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

Joint analysis for integrating two related studies of different data types and different study designs using hierarchical modeling approaches.

Human heredity - 1 Jan 2012

Li Rui, Conti David V, Diaz-Sanchez David, Gilliland Frank, Thomas Duncan C

Abstract excerpt

BACKGROUND: A chronic disease such as asthma is the result of a complex sequence of biological interactions involving multiple genes and pathways in response to a multitude of environmental exposures. However, methods to model jointly all factors are still evolving. Some of the current challenges include how to integrate knowledge from different data types and different disciplines, as well as how to utilize...

Read the complete abstract on PubMed

Topics

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

Share to Asthma
Share to Bayes Theorem
Share to Biomarkers

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Data Interpretation, Statistical

Share to Epidemiologic Studies

Share to Gene-Environment Interaction

Share to Models, Statistical

Share to Research Design

Source

Open in PubMed Open full text

Identifiers

PMID: 23343600
DOI: 10.1159/000345181
PMCID: PMC4106669

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

Joint analysis for integrating two related studies of different data types and different study designs using hierarchical modeling approaches.PMID 23343600Read ↗

Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.Semantic proximity Read ↗

A statistical model for assessing genetic susceptibility as a risk factor in multifactorial diseases: lessons from occupational asthma.Semantic proximity Read ↗

Bayesian variable selection for hierarchical gene-environment and gene-gene interactions.Semantic proximity Read ↗

Pathway-based genetic susceptibility and cleaning agent exposures in adult asthma: A semi explorative GxE analysis in the Personalized Environment and Gene Study (PEGS)Semantic proximity Read ↗

Mechanistic indicators of childhood asthma (MICA) study: piloting an integrative design for evaluating environmental health.Semantic proximity Read ↗

State-of-the-art methods for exposure-health studies: Results from the exposome data challenge eventSemantic proximity Read ↗

Discovery of complex pathways from observational data.Semantic proximity Read ↗

Two-stage Linked Component Analysis for Joint Decomposition of Multiple Biologically Related Data SetsSemantic proximity Read ↗

A mixture model approach in gene-gene and gene-environmental interactions for binary phenotypes.Semantic proximity Read ↗

Bayesian mixture modeling of gene-environment and gene-gene interactions.Semantic proximity Read ↗

Viewpoint: using gene-environment interactions to dissect the effects of complex mixtures.Semantic proximity Read ↗

Integrative systems biology approaches in asthma pharmacogenomics.Semantic proximity Read ↗

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