Maria Mazza

938 total citations
38 papers, 656 citations indexed

About

Maria Mazza is a scholar working on Molecular Biology, Nutrition and Dietetics and Neurology. According to data from OpenAlex, Maria Mazza has authored 38 papers receiving a total of 656 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 17 papers in Nutrition and Dietetics and 10 papers in Neurology. Recurrent topics in Maria Mazza's work include Prion Diseases and Protein Misfolding (28 papers), Trace Elements in Health (17 papers) and Neurological diseases and metabolism (10 papers). Maria Mazza is often cited by papers focused on Prion Diseases and Protein Misfolding (28 papers), Trace Elements in Health (17 papers) and Neurological diseases and metabolism (10 papers). Maria Mazza collaborates with scholars based in Italy, United States and France. Maria Mazza's co-authors include Pier Luigi Acutis, Cristina Casalone, Maria Caramelli, Cristiano Corona, Giuseppe Ru, Simone Peletto, Francesca Martucci, Barbara Iulini, Cristiana Maurella and Maria Vittoria Riina and has published in prestigious journals such as Nature Communications, PLoS ONE and Journal of Virology.

In The Last Decade

Maria Mazza

37 papers receiving 643 citations

Peers

Maria Mazza
Comparison fields: 5 of 71
  • Molecular Biology 591
  • Neurology 270
  • Nutrition and Dietetics 269
  • Materials Chemistry 100
  • Agronomy and Crop Science 37
Replace Clare R. Trevitt with:
Clare R. Trevitt United Kingdom
Carola Muñoz-Montesino Chile
Ulrich Genschel Germany
Yuji Sakasegawa Japan
Bénédicte Doublet France
Hilary E.M. McMahon Ireland
S. P. Ahuja India
Clare L. Newell United Kingdom
Suzana Dos Reis France
V.M. Kryukov Russia
Clare R. Trevitt United Kingdom View profile →
Citations per field, relative to Maria Mazza
Maria Mazza · 1×
Citations per year, relative to Maria Mazza
Maria Mazza · 1×

Countries citing papers authored by Maria Mazza

Since Specialization
Citations

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

Fields of papers citing papers by Maria Mazza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria Mazza

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 13
2 2
3 4
4 4
5 10
6 6
7 25
8 3
9 3
10 12
11 14
12 9
13 12
14 6
15
The AHQ allele is a risk factor for atypical scrapie Nor98 in goat.
1
16 39
17 10
18 32
19 11
20 4

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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