Highly conserved regimes of neighbor-base-dependent mutation generated the background primary-structural heterogeneities along vertebrate chromosomes.

The content of guanine+cytosine varies markedly along the chromosomes of homeotherms and great effort has been devoted to studying this heterogeneity and its biological implications. Already before the DNA-sequencing era, however, it was established that the dinucleotides in the DNA of mammals in particular, and of most organisms in general, show striking over- and under-representations that cannot be explained by the base composition. Here we show that in the coding regions of vertebrates both GC content and codon occurrences are strongly correlated with such "motif preferences" even though we quantify the latter using an index that is not affected by the base composition, codon usage, and protein-sequence encoding.

Topical application of laminin-332 to diabetic mouse wounds.

Background: Keratinocyte migration is essential for wound healing and diabetic wound keratinocytes migrate poorly. Keratinocyte migration and anchorage appears to be mediated by laminin-332 (LM-332). Impaired diabetic wound healing may be due to defective LM-332 mediated keratinocyte migration.

Mammalian mutation pressure, synonymous codon choice, and mRNA degradation.

The usage of synonymous codons (SCs) in mammalian genes is highly correlated with local base composition and is therefore thought to be determined by mutation pressure. The usage is nonetheless structured. For instance, mammals share with Saccharomyces and Drosophila most preferences for the C-ending over the G-ending codon (or vice versa) within each fourfold-degenerate SC family and the fact that their SCs are placed along coding regions in ways that minimize the number of T|A and C|G dinucleotides ("|" being the codon boundary).

When being "most likely" is not enough: examining the performance of three uses of the parametric bootstrap in phylogenetics.

I show that three parametric-bootstrap (PB) applications that have been proposed for phylogenetic analysis, can be misleading as currently implemented. First, I show that simulating a topology estimated from preliminary data in order to determine the sequence length that should allow the best tree obtained from more extensive data to be correct with a desired probability, delivers an accurate estimate of this length only in topological situations in which most preliminary trees are expected to be both correct and statistically significant, i.e.