Marco Ruggiero

3.4k total citations
138 papers, 2.6k citations indexed

About

Marco Ruggiero is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, Marco Ruggiero has authored 138 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Molecular Biology, 20 papers in Cell Biology and 16 papers in Physiology. Recurrent topics in Marco Ruggiero's work include Proteoglycans and glycosaminoglycans research (13 papers), Protease and Inhibitor Mechanisms (9 papers) and Cell Adhesion Molecules Research (9 papers). Marco Ruggiero is often cited by papers focused on Proteoglycans and glycosaminoglycans research (13 papers), Protease and Inhibitor Mechanisms (9 papers) and Cell Adhesion Molecules Research (9 papers). Marco Ruggiero collaborates with scholars based in Italy, United States and United Kingdom. Marco Ruggiero's co-authors include Stefania Pacini, Vincenzo Chiarugi, Massimo Gulisano, Jacalyn H. Pierce, Simonetta Vannucchi, Giampaolo Manfrida, Gabriele Morucci, Timothy P. Fleming, E G Lapetina and Joel S. Greenberger and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Marco Ruggiero

125 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco Ruggiero Italy 29 1.1k 361 326 286 280 138 2.6k
J. Steven Alexander United States 34 1.2k 1.1× 633 1.8× 303 0.9× 192 0.7× 296 1.1× 87 3.1k
Hiroyuki Matsuno Japan 30 1.2k 1.1× 226 0.6× 206 0.6× 250 0.9× 277 1.0× 133 2.7k
David A. Goukassian United States 29 1.4k 1.2× 481 1.3× 331 1.0× 285 1.0× 406 1.4× 77 3.0k
Kaori Yoshida Japan 31 1.6k 1.4× 347 1.0× 346 1.1× 206 0.7× 209 0.7× 92 3.0k
Xiao‐Yan Wen Canada 35 1.5k 1.3× 391 1.1× 279 0.9× 394 1.4× 189 0.7× 113 3.7k
Bernd Kirchhof Germany 45 2.2k 2.0× 570 1.6× 158 0.5× 265 0.9× 234 0.8× 254 9.6k
Takehiro Nakamura Japan 38 1.3k 1.2× 286 0.8× 300 0.9× 127 0.4× 285 1.0× 158 4.8k
Rongli Zhang China 31 1.7k 1.5× 307 0.9× 314 1.0× 175 0.6× 425 1.5× 132 3.0k
Mack H. Wu United States 36 1.6k 1.5× 626 1.7× 342 1.0× 390 1.4× 468 1.7× 66 3.2k
Jianchun Chen China 24 937 0.8× 306 0.8× 220 0.7× 292 1.0× 165 0.6× 56 2.4k

Countries citing papers authored by Marco Ruggiero

Since Specialization
Citations

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

Fields of papers citing papers by Marco Ruggiero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Ruggiero

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Ruggiero. A scholar is included among the top collaborators of Marco Ruggiero 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 Marco Ruggiero. Marco Ruggiero 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.
Ruggiero, Marco, et al.. (2024). Transcritical Cycles With CO2-based Mixtures for CSP Applications: An Overview of the SCARABEUS Findings. SHILAP Revista de lepidopterología. 2. 1 indexed citations
2.
Montomoli, Francesco, et al.. (2024). Application of graph neural networks to predict explosion-induced transient flow. Advanced Modeling and Simulation in Engineering Sciences. 11(1). 1 indexed citations
3.
White, Martin T., et al.. (2023). Integrated Aerodynamic and Mechanical Design of a Large-Scale Axial Turbine Operating With A Supercritical Carbon Dioxide Mixture. Journal of Engineering for Gas Turbines and Power. 146(2). 1 indexed citations
4.
Bilotta, Antonio, et al.. (2023). Effect of the fire action on the seismic isolation system for existing reinforced concrete buildings. Case Studies in Construction Materials. 20. e02727–e02727.
5.
Ruggiero, Marco. (2022). Application of ultrasonography to Neuro-COVID-19. 9(3). 99–103. 1 indexed citations
6.
7.
Pacini, Stefania & Marco Ruggiero. (2017). Description of a Novel Probiotic Concept: Implications for the Modulation of the Immune System. American Journal of Applied Sciences (Multimedia University). 13(2). 107–113. 7 indexed citations
8.
Branca, Jacopo Junio Valerio, Stefania Pacini, & Marco Ruggiero. (2015). Effects of Pre-surgical Vitamin D Supplementation and Ketogenic Diet in a Patient with Recurrent Breast Cancer.. Anticancer Research. 35(10). 5525–32. 39 indexed citations
9.
Boni, Enrico, Simone Pacini, Jacopo Junio Valerio Branca, et al.. (2015). Morphological analysis of neurons: Automatic identification of elongations. PubMed. 2015. 8131–4. 3 indexed citations
10.
11.
Cecchi, Franco, Stefania Pacini, Massimo Gulisano, et al.. (2008). Heparin/heparan sulfate anticoagulant glycosaminoglycans in human plasma of healthy donors: preliminary study on a small group of recruits. Blood Coagulation & Fibrinolysis. 19(5). 349–354. 3 indexed citations
12.
Cecchi, Cristina, Anna Pensalfini, Massimo Stefani, et al.. (2007). Replicating neuroblastoma cells in different cell cycle phases display different vulnerability to amyloid toxicity. Journal of Molecular Medicine. 86(2). 197–209. 20 indexed citations
13.
Pacini, Stefania, Massimo Gulisano, Benedetta Peruzzi, et al.. (2003). Effects of 0.2 T static magnetic field on human skin fibroblasts. Cancer Detection and Prevention. 27(5). 327–332. 44 indexed citations
14.
Chiarugi, Vincenzo, Marco Ruggiero, & Lucia Magnelli. (2002). Angiogenesis and the Unique Nature of Tumor Matrix. Molecular Biotechnology. 21(1). 85–90. 18 indexed citations
15.
Aterini, Stefano, et al.. (1999). Lack of Association between Body Weight, Bone Mineral Density and Vitamin D Receptor Gene Polymorphism in Normal and Osteoporotic Women. Disease Markers. 15(4). 221–227. 9 indexed citations
16.
Pacini, Simone, Stefano Aterini, Patrizia Pacini, et al.. (1999). Influence of static magnetic field on the antiproliferative effects of vitamin D on human breast cancer cells.. PubMed. 11(6). 265–71. 12 indexed citations
17.
Pacini, Simone, et al.. (1996). [The determination of BB genotype of vitamin D receptors identifies patients at risk for osteoporosis].. PubMed. 92(5). 520–4. 4 indexed citations
18.
Mazzanti, Roberto, Ornella Fantappiè, Paola Fabrizio, et al.. (1996). Conferring drug resistance by MDR1 gene transfection increases susceptibility to irradiation and lipid peroxidation in 3T3 cell line. Free Radical Biology and Medicine. 20(4). 601–606. 6 indexed citations
19.
20.
Ruggiero, Marco, Sandra Fedi, P Bianchini, Simonetta Vannucchi, & Vincenzo Casolaro. (1984). Molecular events involved in the proaggregating effect of heparin on human platelets. Biochimica et Biophysica Acta (BBA) - General Subjects. 802(2). 372–377. 22 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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