Daniele Ramazzotti
- Molecular Biology top 10%
- Cancer Research top 5%
- Artificial Intelligence top 10%
- Genetics
- Oncology
- Co-authors
- Bo WangSerafim BatzoglouEmma PiersonJunjie ZhuAlex GraudenziGiulio CaravagnaBud MishraMarco Antoniotti
- Topics
- Cancer Genomics and Diagnostics (23 papers)Gene expression and cancer classification (9 papers)Bayesian Modeling and Causal Inference (9 papers)
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Daniele Ramazzotti
51 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Molecular Biology 813
- Cancer Research 380
- Artificial Intelligence 179
- Genetics 137
- Oncology 106
Countries citing papers authored by Daniele Ramazzotti
This map shows the geographic impact of Daniele Ramazzotti'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 Daniele Ramazzotti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniele Ramazzotti more than expected).
Fields of papers citing papers by Daniele Ramazzotti
This network shows the impact of papers produced by Daniele Ramazzotti. 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 Daniele Ramazzotti. The network helps show where Daniele Ramazzotti may publish in the future.
Co-authorship network of co-authors of Daniele Ramazzotti
This figure shows the co-authorship network connecting the top 25 collaborators of Daniele Ramazzotti. A scholar is included among the top collaborators of Daniele Ramazzotti 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 Daniele Ramazzotti. Daniele Ramazzotti 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 | 1 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 13 | |
| 9 | 11 | |
| 10 | 17 | |
| 11 | 8 | |
| 12 | 8 | |
| 13 | 16 | |
| 14 | 32 | |
| 15 | 129 | |
| 16 | SIMLR: a tool for large-scale single-cell analysis by multi-kernel learning | 3 |
| 17 | 48 | |
| 18 | 21 | |
| 19 | 57 | |
| 20 | Inferring causal models of cancer progression with a shrinkage estimator and probability raising | 1 |
About Daniele Ramazzotti
Daniele Ramazzotti is a scholar working on Cancer Research, Health Informatics and Molecular Biology, having authored 54 papers that have together received 1.3k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (23 papers), Gene expression and cancer classification (9 papers) and Bayesian Modeling and Causal Inference (9 papers). The work is most often cited by research in Cancer Research (380 citations), Health Informatics (29 citations) and Biophysics (98 citations). Daniele Ramazzotti has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Bo Wang, Serafim Batzoglou, Emma Pierson, Junjie Zhu, Alex Graudenzi, Giulio Caravagna, Bud Mishra, Marco Antoniotti, Avantika Lal and Arend Sidow. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Blood.
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.