Angelo Peschiaroli

3.9k total citations · 1 hit paper
40 papers, 3.0k citations indexed

About

Angelo Peschiaroli is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Angelo Peschiaroli has authored 40 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 22 papers in Oncology and 12 papers in Cell Biology. Recurrent topics in Angelo Peschiaroli's work include Cancer-related Molecular Pathways (19 papers), Ubiquitin and proteasome pathways (15 papers) and Epigenetics and DNA Methylation (6 papers). Angelo Peschiaroli is often cited by papers focused on Cancer-related Molecular Pathways (19 papers), Ubiquitin and proteasome pathways (15 papers) and Epigenetics and DNA Methylation (6 papers). Angelo Peschiaroli collaborates with scholars based in Italy, United Kingdom and United States. Angelo Peschiaroli's co-authors include Michele Pagano, Daniele Guardavaccaro, Gerry Melino, N. Valerio Dorrello, Nicholas E. Sherman, Nancy H. Colburn, David Frescas, Francesca Bernassola, Luca Busino and Florian Bassermann and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Angelo Peschiaroli

39 papers receiving 3.0k citations

Hit Papers

S6K1- and ßTRCP-Mediated Degradation of PDCD4 Promotes Pr... 2006 2026 2012 2019 2006 100 200 300 400 500

Peers

Angelo Peschiaroli
Pengbo Zhou United States
Kenneth L. Scott United States
Erik Meulmeester Netherlands
Lori S. Hart United States
Jianfei Qi United States
Angelo Peschiaroli
Citations per year, relative to Angelo Peschiaroli Angelo Peschiaroli (= 1×) peers Michiko Shirane

Countries citing papers authored by Angelo Peschiaroli

Since Specialization
Citations

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

Fields of papers citing papers by Angelo Peschiaroli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Angelo Peschiaroli

This figure shows the co-authorship network connecting the top 25 collaborators of Angelo Peschiaroli. A scholar is included among the top collaborators of Angelo Peschiaroli 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 Angelo Peschiaroli. Angelo Peschiaroli 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.
Nicolai, Sara, Veronica Gatti, Stefano Scalera, et al.. (2024). ABCC1 Is a ΔNp63 Target Gene Overexpressed in Squamous Cell Carcinoma. International Journal of Molecular Sciences. 25(16). 8741–8741.
2.
Gatti, Veronica, et al.. (2023). Senataxin and R-loops homeostasis: multifaced implications in carcinogenesis. Cell Death Discovery. 9(1). 145–145. 17 indexed citations
3.
Liu, Zhanhong, Pengbo Hou, Jiankai Fang, et al.. (2023). Hyaluronic acid metabolism and chemotherapy resistance: recent advances and therapeutic potential. Molecular Oncology. 18(9). 2087–2106. 6 indexed citations
4.
Gatti, Veronica, Stefano Scalera, Giacomo Corleone, et al.. (2023). The long non-coding RNA NEAT1 is a ΔNp63 target gene modulating epidermal differentiation. Nature Communications. 14(1). 3795–3795. 20 indexed citations
5.
Gatti, Veronica, Mirco Compagnone, Alessandro Mauriello, et al.. (2022). ΔNp63-Senataxin circuit controls keratinocyte differentiation by promoting the transcriptional termination of epidermal genes. Proceedings of the National Academy of Sciences. 119(10). e2104718119–e2104718119. 21 indexed citations
6.
Valente, Davide, Marialuisa Casella, Marco Crescenzi, et al.. (2020). Spastin recovery in hereditary spastic paraplegia by preventing neddylation-dependent degradation. Life Science Alliance. 3(12). e202000799–e202000799. 18 indexed citations
7.
Orienti, Isabella, Valentina Salvati, Giovanni Sette, et al.. (2019). A novel oral micellar fenretinide formulation with enhanced bioavailability and antitumour activity against multiple tumours from cancer stem cells. Journal of Experimental & Clinical Cancer Research. 38(1). 373–373. 36 indexed citations
8.
Gatti, Veronica, Mirco Compagnone, Elke Markert, et al.. (2018). ΔNp63 regulates the expression of hyaluronic acid-related genes in breast cancer cells. Oncogenesis. 7(8). 65–65. 22 indexed citations
9.
Rita, Anthea Di, Angelo Peschiaroli, Pasquale D’Acunzo, et al.. (2018). HUWE1 E3 ligase promotes PINK1/PARKIN-independent mitophagy by regulating AMBRA1 activation via IKKα. Nature Communications. 9(1). 3755–3755. 207 indexed citations
10.
Giacobbe, Arianna, Mirco Compagnone, Lucilla Bongiorno‐Borbone, et al.. (2015). p63 controls cell migration and invasion by transcriptional regulation of MTSS1. Oncogene. 35(12). 1602–1608. 37 indexed citations
11.
Nicolai, Sara, Marco Pieraccioli, Angelo Peschiaroli, Gerry Melino, & Giuseppe Raschellà. (2015). Neuroblastoma: oncogenic mechanisms and therapeutic exploitation of necroptosis. Cell Death and Disease. 6(12). e2010–e2010. 47 indexed citations
12.
Kuchay, Shafi, Shanshan Duan, Angelo Peschiaroli, et al.. (2013). FBXL2- and PTPL1-mediated degradation of p110-free p85β regulatory subunit controls the PI(3)K signalling cascade. Nature Cell Biology. 15(5). 472–480. 100 indexed citations
13.
Velletri, Tania, Francesco Romeo, Paola Tucci, et al.. (2013). GLS2 is transcriptionally regulated by p73 and contributes to neuronal differentiation. Cell Cycle. 12(22). 3564–3573. 76 indexed citations
14.
Peschiaroli, Angelo, Arianna Giacobbe, Amanda Formosa, et al.. (2012). miR-143 regulates hexokinase 2 expression in cancer cells. Oncogene. 32(6). 797–802. 154 indexed citations
15.
Peschiaroli, Angelo, et al.. (2010). The E3 ubiquitin ligase WWP1 regulates ΔNp63-dependent transcription through Lys63 linkages. Biochemical and Biophysical Research Communications. 402(2). 425–430. 36 indexed citations
16.
Peschiaroli, Angelo, Jeffrey R. Skaar, Michele Pagano, & Gerry Melino. (2009). The ubiquitin-specific protease USP47 is a novel β-TRCP interactor regulating cell survival. Oncogene. 29(9). 1384–1393. 62 indexed citations
17.
Bassermann, Florian, David Frescas, Daniele Guardavaccaro, et al.. (2008). The Cdc14B-Cdh1-Plk1 Axis Controls the G2 DNA-Damage-Response Checkpoint. Cell. 134(2). 256–267. 325 indexed citations
18.
Melino, Gerry, Ewen Gallagher, Rami I. Aqeilan, et al.. (2008). Itch: a HECT-type E3 ligase regulating immunity, skin and cancer. Cell Death and Differentiation. 15(7). 1103–1112. 142 indexed citations
19.
Malatesta, Martina, et al.. (2008). Itch self-polyubiquitylation occurs through lysine-63 linkages. Biochemical Pharmacology. 76(11). 1515–1521. 47 indexed citations
20.
Dorrello, N. Valerio, Angelo Peschiaroli, Daniele Guardavaccaro, et al.. (2006). S6K1- and ßTRCP-Mediated Degradation of PDCD4 Promotes Protein Translation and Cell Growth. Science. 314(5798). 467–471. 573 indexed citations breakdown →

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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