Sergio Decherchi

3.5k total citations
71 papers, 1.5k citations indexed

About

Sergio Decherchi is a scholar working on Molecular Biology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sergio Decherchi has authored 71 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 21 papers in Artificial Intelligence and 18 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sergio Decherchi's work include Protein Structure and Dynamics (22 papers), Computational Drug Discovery Methods (12 papers) and Face and Expression Recognition (8 papers). Sergio Decherchi is often cited by papers focused on Protein Structure and Dynamics (22 papers), Computational Drug Discovery Methods (12 papers) and Face and Expression Recognition (8 papers). Sergio Decherchi collaborates with scholars based in Italy, United States and Switzerland. Sergio Decherchi's co-authors include Andrea Cavalli, Walter Rocchia, Rodolfo Zunino, Paolo Gastaldo, Giovanni Bottegoni, Luca Mollica, Roberto Gaspari, Andrea Spitaleri, Anna Berteotti and Giuseppina La Sala and has published in prestigious journals such as Chemical Reviews, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

Sergio Decherchi

67 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sergio Decherchi Italy 20 853 452 217 196 136 71 1.5k
Cristian R. Munteanu Spain 29 1.2k 1.4× 916 2.0× 223 1.0× 199 1.0× 119 0.9× 122 2.4k
Justin M. Wozniak United States 20 626 0.7× 167 0.4× 340 1.6× 130 0.7× 161 1.2× 80 2.4k
Kay Hamacher Germany 21 952 1.1× 165 0.4× 144 0.7× 235 1.2× 90 0.7× 102 1.8k
Debsindhu Bhowmik United States 17 1.2k 1.4× 304 0.7× 280 1.3× 90 0.5× 82 0.6× 43 1.7k
Payel Das United States 31 1.2k 1.5× 405 0.9× 718 3.3× 142 0.7× 235 1.7× 86 2.3k
Garrett B. Goh United States 15 654 0.8× 363 0.8× 403 1.9× 78 0.4× 99 0.7× 18 1.2k
Arvind Ramanathan United States 26 967 1.1× 185 0.4× 260 1.2× 180 0.9× 139 1.0× 130 1.8k
Haiguang Liu China 23 930 1.1× 154 0.3× 457 2.1× 122 0.6× 118 0.9× 119 1.9k
Chongli Qin United Kingdom 6 1.5k 1.7× 398 0.9× 523 2.4× 349 1.8× 116 0.9× 7 2.4k
Hugo Penedones United Kingdom 4 1.4k 1.7× 399 0.9× 521 2.4× 255 1.3× 115 0.8× 5 2.2k

Countries citing papers authored by Sergio Decherchi

Since Specialization
Citations

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

Fields of papers citing papers by Sergio Decherchi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sergio Decherchi

This figure shows the co-authorship network connecting the top 25 collaborators of Sergio Decherchi. A scholar is included among the top collaborators of Sergio Decherchi 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 Sergio Decherchi. Sergio Decherchi 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.
Ciccotti, Giovanni, Sergio Decherchi, & Simone Meloni. (2025). Foundations of molecular dynamics simulations: how and what. Rivista Del Nuovo Cimento. 48(1). 1–94. 1 indexed citations
2.
Decherchi, Sergio, et al.. (2024). A hybrid federated kernel regularized least squares algorithm. Knowledge-Based Systems. 305. 112600–112600. 4 indexed citations
3.
Castagnola, Valentina, Valeria Tomati, Luca Boselli, et al.. (2024). Sources of biases in the in vitro testing of nanomaterials: the role of the biomolecular corona. Nanoscale Horizons. 9(5). 799–816. 5 indexed citations
4.
Aldinucci, Marco, Elena Baralis, Valeria Cardellini, et al.. (2023). A Systematic Mapping Study of Italian Research on Workflows. CINECA IRIS Institutial research information system (University of Pisa). 2065–2076. 1 indexed citations
5.
Spyrakis, Francesca, et al.. (2023). Molecular Dynamics and Machine Learning Give Insights on the Flexibility–Activity Relationships in Tyrosine Kinome. Journal of Chemical Information and Modeling. 63(15). 4814–4826. 2 indexed citations
6.
Decherchi, Sergio, et al.. (2023). Graph neural networks for conditional de novo drug design. Wiley Interdisciplinary Reviews Computational Molecular Science. 13(4). 17 indexed citations
7.
Traversa, Fabio L., et al.. (2023). Assessing the Effectiveness of Non-Turing Computing Paradigms. IEEE Access. 11. 98751–98763. 3 indexed citations
8.
Decherchi, Sergio, et al.. (2023). Ligandability and druggability assessment via machine learning. Wiley Interdisciplinary Reviews Computational Molecular Science. 13(5). 11 indexed citations
9.
Decherchi, Sergio, et al.. (2022). Probabilistic Pocket Druggability Prediction via One-Class Learning. Frontiers in Pharmacology. 13. 870479–870479. 8 indexed citations
10.
Decherchi, Sergio, et al.. (2021). Machine Learning and Enhanced Sampling Simulations for Computing the Potential of Mean Force and Standard Binding Free Energy. Journal of Chemical Theory and Computation. 17(8). 5287–5300. 35 indexed citations
11.
Riccardi, Laura, Sergio Decherchi, Walter Rocchia, et al.. (2021). Molecular Recognition by Gold Nanoparticle-Based Receptors as Defined through Surface Morphology and Pockets Fingerprint. The Journal of Physical Chemistry Letters. 12(23). 5616–5622. 9 indexed citations
12.
Ballone, P., et al.. (2020). Solubility Advantage of Amorphous Ketoprofen. Thermodynamic and Kinetic Aspects by Molecular Dynamics and Free Energy Approaches. Journal of Chemical Theory and Computation. 16(7). 4126–4140. 12 indexed citations
13.
Ferraro, Mariarosaria, et al.. (2019). Multi-target dopamine D3 receptor modulators: Actionable knowledge for drug design from molecular dynamics and machine learning. European Journal of Medicinal Chemistry. 188. 111975–111975. 14 indexed citations
14.
Decherchi, Sergio, Giovanni Bottegoni, Andrea Spitaleri, Walter Rocchia, & Andrea Cavalli. (2018). BiKi Life Sciences: A New Suite for Molecular Dynamics and Related Methods in Drug Discovery. Journal of Chemical Information and Modeling. 58(2). 219–224. 46 indexed citations
15.
Decherchi, Sergio, Anna Berteotti, Giovanni Bottegoni, Walter Rocchia, & Andrea Cavalli. (2015). The ligand binding mechanism to purine nucleoside phosphorylase elucidated via molecular dynamics and machine learning. Nature Communications. 6(1). 6155–6155. 90 indexed citations
16.
Mollica, Luca, et al.. (2015). Kinetics of protein-ligand unbinding via smoothed potential molecular dynamics simulations. Scientific Reports. 5(1). 11539–11539. 116 indexed citations
17.
Decherchi, Sergio, et al.. (2014). Implicit solvent methods for free energy estimation. European Journal of Medicinal Chemistry. 91. 27–42. 47 indexed citations
18.
Decherchi, Sergio, Mauro Parodi, & Sandro Ridella. (2011). Learning the mean: A neural network approach. Neurocomputing. 77(1). 129–143. 4 indexed citations
19.
Decherchi, Sergio, Sandro Ridella, Rodolfo Zunino, Paolo Gastaldo, & Davide Anguita. (2010). Using Unsupervised Analysis to Constrain Generalization Bounds for Support Vector Classifiers. IEEE Transactions on Neural Networks. 21(3). 424–438. 16 indexed citations
20.
Decherchi, Sergio, Paolo Gastaldo, Sandro Ridella, & Rodolfo Zunino. (2008). Explicit overall risk minimization transductive bound. La Revue du praticien. 46(10). 1297–304.

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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