Daniela Trisciuzzi

35 papers receiving 619 citations

Peers

Daniela Trisciuzzi
Comparison fields: 5 of 87
  • Computational Theory and Mathematics 349
  • Pharmacology 102
  • Drug Discovery 1
  • Health, Toxicology and Mutagenesis 62
  • Pharmacology 38
Replace Mohamed Diwan M. AbdulHameed with:
Mohamed Diwan M. AbdulHameed United States
Heather L. Ciallella United States
Haixiao Jin China
Shaohua Shi China
Christof H. Schwab Germany
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Emilio Xavier Esposito United States
Yan Guan China
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Mohamed Diwan M. AbdulHameed · 1×
Citations per year

Countries citing papers authored by Daniela Trisciuzzi

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Trisciuzzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniela Trisciuzzi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniela Trisciuzzi Line = papers co-authored together Daniela Trisciuzzi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202066
2 201862
3 201739
4 202237
5 201932
6 201532
7 201730
8 202230
9 201829
10 201825
11 201725
12 202020
13 201719
14 201818
15 202217
16 202315
17 202415
18 201615
19 202414
20 202312

About Daniela Trisciuzzi

Daniela Trisciuzzi is a scholar working on Computational Theory and Mathematics, Molecular Biology, Pharmacology, Organic Chemistry and Pharmacology, having authored 37 papers that have together received 622 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (23 papers), Cholinesterase and Neurodegenerative Diseases (8 papers), Synthesis and biological activity (6 papers), Microbial Natural Products and Biosynthesis (4 papers), Pharmacogenetics and Drug Metabolism (4 papers), Effects and risks of endocrine disrupting chemicals (4 papers), Animal testing and alternatives (3 papers) and Pharmaceutical studies and practices (3 papers). The work is most often cited by research in Computational Theory and Mathematics (349 citations), Pharmacology (102 citations), Drug Discovery (1 citation), Health, Toxicology and Mutagenesis (62 citations) and Pharmacology (38 citations). Daniela Trisciuzzi has collaborated with scholars based in Italy, India and United States. Frequent co-authors include Orazio Nicolotti, Giuseppe Felice Mangiatordi, Domenico Alberga, Nicola Gambacorta, Fulvio Ciriaco, Domenico Alberga, Francesco Leonetti, Nicola Amoroso, Kamel Mansouri and Marco Catto. Their work appears in journals such as Journal of Chemical Information and Modeling, European Journal of Medicinal Chemistry, Molecules, International Journal of Molecular Sciences and Scientific Reports.

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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