List of works - Daniele Ramazzotti

Algorithmic methods to infer the evolutionary trajectories in cancer progression ⬇️

scientific article published on 28 June 2016

CAPRI: efficient inference of cancer progression models from cross-sectional data ⬇️

scientific article

Characterization of intra-host SARS-CoV-2 variants improves phylogenomic reconstruction and may reveal functionally convergent mutations

scientific article published on 26 April 2020

Comprehensive genomic characterization of breast tumors with BRCA1 and BRCA2 mutations

scientific article published on 10 June 2019

Detecting repeated cancer evolution from multi-region tumor sequencing data

scientific article published on 31 August 2018

Improved Survival of Cancer Patients Admitted to the Intensive Care Unit between 2002 and 2011 at a U.S. Teaching Hospital

scientific article published on 10 October 2018

Inferring tree causal models of cancer progression with probability raising

scientific article

Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data

scientific article published on 25 April 2019

Learning the Structure of Bayesian Networks: A Quantitative Assessment of the Effect of Different Algorithmic Schemes

scientific article published on 12 September 2018

Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients

scientific article published on 29 November 2019

Modeling Cumulative Biological Phenomena with Suppes-Bayes Causal Networks.

scientific article published on 4 July 2018

Multi-omic tumor data reveal diversity of molecular mechanisms that correlate with survival

scientific article published in Nature Communications

OncoScore: a novel, Internet-based tool to assess the oncogenic potential of genes.

scientific article published on 07 April 2017

SIMLR: A Tool for Large-Scale Genomic Analyses by Multi-Kernel Learning.

scientific article published on 19 December 2017

SparseSignatures: An R package using LASSO-regularized non-negative matrix factorization to identify mutational signatures from human tumor samples

scientific article published in 2022

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

scientific article

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

scientific article published on 28 January 2021

Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning

scientific article

Withholding or withdrawing invasive interventions may not accelerate time to death among dying ICU patients

scientific article published on 14 February 2019

List of works by Daniele Ramazzotti

Algorithmic methods to infer the evolutionary trajectories in cancer progression ⬇️

CAPRI: efficient inference of cancer progression models from cross-sectional data ⬇️

Characterization of intra-host SARS-CoV-2 variants improves phylogenomic reconstruction and may reveal functionally convergent mutations

Comprehensive genomic characterization of breast tumors with BRCA1 and BRCA2 mutations

Detecting repeated cancer evolution from multi-region tumor sequencing data

Improved Survival of Cancer Patients Admitted to the Intensive Care Unit between 2002 and 2011 at a U.S. Teaching Hospital

Inferring tree causal models of cancer progression with probability raising

Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data

Learning the Structure of Bayesian Networks: A Quantitative Assessment of the Effect of Different Algorithmic Schemes

Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients

Modeling Cumulative Biological Phenomena with Suppes-Bayes Causal Networks.

Multi-omic tumor data reveal diversity of molecular mechanisms that correlate with survival

OncoScore: a novel, Internet-based tool to assess the oncogenic potential of genes.

SIMLR: A Tool for Large-Scale Genomic Analyses by Multi-Kernel Learning.

SparseSignatures: An R package using LASSO-regularized non-negative matrix factorization to identify mutational signatures from human tumor samples

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

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

Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning

Withholding or withdrawing invasive interventions may not accelerate time to death among dying ICU patients