Rosa Buonfiglio

537 citations
12 papers · 422 indexed · h-index 10
Topics
Computational Drug Discovery Methods (5 papers)Cardiac electrophysiology and arrhythmias (3 papers)Protein Structure and Dynamics (2 papers)
Partner nations
ItalySwedenNetherlands

In The Last Decade

Rosa Buonfiglio

12 papers receiving 412 citations

Peers

Rosa Buonfiglio
Comparison fields: 5 of 88
  • Molecular Biology 273
  • Cancer Research 128
  • Computational Theory and Mathematics 76
  • Pharmacology 45
  • Organic Chemistry 44
Replace Lailiang Qu with:
Lailiang Qu China
Junlong Zhu China
Wen Jian Tang China
André Stander South Africa
Akshaya Murugesan Finland
Dong‐Rong Zhu China
Yuan Qing Qu Macao
Liu Zeng Chen China
Lidan Sun China
Madhu Sudhana Saddala United States
Rosa Buonfiglio relative to Lailiang Qu China Lailiang Qu's profile →
Citations per field
00.5×6.6×
Lailiang Qu · 1×
Citations per year

Countries citing papers authored by Rosa Buonfiglio

Since Specialization
Citations

This map shows the geographic impact of Rosa Buonfiglio'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 Rosa Buonfiglio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rosa Buonfiglio more than expected).

Fields of papers citing papers by Rosa Buonfiglio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rosa Buonfiglio. 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 Rosa Buonfiglio. The network helps show where Rosa Buonfiglio may publish in the future.

Co-authorship network of co-authors of Rosa Buonfiglio

This figure shows the co-authorship network connecting the top 25 collaborators of Rosa Buonfiglio. A scholar is included among the top collaborators of Rosa Buonfiglio 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 Rosa Buonfiglio. Rosa Buonfiglio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
#WorkIndexed citations
1 6
2 17
3 25
4 12
5 62
6 26
7 6
8 51
9 16
10 13
11 29
12 159

About Rosa Buonfiglio

Rosa Buonfiglio is a scholar working on Molecular Medicine, Computational Theory and Mathematics and Immunology and Allergy, having authored 12 papers that have together received 422 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Cardiac electrophysiology and arrhythmias (3 papers) and Protein Structure and Dynamics (2 papers). The work is most often cited by research in Cancer Research (128 citations), Computational Theory and Mathematics (76 citations) and Molecular Biology (273 citations). Rosa Buonfiglio has collaborated with scholars based in Italy, Sweden and Netherlands. Frequent co-authors include Maurizio Recanatini, Matteo Masetti, Marinella Roberti, Elisa Giacomini, Marina Vettraino, Marcella Manerba, Giuseppina Di Stefano, L. Fiume, Thierry Kogej and Sesselja Ómarsdóttir. Their work appears in journals such as Journal of Medicinal Chemistry, Biochimica et Biophysica Acta (BBA) - Biomembranes and Molecules.

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.

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