Silvia Benvenuti

3.4k total citations · 2 hit papers
40 papers, 2.6k citations indexed

About

Silvia Benvenuti is a scholar working on Molecular Biology, Oncology and Hepatology. According to data from OpenAlex, Silvia Benvenuti has authored 40 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 15 papers in Oncology and 11 papers in Hepatology. Recurrent topics in Silvia Benvenuti's work include Liver physiology and pathology (11 papers), Cancer Diagnosis and Treatment (5 papers) and Microtubule and mitosis dynamics (4 papers). Silvia Benvenuti is often cited by papers focused on Liver physiology and pathology (11 papers), Cancer Diagnosis and Treatment (5 papers) and Microtubule and mitosis dynamics (4 papers). Silvia Benvenuti collaborates with scholars based in Italy, United States and United Kingdom. Silvia Benvenuti's co-authors include Alberto Bardelli, Paolo M. Comoglio, Andrea Sartore‐Bianchi, Federica Di Nicolantonio, Salvatore Siena, Mauro Moroni, Silvio Veronese, Carlo Zanon, Marcello Gambacorta and Giovanna Marrapese and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Silvia Benvenuti

38 papers receiving 2.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Gene copy number for epidermal growth factor receptor (EGFR) and clinical response to antiEGFR treatment in colorectal cancer: a cohort study

2005 771 citations Mauro Moroni, Silvio Veronese et al. profile →
Oncogenic Activation of the RAS/RAF Signaling Pathway Impairs the Response of Metastatic Colorectal Cancers to Anti–Epidermal Growth Factor Receptor Antibody Therapies

2007 672 citations Silvia Benvenuti, Andrea Sartore‐Bianchi et al. Cancer Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Silvia Benvenuti Italy	20	1.6k	969	923	586	436	40	2.6k
Sid Suggs United States	8	2.1k 1.3×	646 0.7×	830 0.9×	868 1.5×	634 1.5×	8	2.8k
Belinda Cancilla United States	18	1.1k 0.7×	1.5k 1.5×	673 0.7×	309 0.5×	377 0.9×	38	2.7k
Anthony M. D’Amelio United States	16	1.4k 0.9×	1.4k 1.5×	1.6k 1.7×	459 0.8×	697 1.6×	37	2.9k
Katia Bencardino Italy	24	1.8k 1.1×	592 0.6×	806 0.9×	669 1.1×	591 1.4×	77	2.4k
Francesco Galimi Italy	24	1.2k 0.7×	1.1k 1.1×	444 0.5×	322 0.5×	458 1.1×	35	2.5k
Annarita Destro Italy	29	1.5k 0.9×	1.2k 1.2×	1.6k 1.7×	375 0.6×	621 1.4×	58	3.7k
Zhaoshi Zeng United States	27	1.3k 0.8×	1.0k 1.1×	397 0.4×	686 1.2×	897 2.1×	37	2.6k
Courtney Hyland United States	2	2.0k 1.3×	1.9k 2.0×	2.1k 2.3×	398 0.7×	683 1.6×	4	3.6k
Simona Lamba Italy	25	1.5k 0.9×	1.5k 1.6×	760 0.8×	713 1.2×	1.0k 2.4×	39	3.3k
Wendy De Roock Belgium	16	2.3k 1.4×	657 0.7×	1.1k 1.2×	963 1.6×	560 1.3×	31	2.8k

Countries citing papers authored by Silvia Benvenuti

Since Specialization

Citations

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

Fields of papers citing papers by Silvia Benvenuti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Silvia Benvenuti

This figure shows the co-authorship network connecting the top 25 collaborators of Silvia Benvenuti. A scholar is included among the top collaborators of Silvia Benvenuti 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 Silvia Benvenuti. Silvia Benvenuti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Pisacane, Alberto, Eliano Cascardi, Enrico Berrino, et al.. (2022). Real-world histopathological approach to malignancy of undefined primary origin (MUO) to diagnose cancers of unknown primary (CUPs). Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 482(3). 463–475. 14 indexed citations

Arigoni, Maddalena, Silvia Benvenuti, Davide Cacchiarelli, et al.. (2021). MET Exon 14 Skipping: A Case Study for the Detection of Genetic Variants in Cancer Driver Genes by Deep Learning. International Journal of Molecular Sciences. 22(8). 4217–4217. 6 indexed citations

Verginelli, Federica, Alberto Pisacane, Gennaro Gambardella, et al.. (2021). Cancer of unknown primary stem-like cells model multi-organ metastasis and unveil liability to MEK inhibition. Nature Communications. 12(1). 2498–2498. 20 indexed citations

Cova, Emanuela, Laura Pandolfi, Miriam Colombo, et al.. (2019). <p>Pemetrexed-loaded nanoparticles targeted to malignant pleural mesothelioma cells: an in vitro study</p>. International Journal of Nanomedicine. Volume 14. 773–785. 19 indexed citations

Benvenuti, Silvia, Alessandra Gentile, Rebecca Senetta, et al.. (2018). RON tyrosine kinase mutations in brain metastases from lung cancer. ERJ Open Research. 4(1). 83–2017. 6 indexed citations

Zarei, Omid, et al.. (2017). Identification of a RON tyrosine kinase receptor binding peptide using phage display technique and computational modeling of its binding mode. Journal of Molecular Modeling. 23(9). 267–267. 2 indexed citations

Zarei, Omid, et al.. (2016). Strategies of targeting the extracellular domain of RON tyrosine kinase receptor for cancer therapy and drug delivery. Journal of Cancer Research and Clinical Oncology. 142(12). 2429–2446. 15 indexed citations

Lazzari, Luca, Alessandra Gentile, Silvia Benvenuti, Livio Trusolino, & Paolo M. Comoglio. (2013). ROR1 is a pseudokinase that is crucial for MET-driven tumorigenesis. BMC Proceedings. 7(S2). 39 indexed citations

Benvenuti, Silvia, et al.. (2013). An ‘in‐cell trial’ to assess the efficacy of a monovalent anti‐MET antibody as monotherapy and in association with standard cytotoxics. Molecular Oncology. 8(2). 378–388. 8 indexed citations

10.

Gentile, Alessandra, Luca Lazzari, Silvia Benvenuti, Livio Trusolino, & Paolo M. Comoglio. (2011). Ror1 Is a Pseudokinase That Is Crucial for Met-Driven Tumorigenesis. Cancer Research. 71(8). 3132–3141. 107 indexed citations

11.

Benvenuti, Silvia, et al.. (2011). Ron Kinase Transphosphorylation Sustains MET Oncogene Addiction. Cancer Research. 71(5). 1945–1955. 63 indexed citations

12.

Stella, Giulia Maria, Silvia Benvenuti, Daniela Gramaglia, et al.. (2010). MET mutations in cancers of unknown primary origin (CUPs). Human Mutation. 32(1). 44–50. 58 indexed citations

13.

Benvenuti, Silvia, Andrea Sartore‐Bianchi, Federica Di Nicolantonio, et al.. (2007). Oncogenic Activation of the RAS/RAF Signaling Pathway Impairs the Response of Metastatic Colorectal Cancers to Anti–Epidermal Growth Factor Receptor Antibody Therapies. Cancer Research. 67(6). 2643–2648. 672 indexed citations breakdown →

14.

Piazzi, Luigi, Martina Felder, Michele Comberlato, et al.. (2007). Extracorporeal shock wave lithotripsy for clearance of refractory bile duct stones. Digestive and Liver Disease. 39(3). 267–272. 30 indexed citations

15.

Arena, Sabrina, Silvia Benvenuti, & Alberto Bardelli. (2005). Genetic analysis of the kinome and phosphatome in cancer. Cellular and Molecular Life Sciences. 62(18). 2092–2099. 56 indexed citations

16.

Hardy, Kristine, Alan Mackay, Silvia Benvenuti, et al.. (2004). Transcriptional Networks and Cellular Senescence in Human Mammary Fibroblasts. Molecular Biology of the Cell. 16(2). 943–953. 65 indexed citations

17.

Patel, Ketan J., Robert C. Stein, Silvia Benvenuti, & Marketa Zvelebil. (2002). Combinatorial use of mRNA and two-dimensional electrophoresis expression data to choose relevant features for mass spectrometric identification. PROTEOMICS. 2(10). 1464–1473. 3 indexed citations

18.

Piazzi, Luigi, Paige E. Farris, Michele Comberlato, et al.. (2002). 24 P Clearance of refractory bile duct stones with extracorporeal shock-wave lithotripsy (ESWL). Digestive and Liver Disease. 34. A124–A124. 1 indexed citations

19.

Benvenuti, Silvia, Rainer Cramer, Christopher C. Quinn, et al.. (2002). Differential Proteome Analysis of Replicative Senescence in Rat Embryo Fibroblasts. Molecular & Cellular Proteomics. 1(4). 280–292. 39 indexed citations

20.

Bardelli, Alberto, Paola Longati, Tracy Ann Williams, Silvia Benvenuti, & Paolo M. Comoglio. (1999). A Peptide Representing the Carboxyl-terminal Tail of the Met Receptor Inhibits Kinase Activity and Invasive Growth. Journal of Biological Chemistry. 274(41). 29274–29281. 55 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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