Pietro Faccioli

2.4k total citations
82 papers, 1.4k citations indexed

About

Pietro Faccioli is a scholar working on Molecular Biology, Atomic and Molecular Physics, and Optics and Nuclear and High Energy Physics. According to data from OpenAlex, Pietro Faccioli has authored 82 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 29 papers in Atomic and Molecular Physics, and Optics and 25 papers in Nuclear and High Energy Physics. Recurrent topics in Pietro Faccioli's work include Protein Structure and Dynamics (26 papers), Quantum Chromodynamics and Particle Interactions (24 papers) and High-Energy Particle Collisions Research (21 papers). Pietro Faccioli is often cited by papers focused on Protein Structure and Dynamics (26 papers), Quantum Chromodynamics and Particle Interactions (24 papers) and High-Energy Particle Collisions Research (21 papers). Pietro Faccioli collaborates with scholars based in Italy, United States and France. Pietro Faccioli's co-authors include S. a Beccara, Henri Orland, Tatjana Škrbić, Cristian Micheletti, Francesco Pederiva, Edward Shuryak, Marcello Sega, Roberto Covino, Giovanni Garberoglio and M. Traini and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Physical Review Letters.

In The Last Decade

Pietro Faccioli

77 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pietro Faccioli Italy 21 735 361 350 267 132 82 1.4k
Walter Nadler Germany 26 644 0.9× 144 0.4× 612 1.7× 399 1.5× 308 2.3× 61 1.9k
Liao Y. Chen United States 22 431 0.6× 71 0.2× 790 2.3× 186 0.7× 242 1.8× 99 1.5k
Piotr Sułkowski Poland 18 633 0.9× 181 0.5× 208 0.6× 189 0.7× 110 0.8× 41 1.1k
Anders Irbäck Sweden 29 1.5k 2.0× 374 1.0× 414 1.2× 749 2.8× 77 0.6× 75 2.3k
Jan O. Daldrop Germany 13 253 0.3× 162 0.4× 285 0.8× 113 0.4× 191 1.4× 24 691
Andrew Ilin United States 12 600 0.8× 167 0.5× 244 0.7× 180 0.7× 24 0.2× 52 1.3k
Tetsuo Deguchi Japan 24 157 0.2× 114 0.3× 573 1.6× 196 0.7× 477 3.6× 115 1.8k
Jemal Guven Mexico 20 454 0.6× 471 1.3× 359 1.0× 88 0.3× 244 1.8× 59 1.4k
Jian‐Min Yuan United States 27 358 0.5× 81 0.2× 1.2k 3.3× 176 0.7× 583 4.4× 109 2.0k
Kenneth C. Millett United States 24 820 1.1× 46 0.1× 271 0.8× 262 1.0× 98 0.7× 70 2.5k

Countries citing papers authored by Pietro Faccioli

Since Specialization
Citations

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

Fields of papers citing papers by Pietro Faccioli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pietro Faccioli

This figure shows the co-authorship network connecting the top 25 collaborators of Pietro Faccioli. A scholar is included among the top collaborators of Pietro Faccioli 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 Pietro Faccioli. Pietro Faccioli 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.
Spagnolli, Giovanni, Emanuela Zuccaro, Isabella Palazzolo, et al.. (2025). The evolution of eukaryotic linear motifs governing the function of androgen receptor from fish to Homo sapiens. Nucleic Acids Research. 53(14).
2.
Biasini, Emiliano & Pietro Faccioli. (2023). Functional, pathogenic, and pharmacological roles of protein folding intermediates. Proteins Structure Function and Bioinformatics. 93(8). 1299–1307. 6 indexed citations
3.
Micheletti, Cristian, et al.. (2023). RNA folding pathways from all-atom simulations with a variationally improved history-dependent bias. Biophysical Journal. 122(15). 3089–3098. 3 indexed citations
4.
Roggero, Alessandro, et al.. (2022). Stochastic dynamics and bound states of heavy impurities in a Fermi bath. INO Open Portal.
5.
Micheletti, Cristian, Philipp Hauke, & Pietro Faccioli. (2021). Polymer Physics by Quantum Computing. Physical Review Letters. 127(8). 80501–80501. 26 indexed citations
6.
Spagnolli, Giovanni, et al.. (2020). All-atom simulation of the HET-s prion replication. PLoS Computational Biology. 16(9). e1007922–e1007922. 9 indexed citations
7.
Gershenson, Anne, Shachi Gosavi, Pietro Faccioli, & Patrick L. Wintrode. (2019). Successes and challenges in simulating the folding of large proteins. Journal of Biological Chemistry. 295(1). 15–33. 55 indexed citations
8.
Wang, Fang, Simone Orioli, Alan Ianeselli, et al.. (2018). All-Atom Simulations Reveal How Single-Point Mutations Promote Serpin Misfolding. Biophysical Journal. 114(9). 2083–2094. 19 indexed citations
9.
Beccara, S. a, et al.. (2015). Variational Scheme to Compute Protein Reaction Pathways Using Atomistic Force Fields with Explicit Solvent. Physical Review Letters. 114(9). 98103–98103. 26 indexed citations
10.
Wang, Fang, et al.. (2015). Folding Mechanism of Proteins IM7 and IM9, from Computer Simulations in a Realistic Atomistic Force Field. Biophysical Journal. 108(2). 519a–519a. 1 indexed citations
11.
Beccara, S. a, Tatjana Škrbić, Roberto Covino, Cristian Micheletti, & Pietro Faccioli. (2013). Folding Pathways of a Knotted Protein with a Realistic Atomistic Force Field. PLoS Computational Biology. 9(3). e1003002–e1003002. 71 indexed citations
12.
Škrbić, Tatjana, Cristian Micheletti, & Pietro Faccioli. (2012). The Role of Non-Native Interactions in the Folding of Knotted Proteins. PLoS Computational Biology. 8(6). e1002504–e1002504. 51 indexed citations
13.
Beccara, S. a, Tatjana Škrbić, Roberto Covino, & Pietro Faccioli. (2012). Dominant folding pathways of a WW domain. Proceedings of the National Academy of Sciences. 109(7). 2330–2335. 64 indexed citations
14.
Mazzola, Guglielmo, S. a Beccara, Pietro Faccioli, & Henri Orland. (2011). Fluctuations in the ensemble of reaction pathways. The Journal of Chemical Physics. 134(16). 164109–164109. 12 indexed citations
15.
Corradini, Olindo, Pietro Faccioli, & Henri Orland. (2009). Simulating stochastic dynamics using large time steps. Physical Review E. 80(6). 61112–61112. 5 indexed citations
16.
Cristoforetti, M., Pietro Faccioli, Edward Shuryak, & M. Traini. (2004). Instantons, diquarks and the Delta I = 1/2 rule for non-leptonic hyperon decays. arXiv (Cornell University). 1 indexed citations
17.
Faccioli, Pietro. (2004). Instanton contribution to the electromagnetic form factors of the nucleon. Physical Review C. 69(6). 9 indexed citations
18.
Faccioli, Pietro & Thomas DeGrand. (2003). Evidence for Instanton-Induced Dynamics from Lattice QCD. Physical Review Letters. 91(18). 182001–182001. 36 indexed citations
19.
Faccioli, Pietro. (2002). Parameter-free calculation of hadronic masses from instantons. Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields. 65(9). 7 indexed citations
20.
Cano, F., Pietro Faccioli, Sergio Scopetta, & M. Traini. (2000). Orbital angular momentum parton distributions in light-front dynamics. Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields. 62(5). 3 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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