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 regulatory relationships among genomic loci, biological pathways, and disease.

Artificial intelligence in medicine - 1 Jul 2010

Woo Jung Hoon, Cho Sung Bum, Lee Eunjee, Kim Ju Han

Abstract excerpt

OBJECTIVE: Elucidating genetic factors of complex diseases is one of the most important challenges in biomedical research. Recently, a genetical genomics approach of mapping genotype to transcripts has been used in complex disease analysis. This approach treats messenger ribonucleic acid (mRNA) e...

Read the complete abstract on PubMed

Topics

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

Share to Cell Line
Share to Disease
Share to Gene Expression Profiling

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genomics

Share to Polymorphism, Single Nucleotide

Share to Principal Component Analysis

Share to RNA, Messenger

Source

Identifiers

PMID: 20554166
DOI: 10.1016/j.artmed.2010.03.001

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026. Prepared record publication-20554166-2026-09-02.2. Manifest publication-graph-cohort-2026-09-02.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identifying regulatory relationships among genomic loci, biological pathways, and disease.PMID 20554166Read ↗

Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets.Semantic proximity Read ↗

Gene co-expression analysis for functional classification and gene-disease predictions.Semantic proximity Read ↗

Convergent downstream candidate mechanisms of independent intergenic polymorphisms between co-classified diseases implicate epistasis among noncoding elements.Semantic proximity Read ↗

Disease-associated variants are enriched for altering cell-type-specific gene co-expression relationshipsSemantic proximity Read ↗

Leveraging gene co-regulation to identify gene sets enriched for disease heritabilitySemantic proximity Read ↗

A powerful framework for differential co-expression analysis of general risk factorsSemantic proximity Read ↗

Mapping of numerous disease-associated expression polymorphisms in primary peripheral blood CD4+ lymphocytes.Semantic proximity Read ↗

Incorporating gene co-expression network in identification of cancer prognosis markersSemantic proximity Read ↗

A composite network of conserved and tissue specific gene interactions reveals possible genetic interactions in glioma.Semantic proximity Read ↗

Genetic correlations reveal the shared genetic architecture of transcription in human peripheral blood.Semantic proximity Read ↗

Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans.Semantic proximity Read ↗

A systems genomics approach to uncover patient-specific pathogenic pathways and proteins in a complex diseaseSemantic proximity Read ↗

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