Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

A data-driven approach for constructing mutation categories for mutational signature analysis.

PLoS computational biology - 1 Oct 2021

Gilad Gal, Leiserson Mark D M, Sharan Roded

Abstract excerpt

Mutational processes shape the genomes of cancer patients and their understanding has important applications in diagnosis and treatment. Current modeling of mutational processes by identifying their characteristic signatures views each base substitution in a limited context of a single flanking base on each side. This context definition gives rise to 96 categories of mutations that have become the standard in the...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Computational Biology
Share to DNA Damage
Share to DNA Mutational Analysis

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Gene Expression Regulation, Neoplastic

Share to Mutation

Share to Neoplasms

Source

Open in PubMed Open full text

Identifiers

PMID: 34665813
DOI: 10.1371/journal.pcbi.1009542
PMCID: PMC8555780

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A data-driven approach for constructing mutation categories for mutational signature analysis.PMID 34665813Read ↗

A framework for mutational signature analysis based on DNA shape parametersSemantic proximity Read ↗

A framework for mutational signature analysis based on DNA shape parameters.Semantic proximity Read ↗

Learning mutational signatures and their multidimensional genomic properties with TensorSignaturesSemantic proximity Read ↗

MutationalPatterns: The one stop shop for the analysis of mutational processesSemantic proximity Read ↗

Detecting presence of mutational signatures in cancer with confidenceSemantic proximity Read ↗

Accurate and sensitive mutational signature analysis with MuSiCalSemantic proximity Read ↗

MutationalPatterns: the one stop shop for the analysis of mutational processes.Semantic proximity Read ↗

Accurate and sensitive mutational signature analysis with MuSiCal.Semantic proximity Read ↗

Detecting presence of mutational signatures in cancer with confidenceSemantic proximity Read ↗

Mutational signatures: experimental design and analytical frameworkSemantic proximity Read ↗

Mutational Signatures: From Methods to Mechanisms.Semantic proximity Read ↗

Mutational signatures: emerging concepts, caveats and clinical applications.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.