Classification of selectively constrained DNA elements using feature vectors and rule-based classifiers

Scarce work has been done in the analysis of the composition of conserved non-coding elements (CNEs) that are identified by comparisons of two or more genomes and are found to exist in all metazoan genomes.Here we present the analysis of CNEs with a methodology that takes into account word occurrence at various lengths scales in the form of feature vector representation and rule based classifiers. We implement our approach on both protein-coding exons and CNEs, originating from human, insect ( Drosophila melanogaster) and worm (Caenorhabditis elegans) genomes, that are either identified in the present study or obtained from the literature.Alignment free feature vector representation of sequences combined with rule-based classification methods leads to successful classification of the different CNEs classes. Biologically meaningful results are derived by comparison with the genomic signatures approach, and classification rates for a variety of functional elements of the genomes along with surrogates are presented. © 2014 Elsevier Inc.