Daniele Ramazzotti

Orcid: 0000-0002-6087-2666

According to our database1, Daniele Ramazzotti authored at least 38 papers between 2013 and 2024.

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Bibliography

2024
Control-FREEC viewer: a tool for the visualization and exploration of copy number variation data.
BMC Bioinform., December, 2024

2023
LACE 2.0: an interactive R tool for the inference and visualization of longitudinal cancer evolution.
BMC Bioinform., December, 2023

Characterization of cancer subtypes associated with clinical outcomes by multi-omics integrative clustering.
Comput. Biol. Medicine, August, 2023

2022
LACE: Inference of cancer evolution models from longitudinal single-cell sequencing data.
J. Comput. Sci., 2022

PMCE: efficient inference of expressive models of cancer evolution with high prognostic power.
Bioinform., 2022

Exploring the Solution Space of Cancer Evolution Inference Frameworks for Single-Cell Sequencing Data.
Proceedings of the Artificial Life and Evolutionary Computation - 16th Italian Workshop, 2022

2021
De novo mutational signature discovery in tumor genomes using SparseSignatures.
PLoS Comput. Biol., 2021

VERSO: A comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples.
Patterns, 2021

Investigating the performance of multi-objective optimization when learning Bayesian Networks.
Neurocomputing, 2021

Learning the structure of Bayesian Networks via the bootstrap.
Neurocomputing, 2021

2020
Correction to: Exposing the probabilistic causal structure of discrimination.
Int. J. Data Sci. Anal., 2020

The Influence of Nutrients Diffusion on a Metabolism-driven Model of a Multi-cellular System.
Fundam. Informaticae, 2020

2019
Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients.
npj Digit. Medicine, 2019

Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena.
J. Comput. Sci., 2019

Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data.
BMC Bioinform., 2019

cyTRON and cyTRON/JS: Two Cytoscape-Based Applications for the Inference of Cancer Evolution Models.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2019

2018
Causal data science for financial stress testing.
J. Comput. Sci., 2018

Withholding aggressive treatments may not accelerate time to death among dying ICU patients.
CoRR, 2018

Multi-objective optimization to explicitly account for model complexity when learning Bayesian Networks.
CoRR, 2018

Learning the Structure of Bayesian Networks: A Quantitative Assessment of the Effect of Different Algorithmic Schemes.
Complex., 2018

Structural Learning of Probabilistic Graphical Models of Cumulative Phenomena.
Proceedings of the Computational Science - ICCS 2018, 2018

Probabilistic Causal Analysis of Social Influence.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017
Exposing the probabilistic causal structure of discrimination.
Int. J. Data Sci. Anal., 2017

Learning mutational graphs of individual tumor evolution from multi-sample sequencing data.
CoRR, 2017

SIMLR: a tool for large-scale single-cell analysis by multi-kernel learning.
CoRR, 2017

Learning the Probabilistic Structure of Cumulative Phenomena with Suppes-Bayes Causal Networks.
CoRR, 2017

On learning the structure of Bayesian Networks and submodular function maximization.
CoRR, 2017

A quantitative assessment of the effect of different algorithmic schemes to the task of learning the structure of Bayesian Networks.
CoRR, 2017

Efficient Simulation of Financial Stress Testing Scenarios with Suppes-Bayes Causal Networks.
Proceedings of the International Conference on Computational Science, 2017

2016
Design of the TRONCO BioConductor Package for TRanslational ONCOlogy.
R J., 2016

Modeling cumulative biological phenomena with Suppes-Bayes causal networks.
CoRR, 2016

A Model of Selective Advantage for the Efficient Inference of Cancer Clonal Evolution.
CoRR, 2016

TRONCO: an R package for the inference of cancer progression models from heterogeneous genomic data.
Bioinform., 2016

Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks.
Proceedings of the 8th International Joint Conference on Computational Intelligence, 2016

Parallel implementation of efficient search schemes for the inference of cancer progression models.
Proceedings of the 2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2016

2015
CAPRI: efficient inference of cancer progression models from cross-sectional data.
Bioinform., 2015

2014
Inference of Cancer Progression Models with Biological Noise.
CoRR, 2014

2013
A Model of Colonic Crypts using SBML Spatial.
Proceedings of the Proceedings Wivace 2013, 2013


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