A method for gene identification by dynamic feature choosing

Abstract

With growth of sequenced genome, a number of algorithms for gene identification were created. These algorithms use fixed gene features which are chosen based on observation or experience. These features may not be major features of a genome. In this paper, we illustrate several candidate features and propose a dynamic feature choosing algorithm to determine the major features. We describe nucleotide sequence by feature vector and use Discriminant analysis to them to make decision on coding/non-coding. To test the algorithm, we apply the algorithm to the S.cerevisiae genome and achieve accuracy of above 98%. © Springer-Verlag Berlin Heidelberg 2007.