Marco Ramoni
Impact in
- Transplantation top 2%
-
- Geotechnical Engineering and Analysis
Papers in
-
- Bioinformatics and Genomic Networks 23
- Gene expression and cancer classification 15
- Gene Regulatory Network Analysis 11
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- Bayesian Modeling and Causal Inference 35
- AI-based Problem Solving and Planning 9
- Co-authors
- Paola Sebastiani (52 shared papers)Isaac S. Kohane (19 shared papers)Georg Anagnostou (13 shared papers)Georgios Anagnostou (4 shared papers)Gil Alterovitz (22 shared papers)Paul R. Cohen (7 shared papers)Alberto Riva (9 shared papers)Val Nolan (1 shared paper)
- Journals
- Tunnelling and Underground Space Technology (6 papers)PROTEOMICS (3 papers)Machine Learning (3 papers)Proceedings of the National Academy of Sciences (3 papers)BMC Bioinformatics (3 papers)
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Marco Ramoni
145 papers receiving 5.0k citations
Marco Ramoni's Hit Papers
Peers
Comparison fields: 5 of 199
- Transplantation 141
- Safety, Risk, Reliability and Quality 290
- Artificial Intelligence 1.0k
- Family Practice 39
- Molecular Biology 1.6k
Countries citing papers authored by Marco Ramoni
This map shows the geographic impact of Marco Ramoni'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 Marco Ramoni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Ramoni more than expected).
Fields of papers citing papers by Marco Ramoni
This network shows the impact of papers produced by Marco Ramoni. 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 Marco Ramoni. The network helps show where Marco Ramoni may publish in the future.
Co-authors
The 25 scholars most cited alongside Marco Ramoni, 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 151 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Learning Bayesian Networks Hit paper breakdown → | 2005 | 466 |
| 2 | 2002 | 355 | |
| 3 | 2007 | 292 | |
| 4 | 2005 | 249 | |
| 5 | 2004 | 208 | |
| 6 | 2002 | 178 | |
| 7 | 2003 | 161 | |
| 8 | 2003 | 146 | |
| 9 | 2001 | 131 | |
| 10 | 2002 | 131 | |
| 11 | 2010 | 107 | |
| 12 | 2009 | 106 | |
| 13 | 2010 | 106 | |
| 14 | 2009 | 106 | |
| 15 | 1992 | 103 | |
| 16 | 2001 | 91 | |
| 17 | 2006 | 90 | |
| 18 | 2006 | 84 | |
| 19 | 2003 | 82 | |
| 20 | 2007 | 70 |
About Marco Ramoni
Marco Ramoni is a scholar working on Molecular Biology, Artificial Intelligence, Civil and Structural Engineering, Mechanics of Materials and Genetics, having authored 151 papers that have together received 5.2k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (35 papers), Bioinformatics and Genomic Networks (23 papers), Tunneling and Rock Mechanics (17 papers), Gene expression and cancer classification (15 papers), Rock Mechanics and Modeling (11 papers), Gene Regulatory Network Analysis (11 papers), Geotechnical Engineering and Analysis (10 papers) and AI-based Problem Solving and Planning (9 papers). The work is most often cited by research in Transplantation (141 citations), Safety, Risk, Reliability and Quality (290 citations), Artificial Intelligence (1.0k citations), Family Practice (39 citations) and Molecular Biology (1.6k citations). Marco Ramoni has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Paola Sebastiani, Isaac S. Kohane, Georg Anagnostou, Georgios Anagnostou, Gil Alterovitz, Paul R. Cohen, Alberto Riva, Val Nolan, Martin H. Steinberg and Clinton T. Baldwin. Their work appears in journals such as Tunnelling and Underground Space Technology, PROTEOMICS, Machine Learning, Proceedings of the National Academy of Sciences and BMC Bioinformatics.
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.