Fernando Palluzzi

718 total citations
18 papers, 374 citations indexed

About

Fernando Palluzzi is a scholar working on Molecular Biology, Cancer Research and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Fernando Palluzzi has authored 18 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Cancer Research and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Fernando Palluzzi's work include Cancer Genomics and Diagnostics (4 papers), Gene expression and cancer classification (3 papers) and Cancer Mechanisms and Therapy (2 papers). Fernando Palluzzi is often cited by papers focused on Cancer Genomics and Diagnostics (4 papers), Gene expression and cancer classification (3 papers) and Cancer Mechanisms and Therapy (2 papers). Fernando Palluzzi collaborates with scholars based in Italy, Austria and United States. Fernando Palluzzi's co-authors include Mario Grassi, Barbara Borroni, Davide Guido, Luciano Giacò, Marco Masseroli, Enrico Premi, Vahid Jalili, Pietro Pinoli, Heiko Müller and Stefano Ceri and has published in prestigious journals such as Nature Genetics, Bioinformatics and PLoS ONE.

In The Last Decade

Fernando Palluzzi

18 papers receiving 372 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fernando Palluzzi Italy 10 162 69 67 51 41 18 374
Minwei Zhu China 15 167 1.0× 60 0.9× 30 0.4× 77 1.5× 79 1.9× 33 469
Ruizhe Zheng China 12 147 0.9× 37 0.5× 46 0.7× 57 1.1× 124 3.0× 27 419
Joseph H. Rothstein United States 10 166 1.0× 116 1.7× 25 0.4× 29 0.6× 35 0.9× 12 491
Brian M. Schilder United States 13 258 1.6× 28 0.4× 134 2.0× 41 0.8× 44 1.1× 20 532
David R. O’Brien United States 8 200 1.2× 73 1.1× 21 0.3× 54 1.1× 40 1.0× 9 404
Katrina Moore Australia 9 148 0.9× 46 0.7× 18 0.3× 83 1.6× 35 0.9× 18 397
Chunhong Qin China 12 205 1.3× 127 1.8× 26 0.4× 77 1.5× 31 0.8× 19 459
Giovanni Di Liberto Switzerland 14 106 0.7× 16 0.2× 102 1.5× 45 0.9× 38 0.9× 26 464
P. A. Wijeratne United Kingdom 17 251 1.5× 65 0.9× 50 0.7× 47 0.9× 265 6.5× 28 814
Lanting Li China 11 60 0.4× 70 1.0× 22 0.3× 21 0.4× 65 1.6× 31 303

Countries citing papers authored by Fernando Palluzzi

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Palluzzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Palluzzi

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

All Works

18 of 18 papers shown
1.
Fragomeni, Simona Maria, F. Moro, Fernando Palluzzi, et al.. (2023). Evaluating the Risk of Inguinal Lymph Node Metastases before Surgery Using the Morphonode Predictive Model: A Prospective Diagnostic Study in Vulvar Cancer Patients. Cancers. 15(4). 1121–1121. 6 indexed citations
2.
Pitolli, Consuelo, Alberto Marini, Marco Pieraccioli, et al.. (2023). MYC up-regulation confers vulnerability to dual inhibition of CDK12 and CDK13 in high-risk Group 3 medulloblastoma. Journal of Experimental & Clinical Cancer Research. 42(1). 214–214. 6 indexed citations
3.
Palluzzi, Fernando, Paola Nicoli, Marina Melixetian, et al.. (2023). Actionable Genetic Screens Unveil Targeting of AURKA, MEK, and Fatty Acid Metabolism as an Alternative Therapeutic Approach for Advanced Melanoma. Journal of Investigative Dermatology. 143(10). 1993–2006.e10. 1 indexed citations
4.
Jalili, Vahid, Marzia A. Cremona, & Fernando Palluzzi. (2023). Rescuing biologically relevant consensus regions across replicated samples. BMC Bioinformatics. 24(1). 1 indexed citations
5.
Fragomeni, Simona Maria, F. Moro, Fernando Palluzzi, et al.. (2022). 2022-RA-1299-ESGO How to predict preoperative risk of lymph node metastasis in vulvar cancer patients the Morphonode Predictive Model. International Journal of Gynecological Cancer. 32. A445–A446. 2 indexed citations
6.
Giacò, Luciano, Fernando Palluzzi, Davide Guido, et al.. (2022). A Computational Framework for Comprehensive Genomic Profiling in Solid Cancers: The Analytical Performance of a High-Throughput Assay for Small and Copy Number Variants. Cancers. 14(24). 6152–6152. 6 indexed citations
7.
Buttarelli, Marianna, Alessandra Ciucci, Fernando Palluzzi, et al.. (2022). Identification of a novel gene signature predicting response to first-line chemotherapy in BRCA wild-type high-grade serous ovarian cancer patients. Journal of Experimental & Clinical Cancer Research. 41(1). 50–50. 22 indexed citations
8.
Dotolo, Serena, Riziero Esposito Abate, Cristin Roma, et al.. (2022). Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice. Biomedicines. 10(9). 2074–2074. 19 indexed citations
9.
Grassi, Mario, et al.. (2022). SEMgraph: an R package for causal network inference of high-throughput data with structural equation models. Bioinformatics. 38(20). 4829–4830. 11 indexed citations
10.
Caldarella, Carmelo, Fabrizio Cocciolillo, Silvia Taralli, et al.. (2021). The impact of the COVID-19 pandemic on oncological disease extent at FDG PET/CT staging: the ONCOVIPET study. European Journal of Nuclear Medicine and Molecular Imaging. 49(5). 1623–1629. 6 indexed citations
11.
Benussi, Alberto, Mario Grassi, Fernando Palluzzi, et al.. (2021). Classification accuracy of TMS for the diagnosis of mild cognitive impairment. Brain stimulation. 14(2). 241–249. 37 indexed citations
12.
Benussi, Alberto, Mario Grassi, Fernando Palluzzi, et al.. (2020). Classification Accuracy of Transcranial Magnetic Stimulation for the Diagnosis of Neurodegenerative Dementias. Annals of Neurology. 87(3). 394–404. 61 indexed citations
13.
Dellino, Gaetano Ivan, Fernando Palluzzi, Andrea M. Chiariello, et al.. (2019). Release of paused RNA polymerase II at specific loci favors DNA double-strand-break formation and promotes cancer translocations. Nature Genetics. 51(6). 1011–1023. 70 indexed citations
14.
Premi, Enrico, Viviana Cristillo, Stefano Gazzina, et al.. (2019). Brain Connectivity and Information-Flow Breakdown Revealed by a Minimum Spanning Tree-Based Analysis of MRI Data in Behavioral Variant Frontotemporal Dementia. Frontiers in Neuroscience. 13. 211–211. 26 indexed citations
15.
Palluzzi, Fernando, Raffaele Ferrari, Francesca Graziano, et al.. (2017). A novel network analysis approach reveals DNA damage, oxidative stress and calcium/cAMP homeostasis-associated biomarkers in frontotemporal dementia. PLoS ONE. 12(10). e0185797–e0185797. 29 indexed citations
16.
Chicco, Davide, Fernando Palluzzi, & Marco Masseroli. (2017). Novelty Indicator for Enhanced Prioritization of Predicted Gene Ontology Annotations. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 15(3). 954–965. 2 indexed citations
17.
Guido, Davide, et al.. (2015). Telling the Story of Frontotemporal Dementia by Bibliometric Analysis. Journal of Alzheimer s Disease. 48(3). 703–709. 11 indexed citations
18.
Masseroli, Marco, Pietro Pinoli, Vahid Jalili, et al.. (2015). GenoMetric Query Language: a novel approach to large-scale genomic data management. Bioinformatics. 31(12). 1881–1888. 58 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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