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• W2156875887 abstract "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.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." @default.
• W2156875887 created "2016-06-24" @default.
• W2156875887 creator A5056748708 @default.
• W2156875887 date "2003-01-01" @default.
• W2156875887 modified "2023-10-13" @default.
• W2156875887 title "Wavelets in bioinformatics and computational biology: state of art and perspectives" @default.
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• W2156875887 doi "https://doi.org/10.1093/bioinformatics/19.1.2" @default.
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