Nadia Pisanti

2.3k citations
47 papers · 519 indexed · h-index 11
Topics
Algorithms and Data Compression (22 papers)Genomics and Phylogenetic Studies (19 papers)RNA and protein synthesis mechanisms (8 papers)
Journals
Nature CommunicationsSHILAP Revista de lepidopterologíaBioinformatics
Partner nations
ItalyFranceNetherlands

In The Last Decade

Nadia Pisanti

45 papers receiving 505 citations

Peers

Nadia Pisanti
Comparison fields: 5 of 71
  • Molecular Biology 363
  • Artificial Intelligence 191
  • Genetics 160
  • Plant Science 91
  • Computational Theory and Mathematics 54
Replace Gianluca Della Vedova with:
Gianluca Della Vedova Italy
Cenk Sahinalp Canada
German Tischler United Kingdom
Paola Bonizzoni Italy
Paolo Milazzo Italy
Jouni Sirén United States
Manuel Holtgrewe Germany
Rune B. Lyngsø United Kingdom
Riccardo Dondi Italy
Tiago Paixão Austria
Nadia Pisanti relative to Gianluca Della Vedova Italy Gianluca Della Vedova's profile →
Citations per field
00.5×1.5×2.1×
Gianluca Della Vedova · 1×
Citations per year

Countries citing papers authored by Nadia Pisanti

Since Specialization
Citations

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

Fields of papers citing papers by Nadia Pisanti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nadia Pisanti

This figure shows the co-authorship network connecting the top 25 collaborators of Nadia Pisanti. A scholar is included among the top collaborators of Nadia Pisanti 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 Nadia Pisanti. Nadia Pisanti 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 0
2 2
3 0
4 5
5 6
6 3
7 9
8 7
9 1
10 3
11 2
12
Proceedings of the Second international conference on Information technology in bio- and medical informatics
1
13 14
14 6
15 2
16 33
17 10
18
Efficient optimal greedy algorithms for room allocation
1
19
DNA Computing: a survey
6
20
A survey on DNA computing
2

About Nadia Pisanti

Nadia Pisanti is a scholar working on Artificial Intelligence, Molecular Biology and Genetics, having authored 47 papers that have together received 519 indexed citations. Recurring topics across this work include Algorithms and Data Compression (22 papers), Genomics and Phylogenetic Studies (19 papers) and RNA and protein synthesis mechanisms (8 papers). The work is most often cited by research in Artificial Intelligence (191 citations), Genetics (160 citations) and Molecular Biology (363 citations). Nadia Pisanti has collaborated with scholars based in Italy, France and Netherlands. Frequent co-authors include Gunnar W. Klau, Murray Patterson, Tobias Marschall, Alexander Schönhuth, Leen Stougie, Leo van Iersel, Roberto Grossi, Giovanna Rosone, Marie‐France Sagot and Solon P. Pissis. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and Bioinformatics.

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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