PROJECT TITLE :

Extracting Cross-Ontology Weighted Association Rules from Gene Ontology Annotations

ABSTRACT:

Gene Ontology (GO) may be a structured repository of concepts (GO Terms) that are associated to at least one or additional gene products through a method called annotation. The analysis of annotated information is an important opportunity for bioinformatics. There are completely different approaches of analysis, among those, the use of association rules (AR) which provides useful data, discovering biologically relevant associations between terms of GO, not previously known. In a very previous work, we tend to introduced GO-WAR (Gene Ontology-primarily based Weighted Association Rules), a technique for extracting weighted association rules from ontology-based mostly annotated datasets. We have a tendency to here adapt the GO-WAR algorithm to mine cross-ontology association rules, i.e., rules that involve GO terms gift in the 3 sub-ontologies of GO. We conduct a deep performance analysis of GO-WAR by mining publicly accessible GO annotated datasets, showing how GO-WAR outperforms current cutting-edge approaches.