A New Implementation and Detailed Study of Breakpoint Analysis

Phylogenies derived from gene order data may prove crucial in answering some fundamental open questions in biomolecular evolution. Yet very few techniques are available for such phylogenetic reconstructions. One method is breakpoint analysis, developed by Blanchette and Sankoff 2 for solving the breakpoint phylogeny.\u27 Our earlier studies 5;6 confirmed the usefulness of this approach, but also found that BPAnalysis, the implementation developed by Sankoff and Blanchette, was too slow to use on all but very small datasets. We report here on a reimplementation of BPAnalysis using the principles of algorithmic engineering. Our faster (by 2 to 3 orders of magnitude) and flexible implementation allowed us to conduct studies on the characteristics of breakpoint analysis, in terms of running time, quality, and robustness, as well as to analyze datasets that had so far been considered out of reach. We report on these findings and also discuss future directions for our new implementation.\u2

Towards Distributed Petascale Computing

In this chapter we will argue that studying such multi-scale multi-science systems gives rise to inherently hybrid models containing many different algorithms best serviced by different types of computing environments (ranging from massively parallel computers, via large-scale special purpose machines to clusters of PC's) whose total integrated computing capacity can easily reach the PFlop/s scale. Such hybrid models, in combination with the by now inherently distributed nature of the data on which the models `feed' suggest a distributed computing model, where parts of the multi-scale multi-science model are executed on the most suitable computing environment, and/or where the computations are carried out close to the required data (i.e. bring the computations to the data instead of the other way around). We presents an estimate for the compute requirements to simulate the Galaxy as a typical example of a multi-scale multi-physics application, requiring distributed Petaflop/s computational power.Comment: To appear in D. Bader (Ed.) Petascale, Computing: Algorithms and Applications, Chapman & Hall / CRC Press, Taylor and Francis Grou

Fully-dynamic Approximation of Betweenness Centrality

Betweenness is a well-known centrality measure that ranks the nodes of a network according to their participation in shortest paths. Since an exact computation is prohibitive in large networks, several approximation algorithms have been proposed. Besides that, recent years have seen the publication of dynamic algorithms for efficient recomputation of betweenness in evolving networks. In previous work we proposed the first semi-dynamic algorithms that recompute an approximation of betweenness in connected graphs after batches of edge insertions. In this paper we propose the first fully-dynamic approximation algorithms (for weighted and unweighted undirected graphs that need not to be connected) with a provable guarantee on the maximum approximation error. The transfer to fully-dynamic and disconnected graphs implies additional algorithmic problems that could be of independent interest. In particular, we propose a new upper bound on the vertex diameter for weighted undirected graphs. For both weighted and unweighted graphs, we also propose the first fully-dynamic algorithms that keep track of such upper bound. In addition, we extend our former algorithm for semi-dynamic BFS to batches of both edge insertions and deletions. Using approximation, our algorithms are the first to make in-memory computation of betweenness in fully-dynamic networks with millions of edges feasible. Our experiments show that they can achieve substantial speedups compared to recomputation, up to several orders of magnitude

High Performance Computing Applications in Remote Sensing Studies for Land Cover Dynamics

Global and regional land cover studies require the ability to apply complex models on selected subsets of large amounts of multi-sensor and multi-temporal data sets that have been derived from raw instrument measurements using widely accepted pre-processing algorithms. The computational and storage requirements of most such studies far exceed what is possible on a single workstation environment. We have been pursuing a new approach that couples scalable and open distributed heterogeneous hardware with the development of high performance software for processing, indexing, and organizing remotely sensed data. Hierarchical data management tools are used to ingest raw data, create metadata, and organize the archived data so as to automatically achieve computational load balancing among the available nodes and minimize I/O overheads. We illustrate our approach with four specific examples. The first is the development of the first fast operational scheme for the atmospheric correction of Landsat TM scenes, while the second example focuses on image segmentation using a novel hierarchical connected components algorithm. Retrieval of global BRDF (Bidirectional Reflectance Distribution Function) in the red and near infrared wavelengths using four years (1983 to 1986) of Pathfinder AVHRR Land (PAL) data set is the focus of our third example. The fourth example is the development of a hierarchical data organization scheme that allows on-demand processing and retrieval of regional and global AVHRR data sets. Our results show that substantial improvements in computational times can be achieved by using the high performance computing technology

Tooth-surface-specific Effects of Xylitol: Randomized Trial Results

The Xylitol for Adult Caries Trial was a three-year, double-blind, multi-center, randomized clinical trial that evaluated the effectiveness of xylitol vs. placebo lozenges in the prevention of dental caries in caries-active adults. The purpose of this secondary analysis was to investigate whether xylitol lozenges had a differential effect on cumulative caries increments on different tooth surfaces. Participants (ages 21-80 yrs) with at least one follow-up visit (n = 620) were examined at baseline, 12, 24, and 33 months. Negative binomial and zero-inflated negative binomial regression models were used to estimate incidence rate ratios (IRR) for xylitol’s differential effect on cumulative caries increments on root and coronal surfaces and, among coronal surfaces, on smooth (buccal and lingual), occlusal, and proximal surfaces. Participants in the xylitol arm developed 40% fewer root caries lesions (0.23 D2FS/year) than those in the placebo arm (0.38 D2FS/year; IRR = 0.60; 95% CI [0.44, 0.81]; p < .001). There was no statistically significant difference between xylitol and control participants in the incidence of smooth-surface caries (p = .100), occlusal-surface caries (p = .408), or proximal-surface caries (p = .159). Among these caries-active adults, xylitol appears to have a caries-preventive effect on root surfaces (ClinicalTrials.gov NCT00393055)