A Survey of Combinatorial Methods for Phylogenetic Networks

The evolutionary history of a set of species is usually described by a rooted phylogenetic tree. Although it is generally undisputed that bifurcating speciation events and descent with modifications are major forces of evolution, there is a growing belief that reticulate events also have a role to play. Phylogenetic networks provide an alternative to phylogenetic trees and may be more suitable for data sets where evolution involves significant amounts of reticulate events, such as hybridization, horizontal gene transfer, or recombination. In this article, we give an introduction to the topic of phylogenetic networks, very briefly describing the fundamental concepts and summarizing some of the most important combinatorial methods that are available for their computation

A Sensitivity Study of the Enceladus Torus

We have developed a homogeneous model of physical chemistry to investigate the neutral-dominated, water-based Enceladus torus. Electrons are treated as the summation of two isotropic Maxwellian distributions$-$a thermal component and a hot component. The effects of electron impact, electron recombination, charge exchange, and photochemistry are included. The mass source is neutral H$_2$O, and a rigidly-corotating magnetosphere introduces energy via pickup of freshly-ionized neutrals. A small fraction of energy is also input by Coulomb collisions with a small population ($<$ 1%) of supra-thermal electrons. Mass and energy are lost due to radial diffusion, escaping fast neutrals produced by charge exchange and recombination, and a small amount of radiative cooling. We explore a constrained parameter space spanned by water source rate, ion radial diffusion, hot-electron temperature, and hot-electron density. The key findings are: (1) radial transport must take longer than 12 days; (2) water is input at a rate of 100--180 kg s$^{-1}$; (3) hot electrons have energies between 100 and 250 eV; (4) neutrals dominate ions by a ratio of 40:1 and continue to dominate even when thermal electrons have temperatures as high as $\approx$ 5 eV; (5) hot electrons do not exceed 1% of the total electron population within the torus; (6) if hot electrons alone drive the observed longitudinal variation in thermal electron density, then they also drive a significant variation in ion composition.Comment: 9 pages text, 3 tables, 9 figure

Computing galled networks from real data

Motivation: Developing methods for computing phylogenetic networks from biological data is an important problem posed by molecular evolution and much work is currently being undertaken in this area. Although promising approaches exist, there are no tools available that biologists could easily and routinely use to compute rooted phylogenetic networks on real datasets containing tens or hundreds of taxa. Biologists are interested in clades, i.e. groups of monophyletic taxa, and these are usually represented by clusters in a rooted phylogenetic tree. The problem of computing an optimal rooted phylogenetic network from a set of clusters, is hard, in general. Indeed, even the problem of just determining whether a given network contains a given cluster is hard. Hence, some researchers have focused on topologically restricted classes of networks, such as galled trees and level-k networks, that are more tractable, but have the practical draw-back that a given set of clusters will usually not possess such a representation

Improved Lower Bounds for Constant GC-Content DNA Codes

The design of large libraries of oligonucleotides having constant GC-content and satisfying Hamming distance constraints between oligonucleotides and their Watson-Crick complements is important in reducing hybridization errors in DNA computing, DNA microarray technologies, and molecular bar coding. Various techniques have been studied for the construction of such oligonucleotide libraries, ranging from algorithmic constructions via stochastic local search to theoretical constructions via coding theory. We introduce a new stochastic local search method which yields improvements up to more than one third of the benchmark lower bounds of Gaborit and King (2005) for n-mer oligonucleotide libraries when n <= 14. We also found several optimal libraries by computing maximum cliques on certain graphs.Comment: 4 page

High-resolution genetic mapping with pooled sequencing

Background: Modern genetics has been transformed by high-throughput sequencing. New experimental designs in model organisms involve analyzing many individuals, pooled and sequenced in groups for increased efficiency. However, the uncertainty from pooling and the challenge of noisy sequencing data demand advanced computational methods. Results: We present MULTIPOOL, a computational method for genetic mapping in model organism crosses that are analyzed by pooled genotyping. Unlike other methods for the analysis of pooled sequence data, we simultaneously consider information from all linked chromosomal markers when estimating the location of a causal variant. Our use of informative sequencing reads is formulated as a discrete dynamic Bayesian network, which we extend with a continuous approximation that allows for rapid inference without a dependence on the pool size. MULTIPOOL generalizes to include biological replicates and case-only or case-control designs for binary and quantitative traits. Conclusions: Our increased information sharing and principled inclusion of relevant error sources improve resolution and accuracy when compared to existing methods, localizing associations to single genes in several cases. MULTIPOOL is freely available at http://cgs.csail.mit.edu/multipool/ webcite.National Science Foundation (U.S.) (Graduate Research Fellowship Grant 0645960