Simone Spolaor

649 total citations
36 papers, 395 citations indexed

About

Simone Spolaor is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Simone Spolaor has authored 36 papers receiving a total of 395 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 16 papers in Artificial Intelligence and 7 papers in Computational Theory and Mathematics. Recurrent topics in Simone Spolaor's work include Gene Regulatory Network Analysis (15 papers), Microbial Metabolic Engineering and Bioproduction (8 papers) and Evolutionary Algorithms and Applications (7 papers). Simone Spolaor is often cited by papers focused on Gene Regulatory Network Analysis (15 papers), Microbial Metabolic Engineering and Bioproduction (8 papers) and Evolutionary Algorithms and Applications (7 papers). Simone Spolaor collaborates with scholars based in Italy, Netherlands and United Kingdom. Simone Spolaor's co-authors include Marco S. Nobile, Paolo Cazzaniga, Daniela Besozzi, Giancarlo Mauri, Uzay Kaymak, Andrea Tangherloni, Leonardo Rundo, Yoeri van de Burgt, Paschalis Gkoupidenis and Luca Manzoni and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Simone Spolaor

33 papers receiving 387 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simone Spolaor Italy 12 173 112 74 67 32 36 395
Simon L. Harding United Kingdom 10 308 1.8× 101 0.9× 105 1.4× 57 0.9× 4 0.1× 13 410
Devin Kwok Canada 8 66 0.4× 208 1.9× 47 0.6× 26 0.4× 4 0.1× 8 466
Brodie Lawson Australia 10 87 0.5× 72 0.6× 25 0.3× 38 0.6× 2 0.1× 23 349
Dongyuan Li China 12 127 0.7× 67 0.6× 32 0.4× 17 0.3× 5 0.2× 48 383
Haobo Wang China 14 244 1.4× 45 0.4× 30 0.4× 14 0.2× 10 0.3× 56 473
Wouter Caarls Brazil 14 65 0.4× 50 0.4× 63 0.9× 20 0.3× 6 0.2× 51 466
Anand Madhavan India 3 214 1.2× 21 0.2× 64 0.9× 16 0.2× 15 0.5× 8 439
Guancheng Wang China 14 151 0.9× 61 0.5× 116 1.6× 23 0.3× 7 0.2× 44 514
Ngaam J. Cheung China 11 190 1.1× 103 0.9× 40 0.5× 77 1.1× 2 0.1× 16 371

Countries citing papers authored by Simone Spolaor

Since Specialization
Citations

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

Fields of papers citing papers by Simone Spolaor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simone Spolaor

This figure shows the co-authorship network connecting the top 25 collaborators of Simone Spolaor. A scholar is included among the top collaborators of Simone Spolaor 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 Simone Spolaor. Simone Spolaor 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
1.
Spolaor, Simone, et al.. (2024). Predicting Blood Glucose Levels with Organic Neuromorphic Micro‐Networks. Advanced Science. 11(27). e2308261–e2308261. 5 indexed citations
2.
Doremaele, Eveline R. W. van, et al.. (2024). Hardware implementation of backpropagation using progressive gradient descent for in situ training of multilayer neural networks. Science Advances. 10(28). eado8999–eado8999. 8 indexed citations
3.
Spolaor, Simone, Alessandro Favero, Luca Bello, et al.. (2023). Muscle magnetic resonance characterization of STIM1 tubular aggregate myopathy using unsupervised learning. PLoS ONE. 18(5). e0285422–e0285422. 1 indexed citations
4.
Chicco, Davide, Simone Spolaor, & Marco S. Nobile. (2023). Ten quick tips for fuzzy logic modeling of biomedical systems. PLoS Computational Biology. 19(12). e1011700–e1011700. 3 indexed citations
5.
Spolaor, Simone, et al.. (2023). Brain‐Inspired Organic Electronics: Merging Neuromorphic Computing and Bioelectronics Using Conductive Polymers. Advanced Functional Materials. 34(15). 60 indexed citations
6.
Spolaor, Simone, Iman Nazari, Tommaso Leonardi, et al.. (2023). Barcode demultiplexing of nanopore sequencing raw signals by unsupervised machine learning. SHILAP Revista de lepidopterología. 3. 1067113–1067113. 6 indexed citations
7.
Riva, Simone G., Paolo Cazzaniga, Marco S. Nobile, et al.. (2022). SMGen: A Generator of Synthetic Models of Biochemical Reaction Networks. Symmetry. 14(1). 119–119. 7 indexed citations
8.
Nobile, Marco S., et al.. (2022). Shaping and Dilating the Fitness Landscape for Parameter Estimation in Stochastic Biochemical Models. Applied Sciences. 12(13). 6671–6671.
9.
Spolaor, Simone, et al.. (2022). Modeling Calcium Signaling in S. cerevisiae Highlights the Role and Regulation of the Calmodulin-Calcineurin Pathway in Response to Hypotonic Shock. Frontiers in Molecular Biosciences. 9. 856030–856030. 3 indexed citations
10.
Ashlock, Daniel, et al.. (2022). Local Bubble Dilation Functions: Hypersphere-bounded Landscape Deformations Simplify Global Optimization. TU/e Research Portal. 30. 1–8. 1 indexed citations
11.
Tangherloni, Andrea, Marco S. Nobile, Paolo Cazzaniga, et al.. (2021). FiCoS: A fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks. PLoS Computational Biology. 17(9). e1009410–e1009410. 1 indexed citations
12.
Spolaor, Simone, et al.. (2021). Screening for Combination Cancer Therapies With Dynamic Fuzzy Modeling and Multi-Objective Optimization. Frontiers in Genetics. 12. 617935–617935. 5 indexed citations
13.
Manzoni, Luca, Paolo Cazzaniga, Simone Spolaor, et al.. (2020). Surfing on Fitness Landscapes: A Boost on Optimization by Fourier Surrogate Modeling. Entropy. 22(3). 285–285. 15 indexed citations
14.
Spolaor, Simone, et al.. (2020). Simpful: A User-Friendly Python Library for Fuzzy Logic. International Journal of Computational Intelligence Systems. 13(1). 1687–1687. 39 indexed citations
15.
Nobile, Marco S., Simone Spolaor, Paolo Cazzaniga, et al.. (2020). cuProCell: GPU-Accelerated Analysis of Cell Proliferation With Flow Cytometry Data. IEEE Journal of Biomedical and Health Informatics. 24(11). 3173–3181. 1 indexed citations
16.
Rundo, Leonardo, Andrea Tangherloni, Darren R. Tyson, et al.. (2020). ACDC: Automated Cell Detection and Counting for Time-Lapse Fluorescence Microscopy. Applied Sciences. 10(18). 6187–6187. 9 indexed citations
17.
Spolaor, Simone, et al.. (2020). On the automatic calibration of fully analogical spiking neuromorphic chips. TU/e Research Portal. 2. 1–8. 2 indexed citations
18.
Spolaor, Simone, Marco S. Nobile, Giancarlo Mauri, Paolo Cazzaniga, & Daniela Besozzi. (2019). Coupling Mechanistic Approaches and Fuzzy Logic to Model and Simulate Complex Systems. IEEE Transactions on Fuzzy Systems. 28(8). 1748–1759. 16 indexed citations
19.
Tangherloni, Andrea, Simone Spolaor, Leonardo Rundo, et al.. (2019). GenHap: a novel computational method based on genetic algorithms for haplotype assembly. BMC Bioinformatics. 20(S4). 172–172. 23 indexed citations
20.
Nobile, Marco S., Simone Spolaor, Paolo Cazzaniga, et al.. (2019). ProCell: Investigating cell proliferation with Swarm Intelligence. Aisberg (University of Bergamo). 1–8. 1 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.

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