Ontologies and Machine Learning Systems

Abstract

In this chapter we review the uses of ontologies within bioinformatics and neuroinformatics and the various attempts to combine machine learning (ML) and ontologies, and the uses of data mining ontologies. This is a diverse field and there is enormous potential for wider use of ontologies in bioinformatics and neuroinformatics research and system development. A systems biology approach comprising of experimental and computational research using biological, medical, and clinical data is needed to understand complex biological processes and help scientists draw meaningful inferences and to answer questions scientists have not even attempted so far.

Abbreviations

BFO

basic formal ontology

BGO

brain-gene ontology

CDO

chronic disease ontology

DM

data mining

DNA

deoxyribonucleic acid

ECOS

evolving connectionist system

GO

gene ontology

GRN

gene regulatory network

IDA

intelligent discovery assistant

KDD

knowledge discovery in databases

KDDONTO

knowledge discovery in databases ontology

ML

machine learning

OBI

ontology of biomedical investigation

OBO

open biology ontology

OWL

ontology web language

RO

relations ontology

WEKA

Waikato environment for knowledge analysis

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Copyright information

© Springer-Verlag 2014

Authors and Affiliations

  1. 1.Computing and Mathematical SciencesAuckland University of TechnologyAucklandNew Zealand
  2. 2.Department of Computing and Mathematical SciencesAuckland University of TechnologyAucklandNew Zealand
  3. 3.KEDRI – Knowledge Engineering and Discovery Research InstituteAuckland University of TechnologyAucklandNew Zealand

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