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 (CIBB, 2019)

Understanding Deep Learning with Activation Pattern Diagrams. - Francesco Craighero; Alex Graudenzi; Fabrizio Angaroni; Fabio Stella; Marco Antoniotti (XAI.it@AI*IA, 2020)

A closed-loop optimization framework for personalized cancer therapy design. - Fabrizio Angaroni; Mattia Pennati; Lucrezia Patruno; Davide Maspero; Marco Antoniotti; Alex Graudenzi (CIBCB, 2020)

Investigating the Compositional Structure of Deep Neural Networks. - Francesco Craighero; Fabrizio Angaroni; Alex Graudenzi; Fabio Stella; Marco Antoniotti (LOD (1), 2020)

Optimal Control of a Discrete Time Stochastic Model of an Epidemic Spreading in Arbitrary Networks. - Fabrizio Angaroni; Chiara Damiani; Giulia Ramunni; Marco Antoniotti (ANNSIM, 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)

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)

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 (WIVACE, 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)

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)

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)

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, 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., 2023)