Conclusions
This chapter illustrates the usefulness of time-frequency signal processing for the analysis of protein sequence data. Time-frequency representations such as the Wigner-Ville distribution, when appropriately filtered for interference terms, provide frequency as well as spatial information and lead to the ability to identify biologically active sites of certain proteins. However, as illustrated in the homeodomain example, not all mappings are capable of correlating to biological properties. The selection of the numerical mapping is problem-specific since different mappings may highlight different structural properties of proteins which are directly related to a particular protein’s function.
GenomeNet3, a Japanese network of database and computational services for genome research, currently maintains a database of over 400 different numerical mappings of amino acids (Kawashima, 1999). Work is underway to extend the methods described in this chapter, and involves the applicability of these different numerical indices based on the protein family being analyzed.
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Bloch, K.M., Arce, G.R. (2003). Analyzing Protein Sequences Using Signal Analysis Techniques. In: Zhang, W., Shmulevich, I. (eds) Computational and Statistical Approaches to Genomics. Springer, Boston, MA. https://doi.org/10.1007/0-306-47825-0_8
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DOI: https://doi.org/10.1007/0-306-47825-0_8
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