Although the principal theory of molecular phylogenetics is based on the neutral theory of molecular evolution [ 21], convergent evolution is known to occur at the molecular level and can mislead the reconstruction of phylogenetic trees [ 22, 23].
However, viral evolution is known to proceed at a breakneck pace due to the unique features of viral genetics and viral population dynamics (Moya et al. 2004; Domingo et al. 2008).
Since class I evolution is known to be highly erratic, large taxonomic gaps in MHC characterization prevent the examination of the events and processes which have led to class I diversification.
The rate of molecular evolution is known to vary in three predominant ways (changes in: mutation rate, population size, and selection coefficients; [1]), but in practice, the specific causes of rate variation are difficult to isolate [2], [3].
Rates of molecular evolution are known to vary across taxa and among genes, and this requires rate calibration for each specific dataset based on external information.
Dictyostelium discoideum, a microbial model for social evolution, is known to distinguish self from non-self and show genotype-dependent behavior during chimeric development.
Based on previous modeling work (Koelle et al., 2006, 2009, 2010; Zinder et al., 2013), a lower rate of antigenic evolution is known to constrain genetic and antigenic diversity and thus might lead to a spindly HA phylogeny.
The aim of this study is to underline the importance of an early diagnosis by performing a histological examination especially when we are in front of suspected papulonodular lesions arising from a tattoo, followed by a proper treatment, since cutaneous neoplastic evolution is known to be a rare but possible complication.
The aim of this study is to underline the importance of an early diagnosis and proper treatment of tattoo reactions, since cutaneous neoplastic evolution is known to be a rare but possible complication, even if this process was not found in our experience.
With the advent of large-scale genomic data, the role of positive selection in the evolution of protein coding sequences involved in phenotypic evolution is now known to have been underestimated.
