Phenomenology of minority games in efficient regime

We present a comprehensive study of utility function of the minority game in its efficient regime. We develop an effective description of state of the game. For the payoff function g(x)=\sgn (x) we explicitly represent the game as the Markov process and prove the finitness of number of states. We also demonstrate boundedness of the utility function. Using these facts we can explain all interesting observable features of the aggregated demand: appearance of strong fluctuations, their periodicity and existence of prefered levels. For another payoff, $g(x)=x$, the number of states is still finite and utility remains bounded but the number of states cannot be reduced and probabilities of states are not calculated. However, using properties of the utility and analysing the game in terms of de Bruijn graphs, we can also explain distinct peaks of demand and their frequencies

Assembly algorithms for next-generation sequencing data

AbstractThe emergence of next-generation sequencing platforms led to resurgence of research in whole-genome shotgun assembly algorithms and software. DNA sequencing data from the Roche 454, Illumina/Solexa, and ABI SOLiD platforms typically present shorter read lengths, higher coverage, and different error profiles compared with Sanger sequencing data. Since 2005, several assembly software packages have been created or revised specifically for de novo assembly of next-generation sequencing data. This review summarizes and compares the published descriptions of packages named SSAKE, SHARCGS, VCAKE, Newbler, Celera Assembler, Euler, Velvet, ABySS, AllPaths, and SOAPdenovo. More generally, it compares the two standard methods known as the de Bruijn graph approach and the overlap/layout/consensus approach to assembly

Conserved generation of short products at piRNA loci

ABSTRACT: BACKGROUND: The piRNA pathway operates in animal germ lines to ensure genome integrity through retrotransposon silencing. The Piwi protein-associated small RNAs (piRNAs) guide Piwi proteins to retrotransposon transcripts, which are degraded and thereby post-transcriptionally silenced through a ping-pong amplification process. Cleavage of the retrotransposon transcript defines at the same time the 5` end of a secondary piRNA that will in turn guide a Piwi protein to a primary piRNA precursor, thereby amplifying primary piRNAs. Although several studies provided evidence that this mechanism is conserved among metazoa, how the process is initiated and what enzymatic activities are responsible for generating the primary and secondary piRNAs are not entirely clear. RESULTS: Here we analyzed small RNAs from three mammalian species, seeking to gain further insight into the mechanisms responsible for the piRNA amplification loop. We found that in all these species piRNA-directed targeting is accompanied by the generation of short sequences that have a very precisely defined length, 19 nucleotides, and a specific spatial relationship with the guide piRNAs. CONCLUSIONS: This suggests that the processing of the 5` product of piRNA-guided cleavage occurs while the piRNA target is engaged by the Piwi protein. Although they are not stabilized through methylation of their 3` ends, the 19-mers are abundant not only in testes lysates but also in immunoprecipitates of Miwi and Mili proteins. They will enable more accurate identification of piRNA loci in deep sequencing data sets

Augmentation and Optimisation of the Australian Desert Fireball Network to Enable New Planetary Science

Planetary science is limited by the scarcity of extraterrestrial samples of known origin. Fireball camera networks can provide these in the form of meteorites with known pre-atmospheric entry orbits. Here, a new digital fireball observatory implementing a novel timing technique is described. This design has enabled the Desert Fireball Network to cover a third of Australia, recover two meteorites with orbits and observe more than a dozen additional meteorite dropping fireballs

An Introduction to Mechanized Reasoning

Mechanized reasoning uses computers to verify proofs and to help discover new theorems. Computer scientists have applied mechanized reasoning to economic problems but -- to date -- this work has not yet been properly presented in economics journals. We introduce mechanized reasoning to economists in three ways. First, we introduce mechanized reasoning in general, describing both the techniques and their successful applications. Second, we explain how mechanized reasoning has been applied to economic problems, concentrating on the two domains that have attracted the most attention: social choice theory and auction theory. Finally, we present a detailed example of mechanized reasoning in practice by means of a proof of Vickrey's familiar theorem on second-price auctions

SOPRA: Scaffolding algorithm for paired reads via statistical optimization

<p>Abstract</p> <p>Background</p> <p>High throughput sequencing (HTS) platforms produce gigabases of short read (<100 bp) data per run. While these short reads are adequate for resequencing applications, <it>de novo </it>assembly of moderate size genomes from such reads remains a significant challenge. These limitations could be partially overcome by utilizing mate pair technology, which provides pairs of short reads separated by a known distance along the genome.</p> <p>Results</p> <p>We have developed SOPRA, a tool designed to exploit the mate pair/paired-end information for assembly of short reads. The main focus of the algorithm is selecting a sufficiently large subset of simultaneously satisfiable mate pair constraints to achieve a balance between the size and the quality of the output scaffolds. Scaffold assembly is presented as an optimization problem for variables associated with vertices and with edges of the contig connectivity graph. Vertices of this graph are individual contigs with edges drawn between contigs connected by mate pairs. Similar graph problems have been invoked in the context of shotgun sequencing and scaffold building for previous generation of sequencing projects. However, given the error-prone nature of HTS data and the fundamental limitations from the shortness of the reads, the ad hoc greedy algorithms used in the earlier studies are likely to lead to poor quality results in the current context. SOPRA circumvents this problem by treating all the constraints on equal footing for solving the optimization problem, the solution itself indicating the problematic constraints (chimeric/repetitive contigs, etc.) to be removed. The process of solving and removing of constraints is iterated till one reaches a core set of consistent constraints. For SOLiD sequencer data, SOPRA uses a dynamic programming approach to robustly translate the color-space assembly to base-space. For assessing the quality of an assembly, we report the no-match/mismatch error rate as well as the rates of various rearrangement errors.</p> <p>Conclusions</p> <p>Applying SOPRA to real data from bacterial genomes, we were able to assemble contigs into scaffolds of significant length (N50 up to 200 Kb) with very few errors introduced in the process. In general, the methodology presented here will allow better scaffold assemblies of any type of mate pair sequencing data.</p

Lossy Compression of Quality Values in Sequencing Data

The dropping cost of sequencing human DNA has allowed for fast development of several projects around the world generating huge amounts of DNA sequencing data. This deluge of data has run up against limited storage space, a problem that researchers are trying to solve through compression techniques. In this study we address the compression of SAM files, the standard output files for DNA alignment. We specifically study lossy compression techniques used for quality values reported in the SAM file and analyze the impact of such lossy techniques on the CRAM format. We present a series of experiments using a data set corresponding to individual NA12878 with three different fold coverages. We introduce a new lossy model, dynamic binning, and compare its performance to other lossy techniques, namely Illumina binning, LEON and QVZ. We analyze the compression ratio when using CRAM and also study the impact of the lossy techniques on SNP calling. Our results show that lossy techniques allow a better CRAM compression ratio. Furthermore, we show that SNP calling performance is not negatively affected and may even be boosted.Natural Sciences and Engineering Research Council of Canad