Daniele Ramazzotti

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 40

Top Topics

Efficient Inference

Probabilistic Graphical Models

Causal Structure

Top Venues

J. Comput. Sci.

Publications

Valentina Crippa, Emanuela Fina, Daniele Ramazzotti, Rocco Piazza
Control-FREEC viewer: a tool for the visualization and exploration of copy number variation data. BMC Bioinform. 25 (1) (2024)
Valentina Crippa, Federica Malighetti, Matteo Villa, Alex Graudenzi, Rocco Piazza, Luca Mologni, Daniele Ramazzotti
Characterization of cancer subtypes associated with clinical outcomes by multi-omics integrative clustering. Comput. Biol. Medicine 162 (2023)
Gianluca Ascolani, Fabrizio Angaroni, Davide Maspero, Francesco Craighero, Narra Lakshmi Sai Bhavesh, Rocco Piazza, Chiara Damiani, Daniele Ramazzotti, Marco Antoniotti, Alex Graudenzi
LACE 2.0: an interactive R tool for the inference and visualization of longitudinal cancer evolution. BMC Bioinform. 24 (1) (2023)
Fabrizio Angaroni, Kevin Chen, Chiara Damiani, Giulio Caravagna, Alex Graudenzi, Daniele Ramazzotti
PMCE: efficient inference of expressive models of cancer evolution with high prognostic power. Bioinform. 38 (3) (2022)
Davide Maspero, Fabrizio Angaroni, Lucrezia Patruno, Daniele Ramazzotti, David Posada, Alex Graudenzi
Exploring the Solution Space of Cancer Evolution Inference Frameworks for Single-Cell Sequencing Data. WIVACE (2022)
Daniele Ramazzotti, Fabrizio Angaroni, Davide Maspero, Gianluca Ascolani, Isabella Castiglioni, Rocco Piazza, Marco Antoniotti, Alex Graudenzi
LACE: Inference of cancer evolution models from longitudinal single-cell sequencing data. J. Comput. Sci. 58 (2022)
Giulio Caravagna, Daniele Ramazzotti
Learning the structure of Bayesian Networks via the bootstrap. Neurocomputing 448 (2021)
Daniele Ramazzotti, Fabrizio Angaroni, Davide Maspero, Carlo Gambacorti Passerini, Marco Antoniotti, Alex Graudenzi, Rocco Piazza
VERSO: A comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples. Patterns 2 (3) (2021)
Avantika Lal, Keli Liu, Robert Tibshirani, Arend Sidow, Daniele Ramazzotti
De novo mutational signature discovery in tumor genomes using SparseSignatures. PLoS Comput. Biol. 17 (6) (2021)
Marco S. Nobile, Paolo Cazzaniga, Daniele Ramazzotti
Investigating the performance of multi-objective optimization when learning Bayesian Networks. Neurocomputing 461 (2021)
Davide Maspero, Chiara Damiani, Marco Antoniotti, Alex Graudenzi, Marzia Di Filippo, Marco Vanoni, Giulio Caravagna, Riccardo Colombo, Daniele Ramazzotti, Dario Pescini
The Influence of Nutrients Diffusion on a Metabolism-driven Model of a Multi-cellular System. Fundam. Informaticae 171 (1-4) (2020)
Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti
Correction to: Exposing the probabilistic causal structure of discrimination. Int. J. Data Sci. Anal. 9 (3) (2020)
Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti, Alex Graudenzi
Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena. J. Comput. Sci. 30 (2019)
Antonin Dauvin, Carolina Donado, Patrik Bachtiger, Ke-Chun Huang, Christopher Martin Sauer, Daniele Ramazzotti, Matteo Bonvini, Leo Anthony Celi, Molly J. Douglas
Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients. npj Digit. Medicine 2 (2019)
Daniele Ramazzotti, Alex Graudenzi, Luca De Sano, Marco Antoniotti, Giulio Caravagna
Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data. BMC Bioinform. 20 (1) (2019)
Lucrezia Patruno, Edoardo Galimberti, Daniele Ramazzotti, Giulio Caravagna, Luca De Sano, Marco Antoniotti, Alex Graudenzi
cyTRON and cyTRON/JS: Two Cytoscape-Based Applications for the Inference of Cancer Evolution Models. CIBB (2019)
Paolo Cazzaniga, Marco S. Nobile, Daniele Ramazzotti
Multi-objective optimization to explicitly account for model complexity when learning Bayesian Networks. CoRR (2018)
Daniele Ramazzotti, Peter Clardy, Leo Anthony Celi, David J. Stone, Robert S. Rudin
Withholding aggressive treatments may not accelerate time to death among dying ICU patients. CoRR (2018)
Gelin Gao, Bud Mishra, Daniele Ramazzotti
Causal data science for financial stress testing. J. Comput. Sci. 26 (2018)
Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti, Alex Graudenzi
Structural Learning of Probabilistic Graphical Models of Cumulative Phenomena. ICCS (1) (2018)
Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Roberto Henriques, Daniele Ramazzotti
Learning the Structure of Bayesian Networks: A Quantitative Assessment of the Effect of Different Algorithmic Schemes. Complex. 2018 (2018)
Francesco Bonchi, Francesco Gullo, Bud Mishra, Daniele Ramazzotti
Probabilistic Causal Analysis of Social Influence. CoRR (2018)
Francesco Bonchi, Francesco Gullo, Bud Mishra, Daniele Ramazzotti
Probabilistic Causal Analysis of Social Influence. CIKM (2018)
Giulio Caravagna, Daniele Ramazzotti, Guido Sanguinetti
On learning the structure of Bayesian Networks and submodular function maximization. CoRR (2017)
Lucrezia Patruno, Edoardo Galimberti, Daniele Ramazzotti, Giulio Caravagna, Luca De Sano, Marco Antoniotti, Alex Graudenzi
cyTRON and cyTRON/JS: two Cytoscape-based applications for the inference of cancer evolution models. CoRR (2017)
Gelin Gao, Bud Mishra, Daniele Ramazzotti
Efficient Simulation of Financial Stress Testing Scenarios with Suppes-Bayes Causal Networks. CoRR (2017)
Gelin Gao, Bud Mishra, Daniele Ramazzotti
Efficient Simulation of Financial Stress Testing Scenarios with Suppes-Bayes Causal Networks. ICCS (2017)
Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti, Alex Graudenzi
Learning the Probabilistic Structure of Cumulative Phenomena with Suppes-Bayes Causal Networks. CoRR (2017)
Daniele Ramazzotti, Alex Graudenzi, Luca De Sano, Marco Antoniotti, Giulio Caravagna
Learning mutational graphs of individual tumor evolution from multi-sample sequencing data. CoRR (2017)
Daniele Ramazzotti, Marco S. Nobile, Paolo Cazzaniga, Giancarlo Mauri, Marco Antoniotti
Parallel Implementation of Efficient Search Schemes for the Inference of Cancer Progression Models. CoRR (2017)
Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Ivan Merelli, Daniele Ramazzotti
Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks. CoRR (2017)
Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti
Exposing the probabilistic causal structure of discrimination. Int. J. Data Sci. Anal. 3 (1) (2017)
Bo Wang, Daniele Ramazzotti, Luca De Sano, Junjie Zhu, Emma Pierson, Serafim Batzoglou
SIMLR: a tool for large-scale single-cell analysis by multi-kernel learning. CoRR (2017)
Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Daniele Ramazzotti
A quantitative assessment of the effect of different algorithmic schemes to the task of learning the structure of Bayesian Networks. CoRR (2017)
Daniele Ramazzotti, Alex Graudenzi, Marco Antoniotti
Modeling cumulative biological phenomena with Suppes-Bayes causal networks. CoRR (2016)
Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Ivan Merelli, Daniele Ramazzotti
Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks. IJCCI (ECTA) (2016)
Daniele Ramazzotti
A Model of Selective Advantage for the Efficient Inference of Cancer Clonal Evolution. CoRR (2016)
Luca De Sano, Giulio Caravagna, Daniele Ramazzotti, Alex Graudenzi, Giancarlo Mauri, Bud Mishra, Marco Antoniotti
TRONCO: an R package for the inference of cancer progression models from heterogeneous genomic data. Bioinform. 32 (12) (2016)
Marco Antoniotti, Giulio Caravagna, Luca De Sano, Alex Graudenzi, Giancarlo Mauri, Bud Mishra, Daniele Ramazzotti
Design of the TRONCO BioConductor Package for TRanslational ONCOlogy. R J. 8 (2) (2016)
Daniele Ramazzotti, Marco S. Nobile, Paolo Cazzaniga, Giancarlo Mauri, Marco Antoniotti
Parallel implementation of efficient search schemes for the inference of cancer progression models. CIBCB (2016)
Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti
Exposing the Probabilistic Causal Structure of Discrimination. CoRR (2015)
Daniele Ramazzotti, Giulio Caravagna, Loes Olde Loohuis, Alex Graudenzi, Ilya Korsunsky, Giancarlo Mauri, Marco Antoniotti, Bud Mishra
CAPRI: efficient inference of cancer progression models from cross-sectional data. Bioinform. 31 (18) (2015)
Ilya Korsunsky, Daniele Ramazzotti, Giulio Caravagna, Bud Mishra
Inference of Cancer Progression Models with Biological Noise. CoRR (2014)
Daniele Ramazzotti, Carlo Maj, Marco Antoniotti
A Model of Colonic Crypts using SBML Spatial. WIVACE (2013)