107 citations · 372 across the 19 of their papers we have counts for
4 papers · 1 filter
Algorithmic Methods to Infer the Evolutionary Trajectories in Cancer Progression
Giulio Caravagna, Alex Graudenzi, Daniele Ramazzotti +6
The genomic evolution inherent to cancer relates directly to a renewed focus on the voluminous next generation sequencing (NGS) data, and machine learning for the inference of expl…
TRONCO: an R package for the inference of cancer progression models from heterogeneous genomic data
Luca De Sano, Giulio Caravagna, Daniele Ramazzotti +4
Motivation: We introduce TRONCO (TRanslational ONCOlogy), an open-source R package that implements the state-of-the-art algorithms for the inference of cancer progression models fr…
CABeRNET: a Cytoscape app for Augmented Boolean models of gene Regulatory NETworks
Andrea Paroni, Alex Graudenzi, Giulio Caravagna +3
Background. Dynamical models of gene regulatory networks (GRNs) are highly effective in describing complex biological phenomena and processes, such as cell differentiation and canc…
On RAF Sets and Autocatalytic Cycles in Random Reaction Networks
Alessandro Filisetti, Marco Villani, Chiara Damiani +4
The emergence of autocatalytic sets of molecules seems to have played an important role in the origin of life context. Although the possibility to reproduce this emergence in labor…