2,276 research outputs found

    Modeling the IPv6 Internet AS-level Topology

    Full text link
    To measure the IPv6 internet AS-level topology, a network topology discovery system, called Dolphin, was developed. By comparing the measurement result of Dolphin with that of CAIDA's Scamper, it was found that the IPv6 Internet at AS level, similar to other complex networks, is also scale-free but the exponent of its degree distribution is 1.2, which is much smaller than that of the IPv4 Internet and most other scale-free networks. In order to explain this feature of IPv6 Internet we argue that the degree exponent is a measure of uniformity of the degree distribution. Then, for the purpose on modeling the networks, we propose a new model based on the two major factors affecting the exponent of the EBA model. It breaks the lower bound of degree exponent which is 2 for most models. To verify the validity of this model, both theoretical and experimental analyses have been carried out. Finally, we demonstrate how this model can be successfully used to reproduce the topology of the IPv6 Internet.Comment: 15 pages, 5 figure

    The phonon theory of liquid thermodynamics

    Get PDF
    Heat capacity of matter is considered to be its most important property because it holds information about system's degrees of freedom as well as the regime in which the system operates, classical or quantum. Heat capacity is well understood in gases and solids but not in the third state of matter, liquids, and is not discussed in physics textbooks as a result. The perceived difficulty is that interactions in a liquid are both strong and system-specific, implying that the energy strongly depends on the liquid type and that, therefore, liquid energy can not be calculated in general form. Here, we develop a phonon theory of liquids where this problem is avoided. The theory covers both classical and quantum regimes. We demonstrate good agreement of calculated and experimental heat capacity of 21 liquids, including noble, metallic, molecular and hydrogen-bonded network liquids in a wide range of temperature and pressure.Comment: 7 pages, 4 figure

    Calibrating the Performance of SNP Arrays for Whole-Genome Association Studies

    Get PDF
    To facilitate whole-genome association studies (WGAS), several high-density SNP genotyping arrays have been developed. Genetic coverage and statistical power are the primary benchmark metrics in evaluating the performance of SNP arrays. Ideally, such evaluations would be done on a SNP set and a cohort of individuals that are both independently sampled from the original SNPs and individuals used in developing the arrays. Without utilization of an independent test set, previous estimates of genetic coverage and statistical power may be subject to an overfitting bias. Additionally, the SNP arrays' statistical power in WGAS has not been systematically assessed on real traits. One robust setting for doing so is to evaluate statistical power on thousands of traits measured from a single set of individuals. In this study, 359 newly sampled Americans of European descent were genotyped using both Affymetrix 500K (Affx500K) and Illumina 650Y (Ilmn650K) SNP arrays. From these data, we were able to obtain estimates of genetic coverage, which are robust to overfitting, by constructing an independent test set from among these genotypes and individuals. Furthermore, we collected liver tissue RNA from the participants and profiled these samples on a comprehensive gene expression microarray. The RNA levels were used as a large-scale set of quantitative traits to calibrate the relative statistical power of the commercial arrays. Our genetic coverage estimates are lower than previous reports, providing evidence that previous estimates may be inflated due to overfitting. The Ilmn650K platform showed reasonable power (50% or greater) to detect SNPs associated with quantitative traits when the signal-to-noise ratio (SNR) is greater than or equal to 0.5 and the causal SNP's minor allele frequency (MAF) is greater than or equal to 20% (N = 359). In testing each of the more than 40,000 gene expression traits for association to each of the SNPs on the Ilmn650K and Affx500K arrays, we found that the Ilmn650K yielded 15% times more discoveries than the Affx500K at the same false discovery rate (FDR) level

    Construction of a bacterial artificial chromosome library from the spikemoss Selaginella moellendorffii: a new resource for plant comparative genomics

    Get PDF
    BACKGROUND: The lycophytes are an ancient lineage of vascular plants that diverged from the seed plant lineage about 400 Myr ago. Although the lycophytes occupy an important phylogenetic position for understanding the evolution of plants and their genomes, no genomic resources exist for this group of plants. RESULTS: Here we describe the construction of a large-insert bacterial artificial chromosome (BAC) library from the lycophyte Selaginella moellendorffii. Based on cell flow cytometry, this species has the smallest genome size among the different lycophytes tested, including Huperzia lucidula, Diphaiastrum digita, Isoetes engelmanii and S. kraussiana. The arrayed BAC library consists of 9126 clones; the average insert size is estimated to be 122 kb. Inserts of chloroplast origin account for 2.3% of the clones. The BAC library contains an estimated ten genome-equivalents based on DNA hybridizations using five single-copy and two duplicated S. moellendorffii genes as probes. CONCLUSION: The S. moellenforffii BAC library, the first to be constructed from a lycophyte, will be useful to the scientific community as a resource for comparative plant genomics and evolution

    Power analysis for genome-wide association studies

    Get PDF
    Abstract Background Genome-wide association studies are a promising new tool for deciphering the genetics of complex diseases. To choose the proper sample size and genotyping platform for such studies, power calculations that take into account genetic model, tag SNP selection, and the population of interest are required. Results The power of genome-wide association studies can be computed using a set of tag SNPs and a large number of genotyped SNPs in a representative population, such as available through the HapMap project. As expected, power increases with increasing sample size and effect size. Power also depends on the tag SNPs selected. In some cases, more power is obtained by genotyping more individuals at fewer SNPs than fewer individuals at more SNPs. Conclusion Genome-wide association studies should be designed thoughtfully, with the choice of genotyping platform and sample size being determined from careful power calculations.</p

    Allelic spectrum of the natural variation in CRP

    Get PDF
    With the recent completion of the International HapMap Project, many tools are in hand for genetic association studies seeking to test the common variant/common disease hypothesis. In contrast, very few tools and resources are in place for genotype–phenotype studies hypothesizing that rare variation has a large impact on the phenotype of interest. To create these tools for rare variant/common disease studies, much interest is being generated towards investing in re-sequencing either large sample sizes of random chromosomes or smaller sample sizes of patients with extreme phenotypes. As a case study for rare variant discovery in random chromosomes, we have re-sequenced ~1,000 chromosomes representing diverse populations for the gene C-reactive protein (CRP). CRP is an important gene in the fields of cardiovascular and inflammation genetics, and its size (~2 kb) makes it particularly amenable medical or deep re-sequencing. With these data, we explore several issues related to the present-day candidate gene association study including the benefits of complete SNP discovery, the effects of tagSNP selection across diverse populations, and completeness of dbSNP for CRP. Also, we show that while deep re-sequencing uncovers potentially medically relevant coding SNPs, these SNPs are fleetingly rare when genotyped in a population-based survey of 7,000 Americans (NHANES III). Collectively, these data suggest that several different types re-sequencing and genotyping approaches may be required to fully understand the complete spectrum of alleles that impact human phenotypes. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material is available for this article at http://dx.doi.org/10.1007/s00439-006-0160-y and is accessible for authorized users

    ARPES: A probe of electronic correlations

    Full text link
    Angle-resolved photoemission spectroscopy (ARPES) is one of the most direct methods of studying the electronic structure of solids. By measuring the kinetic energy and angular distribution of the electrons photoemitted from a sample illuminated with sufficiently high-energy radiation, one can gain information on both the energy and momentum of the electrons propagating inside a material. This is of vital importance in elucidating the connection between electronic, magnetic, and chemical structure of solids, in particular for those complex systems which cannot be appropriately described within the independent-particle picture. Among the various classes of complex systems, of great interest are the transition metal oxides, which have been at the center stage in condensed matter physics for the last four decades. Following a general introduction to the topic, we will lay the theoretical basis needed to understand the pivotal role of ARPES in the study of such systems. After a brief overview on the state-of-the-art capabilities of the technique, we will review some of the most interesting and relevant case studies of the novel physics revealed by ARPES in 3d-, 4d- and 5d-based oxides.Comment: Chapter to appear in "Strongly Correlated Systems: Experimental Techniques", edited by A. Avella and F. Mancini, Springer Series in Solid-State Sciences (2013). A high-resolution version can be found at: http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Reviews/ARPES_Springer.pdf. arXiv admin note: text overlap with arXiv:cond-mat/0307085, arXiv:cond-mat/020850

    SNP selection for genes of iron metabolism in a study of genetic modifiers of hemochromatosis

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>We report our experience of selecting tag SNPs in 35 genes involved in iron metabolism in a cohort study seeking to discover genetic modifiers of hereditary hemochromatosis.</p> <p>Methods</p> <p>We combined our own and publicly available resequencing data with HapMap to maximise our coverage to select 384 SNPs in candidate genes suitable for typing on the Illumina platform.</p> <p>Results</p> <p>Validation/design scores above 0.6 were not strongly correlated with SNP performance as estimated by Gentrain score. We contrasted results from two tag SNP selection algorithms, LDselect and Tagger. Varying r<sup>2 </sup>from 0.5 to 1.0 produced a near linear correlation with the number of tag SNPs required. We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the ≥ 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing. Resequencing can reveal adjacent SNPs (within 60 bp) which may affect assay performance. We report the number of SNPs present within the region of six of our larger candidate genes, for different versions of stock genotyping assays.</p> <p>Conclusion</p> <p>A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data. Tag SNP software must be fast and flexible to data changes, since tag SNP selection involves iteration as investigators seek to satisfy the competing demands of coverage within and between populations, and typability on the technology platform chosen.</p
    corecore