Daniele Ramazzotti

44 papers A 1C 1Misc 1Journal 36Unranked 5
YearRankTypeTitle / Venue / Authors
2024 J jnl
Control-FREEC viewer: a tool for the visualization and exploration of copy number variation data.
BMC Bioinform.
Valentina Crippa, Emanuela Fina, Daniele Ramazzotti, Rocco Piazza
2023 J jnl
Characterization of cancer subtypes associated with clinical outcomes by multi-omics integrative clustering.
Comput. Biol. Medicine
Valentina Crippa, Federica Malighetti, Matteo Villa, Alex Graudenzi, Rocco Piazza, Luca Mologni, Daniele Ramazzotti
2023 J jnl
LACE 2.0: an interactive R tool for the inference and visualization of longitudinal cancer evolution.
BMC Bioinform.
Gianluca Ascolani, Fabrizio Angaroni, Davide Maspero, Francesco Craighero, Narra Lakshmi Sai Bhavesh, Rocco Piazza, Chiara Damiani, Daniele Ramazzotti, Marco Antoniotti, Alex Graudenzi
2022 — conf
Exploring the Solution Space of Cancer Evolution Inference Frameworks for Single-Cell Sequencing Data.
WIVACE
Davide Maspero, Fabrizio Angaroni, Lucrezia Patruno, Daniele Ramazzotti, David Posada, Alex Graudenzi
2022 J jnl
LACE: Inference of cancer evolution models from longitudinal single-cell sequencing data.
J. Comput. Sci.
Daniele Ramazzotti, Fabrizio Angaroni, Davide Maspero, Gianluca Ascolani, Isabella Castiglioni, Rocco Piazza, Marco Antoniotti, Alex Graudenzi
2022 J jnl
PMCE: efficient inference of expressive models of cancer evolution with high prognostic power.
Bioinform.
Fabrizio Angaroni, Kevin Chen, Chiara Damiani, Giulio Caravagna, Alex Graudenzi, Daniele Ramazzotti
2021 J jnl
De novo mutational signature discovery in tumor genomes using SparseSignatures.
PLoS Comput. Biol.
Avantika Lal, Keli Liu, Robert Tibshirani, Arend Sidow, Daniele Ramazzotti
2021 J jnl
Investigating the performance of multi-objective optimization when learning Bayesian Networks.
Neurocomputing
Marco S. Nobile, Paolo Cazzaniga, Daniele Ramazzotti
2021 J jnl
Learning the structure of Bayesian Networks via the bootstrap.
Neurocomputing
Giulio Caravagna, Daniele Ramazzotti
2021 J jnl
VERSO: A comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples.
Patterns
Daniele Ramazzotti, Fabrizio Angaroni, Davide Maspero, Carlo Gambacorti Passerini, Marco Antoniotti, Alex Graudenzi, Rocco Piazza
2020 J jnl
Correction to: Exposing the probabilistic causal structure of discrimination.
Int. J. Data Sci. Anal.
Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti
2020 J jnl
The Influence of Nutrients Diffusion on a Metabolism-driven Model of a Multi-cellular System.
Fundam. Informaticae
Davide Maspero, Chiara Damiani, Marco Antoniotti, Alex Graudenzi, Marzia Di Filippo, Marco Vanoni, Giulio Caravagna, Riccardo Colombo, Daniele Ramazzotti, Dario Pescini
2019 J jnl
Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena.
J. Comput. Sci.
Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti, Alex Graudenzi
2019 J jnl
Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data.
BMC Bioinform.
Daniele Ramazzotti, Alex Graudenzi, Luca De Sano, Marco Antoniotti, Giulio Caravagna
2019 J jnl
Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients.
npj Digit. Medicine
Antonin Dauvin, Carolina Donado, Patrik Bachtiger, Ke-Chun Huang, Christopher Martin Sauer, Daniele Ramazzotti, Matteo Bonvini, Leo Anthony Celi, Molly J. Douglas
2019 — conf
cyTRON and cyTRON/JS: Two Cytoscape-Based Applications for the Inference of Cancer Evolution Models.
CIBB
Lucrezia Patruno, Edoardo Galimberti, Daniele Ramazzotti, Giulio Caravagna, Luca De Sano, Marco Antoniotti, Alex Graudenzi
2018 J jnl
Causal data science for financial stress testing.
J. Comput. Sci.
Gelin Gao, Bud Mishra, Daniele Ramazzotti
2018 J jnl
Learning the Structure of Bayesian Networks: A Quantitative Assessment of the Effect of Different Algorithmic Schemes.
Complex.
Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Roberto Henriques, Daniele Ramazzotti
2018 J jnl
Multi-objective optimization to explicitly account for model complexity when learning Bayesian Networks.
CoRR
Paolo Cazzaniga, Marco S. Nobile, Daniele Ramazzotti
2018 A conf
Probabilistic Causal Analysis of Social Influence.
CIKM
Francesco Bonchi, Francesco Gullo, Bud Mishra, Daniele Ramazzotti
2018 J jnl
Probabilistic Causal Analysis of Social Influence.
CoRR
Francesco Bonchi, Francesco Gullo, Bud Mishra, Daniele Ramazzotti
2018 — conf
Structural Learning of Probabilistic Graphical Models of Cumulative Phenomena.
ICCS (1)
Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti, Alex Graudenzi
2018 J jnl
Withholding aggressive treatments may not accelerate time to death among dying ICU patients.
CoRR
Daniele Ramazzotti, Peter Clardy, Leo Anthony Celi, David J. Stone, Robert S. Rudin
2017 J jnl
A quantitative assessment of the effect of different algorithmic schemes to the task of learning the structure of Bayesian Networks.
CoRR
Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Daniele Ramazzotti
2017 J jnl
Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks.
CoRR
Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Ivan Merelli, Daniele Ramazzotti
2017 Misc conf
Efficient Simulation of Financial Stress Testing Scenarios with Suppes-Bayes Causal Networks.
ICCS
Gelin Gao, Bud Mishra, Daniele Ramazzotti
2017 J jnl
Efficient Simulation of Financial Stress Testing Scenarios with Suppes-Bayes Causal Networks.
CoRR
Gelin Gao, Bud Mishra, Daniele Ramazzotti
2017 J jnl
Exposing the probabilistic causal structure of discrimination.
Int. J. Data Sci. Anal.
Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti
2017 J jnl
Learning mutational graphs of individual tumor evolution from multi-sample sequencing data.
CoRR
Daniele Ramazzotti, Alex Graudenzi, Luca De Sano, Marco Antoniotti, Giulio Caravagna
2017 J jnl
Learning the Probabilistic Structure of Cumulative Phenomena with Suppes-Bayes Causal Networks.
CoRR
Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti, Alex Graudenzi
2017 J jnl
On learning the structure of Bayesian Networks and submodular function maximization.
CoRR
Giulio Caravagna, Daniele Ramazzotti, Guido Sanguinetti
2017 J jnl
Parallel Implementation of Efficient Search Schemes for the Inference of Cancer Progression Models.
CoRR
Daniele Ramazzotti, Marco S. Nobile, Paolo Cazzaniga, Giancarlo Mauri, Marco Antoniotti
2017 J jnl
SIMLR: a tool for large-scale single-cell analysis by multi-kernel learning.
CoRR
Bo Wang, Daniele Ramazzotti, Luca De Sano, Junjie Zhu, Emma Pierson, Serafim Batzoglou
2017 J jnl
cyTRON and cyTRON/JS: two Cytoscape-based applications for the inference of cancer evolution models.
CoRR
Lucrezia Patruno, Edoardo Galimberti, Daniele Ramazzotti, Giulio Caravagna, Luca De Sano, Marco Antoniotti, Alex Graudenzi
2016 J jnl
A Model of Selective Advantage for the Efficient Inference of Cancer Clonal Evolution.
CoRR
Daniele Ramazzotti
2016 — conf
Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks.
IJCCI (ECTA)
Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Ivan Merelli, Daniele Ramazzotti
2016 J jnl
Design of the TRONCO BioConductor Package for TRanslational ONCOlogy.
R J.
Marco Antoniotti, Giulio Caravagna, Luca De Sano, Alex Graudenzi, Giancarlo Mauri, Bud Mishra, Daniele Ramazzotti
2016 J jnl
Modeling cumulative biological phenomena with Suppes-Bayes causal networks.
CoRR
Daniele Ramazzotti, Alex Graudenzi, Marco Antoniotti
2016 C conf
Parallel implementation of efficient search schemes for the inference of cancer progression models.
CIBCB
Daniele Ramazzotti, Marco S. Nobile, Paolo Cazzaniga, Giancarlo Mauri, Marco Antoniotti
2016 J jnl
TRONCO: an R package for the inference of cancer progression models from heterogeneous genomic data.
Bioinform.
Luca De Sano, Giulio Caravagna, Daniele Ramazzotti, Alex Graudenzi, Giancarlo Mauri, Bud Mishra, Marco Antoniotti
2015 J jnl
CAPRI: efficient inference of cancer progression models from cross-sectional data.
Bioinform.
Daniele Ramazzotti, Giulio Caravagna, Loes Olde Loohuis, Alex Graudenzi, Ilya Korsunsky, Giancarlo Mauri, Marco Antoniotti, Bud Mishra
2015 J jnl
Exposing the Probabilistic Causal Structure of Discrimination.
CoRR
Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti
2014 J jnl
Inference of Cancer Progression Models with Biological Noise.
CoRR
Ilya Korsunsky, Daniele Ramazzotti, Giulio Caravagna, Bud Mishra
2013 — conf
A Model of Colonic Crypts using SBML Spatial.
WIVACE
Daniele Ramazzotti, Carlo Maj, Marco Antoniotti