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

Context-based urban terrain reconstruction from uav-videos for geoinformation applications

Urban terrain reconstruction has many applications in areas of civil engineering, urban planning, surveillance and defense research. Therefore the needs of covering ad-hoc demand and performing a close-range urban terrain reconstruction with miniaturized and relatively inexpensive sensor platforms are constantly growing. Using (miniaturized) unmanned aerial vehicles, (M) UAVs, represents one of the most attractive alternatives to conventional large-scale aerial imagery. We cover in this paper a four-step procedure of obtaining georeferenced 3D urban models from video sequences. The four steps of the procedure - orientation, dense reconstruction, urban terrain modeling and geo-referencing - are robust, straight-forward, and nearly fully-automatic. The two last steps - namely, urban terrain modeling from almost-nadir videos and co-registration of models - represent the main contribution of this work and will therefore be covered with more detail. The essential substeps of the third step include digital terrain model (DTM) extraction, segregation of buildings from vegetation, as well as instantiation of building and tree models. The last step is subdivided into quasi-intrasensorial registration of Euclidean reconstructions and intersensorial registration with a geo-referenced orthophoto. Finally, we present reconstruction results from a real data-set and outline ideas for future work

High Resolution Maps of the Vasculature of An Entire Organ

The structure of vascular networks represents a great, unsolved problem in anatomy. Network geometry and topology differ dramatically from left to right and person to person as evidenced by the superficial venation of the hands and the vasculature of the retinae. Mathematically, we may state that there is no conserved topology in vascular networks. Efficiency demands that these networks be regular on a statistical level and perhaps optimal. We have taken the first steps towards elucidating the principles underlying vascular organization, creating the rst map of the hierarchical vasculature (above the capillaries) of an entire organ. Using serial blockface microscopy and fluorescence imaging, we are able to identify vasculature at 5 μm resolution. We have designed image analysis software to segment, align, and skeletonize the resulting data, yielding a map of the individual vessels. We transformed these data into a mathematical graph, allowing computationally efficient storage and the calculation of geometric and topological statistics for the network. Our data revealed a complexity of structure unexpected by theory. We observe loops at all scales that complicate the assignment of hierarchy within the network and the existence of set length scales, implying a distinctly non-fractal structure of components within

Holistic corpus-based dialectology

This paper is concerned with sketching future directions for corpus-based dialectology. We advocate a holistic approach to the study of geographically conditioned linguistic variability, and we present a suitable methodology, 'corpusbased dialectometry', in exactly this spirit. Specifically, we argue that in order to live up to the potential of the corpus-based method, practitioners need to (i) abandon their exclusive focus on individual linguistic features in favor of the study of feature aggregates, (ii) draw on computationally advanced multivariate analysis techniques (such as multidimensional scaling, cluster analysis, and principal component analysis), and (iii) aid interpretation of empirical results by marshalling state-of-the-art data visualization techniques. To exemplify this line of analysis, we present a case study which explores joint frequency variability of 57 morphosyntax features in 34 dialects all over Great Britain

General functions to transform associate data to host data, and their use in phylogenetic inference from sequences with intra-individual variability

<p>Abstract</p> <p>Background</p> <p>Amongst the most commonly used molecular markers for plant phylogenetic studies are the nuclear ribosomal internal transcribed spacers (ITS). Intra-individual variability of these multicopy regions is a very common phenomenon in plants, the causes of which are debated in literature. Phylogenetic reconstruction under these conditions is inherently difficult. Our approach is to consider this problem as a special case of the general biological question of how to infer the characteristics of hosts (represented here by plant individuals) from features of their associates (represented by cloned sequences here).</p> <p>Results</p> <p>Six general transformation functions are introduced, covering the transformation of associate characters to discrete and continuous host characters, and the transformation of associate distances to host distances. A pure distance-based framework is established in which these transformation functions are applied to ITS sequences collected from the angiosperm genera <it>Acer</it>, <it>Fagus </it>and <it>Zelkova</it>. The formulae are also applied to allelic data of three different loci obtained from <it>Rosa </it>spp. The functions are validated by (1) phylogeny-independent measures of treelikeness; (2) correlation with independent host characters; (3) visualization using splits graphs and comparison with published data on the test organisms. The results agree well with these three measures and the datasets examined as well as with the theoretical predictions and previous results in the literature. High-quality distance matrices are obtained with four of the six transformation formulae. We demonstrate that one of them represents a generalization of the Sørensen coefficient, which is widely applied in ecology.</p> <p>Conclusion</p> <p>Because of their generality, the transformation functions may be applied to a wide range of biological problems that are interpretable in terms of hosts and associates. Regarding cloned sequences, the formulae have a high potential to accurately reflect evolutionary relationships within angiosperm genera, and to identify hybrids and ancestral taxa. These results corroborate earlier ones which showed that treelikeness measures are a valuable tool in comparative studies of biological distance functions.</p