Francesco Costacurta
- Infectious Diseases top 10%
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Epidemiology
- Organic Chemistry
- Co-authors
- Emmanuel HeilmannDorotheé von LaerReuben S. HarrisSeyed Arad MoghadasiChengjin YeLuis Martínez‐SobridoAndré VollandBernhard Rupp
- Topics
- SARS-CoV-2 and COVID-19 Research (6 papers)Computational Drug Discovery Methods (3 papers)vaccines and immunoinformatics approaches (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaScience AdvancesScience Translational Medicine
- Partner nations
- AustriaUnited StatesSaudi Arabia
In The Last Decade
Francesco Costacurta
8 papers receiving 197 citations
Hit Papers
Peers
Comparison fields: 5 of 39
- Infectious Diseases 153
- Computational Theory and Mathematics 81
- Molecular Biology 62
- Epidemiology 18
- Organic Chemistry 17
Countries citing papers authored by Francesco Costacurta
This map shows the geographic impact of Francesco Costacurta'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 Francesco Costacurta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Costacurta more than expected).
Fields of papers citing papers by Francesco Costacurta
This network shows the impact of papers produced by Francesco Costacurta. 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 Francesco Costacurta. The network helps show where Francesco Costacurta may publish in the future.
Co-authorship network of co-authors of Francesco Costacurta
This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Costacurta. A scholar is included among the top collaborators of Francesco Costacurta 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 Francesco Costacurta. Francesco Costacurta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 9 | |
| 3 | 7 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | Transmissible SARS-CoV-2 variants with resistance to clinical protease inhibitorsbreakdown → | 94 |
| 7 | 69 | |
| 8 | 16 |
About Francesco Costacurta
Francesco Costacurta is a scholar working on Infectious Diseases, Computational Theory and Mathematics and Physical and Theoretical Chemistry, having authored 8 papers that have together received 198 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (6 papers), Computational Drug Discovery Methods (3 papers) and vaccines and immunoinformatics approaches (2 papers). The work is most often cited by research in Infectious Diseases (153 citations), Computational Theory and Mathematics (81 citations) and Animal Science and Zoology (16 citations). Francesco Costacurta has collaborated with scholars based in Austria, United States and Saudi Arabia. Frequent co-authors include Emmanuel Heilmann, Dorotheé von Laer, Reuben S. Harris, Seyed Arad Moghadasi, Chengjin Ye, Luis Martínez‐Sobrido, André Volland, Bernhard Rupp, Ahmed Magdy Khalil and Hideki Aihara. Their work appears in journals such as SHILAP Revista de lepidopterología, Science Advances and Science Translational Medicine.
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.