Matteo Pappalardo

712 citations
40 papers · 605 indexed · h-index 15
Topics
Protein Structure and Dynamics (14 papers)Receptor Mechanisms and Signaling (8 papers)Computational Drug Discovery Methods (6 papers)
Partner nations
ItalyUnited StatesIsrael

In The Last Decade

Matteo Pappalardo

40 papers receiving 594 citations

Peers

Matteo Pappalardo
Comparison fields: 5 of 87
  • Molecular Biology 371
  • Physiology 228
  • Biomaterials 59
  • Computational Theory and Mathematics 59
  • Oncology 58
Replace Sinjan Choudhary with:
Sinjan Choudhary India
Seyyed Abolghasem Ghadami Iran
Saima Nusrat India
Milena Quaglia United Kingdom
Katarína Šipošová Slovakia
Ghulam M. Maharvi Pakistan
Song You China
Bartolomé Vilanova Spain
Amit S. Pithadia United States
Parvaneh Maghami Iran
Matteo Pappalardo relative to Sinjan Choudhary India Sinjan Choudhary's profile →
Citations per field
00.5×1.5×1.9×
Sinjan Choudhary · 1×
Citations per year

Countries citing papers authored by Matteo Pappalardo

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Pappalardo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Pappalardo

This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Pappalardo. A scholar is included among the top collaborators of Matteo Pappalardo 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 Matteo Pappalardo. Matteo Pappalardo 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
#WorkIndexed citations
1 3
2 9
3 15
4 5
5 8
6 11
7 6
8 17
9 4
10 18
11 12
12 6
13 7
14 14
15 50
16 40
17 9
18 78
19 4
20 4

About Matteo Pappalardo

Matteo Pappalardo is a scholar working on Molecular Biology, Pollution and Computational Theory and Mathematics, having authored 40 papers that have together received 605 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (14 papers), Receptor Mechanisms and Signaling (8 papers) and Computational Drug Discovery Methods (6 papers). The work is most often cited by research in Physiology (228 citations), Molecular Biology (371 citations) and Biomaterials (59 citations). Matteo Pappalardo has collaborated with scholars based in Italy, United States and Israel. Frequent co-authors include Danilo Milardi, Domenico Grasso, Carmelo La Rosa, Michele F. M. Sciacca, Vito Librando, Marco Cecchini, Ronald Melki, Amedeo Caflisch, Salvatore Guccione and Livia Basile. Their work appears in journals such as PLoS ONE, Journal of Molecular Biology and Chemical Physics Letters.

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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