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This paper presents a brief survey of computational approaches to the DNA sequence analysis. The basic biological background is presented. The various types of algorithms for pattern construction and gene finding are presented with special attention paid to the application of global optimization methods.
Two models for global optimization are considered: statistical model, and radial basis functions. The equivalence of both models in the case of optimization without noise is discussed. Both models are also evaluated with respect to global optimization in the presence of noise by means of experimental testing where approximation errors of passive one dimensional algorithm are estimated.
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