (4 papers)PLoS ONE (3 papers)JMIR Public Health and Surveillance (2 papers)Bone (2 papers)
- Partner nations
- United StatesItalyJapan
In The Last Decade
Simone Marini
68 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Health Information Management 190
- Health Informatics 31
- Reproductive Medicine 145
- Molecular Medicine 47
- Genetics 244
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 69 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 330 | |
| 2 | Machine Learning Methods to Predict Diabetes Complications Hit paper breakdown → | 2017 | 252 |
| 3 | 2018 | 101 | |
| 4 | 2018 | 94 | |
| 5 | 2022 | 89 | |
| 6 | 2019 | 45 | |
| 7 | 2015 | 41 | |
| 8 | 2020 | 39 | |
| 9 | 2015 | 38 | |
| 10 | 2013 | 34 | |
| 11 | 2018 | 30 | |
| 12 | 2020 | 30 | |
| 13 | 2019 | 29 | |
| 14 | 2020 | 27 | |
| 15 | 2022 | 25 | |
| 16 | 2020 | 25 | |
| 17 | 2020 | 23 | |
| 18 | 2020 | 22 | |
| 19 | 1997 | 21 | |
| 20 | 2020 | 17 |
About Simone Marini
Simone Marini is a scholar working on Molecular Medicine, Clinical Biochemistry, Virology, Infectious Diseases and Applied Microbiology and Biotechnology, having authored 69 papers that have together received 1.5k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (10 papers), Antibiotic Resistance in Bacteria (8 papers), vaccines and immunoinformatics approaches (7 papers), SARS-CoV-2 and COVID-19 Research (7 papers), Bioinformatics and Genomic Networks (6 papers), Heterotopic Ossification and Related Conditions (6 papers), Bacterial Identification and Susceptibility Testing (5 papers) and Mesenchymal stem cell research (4 papers). The work is most often cited by research in Health Information Management (190 citations), Health Informatics (31 citations), Reproductive Medicine (145 citations), Molecular Medicine (47 citations) and Genetics (244 citations). Simone Marini has collaborated with scholars based in United States, Italy and Japan. Frequent co-authors include Riccardo Bellazzi, Lucia Sacchi, Arianna Dagliati, Giulia Cogni, Valentina Tibollo, Marsida Teliti, Luca Chiovato, Pasquale De Cata, Jun Z. Li and Mattia Prosperi. Their work appears in journals such as Bioinformatics, Briefings in Bioinformatics, PLoS ONE, JMIR Public Health and Surveillance 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.