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 disease-related pathways using a probabilistic epistasis model.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing - 1 Jan 2009

Kanabar P N, Vaske C J, Yeang C H, Yildiz F H, Stuart J M

Abstract excerpt

MOTIVATION: We present a probabilistic model called a Joint Intervention Network (JIN) for inferring interactions among a chosen set of regulator genes. The input to the method are expression changes of downstream indicator genes observed under the knock-out of the regulators. JIN can use any num...

Read the complete abstract on PubMed

Topics

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

Share to Biofilms
Share to Biometry
Share to Epistasis, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Gene Regulatory Networks

Share to Genes, Bacterial

Share to Models, Genetic

Share to Models, Statistical

Share to Vibrio cholerae

Source

Identifiers

PMID: 19209724
DOI: 10.1142/9789812836939_0046

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026. Prepared record publication-19209724-2026-09-02.2. 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 disease-related pathways using a probabilistic epistasis model.PMID 19209724Read ↗

A statistical-based method for the construction and analysis of gene network: application to bacteriaSemantic proximity Read ↗

Learning epistatic gene interactions from perturbation screensSemantic proximity Read ↗

A fast lasso-based method for inferring higher-order interactions.Semantic proximity Read ↗

Inferring subnetworks from perturbed expression profiles.Semantic proximity Read ↗

Nested effects models for high-dimensional phenotyping screens.Semantic proximity Read ↗

Evolution of the complex transcription network controlling biofilm formation in Candida speciesSemantic proximity Read ↗

A comprehensive co-expression network analysis in <i>Vibrio cholerae</i>Semantic proximity Read ↗

Systematic identification of novel regulatory interactions controlling biofilm formation in the bacterium Escherichia coli.Semantic proximity Read ↗

Gene network inference by probabilistic scoring of relationships from a factorized model of interactions.Semantic proximity Read ↗

Interpreting roles of mutations associated with the emergence of <i>S. aureus</i> USA300 strains using transcriptional regulatory network reconstructionSemantic proximity Read ↗

Derivation of genetic interaction networks from quantitative phenotype data.Semantic proximity Read ↗

Host factor prioritization for pan-viral genetic perturbation screens using random intercept models and network propagationSemantic proximity Read ↗

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