Combined DNA and protein alignment.
Explore the source record for details and available documents.
Algorithms↗
Biomedical subjects
J Støvlbaek
Publications and source records attributed to J Støvlbaek.
A maximum-likelihood approach to analyzing nonoverlapping and overlapping reading frames.
A model is presented for sequence evolution on the basis of which one can analyze combinations of noncoding, singly coding, and multiply coding regions of aligned homologous DNA sequences. It is a generalization of Kimura's (J. Mol. Evol. 16:111-120, 1980) and Li et al.'s (J. Mol. Evol. 36:96-99, 1985) transition-transversion models with selection on replacement substitutions. Based on a hierarchy of hypotheses, one will be able to estimate selection factors and transition and transversion distances for different combinations of regions ranging from many regions, each with their private set of parameters, to one set of parameters for all regions. The method is demonstrated on two aligned HIV1 retroviruses.
Amino Acid Sequence↗
Genomic alignment.
As sequencing techniques become increasingly efficient, the average length of a sequence is bound to grow. Traditional sequence-comparison algorithms can either compare DNA or protein, but not a mixture, which is actually a common situation. Most obtained DNA sequences contain coding regions, and it is more reliable to compare the coding regions as protein than just as DNA. A heuristic algorithm is presented that can compare DNA with both coding and noncoding regions, but that also can compare multiple reading frames and determine which exons are homologous. A program, GenA1 (Genomic Alignment), was developed that implements the algorithm. Its use is demonstrated on two retroviruses.
Algorithms↗