Barbara Di Camillo
- Molecular Biology top 5%
- Endocrinology, Diabetes and Metabolism top 5%
- Cancer Research top 5%
- Epidemiology top 10%
- Surgery
- Co-authors
- Francesca FinotelloGiacomo BaruzzoEnrico LongatoGianna ToffoloClaudio CobelliAlessandra Dal MolinMartina VettorettiAngelo Avogaro
- Topics
- Bioinformatics and Genomic Networks (18 papers)Diabetes Treatment and Management (14 papers)Genomics and Phylogenetic Studies (14 papers)
- Partner nations
- ItalyUnited StatesAustria
In The Last Decade
Barbara Di Camillo
123 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Molecular Biology 1.4k
- Endocrinology, Diabetes and Metabolism 402
- Cancer Research 345
- Epidemiology 299
- Surgery 245
Countries citing papers authored by Barbara Di Camillo
This map shows the geographic impact of Barbara Di Camillo'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 Barbara Di Camillo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Barbara Di Camillo more than expected).
Fields of papers citing papers by Barbara Di Camillo
This network shows the impact of papers produced by Barbara Di Camillo. 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 Barbara Di Camillo. The network helps show where Barbara Di Camillo may publish in the future.
Co-authorship network of co-authors of Barbara Di Camillo
This figure shows the co-authorship network connecting the top 25 collaborators of Barbara Di Camillo. A scholar is included among the top collaborators of Barbara Di Camillo 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 Barbara Di Camillo. Barbara Di Camillo 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 | 0 | |
| 3 | Challenges and opportunities for digital twins in precision medicine from a complex systems perspectivebreakdown → | 34 |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 10 | |
| 8 | 5 | |
| 9 | 13 | |
| 10 | 6 | |
| 11 | 13 | |
| 12 | 4 | |
| 13 | 7 | |
| 14 | Deep Convolutional Neural Network for Survival Estimation of Amyotrophic Lateral Sclerosis patients | 1 |
| 15 | 1 | |
| 16 | 104 | |
| 17 | 38 | |
| 18 | 19 | |
| 19 | 109 | |
| 20 | 1 |
About Barbara Di Camillo
Barbara Di Camillo is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Health Information Management, having authored 132 papers that have together received 2.8k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (18 papers), Diabetes Treatment and Management (14 papers) and Genomics and Phylogenetic Studies (14 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (402 citations), Cancer Research (345 citations) and Molecular Biology (1.4k citations). Barbara Di Camillo has collaborated with scholars based in Italy, United States and Austria. Frequent co-authors include Francesca Finotello, Giacomo Baruzzo, Enrico Longato, Gianna Toffolo, Claudio Cobelli, Alessandra Dal Molin, Martina Vettoretti, Angelo Avogaro, Giovanni Sparacino and Francesco Sambo. Their work appears in journals such as Proceedings of the National Academy of Sciences, Blood and 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.