Computational identification of ultra-conserved elements in the human genome: a hypothesis on homologous DNA pairing.

ABSTRACT: Thousands of prolonged sequences of human ultra-conserved non-coding elements (UCNEs) share only one common feature: peculiarities in the unique composition of their dinucleotides. Here we investigate whether the numerous weak signals emanating from these dinucleotide arrangements can be used for computational identification of UCNEs within the human genome. For this purpose, we analyzed 4272 UCNE sequences, encompassing 1 393 448 nucleotides, alongside equally sized control samples of randomly selected human genomic sequences. Our research identified nine different features of dinucleotide arrangements that enable differentiation of UCNEs from the rest of the genome. We employed these nine features, implementing three Machine Learning techniques - Support Vector Machine, Random Forest, an

SUBMITTER: Crossley ER 

PROVIDER: S-EPMC11217675 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature