Marcella Anselmo

542 citations
28 papers · 125 · h-index 8

Impact in

Papers in

Marcella Anselmo

24 papers receiving 112 citations

Peers

Marcella Anselmo
Comparison fields: 5 of 20
  • Computational Theory and Mathematics 96
  • Artificial Intelligence 81
  • Molecular Biology 95
  • Hardware and Architecture 4
  • Software 2
Replace Robert Mercaş with:
Robert Mercaş Germany
Maria Madonia Italy
Martin Plátek Czechia
Hermann Gruber Germany
Shinnosuke Seki Japan
Markus L. Schmid Germany
Claudio Ferretti Italy
Henning Bordihn Germany
Yuto Nakashima Japan
Hiroshi Umeo Japan
Marcella Anselmo relative to Robert Mercaş Germany Robert Mercaş's profile →
Citations per field
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Citations per year

Countries citing papers authored by Marcella Anselmo

Since Specialization
Citations

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

Fields of papers citing papers by Marcella Anselmo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Marcella Anselmo, 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 Marcella Anselmo Line = papers co-authored together Marcella Anselmo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200619
2 200910
3 20029
4 20109
5 20089
6 20147
7 19917
8 19907
9 19966
10 20166
11 20155
12 20025
13 20054
14 20103
15 20163
16 20163
17 20203
18 20102
19 19972
20
Two-way Probabilistic Automata and Rational Power series
19922

About Marcella Anselmo

Marcella Anselmo is a scholar working on Computational Theory and Mathematics, Molecular Biology, Artificial Intelligence, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 28 papers that have together received 125 indexed citations. Recurring topics across this work include DNA and Biological Computing (20 papers), semigroups and automata theory (20 papers), Algorithms and Data Compression (11 papers), Cellular Automata and Applications (9 papers), Coding theory and cryptography (5 papers), Advanced Algebra and Logic (4 papers), Logic, programming, and type systems (2 papers) and Advanced biosensing and bioanalysis techniques (2 papers). The work is most often cited by research in Computational Theory and Mathematics (96 citations), Artificial Intelligence (81 citations), Molecular Biology (95 citations), Hardware and Architecture (4 citations) and Software (2 citations). Marcella Anselmo has collaborated with scholars based in Italy, South Africa and Germany. Frequent co-authors include Maria Madonia, Dora Giammarresi, Antonio Restivo, Stefano Varricchio, Arno Pauly, Florín Manea, Alberto Bertoni, Gianluca Della Vedova, Andrea Bertoni and Clelia De Felice. Their work appears in journals such as Theoretical Computer Science, International Journal of Foundations of Computer Science, Discrete Mathematics & Theoretical Computer Science, Information and Computation and Advances in Applied Mathematics.

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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