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  •   Open Research
  • AUT Faculties
  • Faculty of Design and Creative Technologies (Te Ara Auaha)
  • School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau
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Ontologies and machine learning systems

Tegginmath, S; Pears, R; Kasabov, N
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hb23-049 with corrections 3 Shoba.pdf (2.294Mb)
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http://hdl.handle.net/10292/6987
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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.
Date
2014
Source
Springer Handbook of Bio-/Neuroinformatics (2014), pp 865-872
Item Type
Chapter in Book
Publisher
Springer
DOI
10.1007/978-3-642-30574-0
Publisher's Version
http://dx.doi.org/10.1007/978-3-642-30574-0_49
Rights Statement
An author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at www.springerlink.com”. (Please also see Publisher’s Version and Citation).

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