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

Identifying potential cancer driver genes by genomic data integration.

Scientific reports - 18 Dec 2013

Chen Yong, Hao Jingjing, Jiang Wei, He Tong, Zhang Xuegong, Jiang Tao, Jiang Rui

Abstract excerpt

Cancer is a genomic disease associated with a plethora of gene mutations resulting in a loss of control over vital cellular functions. Among these mutated genes, driver genes are defined as being causally linked to oncogenesis, while passenger genes are thought to be irrelevant for cancer development. With increasing numbers of large-scale genomic datasets available, integrating these genomic data to identify...

Read the complete abstract on PubMed

Topics

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

Share to Carcinogenesis
Share to Cyclin-Dependent Kinase Inhibitor p16

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to DNA Copy Number Variations

Share to Genomic Library

Share to Liver Neoplasms

Share to Melanoma

Share to Proto-Oncogene Proteins c-akt

Share to Receptors, Cell Surface

Source

Open in PubMed Open full text

Identifiers

PMID: 24346768
DOI: 10.1038/srep03538
PMCID: PMC3866686

Genes

AKT1

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

Identifying potential cancer driver genes by genomic data integration.PMID 24346768Read ↗

Advancing cancer driver gene identification through an integrative network and pathway approach.Semantic proximity Read ↗

LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network.Semantic proximity Read ↗

DriverMP enables improved identification of cancer driver genes.Semantic proximity Read ↗

DriverOmicsNet: An Integrated Graph Convolutional Network for Multi-Omics Exploration of Cancer Driver GenesSemantic proximity Read ↗

Driver gene detection through Bayesian network integration of mutation and expression profiles.Semantic proximity Read ↗

iEDGE: integration of Epi-DNA and Gene Expression and applications to the discovery of somatic copy number-associated drivers in cancerSemantic proximity Read ↗

Cancer driver gene discovery through an integrative genomics approach in a non-parametric Bayesian framework.Semantic proximity Read ↗

Identifying driver genes for individual patients through inductive matrix completion.Semantic proximity Read ↗

DriverDBv2: a database for human cancer driver gene research.Semantic proximity Read ↗

Ontology-based prediction of cancer driver genesSemantic proximity Read ↗

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysisSemantic proximity Read ↗

Computational approaches for the identification of cancer genes and pathways.Semantic proximity Read ↗

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