OntoFing Net (Ontology Fingerprint derived Network)

What is OntoFing Network?

OntoFing Network is a novel, whole genome yeast gene network based on the Ontology Fingerprint--a set of Gene Ontology terms that are overrepresented among the PubMed abstracts discussing a gene or biological concept together with the terms. enrichment p-value [1]. Unlike networks based on protein-protein interaction that rely on one kind of biological relationship (i.e. protein-protein interaction), OntoFing network summarizes all kinds of biological relationship embedded in biomedical literature and Gene Ontology. As an undirected, weighted graph, OntoFing Network quantitatively integrates Gene Ontology and literature information to predict functional associations among genes as well as between genes and pathways. The database currently covers 5446 yeast genes and 109 yeast KEGG pathways.



What does OntoFing Network do?

• Retrieve subnetworks containing the query genes to identify gene-gene associations within the OntoFing network. In the subnetworks, genes are connected by edges weighted by the Similarity Score that measures the functional relevance between query gene pairs.
• Search for query gene-pathway association between query genes and yeast KEGG pathways; the overall functional relevance between a query gene and the pathway is measured by the Total Score.
• Search for novel candidate genes that may be functionally related to the query gene set; the overall functional relevance between a candidate gene and the query gene set is measured by the Total Score.
• Search for candidate genes that are functionally related to the query yeast KEGG pathways, i.e. genes that may modulate the query KEGG pathways; the functional relevance of the candidate genes to the pathway is measured by the Total Score. In addition, pathway name filtering allows identifying novel candidate genes whose linked PubMed abstracts contain no query KEGG pathway names

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Reference
1. Tsoi, L.C., et al., Evaluation of genome-wide association study results through development of ontology fingerprints. Bioinformatics, 2009. 25(10): p. 1314-20.