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

Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimer’s disease patients

1 Dec 2018

Abstract excerpt

BACKGROUND: Gene co-expression network (GCN) mining is a systematic approach to efficiently identify novel disease pathways, predict novel gene functions and search for potential disease biomarkers. However, few studies have systematically identified GCNs in multiple brain transcriptomic data of Alzheimer's disease (AD) patients and looked for their specific functions. METHODS: In this study, we first mined GCN...

Read the complete abstract on PubMed

Topics

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

Share to Alzheimer's disease research and treatments
Share to Bioinformatics and Genomic Networks
Share to Neuroinflammation and Neurodegeneration Mechanisms

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 30598117
DOI: 10.1186/s12920-018-0431-1

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimer’s disease patientsPMID 30598117Read ↗

Application of Weighted Gene Co-Expression Network Analysis to Explore the Key Genes in Alzheimer's Disease.Semantic proximity Read ↗

Identifying and Ranking Potential Driver Genes of Alzheimer's Disease Using Weighted Co-Expression Network AnalysisSemantic proximity Read ↗

Weighted Gene Co-expression Network Analysis Identifies Specific Modules and Hub Genes Related to Alzheimer's DiseaseSemantic proximity Read ↗

Weighted Gene Co-expression Network Analysis Reveals Functionally Coherent Gene Networks Associated with Alzheimer’s Disease PathologySemantic proximity Read ↗

Exploring Shared Pathogenesis of Alzheimer’s Disease and Type 2 Diabetes Mellitus via Co-expression Networks AnalysisSemantic proximity Read ↗

Gene biomarker discovery at different stages of Alzheimer using gene co-expression network approachSemantic proximity Read ↗

Identification of Genetic Markers and Immune Infiltration Characteristics of Alzheimer’s Disease Through Weighted Gene Co-expression Network AnalysisSemantic proximity Read ↗

An Integrative Network-based Analysis Reveals Gene Networks, Biological Mechanisms, and Novel Drug Targets in Alzheimer’s DiseaseSemantic proximity Read ↗

Analysis of Shared Genetic Regulatory Networks for Alzheimer's Disease and Epilepsy.Semantic proximity Read ↗

[Identification of potential hub genes of Alzheimer's disease by weighted gene co-expression network analysis].Semantic proximity Read ↗

Co-expression Network Analysis Reveals Novel Genes Underlying Alzheimer’s Disease PathogenesisSemantic proximity Read ↗

Transcriptional dysregulation study reveals a core network involving the genesis for Alzheimer’s diseaseSemantic proximity Read ↗

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