Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model

Background The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size.

Journalism at the movies

Welcome to the first of what will be a regular review essay on films about journalism, covering recent releases as well as looking back at established classics and under-rated obscurities. And there is plenty to write about. Since 2008, and the end of the research period which informed my 2010 book on Journalists in Film there has been a steady stream of films in which a journalist is a primary character, and in which the nature and functioning of journalism is a theme. Morning Glory (Roger Michell, 2010), the story of a ‘serious’ news man (Harrison Ford) having to adapt to the infotainment environment of breakfast news, came out early in 2011 in the United Kingdom. The well-received UK indie Monsters (Gareth Edwards, 2010), a sci-fi with a journalist at its heart, was released in 2010. In The Soloist (Joe Wright, 2009) Robert Downey Jr played a feature journalist who befriends a mentally ill street musician and seeks to rescue him through his writing. Stieg Larsson’s Millennium trilogy has produced three Swedish films, all of them focused on the campaigning journalist Mikael Blomkvist. The first of these is being remade by Hollywood as of this writing.

Inexact uniformization method for computing transient distributions of Markov chains

The uniformization method (also known as randomization) is a numerically stable algorithm for computing transient distributions of a continuous time Markov chain. When the solution is needed after a long run or when the convergence is slow, the uniformization method involves a large number of matrix-vector products. Despite this, the method remains very popular due to its ease of implementation and its reliability in many practical circumstances. Because calculating the matrix-vector product is the most time-consuming part of the method, overall efficiency in solving large-scale problems can be significantly enhanced if the matrix-vector product is made more economical. In this paper, we incorporate a new relaxation strategy into the uniformization method to compute the matrix-vector products only approximately. We analyze the error introduced by these inexact matrix-vector products and discuss strategies for refining the accuracy of the relaxation while reducing the execution cost. Numerical experiments drawn from computer systems and biological systems are given to show that significant computational savings are achieved in practical applications.