Giulia Lo Russo
Impact in
- Modeling and Simulation top 5%
- Health Informatics top 5%
Papers in
-
- SARS-CoV-2 and COVID-19 Research 9
- Co-authors
- Francesco Pappalardo (74 shared papers)Marzio Pennisi (33 shared papers)Marco Viceconti (13 shared papers)Santo Motta (12 shared papers)Flora Tshinanu Musuamba (3 shared papers)Murray A. Rudd (1 shared paper)Joseph Loscalzo (1 shared paper)Lisa A. Mendes (1 shared paper)
- Journals
- BMC Bioinformatics (11 papers)Computational and Structural Biotechnology Journal (5 papers)Bioinformatics (4 papers)Oncology (4 papers)Briefings in Bioinformatics (3 papers)
- Partner nations
- ItalyUnited KingdomUnited States
In The Last Decade
Giulia Lo Russo
121 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 175
- Modeling and Simulation 86
- Health Informatics 27
- Infectious Diseases 295
- Cardiology and Cardiovascular Medicine 301
- Immunology 190
Countries citing papers authored by Giulia Lo Russo
This map shows the geographic impact of Giulia Lo 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 Lo 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 Lo Russo more than expected).
Fields of papers citing papers by Giulia Lo Russo
This network shows the impact of papers produced by Giulia Lo 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 Lo Russo. The network helps show where Giulia Lo Russo may publish in the future.
Co-authors
The 25 scholars most cited alongside Giulia Lo Russo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 136 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 207 | |
| 2 | 2002 | 132 | |
| 3 | 2016 | 121 | |
| 4 | 2016 | 110 | |
| 5 | 2021 | 105 | |
| 6 | 2014 | 92 | |
| 7 | 2015 | 62 | |
| 8 | 2014 | 54 | |
| 9 | 2020 | 54 | |
| 10 | 2022 | 53 | |
| 11 | 2016 | 49 | |
| 12 | 2019 | 49 | |
| 13 | 2023 | 47 | |
| 14 | 2023 | 45 | |
| 15 | 2000 | 41 | |
| 16 | 2021 | 38 | |
| 17 | 2016 | 37 | |
| 18 | 2020 | 37 | |
| 19 | 2014 | 33 | |
| 20 | 2020 | 33 |
About Giulia Lo Russo
Giulia Lo Russo is a scholar working on Cardiology and Cardiovascular Medicine, Infectious Diseases, Molecular Biology, Immunology and Pathology and Forensic Medicine, having authored 136 papers that have together received 2.3k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (14 papers), vaccines and immunoinformatics approaches (14 papers), Multiple Sclerosis Research Studies (11 papers), SARS-CoV-2 and COVID-19 Research (9 papers), Computational Drug Discovery Methods (7 papers), Influenza Virus Research Studies (7 papers), Bioinformatics and Genomic Networks (7 papers) and Evolution and Genetic Dynamics (6 papers). The work is most often cited by research in Modeling and Simulation (86 citations), Health Informatics (27 citations), Infectious Diseases (295 citations), Cardiology and Cardiovascular Medicine (301 citations) and Immunology (190 citations). Giulia Lo 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 Tshinanu Musuamba, Murray A. Rudd, Joseph Loscalzo, Lisa A. Mendes, Yingyi Zhang and John Edward Jones. Their work appears in journals such as BMC Bioinformatics, Computational and Structural Biotechnology Journal, Bioinformatics, Oncology and Briefings in Bioinformatics.
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.