A Novel Method of Sequence Similarity Evaluation in N-dimensional Sequence Space

Andrzej      Kasperski; Renata      Kasperska

doi:10.2174/157489312802460749

Abstract

The aim of this work is to establish a universal method of searching for similarities between sequences in an ndimensional sequence space. The presented idea extends out of the original Dot-Matrix and semihomology methods with a possibility of making analyses in an n-dimensional sequence space and indicates the method of similarity evaluation. The main novelty of the implemented dotPicker program is to allow for searches of similarities in an n-dimensional sequence space. Sets of identity fragments, which represent given protein families, have been obtained using this program. The idea of evaluation of the obtained identity fragments is proposed and its utilization is presented. Moreover, the potential of the dotPicker program is shown especially when analyzing and identifying previously unknown similarities in protein families.

Keywords: Genetic semihomology, identity, multiple alignment, protein homology, sequence similarity, variability, N-dimensional Sequence Space, Dot-Matrix, dotPicker program, identity fragments.