E. Pieroni

1.6k total citations
21 papers, 485 citations indexed

About

E. Pieroni is a scholar working on Molecular Biology, Immunology and Organic Chemistry. According to data from OpenAlex, E. Pieroni has authored 21 papers receiving a total of 485 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Immunology and 2 papers in Organic Chemistry. Recurrent topics in E. Pieroni's work include Immunotherapy and Immune Responses (4 papers), T-cell and B-cell Immunology (4 papers) and Bioinformatics and Genomic Networks (3 papers). E. Pieroni is often cited by papers focused on Immunotherapy and Immune Responses (4 papers), T-cell and B-cell Immunology (4 papers) and Bioinformatics and Genomic Networks (3 papers). E. Pieroni collaborates with scholars based in Italy, United States and Spain. E. Pieroni's co-authors include Amit Kumar, Antonella Fais, Maria Giovanna Marrosu, Benedetta Era, Luigi Atzori, Eleonora Cocco, Giovanna Delogu, Alberto de la Fuente, Francesca Pintus and Rosaria Medda and has published in prestigious journals such as PLoS ONE, Scientific Reports and Annals of the New York Academy of Sciences.

In The Last Decade

E. Pieroni

21 papers receiving 476 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
E. Pieroni Italy 13 186 100 89 74 60 21 485
Duncan Armstrong United Kingdom 13 279 1.5× 38 0.4× 98 1.1× 40 0.5× 29 0.5× 20 744
Paola Caria Italy 15 182 1.0× 69 0.7× 50 0.6× 84 1.1× 27 0.5× 44 604
Paul V. Kaplita United States 14 388 2.1× 85 0.8× 35 0.4× 121 1.6× 39 0.7× 26 714
Xiaojing Yuan China 15 314 1.7× 69 0.7× 66 0.7× 82 1.1× 64 1.1× 26 557
Roberto Nuti Italy 11 304 1.6× 64 0.6× 168 1.9× 93 1.3× 42 0.7× 16 628
Alyssa Langfald United States 10 290 1.6× 53 0.5× 24 0.3× 40 0.5× 25 0.4× 18 488
Mark E. McDonnell United States 14 186 1.0× 83 0.8× 17 0.2× 105 1.4× 41 0.7× 31 509
Valeria Capurro Italy 15 235 1.3× 125 1.3× 36 0.4× 57 0.8× 28 0.5× 29 593
Susan Khan United States 11 199 1.1× 102 1.0× 34 0.4× 105 1.4× 17 0.3× 14 412

Countries citing papers authored by E. Pieroni

Since Specialization
Citations

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

Fields of papers citing papers by E. Pieroni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of E. Pieroni

This figure shows the co-authorship network connecting the top 25 collaborators of E. Pieroni. A scholar is included among the top collaborators of E. Pieroni 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 E. Pieroni. E. Pieroni 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.
2.
Kumar, Amit, Pierluigi Caboni, Maria Antonietta De Luca, et al.. (2023). In silico characterization of ligand–receptor interactions for U‐47700, N,N‐didesmethyl‐U‐47700, U‐50488 at mu‐ and kappa‐opioid receptors. Archiv der Pharmazie. 356(9). e2300256–e2300256. 2 indexed citations
3.
Valentini, Maria Consuelo, E. Pieroni, Alessandro Concas, & Massimo Pisu. (2022). Docking and Molecular Dynamics Simulations Reveal A Possible Site of Interaction of Olive Leaf Extract Hydroxytyrosol with Polyunsaturated Fatty Acid 5-Lipoxygenase Human Enzyme. 3(2). 6–11. 1 indexed citations
4.
Cappellini, Giancarlo, et al.. (2022). A combined molecular dynamics simulation and DFT study on mercapto-benzamide inhibitors for the HIV NCp7 protein. Physical Chemistry Chemical Physics. 24(41). 25547–25554. 1 indexed citations
5.
6.
Kumar, Amit, Francesca Pintus, Amalia Di Petrillo, et al.. (2018). Novel 2-pheynlbenzofuran derivatives as selective butyrylcholinesterase inhibitors for Alzheimer’s disease. Scientific Reports. 8(1). 4424–4424. 92 indexed citations
7.
Delogu, Giovanna, María João Matos, Maura Fanti, et al.. (2016). 2-Phenylbenzofuran derivatives as butyrylcholinesterase inhibitors: Synthesis, biological activity and molecular modeling. Bioorganic & Medicinal Chemistry Letters. 26(9). 2308–2313. 47 indexed citations
8.
Kumar, Amit, Paola Melis, Vito Genna, et al.. (2014). Antigenic peptide molecular recognition by the DRB1–DQB1 haplotype modulates multiple sclerosis susceptibility. Molecular BioSystems. 10(8). 2043–2054. 21 indexed citations
9.
Caboni, Pierluigi, Barbara Liori, Amit Kumar, et al.. (2014). Metabolomics Analysis and Modeling Suggest a Lysophosphocholines-PAF Receptor Interaction in Fibromyalgia. PLoS ONE. 9(9). e107626–e107626. 54 indexed citations
10.
Kumar, Amit, Leonardo A. Sechi, Pierluigi Caboni, et al.. (2014). Dynamical insights into the differential characteristics of Mycobacterium avium subsp. paratuberculosis peptide binding to HLA-DRB1 proteins associated with multiple sclerosis. New Journal of Chemistry. 39(2). 1355–1366. 22 indexed citations
11.
Kumar, Amit, Naresh C. Bal, Nivedita Jena, et al.. (2013). Identification of calcium binding sites on calsequestrin 1 and their implications for polymerization. Molecular BioSystems. 9(7). 1949–1957. 26 indexed citations
12.
Cocco, Eleonora, Raffaele Murru, Gianna Costa, et al.. (2013). Interaction between HLA-DRB1-DQB1 Haplotypes in Sardinian Multiple Sclerosis Population. PLoS ONE. 8(4). e59790–e59790. 24 indexed citations
13.
Kumar, Amit, Eleonora Cocco, Luigi Atzori, Maria Giovanna Marrosu, & E. Pieroni. (2013). Structural and Dynamical Insights on HLA-DR2 Complexes That Confer Susceptibility to Multiple Sclerosis in Sardinia: A Molecular Dynamics Simulation Study. PLoS ONE. 8(3). e59711–e59711. 35 indexed citations
14.
Cocco, Eleonora, Claudia Sardu, E. Pieroni, et al.. (2012). HLA-DRB1-DQB1 Haplotypes Confer Susceptibility and Resistance to Multiple Sclerosis in Sardinia. PLoS ONE. 7(4). e33972–e33972. 30 indexed citations
15.
Mentzen, Wieslawa I., et al.. (2009). Inferring Gene Networks: Dream or Nightmare?. Annals of the New York Academy of Sciences. 1158(1). 287–301. 9 indexed citations
16.
Pieroni, E., et al.. (2008). Protein networking: insights into global functional organization of proteomes. PROTEOMICS. 8(4). 799–816. 66 indexed citations
17.
Fuente, Alberto de la, et al.. (2008). Insights into biological information processing: structural and dynamical analysis of a human protein signalling network. Journal of Physics A Mathematical and Theoretical. 41(22). 224013–224013. 6 indexed citations
18.
Bonomi, Ernesto, et al.. (1998). 3D spectral reverse time migration with no‐wraparound absorbing conditions. 1925–1928. 7 indexed citations
19.
Bonomi, Ernesto, et al.. (1998). Phase shift plus interpolation; A scheme for high-performance echo-reconstructive imaging. Computers in Physics. 12(2). 126–132. 12 indexed citations
20.
Bagaini, Claudio, Ernesto Bonomi, & E. Pieroni. (1995). Data parallel implementation of 3‐D PSPI. 188–191. 15 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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