Authors: Atulya K. Nagar, Dilbag Sokhi
Addresses: Intelligent and Distributed Systems Laboratory, Deanery of Business and Computer Sciences, Liverpool Hope University, Hope Park, Liverpool L16 9JD, UK. ' Intelligent and Distributed Systems Laboratory, Deanery of Business and Computer Sciences, Liverpool Hope University, Hope Park, Liverpool L16 9JD, UK
Abstract: Recent past has seen an exponential growth in DNA sequence data, which is being made publicly accessible. This has contributed towards enormous effort in understanding the concealed information within DNA sequences. Various heuristic techniques of sequence analysis have given significant results, but as the sequence length increases, these techniques are found to be inefficient, leaving scope for intelligent techniques that can adapt to the variable length of the coding and non-coding sequences. In this paper, we introduce an intrinsic and an intelligent technique of wavelet analysis that has the ability to adapt itself according to the variable length of the coding and non-coding sequences while giving a comprehensive picture of the patterns present within the DNA sequences. These patterns can be compared between the similar genes in different species and can be used for understanding and mapping the process of evolution. We perform the wavelet analysis of nucleotide sequences from different species and report some significant facts about the phylogenetic relationships between the species that are considered to be unrelated. Application of the developed approach provides evidence towards the theory of conservation of genes during the process of evolution.
Keywords: coding sequences; non-coding sequences; DNA sequences; DNA analysis; Haar wavelet transform; intron–exon; phylogeny; gene comparison; pattern recognition; nucleotide sequences; gene conservation; evolution.
International Journal of Intelligent Systems Technologies and Applications, 2008 Vol.5 No.1/2, pp.104 - 114
Published online: 05 May 2008 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article