Mario Giacobini

9.5k total citations · 1 hit paper
223 papers, 6.2k citations indexed

About

Mario Giacobini is a scholar working on Molecular Biology, Pharmacology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Mario Giacobini has authored 223 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Molecular Biology, 66 papers in Pharmacology and 54 papers in Cellular and Molecular Neuroscience. Recurrent topics in Mario Giacobini's work include Cholinesterase and Neurodegenerative Diseases (64 papers), Neuroscience and Neuropharmacology Research (38 papers) and Nicotinic Acetylcholine Receptors Study (38 papers). Mario Giacobini is often cited by papers focused on Cholinesterase and Neurodegenerative Diseases (64 papers), Neuroscience and Neuropharmacology Research (38 papers) and Nicotinic Acetylcholine Receptors Study (38 papers). Mario Giacobini collaborates with scholars based in Italy, United States and Switzerland. Mario Giacobini's co-authors include Robert E. Becker, Adane Nega Tarekegn, Marta E. Hallak, Marco Tomassini, Vincent A. Chiappinelli, Krzysztof Michalak, Kimio Sugaya, Patrizia De Sarno, Francesca Mori and Leslie Luthi and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and SHILAP Revista de lepidopterología.

In The Last Decade

Mario Giacobini

221 papers receiving 5.8k citations

Hit Papers

A review of methods for imbalanced multi-label classifica... 2021 2026 2022 2024 2021 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A review of methods for imbalanced multi-label classification
    2021 262 citations Mario Giacobini et al. profile →

Peers

Mario Giacobini
M. Sandler United Kingdom
Jon Chambers United Kingdom
Nicolas Le Novère United Kingdom
Xinglong Wang United States
Xudong Huang United States
Ravi Iyengar United States
Benjamin Weiss United States
Raymond Scott Turner United States
Hiroshi Saitō Japan
Hugo Geerts United States
M. Sandler United Kingdom
Mario Giacobini
Citations per year, relative to Mario Giacobini Mario Giacobini (= 1×) peers M. Sandler

Countries citing papers authored by Mario Giacobini

Since Specialization
Citations

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

Fields of papers citing papers by Mario Giacobini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mario Giacobini

This figure shows the co-authorship network connecting the top 25 collaborators of Mario Giacobini. A scholar is included among the top collaborators of Mario Giacobini 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 Mario Giacobini. Mario Giacobini 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.
Martini, Fabio & Mario Giacobini. (2024). Aesthetics of Death in the Paleolithic and Mesolithic of Italy. The Evolution of Grave goods. L Anthropologie. 128(3). 103279–103279. 2 indexed citations
2.
Bellino, Claudio, et al.. (2023). A novel machine learning-based web application for field identification of infectious and inflammatory disorders of the central nervous system in cattle. Journal of Veterinary Internal Medicine. 37(2). 766–773. 6 indexed citations
3.
Lombardo, Gianfranco, Michele Tomaiuolo, Stefano Cagnoni, et al.. (2022). Fine-Grained Agent-Based Modeling to Predict Covid-19 Spreading and Effect of Policies in Large-Scale Scenarios. IEEE Journal of Biomedical and Health Informatics. 26(5). 2052–2062. 13 indexed citations
4.
Bajardi, Paolo, et al.. (2014). Interplay of network dynamics and heterogeneity of ties on spreading dynamics. Physical Review E. 90(1). 12812–12812. 11 indexed citations
5.
Vanneschi, Leonardo, et al.. (2013). Evolutionary computation, machine learning and data mining in bioinformatics : 11th European conference, EvoBIO 2013, Vienna, Austria, April 3-5, 2013, proceedings. Springer eBooks. 1 indexed citations
6.
Darabos, Christian, et al.. (2013). Cellular Automata Coevolution of Update Functions and Topologies: A Tradeoff between Accuracy and Speed. 340–347. 1 indexed citations
7.
Bertolotti, Luigi, et al.. (2010). Transmission Dynamics of Borrelia lusitaniae and Borrelia afzelii Among Ixodes ricinus , Lizards, and Mice in Tuscany, Central Italy. Vector-Borne and Zoonotic Diseases. 11(1). 21–28. 24 indexed citations
8.
Darabos, Christian, Mario Giacobini, Marco Tomassini, Paolo Provero, & Ferdinando Di Cunto. (2009). Are cells really operating at the edge of chaos? a case study of two real-life regulatory networks. 281–288. 2 indexed citations
9.
Giacobini, Mario, Gianni A. Di, Andréas Fink, et al.. (2007). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes: Preface. Lecture notes in computer science. 1 indexed citations
10.
Giacobini, Mario, et al.. (2006). A minimal information prisoner's dilemma on evolving networks. IRIS. 5 indexed citations
11.
Giacobini, Mario. (2006). Artificial evolution on network structures: how time and space influence dynamics. reroDoc Digital Library. 1 indexed citations
12.
Giacobini, Mario. (2006). Richesse et diversité du rituel funéraire au paléolithique supérieur. Cairn.info. 24–46. 3 indexed citations
13.
Giacobini, Mario. (2006). Richesse et diversité du rituel funéraire au paléolithique supérieur. Diogène. n° 214(2). 24–46. 8 indexed citations
14.
Luthi, Leslie, Mario Giacobini, & Marco Tomassini. (2005). Synchronous and Asynchronous Network Evolution in a Population of Stubborn Prisoners. IRIS. 225–232. 3 indexed citations
15.
Giacobini, Mario & Marco Tomassini. (2003). Investigating Selection Pressure in Asynchronous Cellular Evolutionary Algorithms.. IRIS. 308–311. 1 indexed citations
16.
Giacobini, Mario, Marco Tomassini, & Leonardo Vanneschi. (2002). How Statistics Can Help In Limiting The Number Of Fitness Cases In Genetic Programming. Genetic and Evolutionary Computation Conference. 889–889. 1 indexed citations
17.
Giacobini, Mario. (1997). From Molecular Structure to Alzheimer Therapy.. The Japanese Journal of Pharmacology. 74(3). 225–241. 87 indexed citations
18.
Giacobini, Mario. (1990). Chapter 34 The cholinergic system in Alzheimer disease. Progress in brain research. 84. 321–332. 82 indexed citations
19.
Becker, Robert E. & Mario Giacobini. (1988). Mechanisms of cholinesterase inhibition in senile dementia of the alzheimer type: Clinical, pharmacological, and therapeutic aspects. Drug Development Research. 12(3-4). 163–195. 153 indexed citations
20.
Giacobini, Mario, et al.. (1985). Le impronte di piedi umani. 362–366. 4 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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