Giulia Russo

105 papers receiving 1.9k citations

Peers

Giulia Russo
Comparison fields: 5 of 168
  • Modeling and Simulation 75
  • Health Informatics 20
  • Infectious Diseases 234
  • Cardiology and Cardiovascular Medicine 249
  • Immunology 171
Replace Xiaobo Zhou with:
Xiaobo Zhou United States
Miyoung Kim South Korea
Lu Tang China
Wan Zhu China
Pei Liu China
Junya Fukuoka Japan
Qi Mi United States
Hua Xu China
Kevin K. Dobbin United States
Naoki Nakashima Japan
Giulia Russo relative to Xiaobo Zhou United States Xiaobo Zhou's profile →
Citations per field
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Citations per year

Countries citing papers authored by Giulia Russo

Since Specialization
Citations

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

Fields of papers citing papers by Giulia Russo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Giulia Russo, 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 Giulia Russo Line = papers co-authored together Giulia Russo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 112 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018185
2 2002127
3 2016108
4 201696
5 202189
6 201477
7 201561
8 202054
9 201449
10 202247
11 201647
12 201942
13 202334
14 202033
15 200033
16 201633
17 202032
18 202131
19 201529
20 202029

About Giulia Russo

Giulia Russo is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Infectious Diseases, Epidemiology and Immunology, having authored 112 papers that have together received 1.9k indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (12 papers), Gene Regulatory Network Analysis (12 papers), Multiple Sclerosis Research Studies (9 papers), SARS-CoV-2 and COVID-19 Research (8 papers), Chemotherapy-induced cardiotoxicity and mitigation (6 papers), Computational Drug Discovery Methods (6 papers), Bioinformatics and Genomic Networks (6 papers) and Immunotherapy and Immune Responses (5 papers). The work is most often cited by research in Modeling and Simulation (75 citations), Health Informatics (20 citations), Infectious Diseases (234 citations), Cardiology and Cardiovascular Medicine (249 citations) and Immunology (171 citations). Giulia Russo has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Francesco Pappalardo, Marzio Pennisi, Marco Viceconti, Santo Motta, Flora T. Musuamba, John E. Jones, Joseph Loscalzo, Lisa A. Mendes, Yingyi Zhang and Murray A. Rudd. Their work appears in journals such as BMC Bioinformatics, Computational and Structural Biotechnology Journal, Bioinformatics, Briefings in Bioinformatics and BioMed Research International.

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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