Toward 959 nematode genomes

The sequencing of the complete genome of the nematode Caenorhabditis elegans was a landmark achievement and ushered in a new era of whole-organism, systems analyses of the biology of this powerful model organism. The success of the C. elegans genome sequencing project also inspired communities working on other organisms to approach genome sequencing of their species. The phylum Nematoda is rich and diverse and of interest to a wide range of research fields from basic biology through ecology and parasitic disease. For all these communities, it is now clear that access to genome scale data will be key to advancing understanding, and in the case of parasites, developing new ways to control or cure diseases. The advent of second-generation sequencing technologies, improvements in computing algorithms and infrastructure and growth in bioinformatics and genomics literacy is making the addition of genome sequencing to the research goals of any nematode research program a less daunting prospect. To inspire, promote and coordinate genomic sequencing across the diversity of the phylum, we have launched a community wiki and the 959 Nematode Genomes initiative (www.nematodegenomes.org/). Just as the deciphering of the developmental lineage of the 959 cells of the adult hermaphrodite C. elegans was the gateway to broad advances in biomedical science, we hope that a nematode phylogeny with (at least) 959 sequenced species will underpin further advances in understanding the origins of parasitism, the dynamics of genomic change and the adaptations that have made Nematoda one of the most successful animal phyla

Model based decision support for planning of road maintenance

In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the Net Present Value of maintenance costs, while the plan is acceptable in terms of technical admissibility, resulting quality, etc. Global restrictions such as budget restrictions can also be imposed.\ud \ud Adequate grouping of maintenance activities in view of quantity discounts is an important aspect of our model. Our approach is to reduce the complexity of the optimisation by hierarchical structuring in four levels. In the lowest two levels maintenance per lane sector is considered, first with an unbounded planning horizon and next with a bounded planning horizon and time-windows for maintenance. The grouping of maintenance activities for a specific road is the topic of the third level. At the fourth level, which we will not consider in this article, the problem of optimal assignment of the available maintenance budgets over a set of roads or road sections takes place. Here, some results are presented to demonstrate the effects of grouping and to show that this hierarchical approach gives rise to improvements compared with previous work

Geometry-based Detection of Flash Worms

While it takes traditional internet worms hours to infect all the vulnerable hosts on the Internet, a flash worm takes seconds. Because of the rapid rate with which flash worms spread, the existing worm defense mechanisms cannot respond fast enough to detect and stop the flash worm infections. In this project, we propose a geometric-based detection mechanism that can detect the spread of flash worms in a short period of time. We tested the mechanism on various simulated flash worm traffics consisting of more than 10,000 nodes. In addition to testing on flash worm traffics, we also tested the mechanism on non-flash worm traffics to see if our detection mechanism produces false alarms. In order to efficiently analyze bulks of various network traffics, we implemented an application that can be used to convert the network traffic data into graphical notations. Using the application, the analysis can be done graphically as it displays the large amount of network relationships as tree structures

Worm eggs: Cost you money

Contents One Million Eggs Daily.......... 3 Damaging Trip......... 4 Worm Remedies......... 5 Modern Worm Remedies......... 6 A Control Program..........

Deriving shape-based features for C. elegans locomotion using dimensionality reduction methods

High-throughput analysis of animal behavior is increasingly common following the advances of recording technology, leading to large high-dimensional data sets. This dimensionality can sometimes be reduced while still retaining relevant information. In the case of the nematode worm Caenorhabditis elegans, more than 90% of the shape variance can be captured using just four principal components. However, it remains unclear if other methods can achieve a more compact representation or contribute further biological insight to worm locomotion. Here we take a data-driven approach to worm shape analysis using independent component analysis (ICA), non-negative matrix factorization (NMF), a cosine series, and jPCA (a dynamic variant of principal component analysis [PCA]) and confirm that the dimensionality of worm shape space is close to four. Projecting worm shapes onto the bases derived using each method gives interpretable features ranging from head movements to tail oscillation. We use these as a comparison method to find differences between the wild type N2 worms and various mutants. For example, we find that the neuropeptide mutant nlp-1(ok1469) has an exaggerated head movement suggesting a mode of action for the previously described increased turning rate. The different bases provide complementary views of worm behavior and we expect that closer examination of the time series of projected amplitudes will lead to new results in the future

Lifted Worm Algorithm for the Ising Model

We design an irreversible worm algorithm for the zero-field ferromagnetic Ising model by using the lifting technique. We study the dynamic critical behavior of an energy estimator on both the complete graph and toroidal grids, and compare our findings with reversible algorithms such as the Prokof'ev-Svistunov worm algorithm. Our results show that the lifted worm algorithm improves the dynamic exponent of the energy estimator on the complete graph, and leads to a significant constant improvement on toroidal grids.Comment: 9 pages, 6 figure