Computational approaches for discovery of mutational signatures in cancer.
Accepted version
Peer-reviewed
Repository URI
Repository DOI
Change log
Authors
Baez-Ortega, Adrian
Gori, Kevin https://orcid.org/0000-0001-7975-4275
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
1477-4054
Volume Title
20
Publisher
Oxford University Press (OUP)
Publisher DOI
Sponsorship
Wellcome Trust (102942/Z/13/Z)