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

Gene2DisCo: Gene to disease using disease commonalities.

Artificial intelligence in medicine - 1 Oct 2017

Frasca Marco

Abstract excerpt

OBJECTIVE: Finding the human genes co-causing complex diseases, also known as "disease-genes", is one of the emerging and challenging tasks in biomedicine. This process, termed gene prioritization (GP), is characterized by a scarcity of known disease-genes for most diseases, and by a vast amount of heterogeneous data, usually encoded into networks describing different types of functional relationships between...

Read the complete abstract on PubMed

Topics

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

Share to Area Under Curve
Share to Data Mining
Share to Databases, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Gene Regulatory Networks

Share to Linear Models

Share to Machine Learning

Share to ROC Curve

Share to Toxicogenetics

Source

Identifiers

PMID: 28882544
DOI: 10.1016/j.artmed.2017.08.001

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

Gene2DisCo: Gene to disease using disease commonalities.PMID 28882544Read ↗

A Comprehensive Evaluation of Disease Phenotype Networks for Gene Prioritization.Semantic proximity Read ↗

DisGeneFormer: Precise Disease Gene Prioritization by Integrating Local and Global Graph AttentionSemantic proximity Read ↗

Phen2Disease: a phenotype-driven model for disease and gene prioritization by bidirectional maximum matching semantic similarities.Semantic proximity Read ↗

pBRIT: gene prioritization by correlating functional and phenotypic annotations through integrative data fusion.Semantic proximity Read ↗

Phen2Gene: Rapid Phenotype-Driven Gene Prioritization for Rare DiseasesSemantic proximity Read ↗

Phenotype-driven gene prioritization for rare diseases using graph convolution on heterogeneous networks.Semantic proximity Read ↗

Phen2Disease: A Phenotype-driven Semantic Similarity-based Integrated Model for Disease and Gene PrioritizationSemantic proximity Read ↗

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypesSemantic proximity Read ↗

Evaluating the Influence of Disease-Gene Associations in the Significance of Disease Modules through the lens of Network MedicineSemantic proximity Read ↗

Integration of multi-source gene interaction networks and omics data with graph attention networks to identify novel disease genesSemantic proximity Read ↗

A heterogeneous graph neural network for candidate gene prediction in endometriosis.Semantic proximity Read ↗

Prioritizing complex disease risk genes by integrating multiple data.Semantic proximity Read ↗

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