17 citations · 31 across the 10 of their papers we have counts for
11 papers
Unity is strength: Improving the Detection of Adversarial Examples with Ensemble Approaches
Francesco Craighero, Fabrizio Angaroni, Fabio Stella +3
A key challenge in computer vision and deep learning is the definition of robust strategies for the detection of adversarial examples. Here, we propose the adoption of ensemble app…
Metabolic enrichment through functional gene rules
Davide Maspero, Claudio Isella, Marzia Di Filippo +6
It is well known that tumors originating from the same tissue have different prognosis and sensitivity to treatments. Over the last decade, cancer genomics consortia like the Cance…
Constraint-based modeling and simulation of cell populations
M. Di Filippo, C. Damiani, R. Colombo +2
The intratumor heterogeneity has been recognized to characterize cancer cells impairing the efficacy of cancer treatments. We here propose an extension of constraint-based modeling…
CABeRNET: a Cytoscape app for Augmented Boolean models of gene Regulatory NETworks
Andrea Paroni, Alex Graudenzi, Giulio Caravagna +3
Background. Dynamical models of gene regulatory networks (GRNs) are highly effective in describing complex biological phenomena and processes, such as cell differentiation and canc…
Dynamical regimes in non-ergodic random Boolean networks
Marco Villani, Davide Campioli, Chiara Damiani +3
Random boolean networks are a model of genetic regulatory networks that has proven able to describe experimental data in biology. They not only reproduce important phenomena in cel…
On RAF Sets and Autocatalytic Cycles in Random Reaction Networks
Alessandro Filisetti, Marco Villani, Chiara Damiani +4
The emergence of autocatalytic sets of molecules seems to have played an important role in the origin of life context. Although the possibility to reproduce this emergence in labor…
PMCE: efficient inference of expressive models of cancer evolution with high prognostic power
Fabrizio Angaroni, Kevin Chen, Chiara Damiani +3
Motivation: Driver (epi)genomic alterations underlie the positive selection of cancer subpopulations, which promotes drug resistance and relapse. Even though substantial heterogene…
A stochastic model of catalytic reaction networks in protocells
Roberto Serra, Alessandro Filisetti, Marco Villani +3
Protocells are supposed to have played a key role in the self-organizing processes leading to the emergence of life. Existing models either (i) describe protocell architecture and…
An ensemble approach to the study of the emergence of metabolic and proliferative disorders via Flux Balance Analysis
Chiara Damiani, Riccardo Colombo, Sara Molinari +5
An extensive rewiring of cell metabolism supports enhanced proliferation in cancer cells. We propose a systems level approach to describe this phenomenon based on Flux Balance Anal…
A model of protocell based on the introduction of a semi-permeable membrane in a stochastic model of catalytic reaction networks
Roberto Serra, Alessandro Filisetti, Alex Graudenzi +2
In this work we introduce some preliminary analyses on the role of a semi-permeable membrane in the dynamics of a stochastic model of catalytic reaction sets (CRSs) of molecules. T…
Recent developments in research on catalytic reaction networks
Chiara Damiani, Alessandro Filisetti, Alex Graudenzi +2
Over the last years, analyses performed on a stochastic model of catalytic reaction networks have provided some indications about the reasons why wet-lab experiments hardly ever co…