Hidden Markov Models for Unaligned DNA Sequence Comparison
2005 (English)In: WSEAS Transactions on Biology and Biomedicine, Vol. 2, 64-69 p.Article in journal (Refereed) PublishedText
Comparison of similarity between sequences can provide information for inferring the function of a newly discovered sequence, and understanding the evolutionary relationships among genes, proteins, and entire species. This paper presents a technique for computing the similarity between unaligned DNA sequences. The computation is based on the Kullback-Leibler divergence of hidden Markov models. We used the data sets taken from the threonine operons of Escherichia coli K-12 and Shigella flexneri to test the proposed method. The result obtained agrees with an alignment-based method. We further tested the proposed method with a data set of 34 complete mammalian mtDNA genomes. The phylogenetic tree derived from the second experiment shows reasonable evolutionary relationships between these species.
Place, publisher, year, edition, pages
2005. Vol. 2, 64-69 p.
Sequence comparison, Hidden Markov models, Kullback-Leibler divergence.
Bioinformatics and Systems Biology
IdentifiersURN: urn:nbn:se:liu:diva-125057OAI: oai:DiVA.org:liu-125057DiVA: diva2:902700