Article

Network analysis allows to unravel breast cancer molecular features and to identify novel targets

2019-03-06

Abstract excerpt

The behaviour of complex biological systems is determined by the orchestrated activity of many components interacting with each other, and can be investigated by networks. In particular, gene co-expression networks have been widely used in the past years thanks to the increasing availability of huge gene expression databases. Breast cancer is a heterogeneous disease usually classified either according to immunohis...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 85ded34d-6215-5d00-918f-66f676e88ac3
DOI: 10.1101/570051

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Network analysis allows to unravel breast cancer molecular features and to identify novel targetsDOI 10.1101/570051Read

Identification of Important Modules and Biomarkers in Breast Cancer Based on WGCNASemantic proximity Read

Integrated transcriptomic meta-analysis provides novel insights into breast cancer molecular subtypesSemantic proximity Read

Identification of Prognostic Candidate Genes in Breast Cancer by Integrated Bioinformatic AnalysisSemantic proximity Read

Insights into Breast Cancer Prognosis: A Differential Regulatory Network Approach to Identify Key Transcription Factor BiomarkersSemantic proximity Read

Genome-wide screen identifies a novel prognostic signature for breast cancer survivalSemantic proximity Read

Prognostic genes of breast cancer revealed by gene co-expression network analysisSemantic proximity Read

Integrative network-based approach identifies key genetic elements in breast invasive carcinoma.Semantic proximity Read

Identification of hub genes and diagnostic efficacy for triple-negative breast cancer through WGCNA and Mendelian randomizationSemantic proximity Read

Identification of significantly mutated subnetworks in the breast cancer genome.Semantic proximity Read

Cohesive data analysis for the identification of prognostic hub genes and significant pathways associated with HER2 + and TN breast cancer typesSemantic proximity Read

Identification of key genes unique to the luminal A and basal-like breast cancer subtypes via bioinformatic analysisSemantic proximity Read

Weighted gene co-expression network analysis reveals modules and hub genes associated with the development of breast cancerSemantic proximity Read