Alessio Ansuini

534 total citations
14 papers, 221 citations indexed

About

Alessio Ansuini is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Alessio Ansuini has authored 14 papers receiving a total of 221 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 4 papers in Artificial Intelligence. Recurrent topics in Alessio Ansuini's work include Neural Networks and Applications (3 papers), Machine Learning in Bioinformatics (2 papers) and Protein Structure and Dynamics (2 papers). Alessio Ansuini is often cited by papers focused on Neural Networks and Applications (3 papers), Machine Learning in Bioinformatics (2 papers) and Protein Structure and Dynamics (2 papers). Alessio Ansuini collaborates with scholars based in Italy, Germany and Japan. Alessio Ansuini's co-authors include Davide Zoccolan, Federica B. Rosselli, Jakob H. Macke, Alireza Alemi, Manuela Scarselli, Emily R. Aurand, M. De Crescenzi, Maurizio Prato, Laura Ballerini and Alessandra Fabbro and has published in prestigious journals such as Bioinformatics, Current Biology and Scientific Reports.

In The Last Decade

Alessio Ansuini

14 papers receiving 220 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Alessio Ansuini Italy 9 78 61 44 43 22 14 221
Suixin Deng China 8 101 1.3× 63 1.0× 71 1.6× 26 0.6× 8 0.4× 12 213
Guoqing Fan China 8 92 1.2× 83 1.4× 56 1.3× 76 1.8× 2 0.1× 12 274
Adam L. Tyson United Kingdom 11 103 1.3× 166 2.7× 162 3.7× 34 0.8× 7 0.3× 19 459
Go Eun Ha South Korea 8 121 1.6× 88 1.4× 65 1.5× 47 1.1× 6 0.3× 15 256
Kun Song China 12 49 0.6× 133 2.2× 222 5.0× 44 1.0× 35 1.6× 18 522
Martin Holub Czechia 9 57 0.7× 104 1.7× 24 0.5× 61 1.4× 3 0.1× 19 344
Caroline Bouillot France 10 119 1.5× 81 1.3× 31 0.7× 22 0.5× 2 0.1× 23 295
Masahiro Katayama Japan 11 43 0.6× 162 2.7× 65 1.5× 36 0.8× 2 0.1× 29 402
Clément Debacker France 10 48 0.6× 39 0.6× 91 2.1× 24 0.6× 3 0.1× 21 295
Inès Hristovska France 8 34 0.4× 54 0.9× 24 0.5× 14 0.3× 2 0.1× 15 245

Countries citing papers authored by Alessio Ansuini

Since Specialization
Citations

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

Fields of papers citing papers by Alessio Ansuini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alessio Ansuini

This figure shows the co-authorship network connecting the top 25 collaborators of Alessio Ansuini. A scholar is included among the top collaborators of Alessio Ansuini 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 Alessio Ansuini. Alessio Ansuini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Laio, Alessandro, et al.. (2025). Unsupervised Domain Classification of AlphaFold2-Predicted Protein Structures. 3(2). 1 indexed citations
2.
Ansuini, Alessio, et al.. (2024). Enhancing predictions of protein stability changes induced by single mutations using MSA-based language models. Bioinformatics. 40(7). 6 indexed citations
3.
Ansuini, Alessio, et al.. (2024). Detach-ROCKET: sequential feature selection for time series classification with random convolutional kernels. Data Mining and Knowledge Discovery. 38(6). 3922–3947. 3 indexed citations
4.
Punta, Marco, et al.. (2024). Protein family annotation for the Unified Human Gastrointestinal Proteome by DPCfam clustering. Scientific Data. 11(1). 568–568. 2 indexed citations
5.
Medvet, Eric, et al.. (2021). Speeding-up pruning for Artificial Neural Networks: Introducing Accelerated Iterative Magnitude Pruning. ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/). 10 indexed citations
6.
Ansuini, Alessio, et al.. (2020). On the Similarity between Hidden Layers of Pruned and Unpruned Convolutional Neural Networks. ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/). 52–59. 4 indexed citations
7.
Onofrillo, Carmine, Marianna Penzo, Alessio Ansuini, et al.. (2020). DKC1 Overexpression Induces a More Aggressive Cellular Behavior and Increases Intrinsic Ribosomal Activity in Immortalized Mammary Gland Cells. Cancers. 12(12). 3512–3512. 20 indexed citations
8.
Ansuini, Alessio, Alessandro Laio, Jakob H. Macke, & Davide Zoccolan. (2019). Intrinsic dimension of data representations in deep neural networks. arXiv (Cornell University). 32. 6109–6119. 9 indexed citations
9.
Ansuini, Alessio, et al.. (2018). Accuracy of Rats in Discriminating Visual Objects Is Explained by the Complexity of Their Perceptual Strategy. Current Biology. 28(7). 1005–1015.e5. 23 indexed citations
10.
Aurand, Emily R., Alessandra Fabbro, Denis Scaini, et al.. (2016). 3D meshes of carbon nanotubes guide functional reconnection of segregated spinal explants. Science Advances. 2(7). e1600087–e1600087. 68 indexed citations
11.
Rosselli, Federica B., Alireza Alemi, Alessio Ansuini, & Davide Zoccolan. (2015). Object similarity affects the perceptual strategy underlying invariant visual object recognition in rats. Frontiers in Neural Circuits. 9. 10–10. 23 indexed citations
12.
13.
Cojoc, Dan, et al.. (2012). Less than 5 Netrin-1 molecules initiate attraction but 200 Sema3A molecules are necessary for repulsion. Scientific Reports. 2(1). 675–675. 21 indexed citations
14.
Poccia, Nicola, Alessio Ansuini, & A. Bianconi. (2011). Far from Equilibrium Percolation, Stochastic and Shape Resonances in the Physics of Life. International Journal of Molecular Sciences. 12(10). 6810–6833. 10 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Suixin Deng Breakdown of academic impact, for papers by Guoqing Fan Breakdown of academic impact, for papers by Adam L. Tyson Breakdown of academic impact, for papers by Go Eun Ha Breakdown of academic impact, for papers by Kun Song Breakdown of academic impact, for papers by Martin Holub Breakdown of academic impact, for papers by Caroline Bouillot Breakdown of academic impact, for papers by Masahiro Katayama Breakdown of academic impact, for papers by Clément Debacker Breakdown of academic impact, for papers by Inès Hristovska
Rankless by CCL
2026