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

Inferring causal phenotype networks from segregating populations.

Genetics - 1 Jun 2008

Chaibub Neto Elias, Ferrara Christine T, Attie Alan D, Yandell Brian S

Abstract excerpt

A major goal in the study of complex traits is to decipher the causal interrelationships among correlated phenotypes. Current methods mostly yield undirected networks that connect phenotypes without causal orientation. Some of these connections may be spurious due to partial correlation that is n...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Biometry
Share to Crosses, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Inbreeding

Share to Lod Score

Share to Metabolism

Share to Mice, Obese

Share to Quantitative Trait Loci

Source

Open in PubMed Open full text

Identifiers

PMID: 18505877
DOI: 10.1534/genetics.107.085167
PMCID: PMC2429862

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026. Prepared record publication-18505877-2026-09-02.2. 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

Inferring causal phenotype networks from segregating populations.PMID 18505877Read ↗

A new method to infer causal phenotype networks using QTL and phenotypic information.Semantic proximity Read ↗

Reconstruction of Networks with Direct and Indirect Genetic Effects.Semantic proximity Read ↗

Inferring a directed acyclic graph of phenotypes from GWAS summary statisticsSemantic proximity Read ↗

Inferring a directed acyclic graph of phenotypes from GWAS summary statistics.Semantic proximity Read ↗

Modeling causality for pairs of phenotypes in system genetics.Semantic proximity Read ↗

Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations.Semantic proximity Read ↗

Predicting the direction of phenotypic differenceSemantic proximity Read ↗

Estimation of a genetic Gaussian network using GWAS summary data.Semantic proximity Read ↗

Using stochastic causal trees to augment Bayesian networks for modeling eQTL datasets.Semantic proximity Read ↗

Genetic interaction networks: toward an understanding of heritability.Semantic proximity Read ↗

Causal inference of regulator-target pairs by gene mapping of expression phenotypes.Semantic proximity Read ↗

Disentangling direct and pleiotropic SNP effects in alfalfa (Medicago sativa L.) using causal graph learning.Semantic proximity Read ↗

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