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
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
2020
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
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
Proceedings of the Computational Science - ICCS 2018, 2018
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018
2017
Int. J. Data Sci. Anal., 2017
Learning mutational graphs of individual tumor evolution from multi-sample sequencing data.
CoRR, 2017
CoRR, 2017
Learning the Probabilistic Structure of Cumulative Phenomena with Suppes-Bayes Causal Networks.
CoRR, 2017
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
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
Bioinform., 2015
2014
2013
Proceedings of the Proceedings Wivace 2013, 2013