Marco Frasca
- Molecular Biology
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 10%
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition
- Co-authors
- Giorgio ValentiniDario MalchiodiAlessandro PetriniMatteo RéAlberto BertoniMarco MesitiElena CasiraghiNicolò Cesa‐Bianchi
- Topics
- Bioinformatics and Genomic Networks (19 papers)Gene expression and cancer classification (11 papers)Machine Learning in Bioinformatics (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsPLoS ONE
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Marco Frasca
30 papers receiving 364 citations
Peers
Comparison fields: 5 of 85
- Molecular Biology 186
- Artificial Intelligence 102
- Computational Theory and Mathematics 55
- Radiology, Nuclear Medicine and Imaging 51
- Computer Vision and Pattern Recognition 42
Countries citing papers authored by Marco Frasca
This map shows the geographic impact of Marco Frasca'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 Frasca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Frasca more than expected).
Fields of papers citing papers by Marco Frasca
This network shows the impact of papers produced by Marco Frasca. 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 Frasca. The network helps show where Marco Frasca may publish in the future.
Co-authorship network of co-authors of Marco Frasca
This figure shows the co-authorship network connecting the top 25 collaborators of Marco Frasca. A scholar is included among the top collaborators of Marco Frasca 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 Marco Frasca. Marco Frasca is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 6 | |
| 3 | 7 | |
| 4 | 12 | |
| 5 | 4 | |
| 6 | 9 | |
| 7 | 56 | |
| 8 | 6 | |
| 9 | 7 | |
| 10 | 6 | |
| 11 | Combining Cost-Sensitive Classification with Negative Selection for Protein Function Prediction. | 1 |
| 12 | 1 | |
| 13 | 15 | |
| 14 | 2 | |
| 15 | 5 | |
| 16 | 12 | |
| 17 | 11 | |
| 18 | 38 | |
| 19 | An unbalance-aware network integration method for gene function prediction | 0 |
| 20 | 3 |
About Marco Frasca
Marco Frasca is a scholar working on Health Informatics, Computational Theory and Mathematics and Molecular Biology, having authored 31 papers that have together received 369 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (19 papers), Gene expression and cancer classification (11 papers) and Machine Learning in Bioinformatics (9 papers). The work is most often cited by research in Health Informatics (11 citations), Computational Theory and Mathematics (55 citations) and Artificial Intelligence (102 citations). Marco Frasca has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Giorgio Valentini, Dario Malchiodi, Alessandro Petrini, Matteo Ré, Alberto Bertoni, Marco Mesiti, Elena Casiraghi, Nicolò Cesa‐Bianchi, Peter N. Robinson and Giulio Pavesi. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.
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.