Phylogenetic Networks Do not Need to Be Complex: Using Fewer Reticulations to Represent Conflicting Clusters

Phylogenetic trees are widely used to display estimates of how groups of species evolved. Each phylogenetic tree can be seen as a collection of clusters, subgroups of the species that evolved from a common ancestor. When phylogenetic trees are obtained for several data sets (e.g. for different genes), then their clusters are often contradicting. Consequently, the set of all clusters of such a data set cannot be combined into a single phylogenetic tree. Phylogenetic networks are a generalization of phylogenetic trees that can be used to display more complex evolutionary histories, including reticulate events such as hybridizations, recombinations and horizontal gene transfers. Here we present the new CASS algorithm that can combine any set of clusters into a phylogenetic network. We show that the networks constructed by CASS are usually simpler than networks constructed by other available methods. Moreover, we show that CASS is guaranteed to produce a network with at most two reticulations per biconnected component, whenever such a network exists. We have implemented CASS and integrated it in the freely available Dendroscope software

Algorithms for Visualizing Phylogenetic Networks

We study the problem of visualizing phylogenetic networks, which are extensions of the Tree of Life in biology. We use a space filling visualization method, called DAGmaps, in order to obtain clear visualizations using limited space. In this paper, we restrict our attention to galled trees and galled networks and present linear time algorithms for visualizing them as DAGmaps.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

Corporate governance structure and firm performance : empirical evidence from Brusa Malaysia, Kuala Lumper

The issue of corporate governance has been emerging as important phenomena that has been searched extensively both in developed countries due to its strategic impact on the monitoring of management activities and firms&rsquo; performance. Yet little attempt has been made in developing countries like Malaysia to ascertain what constitute corporate governance and its impact on firm\u27s performance. Therefore, this study aims at examining the structure of the corporate governance and its impact on firm&rsquo;s performance. This study is based on 100 firms, which are the component of the Composite Index (CI) serve as market barometer. This study employs cross-sectional annual multiple regression model to examine, what constitutes the corporate governance structure and its impact on performance of the firm. The analysis was based on annual regression over 5 years period from 1997 through 2001. Three different blend of surrogate for corporate governance were developed for good corporate governance structure. These are the independent non-executive (outside) directors, audit committee and remuneration committee. To isolate the size effect from the impact of corporate governance structure on firm&rsquo;s performance, firm&rsquo;s size was also included are variable in the model. The ratio of net income before tax to total asset is used as a surrogate for firm&rsquo;s performance. Evidence from the study indicates that there is partial relation between corporate governance structure and corporate performance. The presence of both audit and remuneration committee serves as an important monitoring device to control management activities that lead to increase firm\u27s performance. While on average, the presence of independent nonexecutive directors does not provide any significant explanation for the firm\u27s performance. However, the firm size appears to have significant impact on corporate performance.<br /

On Three-Dimensional Space Groups

An entirely new and independent enumeration of the crystallographic space groups is given, based on obtaining the groups as fibrations over the plane crystallographic groups, when this is possible. For the 35 ``irreducible'' groups for which it is not, an independent method is used that has the advantage of elucidating their subgroup relationships. Each space group is given a short ``fibrifold name'' which, much like the orbifold names for two-dimensional groups, while being only specified up to isotopy, contains enough information to allow the construction of the group from the name.Comment: 26 pages, 8 figure

An SVAR Analysis of Monetary Policy Dynamics and Housing Market Responses in Australia

This paper examines the impact of monetary policy and a range of sector-specific and macroeconomic shocks on the Australian housing market using quarterly data for a period of 1974-2008. The paper develops a structural vector autoregressive (SVAR) model based on contemporaneous restrictions to analyse the dynamics of these shocks. The results indicate that supply of new houses in Australia rises with higher real house prices; and that house prices rise and fall with higher inflation rate and interest rate, respectively. Dynamics of the impulse responses reveal significant effect of monetary policy on new house constructions, real house prices, material costs and inflation. Results also suggest that housing output, real house prices and interest rates respond significantly to shocks to housing supply, housing demand and to a number of other variables. These results are expected to shed some lights on the current policy environment pertaining to the Australian housing sector.Monetary transmission, Housing market, Structural VAR

Circular Networks from Distorted Metrics

Trees have long been used as a graphical representation of species relationships. However complex evolutionary events, such as genetic reassortments or hybrid speciations which occur commonly in viruses, bacteria and plants, do not fit into this elementary framework. Alternatively, various network representations have been developed. Circular networks are a natural generalization of leaf-labeled trees interpreted as split systems, that is, collections of bipartitions over leaf labels corresponding to current species. Although such networks do not explicitly model specific evolutionary events of interest, their straightforward visualization and fast reconstruction have made them a popular exploratory tool to detect network-like evolution in genetic datasets. Standard reconstruction methods for circular networks, such as Neighbor-Net, rely on an associated metric on the species set. Such a metric is first estimated from DNA sequences, which leads to a key difficulty: distantly related sequences produce statistically unreliable estimates. This is problematic for Neighbor-Net as it is based on the popular tree reconstruction method Neighbor-Joining, whose sensitivity to distance estimation errors is well established theoretically. In the tree case, more robust reconstruction methods have been developed using the notion of a distorted metric, which captures the dependence of the error in the distance through a radius of accuracy. Here we design the first circular network reconstruction method based on distorted metrics. Our method is computationally efficient. Moreover, the analysis of its radius of accuracy highlights the important role played by the maximum incompatibility, a measure of the extent to which the network differs from a tree.Comment: Submitte

Performance of Some Correlation Coefficients When Applied to Zero-Clustered Data

Zero-clustered data occur widely in medical research and are characterised by the presence of a group of observations of value zero in a distribution of otherwise continuous non-negative responses. A simulation study was conducted to investigate the properties of a number of correlation coefficients applied to samples of zero-clustered data

Computing the blocks of a quasi-median graph

Quasi-median graphs are a tool commonly used by evolutionary biologists to visualise the evolution of molecular sequences. As with any graph, a quasi-median graph can contain cut vertices, that is, vertices whose removal disconnect the graph. These vertices induce a decomposition of the graph into blocks, that is, maximal subgraphs which do not contain any cut vertices. Here we show that the special structure of quasi-median graphs can be used to compute their blocks without having to compute the whole graph. In particular we present an algorithm that, for a collection of $n$ aligned sequences of length $m$, can compute the blocks of the associated quasi-median graph together with the information required to correctly connect these blocks together in run time $\mathcal O(n^2m^2)$, independent of the size of the sequence alphabet. Our primary motivation for presenting this algorithm is the fact that the quasi-median graph associated to a sequence alignment must contain all most parsimonious trees for the alignment, and therefore precomputing the blocks of the graph has the potential to help speed up any method for computing such trees.Comment: 17 pages, 2 figure

How much information is needed to infer reticulate evolutionary histories?

Phylogenetic networks are a generalization of evolutionary trees and are an important tool for analyzing reticulate evolutionary histories. Recently, there has been great interest in developing new methods to construct rooted phylogenetic networks, that is, networks whose internal vertices correspond to hypothetical ancestors, whose leaves correspond to sampled taxa, and in which vertices with more than one parent correspond to taxa formed by reticulate evolutionary events such as recombination or hybridization. Several methods for constructing evolutionary trees use the strategy of building up a tree from simpler building blocks (such as triplets or clusters), and so it is natural to look for ways to construct networks from smaller networks. In this article, we shall demonstrate a fundamental issue with this approach. Namely, we show that even if we are given all of the subnetworks induced on all proper subsets of the leaves of some rooted phylogenetic network, we still do not have all of the information required to completely determine that network. This implies that even if all of the building blocks for some reticulate evolutionary history were to be taken as the input for any given network building method, the method might still output an incorrect history. We also discuss some potential consequences of this result for constructing phylogenetic networks