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

System-scale network modeling of cancer using EPoC.

Advances in experimental medicine and biology - 1 Jan 2012

Abenius Tobias, Jörnsten Rebecka, Kling Teresia, Schmidt Linnéa, Sánchez José, Nelander Sven

Abstract excerpt

One of the central problems of cancer systems biology is to understand the complex molecular changes of cancerous cells and tissues, and use this understanding to support the development of new targeted therapies. EPoC (Endogenous Perturbation analysis of Cancer) is a network modeling technique for tumor molecular profiles. EPoC models are constructed from combined copy number aberration (CNA) and mRNA data and...

Read the complete abstract on PubMed

Topics

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

Share to Systems Biology
Share to Algorithms
Share to Computational Biology

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Gene Dosage

Share to Gene Regulatory Networks

Share to Glioblastoma

Share to Reproducibility of Results

Share to Survival Analysis

Source

Identifiers

PMID: 22161356
DOI: 10.1007/978-1-4419-7210-1_37

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

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

System-scale network modeling of cancer using EPoC.PMID 22161356Read ↗

Network modeling of the transcriptional effects of copy number aberrations in glioblastomaSemantic proximity Read ↗

Principles and strategies for developing network models in cancer.Semantic proximity Read ↗

Inferring perturbation profiles of cancer samplesSemantic proximity Read ↗

Geometric network analysis provides prognostic information in patients with high grade serous carcinoma of the ovary treated with immune checkpoint inhibitorsSemantic proximity Read ↗

Geometric Network Analysis Provides Prognostic Information in Patients with High Grade Serous Carcinoma of the Ovary Treated with Immune Checkpoint InhibitorsSemantic proximity Read ↗

Evaluation of single-sample network inference methods for precision oncologySemantic proximity Read ↗

Perturbation-based gene regulatory network inference to unravel oncogenic mechanismsSemantic proximity Read ↗

Gene network modeling via TopNet reveals functional dependencies between diverse tumor-critical mediator genes.Semantic proximity Read ↗

Identifying Network Perturbation in CancerSemantic proximity Read ↗

A Complex Systems Analysis of Cancer NetworksSemantic proximity Read ↗

DiCE: differential centrality-ensemble analysis based on gene expression profiles and protein-protein interaction networkSemantic proximity Read ↗

Systems Biology Approach to Gene Network Analysis Identifies Therapeutic and Diagnostic Targets in Colorectal CancerSemantic proximity Read ↗

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