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Computational approaches for discovery of mutational signatures in cancer.

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Baez-Ortega, Adrian 

Abstract

The accumulation of somatic mutations in a genome is the result of the activity of one or more mutagenic processes, each of which leaves its own imprint. The study of these DNA fingerprints, termed mutational signatures, holds important potential for furthering our understanding of the causes and evolution of cancer, and can provide insights of relevance for cancer prevention and treatment. In this review, we focus our attention on the mathematical models and computational techniques that have driven recent advances in the field.

Description

Keywords

Bayes Theorem, Computational Biology, DNA, Neoplasm, Genome, Human, High-Throughput Nucleotide Sequencing, Humans, Models, Genetic, Models, Statistical, Mutation, Neoplasms, Sequence Analysis, DNA, Software

Journal Title

Brief Bioinform

Conference Name

Journal ISSN

1467-5463
1477-4054

Volume Title

20

Publisher

Oxford University Press (OUP)
Sponsorship
Wellcome Trust (102942/Z/13/Z)