Murray Wolinsky
Los Alamos National Laboratory
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Featured researches published by Murray Wolinsky.
ieee visualization | 1997
Mark A. Duchaineau; Murray Wolinsky; David E. Sigeti; Mark C. Miller; Charles Aldrich; Mark Mineev-Weinstein
Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and ground-based aircraft testing using synthetic sensor simulation. On current graphics hardware, the problem is to maintain dynamic, view-dependent triangle meshes and texture maps that produce good images at the required frame rate. We present an algorithm for constructing triangle meshes that optimizes flexible view-dependent error metrics, produces guaranteed error bounds, achieves specified triangle counts directly and uses frame-to-frame coherence to operate at high frame rates for thousands of triangles per frame. Our method, dubbed Real-time Optimally Adapting Meshes (ROAM), uses two priority queues to drive split and merge operations that maintain continuous triangulations built from pre-processed bintree triangles. We introduce two additional performance optimizations: incremental triangle stripping and priority-computation deferral lists. ROAMs execution time is proportional to the number of triangle changes per frame, which is typically a few percent of the output mesh size; hence ROAMs performance is insensitive to the resolution and extent of the input terrain. Dynamic terrain and simple vertex morphing are supported.
Bioinformatics | 2005
Jian Song; Yan Xu; P. Scott White; Kevin W. P. Miller; Murray Wolinsky
UNLABELLED Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variations in closely related microbial species, strains or isolates. Some SNPs confer selective advantages for microbial pathogens during infection and many others are powerful genetic markers for distinguishing closely related strains or isolates that could not be distinguished otherwise. To facilitate SNP discovery in microbial genomes, we have developed a web-based application, SNPsFinder, for genome-wide identification of SNPs. SNPsFinder takes multiple genome sequences as input to identify SNPs within homologous regions. It can also take contig sequences and sequence quality scores from ongoing sequencing projects for SNP prediction. SNPsFinder will use genome sequence annotation if available and map the predicted SNP regions to known genes or regions to assist further evaluation of the predicted SNPs for their functional significance. SNPsFinder can generate PCR primers for all predicted SNP regions according to users input parameters to facilitate experimental validation. The results from SNPsFinder analysis are accessible through the World Wide Web. AVAILABILITY The SNPsFinder program is available at http://snpsfinder.lanl.gov/. SUPPLEMENTARY INFORMATION The users manual is available at http://snpsfinder.lanl.gov/UsersManual/
BMC Research Notes | 2012
Joel Berendzen; William J. Bruno; Judith D. Cohn; Nicolas W. Hengartner; Cheryl R. Kuske; Benjamin H. McMahon; Murray Wolinsky; Gary Xie
BackgroundClassification is difficult for shotgun metagenomics data from environments such as soils, where the diversity of sequences is high and where reference sequences from close relatives may not exist. Approaches based on sequence-similarity scores must deal with the confounding effects that inheritance and functional pressures exert on the relation between scores and phylogenetic distance, while approaches based on sequence alignment and tree-building are typically limited to a small fraction of gene families. We describe an approach based on finding one or more exact matches between a read and a precomputed set of peptide 10-mers.ResultsAt even the largest phylogenetic distances, thousands of 10-mer peptide exact matches can be found between pairs of bacterial genomes. Genes that share one or more peptide 10-mers typically have high reciprocal BLAST scores. Among a set of 403 representative bacterial genomes, some 20 million 10-mer peptides were found to be shared. We assign each of these peptides as a signature of a particular node in a phylogenetic reference tree based on the RNA polymerase genes. We classify the phylogeny of a genomic fragment (e.g., read) at the most specific node on the reference tree that is consistent with the phylogeny of observed signature peptides it contains. Using both synthetic data from four newly-sequenced soil-bacterium genomes and ten real soil metagenomics data sets, we demonstrate a sensitivity and specificity comparable to that of the MEGAN metagenomics analysis package using BLASTX against the NR database. Phylogenetic and functional similarity metrics applied to real metagenomics data indicates a signal-to-noise ratio of approximately 400 for distinguishing among environments. Our method assigns ~6.6 Gbp/hr on a single CPU, compared with 25 kbp/hr for methods based on BLASTX against the NR database.ConclusionsClassification by exact matching against a precomputed list of signature peptides provides comparable results to existing techniques for reads longer than about 300 bp and does not degrade severely with shorter reads. Orders of magnitude faster than existing methods, the approach is suitable now for inclusion in analysis pipelines and appears to be extensible in several different directions.
Cytometry Part A | 2004
Matthew M. Ferris; Robbert C. Habbersett; Murray Wolinsky; James H. Jett; Thomas M. Yoshida; Richard A. Keller
The measurement of physical properties from single molecules has been demonstrated. However, the majority of single‐molecule studies report values based on relatively large data sets (e.g., N > 50). While there are studies that report physical quantities based on small sample sets, there has not been a detailed statistical analysis relating sample size to the reliability of derived parameters.
BMC Genomics | 2009
Chris J. Stubben; Melanie Duffield; Ian A. Cooper; Donna C. Ford; Jason D. Gans; Andrey V. Karlyshev; Bryan Lingard; Petra C. F. Oyston; Anna de Rochefort; Jian Song; Brendan W. Wren; Richard W. Titball; Murray Wolinsky
BackgroundNew and improved antimicrobial countermeasures are urgently needed to counteract increased resistance to existing antimicrobial treatments and to combat currently untreatable or new emerging infectious diseases. We demonstrate that computational comparative genomics, together with experimental screening, can identify potential generic (i.e., conserved across multiple pathogen species) and novel virulence-associated genes that may serve as targets for broad-spectrum countermeasures.ResultsUsing phylogenetic profiles of protein clusters from completed microbial genome sequences, we identified seventeen protein candidates that are common to diverse human pathogens and absent or uncommon in non-pathogens. Mutants of 13 of these candidates were successfully generated in Yersinia pseudotuberculosis and the potential role of the proteins in virulence was assayed in an animal model. Six candidate proteins are suggested to be involved in the virulence of Y. pseudotuberculosis, none of which have previously been implicated in the virulence of Y. pseudotuberculosis and three have no record of involvement in the virulence of any bacteria.ConclusionThis work demonstrates a strategy for the identification of potential virulence factors that are conserved across a number of human pathogenic bacterial species, confirming the usefulness of this tool.
Nucleic Acids Research | 2012
Jason D. Gans; John Dunbar; La Verne Gallegos-Graves; Murray Wolinsky; Cheryl R. Kuske
Environmental biosurveillance and microbial ecology studies use PCR-based assays to detect and quantify microbial taxa and gene sequences within a complex background of microorganisms. However, the fragmentary nature and growing quantity of DNA-sequence data make group-specific assay design challenging. We solved this problem by developing a software platform that enables PCR-assay design at an unprecedented scale. As a demonstration, we developed quantitative PCR assays for a globally widespread, ecologically important bacterial group in soil, Acidobacteria Group 1. A total of 33 684 Acidobacteria 16S rRNA gene sequences were used for assay design. Following 1 week of computation on a 376-core cluster, 83 assays were obtained. We validated the specificity of the top three assays, collectively predicted to detect 42% of the Acidobacteria Group 1 sequences, by PCR amplification and sequencing of DNA from soil. Based on previous analyses of 16S rRNA gene sequencing, Acidobacteria Group 1 species were expected to decrease in response to elevated atmospheric CO2. Quantitative PCR results, using the Acidobacteria Group 1-specific PCR assays, confirmed the expected decrease and provided higher statistical confidence than the 16S rRNA gene-sequencing data. These results demonstrate a powerful capacity to address previously intractable assay design challenges.
BMC Bioinformatics | 2007
Jason D. Gans; Murray Wolinsky
BackgroundThe ability to visualize genomic features and design experimental assays that can target specific regions of a genome is essential for modern biology. To assist in these tasks, we present Genomorama, a software program for interactively displaying multiple genomes and identifying potential DNA hybridization sites for assay design.ResultsUseful features of Genomorama include genome search by DNA hybridization (probe binding and PCR amplification), efficient multi-scale display and manipulation of multiple genomes, support for many genome file types and the ability to search for and retrieve data from the National Center for Biotechnology Information (NCBI) Entrez server.ConclusionGenomorama provides an efficient computational platform for visualizing and analyzing multiple genomes.
International Journal of Hydrogen Energy | 2002
Jack Horner; Murray Wolinsky
Abstract Melis et al. have demonstrated that the green alga Chlamydomonas reinhardtii, when deprived of sulfur, can produce hydrogen gas for ∼70 h , then can resume hydrogen gas production after a brief period of “recharging” in the presence of sulfur. Here we describe an S-system model of H2 production by C. reinhardtii. Through that model we investigate the sensitivity of H2 production to photosynthetic efficiency, and to contention for the protons produced by the photolysis of water, between hydrogen production on the one hand, and ATP consumption by cellular functions outside the H2 production path on the other. The model identifies for experimental investigation several potential systemic constraints on any genetic re-engineering effort aimed at increasing the H2 production efficiency of the alga.
Advances in Experimental Medicine and Biology | 2010
Jian Song; Po-E Li; Jason D. Gans; Momchilo Vuyisich; Alina Deshpande; Murray Wolinsky; P. Scott White
Extensive use of antibiotics in both public health and animal husbandry has resulted in rapid emergence of antibiotic resistance in almost all human pathogens, including biothreat pathogens. Antibiotic resistance has thus become a major concern for both public health and national security. We developed multiplexed assays for rapid, simultaneous pathogen detection and characterization of ciprofloxacin and doxycycline resistance in Bacillus anthracis, Yersinia pestis, and Francisella tularensis. These assays are SNP-based and use Multiplexed Oligonucleotide Ligation-PCR (MOL-PCR). The MOL-PCR assay chemistry and MOLigo probe design process are presented. A web-based tool - MOLigoDesigner (http://MOLigoDesigner.lanl.gov) was developed to facilitate the probe design. All probes were experimentally validated individually and in multiplexed assays, and minimal sets of multiplexed MOLigo probes were identified for simultaneous pathogen detection and antibiotic resistance characterization.
Data Visualization: The State of the Art | 2003
Benjamin F. Gregorski; David E. Sigeti; John Joseph Ambrosiano; Gerald Graham; Murray Wolinsky; Mark A. Duchaineau; Bernd Hamann; Kenneth I. Joy
We present a new method for constructing multiresolution representations of data sets that contain material interfaces. Material interfaces embedded in the meshes of computational data sets are often a source of error for simplification algorithms because they represent discontinuities in the scalar or vector field over mesh elements. By representing material interfaces explicitly, we are able to provide separate field representations for each material over a single cell. Multiresolution representations utilizing separate field representations can accurately approximate datasets that contain discontinuities without placing a large percentage of cells around the discontinuous regions. Our algorithm uses a multiresolution tetrahedral mesh supporting fast coarsening and refinement capabilities; error bounds for feature preservation; explicit representation of discontinuities within cells; and separate field representations for each material within a cell.