DNA : Next Target
A competitive and efficive mathematical tool, wavelets have now an important role to play in ongoing scientific and technical progress. When applied to biology, they offer new ways of exploring DNA. Samuel Nicolay co-authored two important papers examining this nascent application, and the first results have been very promising. Wavelets were first applied to the fields of astrophysics, climatology, geography, medicine, and finance. Their main functions were signal processing, detection of singularity, and noise reduction. Wavelets constitute a mathematical microscope capable of decomposing any complex signal into a series of filtered signals, somewhat like different notes come together to compose a melody. The complex signal is observed through several "magnifications", each of which records the signal with its own level of precision and noise. When this process is complete, the continuous wavelet transform unwinds all one-dimensional signals into a two-dimensional space, i.e., their position and their enlargement. The idea is to introduce a certain degree of redundancy in data, which will hopefully yield new information.  In addition to 1D signals, wavelets may also be applied to 2D images, where they have already radically transformed the world of image compression by opening the way for the creation of the JPEG 2000 program. The concept here is to replace an image taking up a great deal of disk space with a series of different antialiased images which can be recombined afterwards. Storing these antialiased images requires much less space than the original one. Wavelets are also an ideal tool for detecting borders, analizing turbulence and studying share prices in the stock market. Samuel Nicolay, a mathematician at the University of Liège, is examining their application to biology, in particular to the study of DNA sequences in living organisms. |
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