Filippo Lunghini
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Health, Toxicology and Mutagenesis
- Materials Chemistry
- Pollution
- Co-authors
- Philippe AzamGilles MarcouAlexandre VarnekErik Van MiertDragos HorvathAndrea R. BeccariMonica LocatelliAndrea Spinazzè
- Topics
- Computational Drug Discovery Methods (13 papers)Metabolomics and Mass Spectrometry Studies (4 papers)Machine Learning in Materials Science (3 papers)
- Cited by
- Chemical Health and SafetyComputational Theory and MathematicsHealth, Toxicology and Mutagenesis
- Journals
- International Journal of Molecular SciencesFrontiers in PharmacologyMethods in molecular biology
In The Last Decade
Filippo Lunghini
15 papers receiving 180 citations
Peers
Comparison fields: 5 of 68
- Computational Theory and Mathematics 101
- Molecular Biology 49
- Health, Toxicology and Mutagenesis 45
- Materials Chemistry 25
- Pollution 16
Countries citing papers authored by Filippo Lunghini
This map shows the geographic impact of Filippo Lunghini'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 Filippo Lunghini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Filippo Lunghini more than expected).
Fields of papers citing papers by Filippo Lunghini
This network shows the impact of papers produced by Filippo Lunghini. 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 Filippo Lunghini. The network helps show where Filippo Lunghini may publish in the future.
Co-authorship network of co-authors of Filippo Lunghini
This figure shows the co-authorship network connecting the top 25 collaborators of Filippo Lunghini. A scholar is included among the top collaborators of Filippo Lunghini 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 Filippo Lunghini. Filippo Lunghini 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 | 0 | |
| 4 | 1 | |
| 5 | 14 | |
| 6 | 9 | |
| 7 | 5 | |
| 8 | 5 | |
| 9 | 5 | |
| 10 | 15 | |
| 11 | 3 | |
| 12 | 22 | |
| 13 | 3 | |
| 14 | 15 | |
| 15 | 26 | |
| 16 | 28 | |
| 17 | 33 |
About Filippo Lunghini
Filippo Lunghini is a scholar working on Chemical Health and Safety, Computational Theory and Mathematics and Analytical Chemistry, having authored 17 papers that have together received 185 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Metabolomics and Mass Spectrometry Studies (4 papers) and Machine Learning in Materials Science (3 papers). The work is most often cited by research in Chemical Health and Safety (9 citations), Computational Theory and Mathematics (101 citations) and Health, Toxicology and Mutagenesis (45 citations). Filippo Lunghini has collaborated with scholars based in Italy, France and Czechia. Frequent co-authors include Philippe Azam, Gilles Marcou, Alexandre Varnek, Erik Van Miert, Dragos Horvath, Andrea R. Beccari, Monica Locatelli, Andrea Spinazzè, Andrea Cattaneo and Davide Campagnolo. Their work appears in journals such as International Journal of Molecular Sciences, Frontiers in Pharmacology and Methods in molecular biology.
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.