107 citations · 355 across the 19 of their papers we have counts for
Showing q-bio.GNShow all
2 papers · 1 filter
q-bio.GN2017
Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data
Daniele Ramazzotti, Alex Graudenzi, Luca De Sano +2
Background. A large number of algorithms is being developed to reconstruct evolutionary models of individual tumours from genome sequencing data. Most methods can analyze multiple…
q-bio.GN2015★ 100 cited
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…