Search

Efficient (linear time) algorithms are described for identifying global molecular sequence features allowing for errors including repeats, matches between sequences, dyad symmetry pairings, and other sequence patterns. A multiple sequence alignment algorithm is also described. Specific applications are given to hepatitis B viruses and the J5-C (J, joining; C, constant) region of the immunoglobulin kappa gene.

Four categories of data representations are used to help interpret structures and similarities of nucleic acid and protein sequences. Statistical significance of the observed relationships revealed by these representations are assessed by a hierarchy of permutation procedures and by comparisons with theoretical random models. Applications are presented for various DNA sequences including papovaviruses, Epstein-Barr virus, mitochondrial genomes, and several globin and immunoglobulin genes.

Efficient algorithms are described for identifying local molecular sequence features including repeats, dyad symmetry pairings and aligned matches between sequences, while allowing for errors. Specific applications are given to the genomic sequences of the Epstein-Barr virus, Varicella-Zoster virus and the bacteriophages lambda and T7.

Concepts and methods [Karlin, S. & Ghandour, G. (1985) Proc. Natl. Acad. Sci. USA 82, 5800-5804] for the analysis of patterns and relationships are extended to multiple DNA and protein sequences. Functionals include multiple sequence common word occurrence distributions, characterizations of high frequency shared words, and ascertainment of long block identities. Various comparisons of sequences using natural alphabets obtained from grouping nucleotides or amino acids by their chemical and functional characteristics are described. Specific applications are given to globin genes, mitochondrial genomes, and a variety of mammalian viruses.