Philip Vitorino
About
In The Last Decade
Philip Vitorino
7 papers receiving 496 citations
Peers
Comparison fields: 5 of 68
- Cell Biology 256
- Molecular Biology 240
- Biomedical Engineering 117
- Oncology 116
- Immunology and Allergy 71
Countries citing papers authored by Philip Vitorino
This map shows the geographic impact of Philip Vitorino'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 Philip Vitorino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip Vitorino more than expected).
Fields of papers citing papers by Philip Vitorino
This network shows the impact of papers produced by Philip Vitorino. 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 Philip Vitorino. The network helps show where Philip Vitorino may publish in the future.
Co-authorship network of co-authors of Philip Vitorino
This figure shows the co-authorship network connecting the top 25 collaborators of Philip Vitorino. A scholar is included among the top collaborators of Philip Vitorino 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 Philip Vitorino. Philip Vitorino is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 32 | |
| 2 | 18 | |
| 3 | 2 | |
| 4 | 107 | |
| 5 | 48 | |
| 6 | 71 | |
| 7 | 224 |
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.