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

Prioritization of cancer driver gene with prize-collecting steiner tree by introducing an edge weighted strategy in the personalized gene interaction network.

BMC bioinformatics - 16 Aug 2022

Zhang Shao-Wu, Wang Zhen-Nan, Li Yan, Guo Wei-Feng

Abstract excerpt

BACKGROUND: Cancer is a heterogeneous disease in which tumor genes cooperate as well as adapt and evolve to the changing conditions for individual patients. It is a meaningful task to discover the personalized cancer driver genes that can provide diagnosis and target drug for individual patients. However, most of existing methods mainly ranks potential personalized cancer driver genes by considering the...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Gene Regulatory Networks

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Mutation

Share to Neoplasms

Share to Oncogenes

Share to Precision Medicine

Source

Open in PubMed Open full text

Identifiers

PMID: 35974311
DOI: 10.1186/s12859-022-04802-y
PMCID: PMC9380343

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

Prioritization of cancer driver gene with prize-collecting steiner tree by introducing an edge weighted strategy in the personalized gene interaction network.PMID 35974311Read ↗

Identifying cooperating cancer driver genes in individual patients through hypergraph random walk.Semantic proximity Read ↗

Exploring gene-patient association to identify personalized cancer driver genes by linear neighborhood propagation.Semantic proximity Read ↗

PRODIGY: personalized prioritization of driver genesSemantic proximity Read ↗

Discovering potential cancer driver genes by an integrated network-based approach.Semantic proximity Read ↗

Enhancing Cancer Driver Gene Prediction by Protein-Protein Interaction Network.Semantic proximity Read ↗

PRODIGY: personalized prioritization of driver genes.Semantic proximity Read ↗

PersonaDrive: A Method for the Identification and Prioritization of Personalized Cancer DriversSemantic proximity Read ↗

Discovering personalized driver mutation profiles of single samples in cancer by network control strategy.Semantic proximity Read ↗

A novel hypergraph model for identifying and prioritizing personalized drivers in cancer.Semantic proximity Read ↗

PITCH: A Pathway-Induced Prioritization of Personalized Cancer Driver Genes Based on Higher-Order Interactions.Semantic proximity Read ↗

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

Integrating Protein Interaction Networks and Somatic Mutation Data to Detect Driver Modules in Pan-CancerSemantic proximity Read ↗

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