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

Detecting disease genes based on semi-supervised learning and protein-protein interaction networks.

Artificial intelligence in medicine - 1 Jan 2012

Nguyen Thanh-Phuong, Ho Tu-Bao

Abstract excerpt

OBJECTIVE: Predicting or prioritizing the human genes that cause disease, or "disease genes", is one of the emerging tasks in biomedicine informatics. Research on network-based approach to this problem is carried out upon the key assumption of "the network-neighbour of a disease gene is likely to cause the same or a similar disease", and mostly employs data regarding well-known disease genes, using supervised...

Read the complete abstract on PubMed

Topics

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

Share to Artificial Intelligence
Share to Databases, Nucleic Acid
Share to Databases, Protein

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Disease

Share to Protein Interaction Mapping

Share to Protein Interaction Maps

Share to Proteomics

Share to Sensitivity and Specificity

Source

Identifiers

PMID: 22000346
DOI: 10.1016/j.artmed.2011.09.003

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

Detecting disease genes based on semi-supervised learning and protein-protein interaction networks.PMID 22000346Read ↗

Network-based prediction and knowledge mining of disease genes.Semantic proximity Read ↗

Integration of Biological Data via NMF for Identification of Human Disease-Associated Gene Modules through Multi-label ClassificationSemantic proximity Read ↗

Disease genes prediction by HMM based PU-learning using gene expression profiles.Semantic proximity Read ↗

Predicting disease-related genes using integrated biomedical networks.Semantic proximity Read ↗

Protein Interaction Network-based Deep Learning Framework for Identifying Disease-Associated Human ProteinsSemantic proximity Read ↗

Integration of Human Protein Sequence and Protein-Protein Interaction Data by Graph Autoencoder to Identify Novel Protein-Abnormal Phenotype Associations.Semantic proximity Read ↗

A computational method based on the integration of heterogeneous networks for predicting disease-gene associations.Semantic proximity Read ↗

Integration of biological data via NMF for identification of human disease-associated gene modules through multi-label classification.Semantic proximity Read ↗

DGHNE: network enhancement-based method in identifying disease-causing genes through a heterogeneous biomedical network.Semantic proximity Read ↗

Network-based characterization of disease-disease relationships in terms of drugs and therapeutic targets.Semantic proximity Read ↗

Biomedical data, computational methods and tools for evaluating disease-disease associations.Semantic proximity Read ↗

Discovering disease-genes by topological features in human protein-protein interaction network.Semantic proximity Read ↗

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