Giulia Russo

3.1k total citations
113 papers, 1.9k citations indexed

About

Giulia Russo is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Infectious Diseases. According to data from OpenAlex, Giulia Russo has authored 113 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 21 papers in Cardiology and Cardiovascular Medicine and 17 papers in Infectious Diseases. Recurrent topics in Giulia Russo's work include vaccines and immunoinformatics approaches (19 papers), Gene Regulatory Network Analysis (13 papers) and Multiple Sclerosis Research Studies (10 papers). Giulia Russo is often cited by papers focused on vaccines and immunoinformatics approaches (19 papers), Gene Regulatory Network Analysis (13 papers) and Multiple Sclerosis Research Studies (10 papers). Giulia Russo collaborates with scholars based in Italy, United Kingdom and United States. Giulia Russo's co-authors include Francesco Pappalardo, Marzio Pennisi, Marco Viceconti, Santo Motta, Flora T. Musuamba, Murray A. Rudd, Joseph Loscalzo, Yingyi Zhang, John E. Jones and Lisa A. Mendes and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Giulia Russo

101 papers receiving 1.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Giulia Russo Italy 25 573 315 291 286 240 113 1.9k
Vipul C. Chitalia United States 30 905 1.6× 180 0.6× 166 0.6× 271 0.9× 260 1.1× 94 2.5k
Ståle Nygård Norway 28 784 1.4× 536 1.7× 406 1.4× 138 0.5× 346 1.4× 80 2.2k
Jorge L. Sepulveda United States 26 1.1k 2.0× 243 0.8× 227 0.8× 207 0.7× 310 1.3× 54 2.1k
Gina Zini Italy 28 461 0.8× 110 0.3× 278 1.0× 296 1.0× 162 0.7× 123 3.0k
Naoki Nakashima Japan 30 1.1k 1.9× 189 0.6× 553 1.9× 183 0.6× 594 2.5× 194 3.1k
Ya‐Wen Yang Taiwan 24 975 1.7× 193 0.6× 548 1.9× 229 0.8× 378 1.6× 81 3.1k
Jianye Wang China 26 365 0.6× 95 0.3× 315 1.1× 106 0.4× 274 1.1× 226 2.4k
Giuseppe d’Onofrio Italy 23 238 0.4× 377 1.2× 310 1.1× 268 0.9× 367 1.5× 83 2.4k
In‐Cheol Kim South Korea 20 210 0.4× 582 1.8× 163 0.6× 266 0.9× 373 1.6× 179 1.8k
Vishnu Reddy United States 25 251 0.4× 209 0.7× 269 0.9× 115 0.4× 260 1.1× 137 2.4k

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-authorship network of co-authors of Giulia Russo

This figure shows the co-authorship network connecting the top 25 collaborators of Giulia Russo. A scholar is included among the top collaborators of Giulia Russo 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 Giulia Russo. Giulia Russo 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
1.
Pistollato, Francesca, et al.. (2025). Advancing the frontier of rare disease modeling: a critical appraisal of in silico technologies. npj Digital Medicine. 8(1). 676–676.
2.
Ghodousi, Arash, et al.. (2024). Evaluating the efficacy of whole genome sequencing in predicting susceptibility profiles for first-line antituberculosis drugs. Clinical Microbiology and Infection. 31(1). 121.e1–121.e5. 2 indexed citations
3.
4.
Bisceglia, Irma, Maria Laura Canale, Massimiliano Camilli, et al.. (2022). Cardioncogeriatria: position paper ANMCO sulla gestione cardioncologica del paziente anziano. Giornale italiano di cardiologia. 23(11). 878–891.
5.
Russo, Giulia, et al.. (2022). In silico design of recombinant multi-epitope vaccine against influenza A virus. BMC Bioinformatics. 22(S14). 617–617. 39 indexed citations
6.
Pappalardo, Francesco, et al.. (2022). In silico clinical trials for relapsing-remitting multiple sclerosis with MS TreatSim. BMC Medical Informatics and Decision Making. 22(S6). 294–294. 7 indexed citations
7.
Russo, Giulia, et al.. (2022). Model verification tools: a computational framework for verification assessment of mechanistic agent-based models. BMC Bioinformatics. 22(S14). 626–626. 1 indexed citations
8.
Bisceglia, Irma, Domenico Gabrielli, Maria Laura Canale, et al.. (2021). Position paper ANMCO: Cardio-oncologia in era COVID-19. Giornale italiano di cardiologia. 22(10). 800–825. 1 indexed citations
9.
Bonaccorso, Angela, Giulia Russo, Francesco Pappalardo, et al.. (2021). Quality by design tools reducing the gap from bench to bedside for nanomedicine. European Journal of Pharmaceutics and Biopharmaceutics. 169. 144–155. 23 indexed citations
10.
Russo, Giulia, Marzio Pennisi, Santo Motta, et al.. (2020). In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 33 indexed citations
11.
Pasquinucci, Lorella, Rita Turnaturi, Girolamo Calò, et al.. (2019). (2S)-N-2-methoxy-2-phenylethyl-6,7-benzomorphan compound (2S-LP2): Discovery of a biased mu/delta opioid receptor agonist. European Journal of Medicinal Chemistry. 168. 189–198. 18 indexed citations
12.
Tarantini, Luigi, Michele Massimo Gulizia, Andrea Di Lenarda, et al.. (2017). [ANMCO/AICO/AIOM Consensus document: Clinical and management pathways in cardio-oncology].. PubMed. 18(1). 14–66. 3 indexed citations
13.
Tarantini, Luigi, Michele Massimo Gulizia, Andrea Di Lenarda, et al.. (2017). Documento di consenso ANMCO/AICO/AIOM: Snodi clinico-gestionali in ambito cardioncologico. Giornale italiano di cardiologia. 18(1). 14–66. 2 indexed citations
14.
Tarantini, Luigi, Michele Massimo Gulizia, Andrea Di Lenarda, et al.. (2017). ANMCO/AIOM/AICO Consensus Document on clinical and management pathways of cardio-oncology: executive summary. European Heart Journal Supplements. 19(suppl_D). D370–D379. 24 indexed citations
15.
Barcellini, Lucia, Emanuele Borroni, James Brown, et al.. (2016). First evaluation of QuantiFERON-TB Gold Plus performance in contact screening. European Respiratory Journal. 48(5). 1411–1419. 106 indexed citations
16.
Pulignano, Giovanni, Donatella Del Sindaco, Andrea Di Lenarda, et al.. (2016). Incremental Value of Gait Speed in Predicting Prognosis of Older Adults With Heart Failure. JACC Heart Failure. 4(4). 289–298. 92 indexed citations
17.
Pennisi, Marzio, Giulia Russo, Santo Motta, & Francesco Pappalardo. (2015). Agent based modeling of the effects of potential treatments over the blood–brain barrier in multiple sclerosis. Journal of Immunological Methods. 427. 6–12. 19 indexed citations
18.
Cioffi, Giovanni, Giovanni Pulignano, Giulia Barbati, et al.. (2014). Reasons why patients suffering from chronic heart failure at very high risk for death survive. International Journal of Cardiology. 177(1). 213–218. 3 indexed citations
19.
Witort, Ewa, Laura Papucci, Nicola Schiavone, et al.. (2007). Autologous Lipofilling: Coenzyme Q10 Can Rescue Adipocytes from Stress-Induced Apoptotic Death. Plastic & Reconstructive Surgery. 119(4). 1191–1199. 21 indexed citations
20.
Condorelli, Fabrizio, Aldo Stivala, Rita Gallo, et al.. (1997). Improvement in establishing the period of rubella virus primary infection using a mild protein denaturant. Journal of Virological Methods. 66(1). 109–112. 5 indexed citations

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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