Fabrizio Angaroni

According to our database, Fabrizio Angaroni authored at least 13 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

LACE 2.0: an interactive R tool for the inference and visualization of longitudinal cancer evolution.

Gianluca Ascolani, Fabrizio Angaroni, Davide Maspero, Francesco Craighero, Narra Lakshmi Sai Bhavesh, Rocco Piazza, Chiara Damiani, Daniele Ramazzotti, Marco Antoniotti, Alex Graudenzi

BMC Bioinform., December, 2023

Unity is strength: Improving the detection of adversarial examples with ensemble approaches.

Francesco Craighero, Fabrizio Angaroni, Fabio Stella, Chiara Damiani, Marco Antoniotti, Alex Graudenzi

Neurocomputing, October, 2023

2022

LACE: Inference of cancer evolution models from longitudinal single-cell sequencing data.

Daniele Ramazzotti, Fabrizio Angaroni, Davide Maspero, Gianluca Ascolani, Isabella Castiglioni, Rocco Piazza, Marco Antoniotti, Alex Graudenzi

J. Comput. Sci., 2022

J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments.

Fabrizio Angaroni, Alessandro Guidi, Gianluca Ascolani, Alberto d'Onofrio, Marco Antoniotti, Alex Graudenzi

BMC Bioinform., 2022

PMCE: efficient inference of expressive models of cancer evolution with high prognostic power.

Fabrizio Angaroni, Kevin Chen, Chiara Damiani, Giulio Caravagna, Alex Graudenzi, Daniele Ramazzotti

Bioinform., 2022

Exploring the Solution Space of Cancer Evolution Inference Frameworks for Single-Cell Sequencing Data.

Davide Maspero, Fabrizio Angaroni, Lucrezia Patruno, Daniele Ramazzotti, David Posada, Alex Graudenzi

Proceedings of the Artificial Life and Evolutionary Computation - 16th Italian Workshop, 2022

2021

VERSO: A comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples.

Daniele Ramazzotti, Fabrizio Angaroni, Davide Maspero, Carlo Gambacorti Passerini, Marco Antoniotti, Alex Graudenzi, Rocco Piazza

Patterns, 2021

EAD: an ensemble approach to detect adversarial examples from the hidden features of deep neural networks.

Francesco Craighero, Fabrizio Angaroni, Fabio Stella, Chiara Damiani, Marco Antoniotti, Alex Graudenzi

CoRR, 2021

Optimal Control of a Discrete Time Stochastic Model of an Epidemic Spreading in Arbitrary Networks.

Fabrizio Angaroni, Chiara Damiani, Giulia Ramunni, Marco Antoniotti

Proceedings of the Annual Modeling and Simulation Conference, 2021

2020

Investigating the Compositional Structure of Deep Neural Networks.

Francesco Craighero, Fabrizio Angaroni, Alex Graudenzi, Fabio Stella, Marco Antoniotti

Proceedings of the Machine Learning, Optimization, and Data Science, 2020

A closed-loop optimization framework for personalized cancer therapy design.

Fabrizio Angaroni, Mattia Pennati, Lucrezia Patruno, Davide Maspero, Marco Antoniotti, Alex Graudenzi

Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2020

Understanding Deep Learning with Activation Pattern Diagrams.

Francesco Craighero, Alex Graudenzi, Fabrizio Angaroni, Fabio Stella, Marco Antoniotti

Proceedings of the Italian Workshop on Explainable Artificial Intelligence co-located with 19th International Conference of the Italian Association for Artificial Intelligence, 2020

2019

Integration of Single-Cell RNA-Sequencing Data into Flux Balance Cellular Automata.

Davide Maspero, Marzia Di Filippo, Fabrizio Angaroni, Dario Pescini, Giancarlo Mauri, Marco Vanoni, Alex Graudenzi, Chiara Damiani

Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2019