Integration of Hybrid Bio-Ontologies using Bayesian Networks for Knowledge Discovery

McGarry, Kenneth, Garfield, Sheila, Morris, Nick and Wermter, Stefan (2007) Integration of Hybrid Bio-Ontologies using Bayesian Networks for Knowledge Discovery. In: Third International Workshop on Neural-Symbolic Learning and Reasoning, 6-12 January 2007, Hyderabad, India.

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Abstract

This paper describes how high level biological
knowledge obtained from ontologies such as the
Gene Ontology (GO) can be integrated with low
level information extracted from a Bayesian net-
work trained on protein interaction data. We can
automatically generate a biological ontology by text mining the type II diabetes research literature. The ontology is populated with the entities and
relationships from protein-to-protein interactions.
New, previously unrelated information is extracted
from the growing body of research literature and in-
corporated with knowledge already known on this subject from the gene ontology and databases such as BIND and BioGRID. We integrate the ontology within the probabilistic framework of Bayesian networks which enables reasoning and prediction of protein function.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computing > Artificial Intelligence
Computing
Divisions: Faculty of Applied Sciences > Department of Computing Engineering and Technology
Depositing User: Sheila Garfield
Date Deposited: 09 Oct 2015 14:17
Last Modified: 09 Oct 2015 14:17
URI: http://sure.sunderland.ac.uk/id/eprint/5769

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