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ORCIDDaniele Ramazzotti
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2020 – today
- 2024
[j20]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): 72 (2024)- 2023
- [j19]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): 99 (2023) - [j18]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: 107064 (2023) - 2022
- [j17]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): 754-762 (2022) - [j16]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: 101523 (2022) - [c8]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: 70-81 - 2021
- [j15]Giulio Caravagna, Daniele Ramazzotti:
Learning the structure of Bayesian Networks via the bootstrap. Neurocomputing 448: 48-59 (2021) - [j14]Marco S. Nobile, Paolo Cazzaniga, Daniele Ramazzotti:
Investigating the performance of multi-objective optimization when learning Bayesian Networks. Neurocomputing 461: 281-291 (2021) - [j13]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): 100212 (2021) - [j12]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) - 2020
- [j11]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): 279-295 (2020) - [j10]Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti:
Correction to: Exposing the probabilistic causal structure of discrimination. Int. J. Data Sci. Anal. 9(3): 373 (2020)
2010 – 2019
- 2019
- [j9]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): 210:1-210:13 (2019) - [j8]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: 1-10 (2019) - [j7]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) - [c7]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: 13-18 - 2018
- [j6]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: 1591878:1-1591878:12 (2018) - [j5]Gelin Gao, Bud Mishra, Daniele Ramazzotti:
Causal data science for financial stress testing. J. Comput. Sci. 26: 294-304 (2018) - [c6]Francesco Bonchi, Francesco Gullo, Bud Mishra, Daniele Ramazzotti:
Probabilistic Causal Analysis of Social Influence. CIKM 2018: 1003-1012 - [c5]Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti, Alex Graudenzi:
Structural Learning of Probabilistic Graphical Models of Cumulative Phenomena. ICCS (1) 2018: 678-693 - [i16]Paolo Cazzaniga, Marco S. Nobile, Daniele Ramazzotti:
Multi-objective optimization to explicitly account for model complexity when learning Bayesian Networks. CoRR abs/1808.01345 (2018) - [i15]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 abs/1808.02017 (2018) - [i14]Francesco Bonchi, Francesco Gullo, Bud Mishra, Daniele Ramazzotti:
Probabilistic Causal Analysis of Social Influence. CoRR abs/1808.02129 (2018) - 2017
- [j4]Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti:
Exposing the probabilistic causal structure of discrimination. Int. J. Data Sci. Anal. 3(1): 1-21 (2017) - [c4]Gelin Gao, Bud Mishra, Daniele Ramazzotti:
Efficient Simulation of Financial Stress Testing Scenarios with Suppes-Bayes Causal Networks. ICCS 2017: 272-284 - [i13]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 abs/1703.03038 (2017) - [i12]Stefano Beretta, Mauro Castelli, Ivo Gonçalves, Ivan Merelli, Daniele Ramazzotti:
Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks. CoRR abs/1703.03041 (2017) - [i11]Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti, Alex Graudenzi:
Learning the Probabilistic Structure of Cumulative Phenomena with Suppes-Bayes Causal Networks. CoRR abs/1703.03074 (2017) - [i10]Gelin Gao, Bud Mishra, Daniele Ramazzotti:
Efficient Simulation of Financial Stress Testing Scenarios with Suppes-Bayes Causal Networks. CoRR abs/1703.03076 (2017) - [i9]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 abs/1703.07844 (2017) - [i8]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 abs/1704.08676 (2017) - [i7]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 abs/1705.03067 (2017) - [i6]Giulio Caravagna, Daniele Ramazzotti, Guido Sanguinetti:
On learning the structure of Bayesian Networks and submodular function maximization. CoRR abs/1706.02386 (2017) - [i5]Daniele Ramazzotti, Alex Graudenzi, Luca De Sano, Marco Antoniotti, Giulio Caravagna:
Learning mutational graphs of individual tumor evolution from multi-sample sequencing data. CoRR abs/1709.01076 (2017) - 2016
- [j3]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): 1911-1913 (2016) - [j2]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): 39 (2016) - [c3]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: 1-6 - [c2]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: 217-224 - [i4]Daniele Ramazzotti:
A Model of Selective Advantage for the Efficient Inference of Cancer Clonal Evolution. CoRR abs/1602.07614 (2016) - [i3]Daniele Ramazzotti, Alex Graudenzi, Marco Antoniotti:
Modeling cumulative biological phenomena with Suppes-Bayes causal networks. CoRR abs/1602.07857 (2016) - 2015
- [j1]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): 3016-3026 (2015) - [i2]Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti:
Exposing the Probabilistic Causal Structure of Discrimination. CoRR abs/1510.00552 (2015) - 2014
- [i1]Ilya Korsunsky, Daniele Ramazzotti, Giulio Caravagna, Bud Mishra:
Inference of Cancer Progression Models with Biological Noise. CoRR abs/1408.6032 (2014) - 2013
- [c1]Daniele Ramazzotti, Carlo Maj, Marco Antoniotti:
A Model of Colonic Crypts using SBML Spatial. WIVACE 2013: 74-78
Coauthor Index
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