2004/04/07 by Matthew J. Berryman, Berryman, Matthew J., Andrew Allison +3
Biochemistry, Genetics and Molecular Biology · #FOS: Biological sciences #Fractal and DNA sequence analysis #Genomics and Phylogenetic Studies #Machine Learning in Bioinformatics #Populations and Evolution (q-bio.PE) #q-bio.PE
paper · pdf · doi:10.48550/arxiv.q-bio/0404010
8 pages, 3 figures
arxiv created 2004/04/07 · openalex publication_date 2004/04/07 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper examines two methods for finding whether long-range correlations exist in DNA: a fractal measure and a mutual information technique. We evaluate the performance and implications of these methods in detail. In particular we explore their use comparing DNA sequences from a variety of sources. Using software for performing in silico mutations, we also consider evolutionary events leading to long range correlations and analyse these correlations using the techniques presented. Comparisons are made between these virtual sequences, randomly generated sequences, and real sequences. We also explore correlations in chromosomes from different species.