Wavelets in bioinformatics and computational biology: state of art and perspectives

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Abstract
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@hgmp.mrc.ac.uk † XIX SMC 2001 ‘Wavelets in Statistics’, Vico Equense, Naples, I, 2–7 April 2001.

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