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lüll Wavelets in bioinformatics and computational biology: state of art and perspectives Lio PBioinformatics 2003[Jan]; 19 (1): 2-9MOTIVATION: 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.|*Algorithms[MESH]|*Models, Biological[MESH]|*Models, Statistical[MESH]|*Signal Processing, Computer-Assisted[MESH]|Computational Biology/methods/*trends[MESH]|Computer Simulation[MESH]|Oligonucleotide Array Sequence Analysis/methods[MESH]|Pattern Recognition, Automated[MESH]|Proteins/chemistry[MESH]|Sequence Analysis, DNA/methods[MESH]|Stochastic Processes[MESH] |