Pedro G. Pascutti
- Molecular Biology top 10%
- Computational Theory and Mathematics top 2%
- Materials Chemistry
- Organic Chemistry top 10%
- Public Health, Environmental and Occupational Health top 10%
- Co-authors
- Paulo M. BischMarcelo A. MoretPaulo Ricardo BatistaTanos C. C. FrançaJosé Daniel Figueroa‐VillarKleber C. MundimArlan da Silva GonçalvesMaurício G. S. Costa
- Topics
- Protein Structure and Dynamics (26 papers)Trypanosoma species research and implications (17 papers)Computational Drug Discovery Methods (13 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryThe Journal of Chemical Physics
- Partner nations
- BrazilUnited StatesFrance
In The Last Decade
Pedro G. Pascutti
94 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 135
- Molecular Biology 757
- Computational Theory and Mathematics 223
- Materials Chemistry 163
- Organic Chemistry 157
- Public Health, Environmental and Occupational Health 156
Countries citing papers authored by Pedro G. Pascutti
This map shows the geographic impact of Pedro G. Pascutti'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 Pedro G. Pascutti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pedro G. Pascutti more than expected).
Fields of papers citing papers by Pedro G. Pascutti
This network shows the impact of papers produced by Pedro G. Pascutti. 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 Pedro G. Pascutti. The network helps show where Pedro G. Pascutti may publish in the future.
Co-authorship network of co-authors of Pedro G. Pascutti
This figure shows the co-authorship network connecting the top 25 collaborators of Pedro G. Pascutti. A scholar is included among the top collaborators of Pedro G. Pascutti 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 Pedro G. Pascutti. Pedro G. Pascutti 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 | 1 | |
| 4 | 8 | |
| 5 | 5 | |
| 6 | 21 | |
| 7 | 26 | |
| 8 | 18 | |
| 9 | 6 | |
| 10 | 12 | |
| 11 | 20 | |
| 12 | 3 | |
| 13 | 13 | |
| 14 | 29 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | 3 | |
| 18 | 5 | |
| 19 | 2 | |
| 20 | 32 |
About Pedro G. Pascutti
Pedro G. Pascutti is a scholar working on Virology, Toxicology and Physical and Theoretical Chemistry, having authored 98 papers that have together received 1.4k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (26 papers), Trypanosoma species research and implications (17 papers) and Computational Drug Discovery Methods (13 papers). The work is most often cited by research in Computational Theory and Mathematics (223 citations), Virology (65 citations) and Molecular Biology (757 citations). Pedro G. Pascutti has collaborated with scholars based in Brazil, United States and France. Frequent co-authors include Paulo M. Bisch, Marcelo A. Moret, Paulo Ricardo Batista, Tanos C. C. França, José Daniel Figueroa‐Villar, Kleber C. Mundim, Arlan da Silva Gonçalves, Maurício G. S. Costa, Pedro Henrique Monteiro Torres and Diego E. B. Gomes. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Chemical Physics.
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.