8,101 research outputs found
Maximum likelihood estimates of pairwise rearrangement distances
Accurate estimation of evolutionary distances between taxa is important for
many phylogenetic reconstruction methods. In the case of bacteria, distances
can be estimated using a range of different evolutionary models, from single
nucleotide polymorphisms to large-scale genome rearrangements. In the case of
sequence evolution models (such as the Jukes-Cantor model and associated
metric) have been used to correct pairwise distances. Similar correction
methods for genome rearrangement processes are required to improve inference.
Current attempts at correction fall into 3 categories: Empirical computational
studies, Bayesian/MCMC approaches, and combinatorial approaches. Here we
introduce a maximum likelihood estimator for the inversion distance between a
pair of genomes, using the group-theoretic approach to modelling inversions
introduced recently. This MLE functions as a corrected distance: in particular,
we show that because of the way sequences of inversions interact with each
other, it is quite possible for minimal distance and MLE distance to
differently order the distances of two genomes from a third. This has obvious
implications for the use of minimal distance in phylogeny reconstruction. The
work also tackles the above problem allowing free rotation of the genome.
Generally a frame of reference is locked, and all computation made accordingly.
This work incorporates the action of the dihedral group so that distance
estimates are free from any a priori frame of reference.Comment: 21 pages, 7 figures. To appear in the Journal of Theoretical Biolog
Problem-orientable numerical algorithm for modelling multi-dimensional radiative MHD flows in astrophysics -- the hierarchical solution scenario
We present a hierarchical approach for enhancing the robustness of numerical
solvers for modelling radiative MHD flows in multi-dimensions. This approach is
based on clustering the entries of the global Jacobian in a hierarchical manner
that enables employing a variety of solution procedures ranging from a purely
explicit time-stepping up to fully implicit schemes. A gradual coupling of the
radiative MHD equation with the radiative transfer equation in higher
dimensions is possible. Using this approach, it is possible to follow the
evolution of strongly time-dependent flows with low/high accuracies and with
efficiency comparable to explicit methods, as well as searching
quasi-stationary solutions for highly viscous flows. In particular, it is shown
that the hierarchical approach is capable of modelling the formation of jets in
active galactic nuclei and reproduce the corresponding spectral energy
distribution with a reasonable accuracy.Comment: 28 pages, 9 figure
The role of concurrency in an evolutionary view of programming abstractions
In this paper we examine how concurrency has been embodied in mainstream
programming languages. In particular, we rely on the evolutionary talking
borrowed from biology to discuss major historical landmarks and crucial
concepts that shaped the development of programming languages. We examine the
general development process, occasionally deepening into some language, trying
to uncover evolutionary lineages related to specific programming traits. We
mainly focus on concurrency, discussing the different abstraction levels
involved in present-day concurrent programming and emphasizing the fact that
they correspond to different levels of explanation. We then comment on the role
of theoretical research on the quest for suitable programming abstractions,
recalling the importance of changing the working framework and the way of
looking every so often. This paper is not meant to be a survey of modern
mainstream programming languages: it would be very incomplete in that sense. It
aims instead at pointing out a number of remarks and connect them under an
evolutionary perspective, in order to grasp a unifying, but not simplistic,
view of the programming languages development process
Distance-Based Genome Rearrangement Phylogeny
Evolution operates on whole genomes through direct rearrangements of genes, such as inversions, transpositions, and inverted transpositions, as well as through operations, such as duplications, losses, and transfers, that also affect the gene content of the genomes. Because these events are rare relative to nucleotide substitutions, gene order data offer the possibility of resolving ancient branches in the tree of life; the combination of gene order data with sequence data also has the potential to provide more robust phylogenetic reconstructions, since each can elucidate evolution at different time scales. Distance corrections greatly improve the accuracy of phylogeny reconstructions from DNA sequences, enabling distance-based methods to approach the accuracy of the more elaborate methods based on parsimony or likelihood at a fraction of the computational cost. This paper focuses on developing distance correction methods for phylogeny reconstruction from whole genomes. The main question we investigate is how to estimate evolutionary histories from whole genomes with equal gene content, and we present a technique, the empirically derived estimator (EDE), that we have developed for this purpose. We study the use of EDE on whole genomes with identical gene content, and we explore the accuracy of phylogenies inferred using EDE with the neighbor joining and minimum evolution methods under a wide range of model conditions. Our study shows that tree reconstruction under these two methods is much more accurate when based on EDE distances than when based on other distances previously suggested for whole genomes
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