Motivation Cancer is characterized by intra-tumor heterogeneity, the presence of distinct cell
populations with distinct complements of somatic mutations, which include single-nucleotide …

Available computational methods for tumor phylogeny inference via single-cell sequencing
(SCS) data typically aim to identify the most likely perfect phylogeny tree satisfying the …

CRISPR-Cas9-based genome editing combined with single-cell sequencing enables the
tracing of the history of cell divisions, or cellular lineage, in tissues and whole organisms …

Integer linear programming (ILP) is a versatile modeling and optimization technique that is
increasingly used in non-traditional ways in biology, with the potential to transform biological …

Motivation In recent years, the well-known Infinite Sites Assumption has been a fundamental
feature of computational methods devised for reconstructing tumor phylogenies and inferring …

Motivation The latest advances in cancer sequencing, and the availability of a wide range of
methods to infer the evolutionary history of tumors, have made it important to evaluate …

Motivation Cancer phylogenies are key to studying tumorigenesis and have clinical
implications. Due to the heterogeneous nature of cancer and limitations in current …

The last decade of phylogenetics has seen the development of many methods that leverage
constraints plus dynamic programming. The goal of this algorithmic technique is to produce …

Motivation DNA sequencing of multiple bulk samples from a tumor provides the opportunity
to investigate tumor heterogeneity and reconstruct a phylogeny of a patient's cancer …

The chapter shines a light on the strong links shared by Artificial intelligence and
Bioinformatics since many years. Bioinformatics offers many NP-hard problems that are …