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

Multipartite network analysis to identify environmental and genetic associations of metabolic syndrome in the Korean population.

Scientific reports - 31 Aug 2024

Shin Ji-Eun, Shin Nari, Park Taesung, Park Mira

Abstract excerpt

Network analysis has become a crucial tool in genetic research, enabling the exploration of associations between genes and diseases. Its utility extends beyond genetics to include the assessment of environmental factors. Unipartite network analysis is commonly used in genomics to visualize initial insights and relationships among variables. Syndromic diseases, such as metabolic syndrome, are characterized by the...

Read the complete abstract on PubMed

Topics

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

Share to Aged
Share to Gene-Environment Interaction
Share to Gene Regulatory Networks

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genetic Predisposition to Disease

Share to Genome-Wide Association Study

Share to Metabolic Syndrome

Share to Polymorphism, Single Nucleotide

Share to Republic of Korea

Source

Open in PubMed Open full text

Identifiers

PMID: 39217223
DOI: 10.1038/s41598-024-71217-5
PMCID: PMC11366034

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

Multipartite network analysis to identify environmental and genetic associations of metabolic syndrome in the Korean population.PMID 39217223Read ↗

NETMAGE: A human disease phenotype map generator for the network-based visualization of phenome-wide association study results.Semantic proximity Read ↗

Visualizing novel connections and genetic similarities across diseases using a network-medicine based approach.Semantic proximity Read ↗

Constructing genotype and phenotype network helps revealSemantic proximity Read ↗

Constructing genotype and phenotype network helps reveal disease heritability and phenome-wide association studiesSemantic proximity Read ↗

Network analysis of genes and their association with diseases.Semantic proximity Read ↗

Genome-wide epistasis and pleiotropy characterized by the bipartite human phenotype network.Semantic proximity Read ↗

Using the bipartite human phenotype network to reveal pleiotropy and epistasis beyond the gene.Semantic proximity Read ↗

Constructing genotype and phenotype network helps reveal disease heritability and phenome-wide association studies.Semantic proximity Read ↗

Uncovering genetic associations in the human diseasome using an endophenotype-augmented disease networkSemantic proximity Read ↗

Gene modules associated with human diseases revealed by network analysisSemantic proximity Read ↗

A novel method for multiple phenotype association studies based on genotype and phenotype network.Semantic proximity Read ↗

NETMAGE: a humaN-disEase phenoType MAp GEnerator for the Visualization of PheWASSemantic proximity Read ↗

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