Luca Raiola

532 citations
18 papers · 439 · h-index 13

Impact in

Papers in

    • Prion Diseases and Protein Misfolding 3
    • Ubiquitin and proteasome pathways 2
    • Protein Structure and Dynamics 2
    • Herpesvirus Infections and Treatments 2

Luca Raiola

18 papers receiving 437 citations

Peers

Luca Raiola
Comparison fields: 5 of 83
  • Biomaterials 64
  • Microbiology 26
  • Cell Biology 60
  • Molecular Biology 224
  • Pharmaceutical Science 20
Replace Madhuresh Sumit with:
Madhuresh Sumit United States
V. Antonini Italy
Dipannita Dutta United States
Mathieu Mével France
Jung Su Ryu United States
Masami Ukawa Japan
Stéphane Desgranges France
Aparajita Khatri Australia
Wolfgang Röedl Germany
Luca Raiola relative to Madhuresh Sumit United States Madhuresh Sumit's profile →
Citations per field
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Madhuresh Sumit · 1×
Citations per year

Countries citing papers authored by Luca Raiola

Since Specialization
Citations

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

Fields of papers citing papers by Luca Raiola

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Luca Raiola, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Luca Raiola Line = papers co-authored together Luca Raiola links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 200853
2 201053
3 201743
4 201740
5 201636
6 201430
7 201028
8 200427
9 201324
10 201723
11 201518
12 200517
13 201616
14 200710
15 20137
16 20137
17 20216
18
Mesh analysis and topological optimization of a drone propeller using CFD software
20201

About Luca Raiola

Luca Raiola is a scholar working on Molecular Biology, Epidemiology, Biomaterials, Cell Biology and Immunology, having authored 18 papers that have together received 439 indexed citations. Recurring topics across this work include Prion Diseases and Protein Misfolding (3 papers), Ubiquitin and proteasome pathways (2 papers), Nanoparticle-Based Drug Delivery (2 papers), Protein Structure and Dynamics (2 papers), Herpesvirus Infections and Treatments (2 papers), Enzyme Structure and Function (2 papers), Toxin Mechanisms and Immunotoxins (2 papers) and Physiological and biochemical adaptations (2 papers). The work is most often cited by research in Biomaterials (64 citations), Microbiology (26 citations), Cell Biology (60 citations), Molecular Biology (224 citations) and Pharmaceutical Science (20 citations). Luca Raiola has collaborated with scholars based in Italy, Canada and United Kingdom. Frequent co-authors include Carla Isernia, James G. Omichinski, Stefania Galdiero, Annarita Falanga, Mariateresa Vitiello, Carlo Pedone, Massimiliano Galdiero, Geneviève Arseneault, Paolo A. Netti and Daniela Guarnieri. Their work appears in journals such as Journal of Biological Chemistry, Colloids and Surfaces B Biointerfaces, Nucleic Acids Research, Protein Science and Gels.

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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