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Briefings in Bioinformatics Advance Access originally published online on May 5, 2008
Briefings in Bioinformatics 2008 9(4):307-316; doi:10.1093/bib/bbn021
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© The Author 2008. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

Computational intelligence approaches for pattern discovery in biological systems

Gary B. Fogel

Corresponding author. Gary B. Fogel, Natural Selection, Inc., 9330 Scranton Rd., Suite 150, San Diego, CA 92121, USA. Tel: 858 455 6449; Fax: 858 455 1560; E-mail: gfogel{at}natural-selection.com

Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a commentary about the anticipated impact of these approaches in bioinformatics.

Keywords: computational intelligence, artificial neural networks, fuzzy logic, evolutionary computation, machine learning, bioinformatics

Submitted: January 21, 2008. Received (in revised form): March 29, 2008.


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