The Diffusion of Perturbations in a Model of Coupled Random Boolean Networks. - Roberto Serra; Marco Villani 001; Chiara Damiani; Alex Graudenzi; Annamaria Colacci (ACRI, 2008)

Genetic Regulatory Networks and Neural Networks. - Roberto Serra; Alex Graudenzi; Marco Villani 001 (WIRN, 2008)

The simulation of gene knock-out in scale-free random Boolean models of genetic networks. - Roberto Serra; Marco Villani 001; Alex Graudenzi; Annamaria Colacci; Stuart A. Kauffman (Networks Heterog. Media, 2008)

The influence of the residence time on the dynamics of catalytic reaction networks. - Alessandro Filisetti; Roberto Serra; Marco Villani 001; Alex Graudenzi; Rudolf M. Füchslin; Irene Poli (WIRN, 2010)

The role of energy in a stochastic model of the emergence of autocatalytic sets. - Alessandro Filisetti; Alex Graudenzi; Roberto Serra; Marco Villani 001; Davide De Lucrezia; Irene Poli (ECAL, 2011)

Robustness Analysis of a Boolean Model of Gene Regulatory Network with Memory. - Alex Graudenzi; Roberto Serra; Marco Villani 001; Annamaria Colacci; Stuart A. Kauffman (J. Comput. Biol., 2011)

Dynamical Properties of a Boolean Model of Gene Regulatory Network with Memory. - Alex Graudenzi; Roberto Serra; Marco Villani 001; Chiara Damiani; Annamaria Colacci; Stuart A. Kauffman (J. Comput. Biol., 2011)

Effects of delayed immune-response in tumor immune-system interplay - Giulio Caravagna; Alex Graudenzi; Marco Antoniotti; Giancarlo Mauri; Alberto d'Onofrio (HSB, 2012)

A stochastic model of autocatalytic reaction networks. - Alessandro Filisetti; Alex Graudenzi; Roberto Serra; Marco Villani 001; Rudolf M. Füchslin; Norman H. Packard; Stuart A. Kauffman; Irene Poli (Theory Biosci., 2012)

The role of backward reactions in a stochastic model of catalytic reaction networks. - Alessandro Filisetti; Alex Graudenzi; Chiara Damiani; Marco Villani 001; Roberto Serra (ECAL, 2013)

GeStoDifferent: a Cytoscape plugin for the generation and the identification of gene regulatory networks describing a stochastic cell differentiation process. - Marco Antoniotti; Gary D. Bader; Giulio Caravagna; Silvia Crippa; Alex Graudenzi; Giancarlo Mauri (Bioinform., 2013)

Parameter sensitivity analysis of stochastic models: Application to catalytic reaction networks. - Chiara Damiani; Alessandro Filisetti; Alex Graudenzi; Paola Lecca (Comput. Biol. Chem., 2013)

Analysis of the spatial and dynamical properties of a multiscale model of intestinal crypts. - Giulio Caravagna; Alex Graudenzi; Marco Antoniotti; Giovanni De Matteis (WIVACE, 2013)

Recent developments in research on catalytic reaction networks. - Chiara Damiani; Alessandro Filisetti; Alex Graudenzi; Marco Villani 001; Roberto Serra (WIVACE, 2013)

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; Chiara Damiani; Marco Villani 001 (WIVACE, 2013)

On RAF Sets and Autocatalytic Cycles in Random Reaction Networks. - Alessandro Filisetti; Marco Villani 001; Chiara Damiani; Alex Graudenzi; Andrea Roli; Wim Hordijk; Roberto Serra (WIVACE, 2014)

Investigating the Role of Network Topology and Dynamical Regimes on the Dynamics of a Cell Differentiation Model. - Alex Graudenzi; Chiara Damiani; Andrea Paroni; Alessandro Filisetti; Marco Villani 001; Roberto Serra; Marco Antoniotti (WIVACE, 2014)

Preface. - Alex Graudenzi; Giulio Caravagna; Giancarlo Mauri (Nat. Comput., 2014)

A stochastic model of catalytic reaction networks in protocells. - Roberto Serra; Alessandro Filisetti; Marco Villani 001; Alex Graudenzi; Chiara Damiani; Tommaso Panini (Nat. Comput., 2014)

CAPRI: efficient inference of cancer progression models from cross-sectional data. - Daniele Ramazzotti; Giulio Caravagna; Loes Olde Loohuis; Alex Graudenzi; Ilya Korsunsky; Giancarlo Mauri; Marco Antoniotti; Bud Mishra (Bioinform., 2015)

TRONCO: an R package for the inference of cancer progression models from heterogeneous genomic data. - Luca De Sano; Giulio Caravagna; Daniele Ramazzotti; Alex Graudenzi; Giancarlo Mauri; Bud Mishra; Marco Antoniotti (Bioinform., 2016)

CABeRNET: a Cytoscape app for augmented Boolean models of gene regulatory NETworks. - Andrea Paroni; Alex Graudenzi; Giulio Caravagna; Chiara Damiani; Giancarlo Mauri; Marco Antoniotti (BMC Bioinform., 2016)

Modeling cumulative biological phenomena with Suppes-Bayes causal networks. - Daniele Ramazzotti; Alex Graudenzi; Marco Antoniotti (CoRR, 2016)

Ordering cancer mutational profiles of cross-sectional copy number alterations. - Alex Graudenzi; Giulio Caravagna; Iuliana M. Bocicor; Claudia Cava; Marco Antoniotti; Giancarlo Mauri (Int. J. Data Min. Bioinform., 2016)

Design of the TRONCO BioConductor Package for TRanslational ONCOlogy. - Marco Antoniotti; Giulio Caravagna; Luca De Sano; Alex Graudenzi; Giancarlo Mauri; Bud Mishra; Daniele Ramazzotti (R J., 2016)

Learning the Probabilistic Structure of Cumulative Phenomena with Suppes-Bayes Causal Networks. - Daniele Ramazzotti; Marco S. Nobile; Marco Antoniotti; Alex Graudenzi (CoRR, 2017)

Learning mutational graphs of individual tumor evolution from multi-sample sequencing data. - Daniele Ramazzotti; Alex Graudenzi; Luca De Sano; Marco Antoniotti; Giulio Caravagna (CoRR, 2017)

Modeling Spatio-Temporal Dynamics of Metabolic Networks with Cellular Automata and Constraint-Based Methods. - Alex Graudenzi; Davide Maspero; Chiara Damiani (ACRI, 2018)

Structural Learning of Probabilistic Graphical Models of Cumulative Phenomena. - Daniele Ramazzotti; Marco S. Nobile; Marco Antoniotti; Alex Graudenzi (ICCS (1), 2018)

Synchronization Effects in a Metabolism-Driven Model of Multi-cellular System. - Davide Maspero; Alex Graudenzi; Satwinder Singh; Dario Pescini; Giancarlo Mauri; Marco Antoniotti; Chiara Damiani (WIVACE, 2018)

Integration of transcriptomic data and metabolic networks in cancer samples reveals highly significant prognostic power. - Alex Graudenzi; Davide Maspero; Marzia Di Filippo; Marco Gnugnoli; Claudio Isella; Giancarlo Mauri; Enzo Medico; Marco Antoniotti; Chiara Damiani (J. Biomed. Informatics, 2018)

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)

cyTRON and cyTRON/JS: Two Cytoscape-Based Applications for the Inference of Cancer Evolution Models. - Lucrezia Patruno; Edoardo Galimberti; Daniele Ramazzotti; Giulio Caravagna; Luca De Sano; Marco Antoniotti; Alex Graudenzi (CIBB, 2019)

The Detection of Dynamical Organization in Cancer Evolution Models. - Laura Sani; Gianluca D'Addese; Alex Graudenzi; Marco Villani 001 (WIVACE, 2019)

Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data. - Daniele Ramazzotti; Alex Graudenzi; Luca De Sano; Marco Antoniotti; Giulio Caravagna (BMC Bioinform., 2019)

Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena. - Daniele Ramazzotti; Marco S. Nobile; Marco Antoniotti; Alex Graudenzi (J. Comput. Sci., 2019)

Integration of single-cell RNA-seq data into population models to characterize cancer metabolism. - Chiara Damiani; Davide Maspero; Marzia Di Filippo; Riccardo Colombo; Dario Pescini; Alex Graudenzi; Hans V. Westerhoff; Lilia Alberghina; Marco Vanoni; Giancarlo Mauri (PLoS Comput. Biol., 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)

The Influence of Nutrients Diffusion on a Metabolism-driven Model of a Multi-cellular System. - Davide Maspero; Chiara Damiani; Marco Antoniotti; Alex Graudenzi; Marzia Di Filippo; Marco Vanoni; Giulio Caravagna; Riccardo Colombo; Daniele Ramazzotti; Dario Pescini (Fundam. Informaticae, 2020)

FBCA, A Multiscale Modeling Framework Combining Cellular Automata and Flux Balance Analysis. - Alex Graudenzi; Davide Maspero; Chiara Damiani (J. Cell. Autom., 2020)

Two-Level Detection of Dynamic Organization in Cancer Evolution Models. - Gianluca D'Addese; Alex Graudenzi; Luca La Rocca; Marco Villani 001 (WIVACE, 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)

Combining multi-target regression deep neural networks and kinetic modeling to predict relative fluxes in reaction systems. - Lucrezia Patruno; Francesco Craighero; Davide Maspero; Alex Graudenzi; Chiara Damiani (Inf. Comput., 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)

Characterization of cancer subtypes associated with clinical outcomes by multi-omics integrative clustering. - Valentina Crippa; Federica Malighetti; Matteo Villa; Alex Graudenzi; Rocco Piazza; Luca Mologni; Daniele Ramazzotti (Comput. Biol. Medicine, 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, 2023)

A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing. - Lucrezia Patruno; Salvatore Milite; Riccardo Bergamin; Nicola Calonaci; Alberto d'Onofrio; Fabio Anselmi; Marco Antoniotti; Alex Graudenzi; Giulio Caravagna (PLoS Comput. Biol., 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)