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Computational methods for the analysis of differential conservation in groups of similar DNA sequences.

Authors: Stojanovic, Nikola;

Computational methods for the analysis of differential conservation in groups of similar DNA sequences.

Abstract

Multiple sequence alignments are a powerful tool for identifying the regions of DNA which have been constrained in evolutionary divergence, presumably due to their functional role. However, such constraints rarely manifest themselves as perfect conservation of a site clearly standing out in its broader environment, as they reflect the species-specific differences in proteins, as well as the ability of some proteins to interact with multiple variants of their binding sequence. In this paper we explore the use of alignment column uncertainty as an aid in locating differential phylogenetic footprints, which refer to the sites in DNA where groups of related species exhibit sequence conservation, but where the pattern may vary between the groups. We use efficient, linear-time algorithms to locate such sites. We have performed a study of the mammalian CAV2-CAV1 gene region using our software, and we conclude with several observations concerning the differential conservation and the use of computational methods for its detection. The software developed for this project is available, free of charge, by contacting the author.

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Keywords

phylogenetic footprints, Caveolin 2, Caveolin 1, Computational Biology, Evolution, Molecular, Animals, Humans, differential phylogenetic footprints, Sequence Alignment, Conserved Sequence, Software, multiple alignments

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average