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

An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer.

PLoS computational biology - 1 Sept 2015

Foo Jasmine, Liu Lin L, Leder Kevin, Riester Markus, Iwasa Yoh, Lengauer Christoph, Michor Franziska

Abstract excerpt

The traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provide a fitness advantage to the cell. Distinguishing such "driver" mutations from innocuous "passenger" events is...

Read the complete abstract on PubMed

Topics

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

Share to Colorectal Neoplasms
Share to Computational Biology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Cross-Sectional Studies

Share to Evolution, Molecular

Share to Models, Genetic

Share to Models, Statistical

Share to Mutation

Share to Population Dynamics

Source

Open in PubMed Open full text

Identifiers

PMID: 26379039
DOI: 10.1371/journal.pcbi.1004350
PMCID: PMC4575033

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

An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer.PMID 26379039Read ↗

Algorithmic Methods to Infer the Evolutionary Trajectories in Cancer ProgressionSemantic proximity Read ↗

Identification of constrained cancer driver genes based on mutation timing.Semantic proximity Read ↗

Modeling Functional Genetic Alteration in Cancer Reveals New Candidate Driver GenesSemantic proximity Read ↗

Mutations, substitutions, and selection: Linking mutagenic processes to cancer using evolutionary theory.Semantic proximity Read ↗

Somatic mutation distribution across tumour cohorts provides a signal for positive selection in cancer.Semantic proximity Read ↗

A mathematical framework to determine the temporal sequence of somatic genetic events in cancer.Semantic proximity Read ↗

Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools.Semantic proximity Read ↗

MADGiC: a model-based approach for identifying driver genes in cancer.Semantic proximity Read ↗

Impact of deleterious passenger mutations on cancer progression.Semantic proximity Read ↗

Estimating growth patterns and driver effects in tumor evolution from individual samples.Semantic proximity Read ↗

The Evolutionary Landscape of Colorectal Tumorigenesis: Recent Paradigms, Models, and Hypotheses.Semantic proximity Read ↗

Inferring the paths of somatic evolution in cancer.Semantic proximity Read ↗

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