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

Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data.

BMC systems biology - 1 Jan 2012

Liu Yu, Maxwell Sean, Feng Tao, Zhu Xiaofeng, Elston Robert C, Koyutürk Mehmet, Chance Mark R

Abstract excerpt

BACKGROUND: Interactions among genomic loci (also known as epistasis) have been suggested as one of the potential sources of missing heritability in single locus analysis of genome-wide association studies (GWAS). The computational burden of searching for interactions is compounded by the extremely low threshold for identifying significant p-values due to multiple hypothesis testing corrections. Utilizing prior...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Computational Biology

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

Share to Databases, Genetic

Share to Diabetes Mellitus, Type 2

Share to Epistasis, Genetic

Share to Gene Expression

Share to Genetic Loci

Share to Logistic Models

Source

Open in PubMed Open full text

Identifiers

PMID: 23281810
DOI: 10.1186/1752-0509-6-S3-S15
PMCID: PMC3524014

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. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data.PMID 23281810Read ↗

Characterizing genetic interactions in human disease association studies using statistical epistasis networks.Semantic proximity Read ↗

Discovering genetic interactions bridging pathways in genome-wide association studiesSemantic proximity Read ↗

Using biological networks to search for interacting loci in genome-wide association studies.Semantic proximity Read ↗

INTERSNP: genome-wide interaction analysis guided by a priori information.Semantic proximity Read ↗

Detecting gene-gene interactions that underlie human diseases.Semantic proximity Read ↗

PANOGA: a web server for identification of SNP-targeted pathways from genome-wide association study data.Semantic proximity Read ↗

On epistasis: a methodological review for detecting gene-gene interactions underlying various types of phenotypic traits.Semantic proximity Read ↗

Functional and genomic context in pathway analysis of GWAS data.Semantic proximity Read ↗

A Tool for Detecting Complementary Single Nucleotide Polymorphism Pairs in Genome-Wide Association Studies for Epistasis Testing.Semantic proximity Read ↗

EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units.Semantic proximity Read ↗

Epistasis analysis for quantitative traits by functional regression model.Semantic proximity Read ↗

A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the breast cancer association consortium.Semantic proximity Read ↗

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