Davide Sabbadin

1.7k total citations
22 papers, 1.1k citations indexed

About

Davide Sabbadin is a scholar working on Molecular Biology, Computational Theory and Mathematics and Physiology. According to data from OpenAlex, Davide Sabbadin has authored 22 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 7 papers in Physiology. Recurrent topics in Davide Sabbadin's work include Receptor Mechanisms and Signaling (11 papers), Computational Drug Discovery Methods (7 papers) and Adenosine and Purinergic Signaling (6 papers). Davide Sabbadin is often cited by papers focused on Receptor Mechanisms and Signaling (11 papers), Computational Drug Discovery Methods (7 papers) and Adenosine and Purinergic Signaling (6 papers). Davide Sabbadin collaborates with scholars based in Italy, United States and Switzerland. Davide Sabbadin's co-authors include Stefano Moro, Gianni De Fabritiis, Miha Škalič, Antonella Ciancetta, José Jiménez-Luna, Anne Picard, Ildikò Szabó, Giulia Merli, Vanessa Checchetto and Anna Raffaello and has published in prestigious journals such as The EMBO Journal, FEBS Letters and Journal of Medicinal Chemistry.

In The Last Decade

Davide Sabbadin

22 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Davide Sabbadin Italy 16 881 337 178 150 129 22 1.1k
Ann E. Cleves United States 19 1.7k 1.9× 368 1.1× 81 0.5× 125 0.8× 95 0.7× 37 2.2k
Mayako Michino United States 18 1.1k 1.3× 317 0.9× 564 3.2× 52 0.3× 27 0.2× 32 1.4k
Young Ho Seo South Korea 21 942 1.1× 85 0.3× 48 0.3× 51 0.3× 58 0.4× 58 1.4k
Andreas Evers Germany 21 1.1k 1.3× 528 1.6× 280 1.6× 102 0.7× 23 0.2× 55 1.6k
Usha Warrior United States 21 672 0.8× 84 0.2× 172 1.0× 51 0.3× 28 0.2× 44 1.2k
Jichun Ma United States 12 463 0.5× 109 0.3× 90 0.5× 58 0.4× 42 0.3× 19 1.1k
Enrico Guarnera Singapore 21 1.3k 1.5× 462 1.4× 93 0.5× 187 1.2× 11 0.1× 39 1.6k
Gudrun M. Spitzer Austria 14 568 0.6× 364 1.1× 32 0.2× 70 0.5× 23 0.2× 18 864
L. Michel Espinoza‐Fonseca United States 20 833 0.9× 119 0.4× 98 0.6× 153 1.0× 33 0.3× 59 1.1k
Nicolas Pietrancosta France 20 468 0.5× 97 0.3× 102 0.6× 63 0.4× 15 0.1× 63 1.0k

Countries citing papers authored by Davide Sabbadin

Since Specialization
Citations

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

Fields of papers citing papers by Davide Sabbadin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Davide Sabbadin

This figure shows the co-authorship network connecting the top 25 collaborators of Davide Sabbadin. A scholar is included among the top collaborators of Davide Sabbadin 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 Davide Sabbadin. Davide Sabbadin 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.
Elzinga, Dezi, Erin L. Sternburg, Davide Sabbadin, et al.. (2019). Defining and Exploiting Hypersensitivity Hotspots to Facilitate Abscisic Acid Agonist Optimization. ACS Chemical Biology. 14(3). 332–336. 14 indexed citations
2.
Škalič, Miha, Davide Sabbadin, Boris Sattarov, Simone Sciabola, & Gianni De Fabritiis. (2019). From Target to Drug: Generative Modeling for the Multimodal Structure-Based Ligand Design. Molecular Pharmaceutics. 16(10). 4282–4291. 92 indexed citations
3.
Škalič, Miha, José Jiménez-Luna, Davide Sabbadin, & Gianni De Fabritiis. (2019). Shape-Based Generative Modeling for de Novo Drug Design. Journal of Chemical Information and Modeling. 59(3). 1205–1214. 150 indexed citations
4.
Huang, Yen‐Hua, Conan K. Wang, Aurélien Bigot, et al.. (2019). Insecticidal spider toxins are high affinity positive allosteric modulators of the nicotinic acetylcholine receptor. FEBS Letters. 593(12). 1336–1350. 29 indexed citations
5.
Sabbadin, Davide, Veronica Salmaso, Mattia Sturlese, & Stefano Moro. (2018). Supervised Molecular Dynamics (SuMD) Approaches in Drug Design. Methods in molecular biology. 1824. 287–298. 15 indexed citations
6.
Jiménez-Luna, José, Davide Sabbadin, Alberto Cuzzolin, et al.. (2018). PathwayMap: Molecular Pathway Association with Self-Normalizing Neural Networks. Journal of Chemical Information and Modeling. 59(3). 1172–1181. 25 indexed citations
7.
Ciancetta, Antonella, Alberto Cuzzolin, Giuseppe Deganutti, et al.. (2016). New Trends in Inspecting GPCR‐ligand Recognition Process: the Contribution of the Molecular Modeling Section (MMS) at the University of Padova. Molecular Informatics. 35(8-9). 440–448. 3 indexed citations
8.
Ciancetta, Antonella, Davide Sabbadin, Stephanie Federico, Giampiero Spalluto, & Stefano Moro. (2015). Advances in Computational Techniques to Study GPCR–Ligand Recognition. Trends in Pharmacological Sciences. 36(12). 878–890. 38 indexed citations
9.
Paoletta, Silvia, Davide Sabbadin, Ivar von Kügelgen, et al.. (2015). Modeling ligand recognition at the P2Y12 receptor in light of X-ray structural information. Journal of Computer-Aided Molecular Design. 29(8). 737–756. 43 indexed citations
10.
Sabbadin, Davide, Antonella Ciancetta, Giuseppe Deganutti, Alberto Cuzzolin, & Stefano Moro. (2015). Exploring the recognition pathway at the human A2A adenosine receptor of the endogenous agonist adenosine using supervised molecular dynamics simulations. MedChemComm. 6(6). 1081–1085. 35 indexed citations
11.
Moscetti, Ilaria, Franco Faoro, Stefano Moro, et al.. (2014). The xylanase inhibitor TAXI‐III counteracts the necrotic activity of a F usarium graminearum xylanase in vitro and in durum wheat transgenic plants. Molecular Plant Pathology. 16(6). 583–592. 15 indexed citations
12.
Sabbadin, Davide, Antonella Ciancetta, & Stefano Moro. (2014). Perturbation of Fluid Dynamics Properties of Water Molecules during G Protein-Coupled Receptor–Ligand Recognition: The Human A2AAdenosine Receptor as a Key Study. Journal of Chemical Information and Modeling. 54(10). 2846–2855. 19 indexed citations
13.
Floris, Matteo, et al.. (2013). Implementing the “Best Template Searching” tool into Adenosiland platform. In Silico Pharmacology. 1(1). 25–25. 11 indexed citations
14.
Raffaello, Anna, Diego De Stefani, Davide Sabbadin, et al.. (2013). The mitochondrial calcium uniporter is a multimer that can include a dominant‐negative pore‐forming subunit. The EMBO Journal. 32(17). 2362–2376. 385 indexed citations
15.
Floris, Matteo, et al.. (2013). MMsDusty: an Alternative InChI‐Based Tool to Minimize Chemical Redundancy. Molecular Informatics. 32(8). 681–684. 2 indexed citations
16.
Pandya, Amit N., V. Sudarsanam, Sonja Kachler, et al.. (2013). New insight into adenosine receptors selectivity derived from a novel series of [5-substituted-4-phenyl-1,3-thiazol-2-yl] benzamides and furamides. European Journal of Medicinal Chemistry. 63. 924–934. 29 indexed citations
17.
Sabbadin, Davide, Antonella Ciancetta, & Stefano Moro. (2013). Bridging Molecular Docking to Membrane Molecular Dynamics To Investigate GPCR–Ligand Recognition: The Human A2AAdenosine Receptor as a Key Study. Journal of Chemical Information and Modeling. 54(1). 169–183. 56 indexed citations
18.
Colotta, Vittoria, Ombretta Lenzi, Daniela Catarzi, et al.. (2012). 3-Hydroxy-1H-quinazoline-2,4-dione derivatives as new antagonists at ionotropic glutamate receptors: Molecular modeling and pharmacological studies. European Journal of Medicinal Chemistry. 54. 470–482. 34 indexed citations
19.
Floris, Matteo, et al.. (2012). Adenosiland: Walking through adenosine receptors landscape. European Journal of Medicinal Chemistry. 58. 248–257. 29 indexed citations
20.
Coluccia, Antonio, Davide Sabbadin, & Andrea Brancale. (2011). Molecular modelling studies on Arylthioindoles as potent inhibitors of tubulin polymerization. European Journal of Medicinal Chemistry. 46(8). 3519–3525. 15 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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