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Bioinformatics Vol. 19 no. 1 2003
Pages 2-9
© 2003 Oxford University Press
Review |
Wavelets in bioinformatics and computational biology: state of art and perspectives
Department of Zoology, University of Cambridge,
Cambridge, UK
European Bioinformatics Institute, Wellcome Trust Genome Campus,
Hinxton, Cambs, UK
Received on October 17, 2002
; revised on May 21, 2002 and July 7, 2002
; accepted on July 7, 2002
Motivation: At a recent meeting
, the
wavelet transform was depicted as a small child kicking back at
its father, the Fourier transform. Wavelets are more efficient
and faster than Fourier methods in capturing the essence of
data. Nowadays there is a growing interest in using wavelets in
the analysis of biological sequences and molecular
biology-related signals.
Results: This review is intended to summarize the potential of state of the art wavelets, and in particular wavelet statistical methodology, in different areas of molecular biology: genome sequence, protein structure and microarray data analysis. I conclude by discussing the use of wavelets in modeling biological structures.
Contact: plio{at}hgmp.mrc.ac.uk
XIX SMC 2001 ‘Wavelets in Statistics’, Vico Equense, Naples, I, 2–7
April 2001.
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