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

Bayesian neural networks for detecting epistasis in genetic association studies.

BMC bioinformatics - 21 Nov 2014

Beam Andrew L, Motsinger-Reif Alison, Doyle Jon

Abstract excerpt

BACKGROUND: Discovering causal genetic variants from large genetic association studies poses many difficult challenges. Assessing which genetic markers are involved in determining trait status is a computationally demanding task, especially in the presence of gene-gene interactions. RESULTS: A non-parametric Bayesian approach in the form of a Bayesian neural network is proposed for use in analyzing genetic...

Read the complete abstract on PubMed

Topics

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

Share to Bayes Theorem
Share to Computational Biology
Share to Epistasis, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genetic Association Studies

Share to Models, Genetic

Share to Mycobacterium

Share to Neural Networks, Computer

Share to Tuberculosis

Source

Open in PubMed Open full text

Identifiers

PMID: 25413600
DOI: 10.1186/s12859-014-0368-0
PMCID: PMC4256933

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

Bayesian neural networks for detecting epistasis in genetic association studies.PMID 25413600Read ↗

A bayesian method for evaluating and discovering disease loci associations.Semantic proximity Read ↗

Genetic studies of complex human diseases: characterizing SNP-disease associations using Bayesian networks.Semantic proximity Read ↗

A fast algorithm for learning epistatic genomic relationships.Semantic proximity Read ↗

Identifying genetic interactions in genome-wide data using Bayesian networks.Semantic proximity Read ↗

Interpretable artificial neural networks incorporating Bayesian alphabet models for genome-wide prediction and association studies.Semantic proximity Read ↗

Bayesian statistical methods for genetic association studies.Semantic proximity Read ↗

Causal Genomics in the Deep Learning EraSemantic proximity Read ↗

Bayesian modelling in genetic association studiesSemantic proximity Read ↗

Multi-scale inference of genetic trait architecture using biologically annotated neural networks.Semantic proximity Read ↗

Biologically-informed Interpretable Deep Learning Framework for Phenotype Prediction and Gene Interaction DetectionSemantic proximity Read ↗

Neural networks and disease association studies.Semantic proximity Read ↗

Detecting epistatic SNPs associated with complex diseases via a Bayesian classification tree search method.Semantic proximity Read ↗

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