Michele Catanzaro

3.2k citations
49 papers · 2.1k indexed · 2 hit papers · h-index 23
Topics
Complex Network Analysis Techniques (13 papers)Opinion Dynamics and Social Influence (10 papers)Science, Research, and Medicine (7 papers)
Partner nations
ItalySpainUnited States

In The Last Decade

Michele Catanzaro

43 papers receiving 2.1k citations

Hit Papers

Generation of uncorrelated random scale-free networks200520262012201920052020100200300400500

Peers

Michele Catanzaro
Comparison fields: 5 of 176
  • Statistical and Nonlinear Physics 850
  • Molecular Biology 369
  • Infectious Diseases 343
  • Sociology and Political Science 186
  • Neurology 150
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Lin Tao China
Natali Gulbahce United States
Reinhard Laubenbacher United States
Guo‐Wei Wei United States
Chang No Yoon South Korea
Eivind Almaas Norway
Nataša Pržulj United Kingdom
Xinchu Fu China
Hidde de Jong France
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Michele Catanzaro relative to Lin Tao China Lin Tao's profile →
Citations per field
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Citations per year

Countries citing papers authored by Michele Catanzaro

Since Specialization
Citations

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

Fields of papers citing papers by Michele Catanzaro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michele Catanzaro

This figure shows the co-authorship network connecting the top 25 collaborators of Michele Catanzaro. A scholar is included among the top collaborators of Michele Catanzaro 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 Michele Catanzaro. Michele Catanzaro 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
#WorkIndexed citations
1 0
2 2
3 1
4 25
5
Immune response in COVID-19: addressing a pharmacological challenge by targeting pathways triggered by SARS-CoV-2breakdown →
457
6 24
7 61
8 48
9 51
10 4
11 34
12 91
13 18
14 0
15
Networks: A Very Short Introduction
29
16 49
17 45
18 65
19
Generation of uncorrelated random scale-free networksbreakdown →
522
20 88

About Michele Catanzaro

Michele Catanzaro is a scholar working on Statistical and Nonlinear Physics, Reproductive Medicine and Molecular Medicine, having authored 49 papers that have together received 2.1k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (13 papers), Opinion Dynamics and Social Influence (10 papers) and Science, Research, and Medicine (7 papers). The work is most often cited by research in Statistical and Nonlinear Physics (850 citations), Modeling and Simulation (115 citations) and Molecular Medicine (119 citations). Michele Catanzaro has collaborated with scholars based in Italy, Spain and United States. Frequent co-authors include Romualdo Pastor‐Satorras, Marián Boguñá, Cristina Lanni, Marco Racchi, Emanuela Corsini, Guido Caldarelli, Stefano Govoni, Francesca Fagiani, Michela Rosini and Stefano Battiston. Their work appears in journals such as Nature, Science and Nature Medicine.

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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