Simone Daminelli

588 citations
10 papers · 427 · h-index 9

Impact in

Papers in

Simone Daminelli

10 papers receiving 417 citations

Peers

Simone Daminelli
Comparison fields: 5 of 80
  • Computational Theory and Mathematics 232
  • Molecular Biology 298
  • Pharmacology 31
  • Toxicology 10
  • Pharmacology 47
Replace Kalaimathy Singaravelu with:
Kalaimathy Singaravelu Finland
Billy J. Williams‐Noonan Australia
Yang Ying United States
Noé Sturm Sweden
Luigi Capoferri Netherlands
Natalia Khuri United States
Liliana Halip Romania
Selvaraman Nagamani India
Péter Hári Hungary
Ming-Xi Liu China
Simone Daminelli relative to Kalaimathy Singaravelu Finland Kalaimathy Singaravelu's profile →
Citations per field
00.5×3.1×
Kalaimathy Singaravelu · 1×
Citations per year

Countries citing papers authored by Simone Daminelli

Since Specialization
Citations

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

Fields of papers citing papers by Simone Daminelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Simone Daminelli, 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 Simone Daminelli Line = papers co-authored together Simone Daminelli links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2013108
2 2014103
3 201746
4 201744
5 201239
6 201627
7 201025
8 201321
9 201613
10 20191

About Simone Daminelli

Simone Daminelli is a scholar working on Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Pharmacology and Pulmonary and Respiratory Medicine, having authored 10 papers that have together received 427 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Protein Structure and Dynamics (3 papers), Microbial Natural Products and Biosynthesis (2 papers), Bioinformatics and Genomic Networks (2 papers), Gene Regulatory Network Analysis (2 papers), Prostate Cancer Treatment and Research (1 paper), Malaria Research and Control (1 paper) and Biochemical and Molecular Research (1 paper). The work is most often cited by research in Computational Theory and Mathematics (232 citations), Molecular Biology (298 citations), Pharmacology (31 citations), Toxicology (10 citations) and Pharmacology (47 citations). Simone Daminelli has collaborated with scholars based in Germany, United States and Italy. Frequent co-authors include Michael Schroeder, V. Joachim Haupt, Sebastian Salentin, Claudio Durán, Carlo Vittorio Cannistraci, Josephine Maria Thomas, Jörg C. Heinrich, Melissa F. Adasme, Yixin Zhang and Janez Konc. Their work appears in journals such as PLoS ONE, Scientific Reports, Progress in Biophysics and Molecular Biology, Integrative Biology and Journal of Medicinal Chemistry.

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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