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Sample records for solexa sequencing dataset

  1. An efficient annotation and gene-expression derivation tool for Illumina Solexa datasets.

    Science.gov (United States)

    Hosseini, Parsa; Tremblay, Arianne; Matthews, Benjamin F; Alkharouf, Nadim W

    2010-07-02

    The data produced by an Illumina flow cell with all eight lanes occupied, produces well over a terabyte worth of images with gigabytes of reads following sequence alignment. The ability to translate such reads into meaningful annotation is therefore of great concern and importance. Very easily, one can get flooded with such a great volume of textual, unannotated data irrespective of read quality or size. CASAVA, a optional analysis tool for Illumina sequencing experiments, enables the ability to understand INDEL detection, SNP information, and allele calling. To not only extract from such analysis, a measure of gene expression in the form of tag-counts, but furthermore to annotate such reads is therefore of significant value. We developed TASE (Tag counting and Analysis of Solexa Experiments), a rapid tag-counting and annotation software tool specifically designed for Illumina CASAVA sequencing datasets. Developed in Java and deployed using jTDS JDBC driver and a SQL Server backend, TASE provides an extremely fast means of calculating gene expression through tag-counts while annotating sequenced reads with the gene's presumed function, from any given CASAVA-build. Such a build is generated for both DNA and RNA sequencing. Analysis is broken into two distinct components: DNA sequence or read concatenation, followed by tag-counting and annotation. The end result produces output containing the homology-based functional annotation and respective gene expression measure signifying how many times sequenced reads were found within the genomic ranges of functional annotations. TASE is a powerful tool to facilitate the process of annotating a given Illumina Solexa sequencing dataset. Our results indicate that both homology-based annotation and tag-count analysis are achieved in very efficient times, providing researchers to delve deep in a given CASAVA-build and maximize information extraction from a sequencing dataset. TASE is specially designed to translate sequence data

  2. Sequencing of chloroplast genome using whole cellular DNA and Solexa sequencing technology

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    Jian eWu

    2012-11-01

    Full Text Available Sequencing of the chloroplast genome using traditional sequencing methods has been difficult because of its size (>120 kb and the complicated procedures required to prepare templates. To explore the feasibility of sequencing the chloroplast genome using DNA extracted from whole cells and Solexa sequencing technology, we sequenced whole cellular DNA isolated from leaves of three Brassica rapa accessions with one lane per accession. In total, 246 Mb, 362Mb, 361 Mb sequence data were generated for the three accessions Chiifu-401-42, Z16 and FT, respectively. Microreads were assembled by reference-guided assembly using the cpDNA sequences of B. rapa, Arabidopsis thaliana, and Nicotiana tabacum. We achieved coverage of more than 99.96% of the cp genome in the three tested accessions using the B. rapa sequence as the reference. When A. thaliana or N. tabacum sequences were used as references, 99.7–99.8% or 95.5–99.7% of the B. rapa chloroplast genome was covered, respectively. These results demonstrated that sequencing of whole cellular DNA isolated from young leaves using the Illumina Genome Analyzer is an efficient method for high-throughput sequencing of chloroplast genome.

  3. Identification of microRNA-Like RNAs in the filamentous fungus Trichoderma reesei by solexa sequencing.

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    Kang Kang

    Full Text Available microRNAs (miRNAs are non-coding small RNAs (sRNAs capable of negatively regulating gene expression. Recently, microRNA-like small RNAs (milRNAs were discovered in several filamentous fungi but not yet in Trichoderma reesei, an industrial filamentous fungus that can secrete abundant hydrolases. To explore the presence of milRNA in T. reesei and evaluate their expression under induction of cellulose, two T. reesei sRNA libraries of cellulose induction (IN and non-induction (CON were generated and sequenced using Solexa sequencing technology. A total of 726 and 631 sRNAs were obtained from the IN and CON samples, respectively. Global expression analysis showed an extensively differential expression of sRNAs in T. reesei under the two conditions. Thirteen predicted milRNAs were identified in T. reesei based on the short hairpin structure analysis. The milRNA profiles obtained in deep sequencing were further validated by RT-qPCR assay. Computational analysis predicted a number of potential targets relating to many processes including regulation of enzyme expression. The presence and differential expression of T. reesei milRNAs imply that milRNA might play a role in T. reesei growth and cellulase induction. This work lays foundation for further functional study of fungal milRNAs and their industrial application.

  4. Discovery of cashmere goat (Capra hircus) microRNAs in skin and hair follicles by Solexa sequencing.

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    Yuan, Chao; Wang, Xiaolong; Geng, Rongqing; He, Xiaolin; Qu, Lei; Chen, Yulin

    2013-07-28

    MicroRNAs (miRNAs) are a large family of endogenous, non-coding RNAs, about 22 nucleotides long, which regulate gene expression through sequence-specific base pairing with target mRNAs. Extensive studies have shown that miRNA expression in the skin changes remarkably during distinct stages of the hair cycle in humans, mice, goats and sheep. In this study, the skin tissues were harvested from the three stages of hair follicle cycling (anagen, catagen and telogen) in a fibre-producing goat breed. In total, 63,109,004 raw reads were obtained by Solexa sequencing and 61,125,752 clean reads remained for the small RNA digitalisation analysis. This resulted in the identification of 399 conserved miRNAs; among these, 326 miRNAs were expressed in all three follicular cycling stages, whereas 3, 12 and 11 miRNAs were specifically expressed in anagen, catagen, and telogen, respectively. We also identified 172 potential novel miRNAs by Mireap, 36 miRNAs were expressed in all three cycling stages, whereas 23, 29 and 44 miRNAs were specifically expressed in anagen, catagen, and telogen, respectively. The expression level of five arbitrarily selected miRNAs was analyzed by quantitative PCR, and the results indicated that the expression patterns were consistent with the Solexa sequencing results. Gene Ontology and KEGG pathway analyses indicated that five major biological pathways (Metabolic pathways, Pathways in cancer, MAPK signalling pathway, Endocytosis and Focal adhesion) accounted for 23.08% of target genes among 278 biological functions, indicating that these pathways are likely to play significant roles during hair cycling. During all hair cycle stages of cashmere goats, a large number of conserved and novel miRNAs were identified through a high-throughput sequencing approach. This study enriches the Capra hircus miRNA databases and provides a comprehensive miRNA transcriptome profile in the skin of goats during the hair follicle cycle.

  5. Solexa sequencing identification of conserved and novel microRNAs in backfat of Large White and Chinese Meishan pigs.

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    Chen Chen

    Full Text Available The domestic pig (Sus scrofa, an important species in animal production industry, is a right model for studying adipogenesis and fat deposition. In order to expand the repertoire of porcine miRNAs and further explore potential regulatory miRNAs which have influence on adipogenesis, high-throughput Solexa sequencing approach was adopted to identify miRNAs in backfat of Large White (lean type pig and Meishan pigs (Chinese indigenous fatty pig. We identified 215 unique miRNAs comprising 75 known pre-miRNAs, of which 49 miRNA*s were first identified in our study, 73 miRNAs were overlapped in both libraries, and 140 were novelly predicted miRNAs, and 215 unique miRNAs were collectively corresponding to 235 independent genomic loci. Furthermore, we analyzed the sequence variations, seed edits and phylogenetic development of the miRNAs. 17 miRNAs were widely conserved from vertebrates to invertebrates, suggesting that these miRNAs may serve as potential evolutional biomarkers. 9 conserved miRNAs with significantly differential expressions were determined. The expression of miR-215, miR-135, miR-224 and miR-146b was higher in Large White pigs, opposite to the patterns shown by miR-1a, miR-133a, miR-122, miR-204 and miR-183. Almost all novel miRNAs could be considered pig-specific except ssc-miR-1343, miR-2320, miR-2326, miR-2411 and miR-2483 which had homologs in Bos taurus, among which ssc-miR-1343, miR-2320, miR-2411 and miR-2483 were validated in backfat tissue by stem-loop qPCR. Our results displayed a high level of concordance between the qPCR and Solexa sequencing method in 9 of 10 miRNAs comparisons except for miR-1a. Moreover, we found 2 miRNAs, miR-135 and miR-183, may exert impacts on porcine backfat development through WNT signaling pathway. In conclusion, our research develops porcine miRNAs and should be beneficial to study the adipogenesis and fat deposition of different pig breeds based on miRNAs.

  6. Genome-wide profiling of DNA-binding proteins using barcode-based multiplex Solexa sequencing.

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    Raghav, Sunil Kumar; Deplancke, Bart

    2012-01-01

    Chromatin immunoprecipitation (ChIP) is a commonly used technique to detect the in vivo binding of proteins to DNA. ChIP is now routinely paired to microarray analysis (ChIP-chip) or next-generation sequencing (ChIP-Seq) to profile the DNA occupancy of proteins of interest on a genome-wide level. Because ChIP-chip introduces several biases, most notably due to the use of a fixed number of probes, ChIP-Seq has quickly become the method of choice as, depending on the sequencing depth, it is more sensitive, quantitative, and provides a greater binding site location resolution. With the ever increasing number of reads that can be generated per sequencing run, it has now become possible to analyze several samples simultaneously while maintaining sufficient sequence coverage, thus significantly reducing the cost per ChIP-Seq experiment. In this chapter, we provide a step-by-step guide on how to perform multiplexed ChIP-Seq analyses. As a proof-of-concept, we focus on the genome-wide profiling of RNA Polymerase II as measuring its DNA occupancy at different stages of any biological process can provide insights into the gene regulatory mechanisms involved. However, the protocol can also be used to perform multiplexed ChIP-Seq analyses of other DNA-binding proteins such as chromatin modifiers and transcription factors.

  7. A combination of LongSAGE with Solexa sequencing is well suited to explore the depth and the complexity of transcriptome

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    Scoté-Blachon Céline

    2008-09-01

    Full Text Available Abstract Background "Open" transcriptome analysis methods allow to study gene expression without a priori knowledge of the transcript sequences. As of now, SAGE (Serial Analysis of Gene Expression, LongSAGE and MPSS (Massively Parallel Signature Sequencing are the mostly used methods for "open" transcriptome analysis. Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript. In contrast to LongSAGE, the high throughput sequencing method used in MPSS enables the rapid sequencing of very large libraries containing several millions of tags, allowing deep transcriptome analysis. However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered. Results In order to make a deep analysis of mouse hypothalamus transcriptome avoiding the limitation introduced by MPSS, we combined LongSAGE with the Solexa sequencing technology and obtained a library of more than 11 millions of tags. We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method. Conclusion We found that Solexa sequencing technology combined with LongSAGE is perfectly suited for deep transcriptome analysis. In contrast to MPSS, it gives a complex representation of transcriptome as reliable as a LongSAGE library sequenced by the Sanger method.

  8. Identification and differential expression of microRNAs in ovaries of laying and Broody geese (Anser cygnoides by Solexa sequencing.

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    Qi Xu

    Full Text Available BACKGROUND: Recent functional studies have demonstrated that the microRNAs (miRNAs play critical roles in ovarian gonadal development, steroidogenesis, apoptosis, and ovulation in mammals. However, little is known about the involvement of miRNAs in the ovarian function of fowl. The goose (Anas cygnoides is a commercially important food that is cultivated widely in China but the goose industry has been hampered by high broodiness and poor egg laying performance, which are influenced by ovarian function. METHODOLOGY/PRINCIPAL FINDINGS: In this study, the miRNA transcriptomes of ovaries from laying and broody geese were profiled using Solexa deep sequencing and bioinformatics was used to determine differential expression of the miRNAs. As a result, 11,350,396 and 9,890,887 clean reads were obtained in laying and broodiness goose, respectively, and 1,328 conserved known miRNAs and 22 novel potential miRNA candidates were identified. A total of 353 conserved microRNAs were significantly differentially expressed between laying and broody ovaries. Compared with miRNA expression in the laying ovary, 127 miRNAs were up-regulated and 126 miRNAs were down-regulated in the ovary of broody birds. A subset of the differentially expressed miRNAs (G-miR-320, G-miR-202, G-miR-146, and G-miR-143* were validated using real-time quantitative PCR. In addition, 130,458 annotated mRNA transcripts were identified as putative target genes. Gene ontology annotation and KEGG (Kyoto Encyclopedia of Genes and Genomes pathway analysis suggested that the differentially expressed miRNAs are involved in ovarian function, including hormone secretion, reproduction processes and so on. CONCLUSIONS: The present study provides the first global miRNA transcriptome data in A. cygnoides and identifies novel and known miRNAs that are differentially expressed between the ovaries of laying and broody geese. These findings contribute to our understanding of the functional involvement of mi

  9. MicroRNA of the fifth-instar posterior silk gland of silkworm identified by Solexa sequencing

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    Jisheng Li

    2014-12-01

    Full Text Available No special studies have been focused on the microRNA (miRNA in the fifth-instar posterior silk gland of Bombyx mori. Here, using next-generation sequencing, we acquired 93.2 million processed reads from 10 small RNA libraries. In this paper, we tried to thoroughly describe how our dataset generated from deep sequencing which was recently published in BMC genomics. Results showed that our findings are largely enriched silkworm miRNA depository and may benefit us to reveal the miRNA functions in the process of silk production.

  10. Solexa sequencing and custom microRNA chip reveal repertoire of microRNAs in mammary gland of bovine suffering from natural infectious mastitis.

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    Ju, Zhihua; Jiang, Qiang; Liu, Gang; Wang, Xiuge; Luo, Guojing; Zhang, Yan; Zhang, Jibin; Zhong, Jifeng; Huang, Jinming

    2018-02-01

    Identification of microRNAs (miRNAs), target genes and regulatory networks associated with innate immune and inflammatory responses and tissue damage is essential to elucidate the molecular and genetic mechanisms for resistance to mastitis. In this study, a combination of Solexa sequencing and custom miRNA chip approaches was used to profile the expression of miRNAs in bovine mammary gland at the late stage of natural infection with Staphylococcus aureus, a widespread mastitis pathogen. We found 383 loci corresponding to 277 known and 49 putative novel miRNAs, two potential mitrons and 266 differentially expressed miRNAs in the healthy and mastitic cows' mammary glands. Several interaction networks and regulators involved in mastitis susceptibility, such as ALCAM, COL1A1, APOP4, ITIH4, CRP and fibrinogen alpha (FGA), were highlighted. Significant down-regulation and location of bta-miR-26a, which targets FGA in the mastitic mammary glands, were validated using quantitative real-time PCR, in situ hybridization and dual-luciferase reporter assays. We propose that the observed miRNA variations in mammary glands of mastitic cows are related to the maintenance of immune and defense responses, cell proliferation and apoptosis, and tissue injury and healing during the late stage of infection. Furthermore, the effect of bta-miR-26a in mastitis, mediated at least in part by enhancing FGA expression, involves host defense, inflammation and tissue damage. © 2018 Stichting International Foundation for Animal Genetics.

  11. Geoseq: a tool for dissecting deep-sequencing datasets

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    Homann Robert

    2010-10-01

    Full Text Available Abstract Background Datasets generated on deep-sequencing platforms have been deposited in various public repositories such as the Gene Expression Omnibus (GEO, Sequence Read Archive (SRA hosted by the NCBI, or the DNA Data Bank of Japan (ddbj. Despite being rich data sources, they have not been used much due to the difficulty in locating and analyzing datasets of interest. Results Geoseq http://geoseq.mssm.edu provides a new method of analyzing short reads from deep sequencing experiments. Instead of mapping the reads to reference genomes or sequences, Geoseq maps a reference sequence against the sequencing data. It is web-based, and holds pre-computed data from public libraries. The analysis reduces the input sequence to tiles and measures the coverage of each tile in a sequence library through the use of suffix arrays. The user can upload custom target sequences or use gene/miRNA names for the search and get back results as plots and spreadsheet files. Geoseq organizes the public sequencing data using a controlled vocabulary, allowing identification of relevant libraries by organism, tissue and type of experiment. Conclusions Analysis of small sets of sequences against deep-sequencing datasets, as well as identification of public datasets of interest, is simplified by Geoseq. We applied Geoseq to, a identify differential isoform expression in mRNA-seq datasets, b identify miRNAs (microRNAs in libraries, and identify mature and star sequences in miRNAS and c to identify potentially mis-annotated miRNAs. The ease of using Geoseq for these analyses suggests its utility and uniqueness as an analysis tool.

  12. Using quality scores and longer reads improves accuracy of Solexa read mapping

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    Xuan Zhenyu

    2008-02-01

    Full Text Available Abstract Background Second-generation sequencing has the potential to revolutionize genomics and impact all areas of biomedical science. New technologies will make re-sequencing widely available for such applications as identifying genome variations or interrogating the oligonucleotide content of a large sample (e.g. ChIP-sequencing. The increase in speed, sensitivity and availability of sequencing technology brings demand for advances in computational technology to perform associated analysis tasks. The Solexa/Illumina 1G sequencer can produce tens of millions of reads, ranging in length from ~25–50 nt, in a single experiment. Accurately mapping the reads back to a reference genome is a critical task in almost all applications. Two sources of information that are often ignored when mapping reads from the Solexa technology are the 3' ends of longer reads, which contain a much higher frequency of sequencing errors, and the base-call quality scores. Results To investigate whether these sources of information can be used to improve accuracy when mapping reads, we developed the RMAP tool, which can map reads having a wide range of lengths and allows base-call quality scores to determine which positions in each read are more important when mapping. We applied RMAP to analyze data re-sequenced from two human BAC regions for varying read lengths, and varying criteria for use of quality scores. RMAP is freely available for downloading at http://rulai.cshl.edu/rmap/. Conclusion Our results indicate that significant gains in Solexa read mapping performance can be achieved by considering the information in 3' ends of longer reads, and appropriately using the base-call quality scores. The RMAP tool we have developed will enable researchers to effectively exploit this information in targeted re-sequencing projects.

  13. fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

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    Madrigal, Pedro

    2017-03-01

    Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . pmb59@cam.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  14. Genetic architecture of vitamin B12 and folate levels uncovered applying deeply sequenced large datasets

    DEFF Research Database (Denmark)

    Grarup, Niels; Sulem, Patrick; Sandholt, Camilla H

    2013-01-01

    of the underlying biology of human traits and diseases. Here, we used a large Icelandic whole genome sequence dataset combined with Danish exome sequence data to gain insight into the genetic architecture of serum levels of vitamin B12 (B12) and folate. Up to 22.9 million sequence variants were analyzed in combined...... in serum B12 or folate levels do not modify the risk of developing these conditions. Yet, the study demonstrates the value of combining whole genome and exome sequencing approaches to ascertain the genetic and molecular architectures underlying quantitative trait associations....

  15. Re-inspection of small RNA sequence datasets reveals several novel human miRNA genes.

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    Thomas Birkballe Hansen

    Full Text Available BACKGROUND: miRNAs are key players in gene expression regulation. To fully understand the complex nature of cellular differentiation or initiation and progression of disease, it is important to assess the expression patterns of as many miRNAs as possible. Thereby, identifying novel miRNAs is an essential prerequisite to make possible a comprehensive and coherent understanding of cellular biology. METHODOLOGY/PRINCIPAL FINDINGS: Based on two extensive, but previously published, small RNA sequence datasets from human embryonic stem cells and human embroid bodies, respectively [1], we identified 112 novel miRNA-like structures and were able to validate miRNA processing in 12 out of 17 investigated cases. Several miRNA candidates were furthermore substantiated by including additional available small RNA datasets, thereby demonstrating the power of combining datasets to identify miRNAs that otherwise may be assigned as experimental noise. CONCLUSIONS/SIGNIFICANCE: Our analysis highlights that existing datasets are not yet exhaustedly studied and continuous re-analysis of the available data is important to uncover all features of small RNA sequencing.

  16. Haematobia irritans dataset of raw sequence reads from Illumina and Pac Bio sequencing of genomic DNA

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    The genome of the horn fly, Haematobia irritans, was sequenced using Illumina- and Pac Bio-based protocols. Following quality filtering, the raw reads have been deposited at NCBI under the BioProject and BioSample accession numbers PRJNA30967 and SAMN07830356, respectively. The Illumina reads are un...

  17. TRDistiller: a rapid filter for enrichment of sequence datasets with proteins containing tandem repeats.

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    Richard, François D; Kajava, Andrey V

    2014-06-01

    The dramatic growth of sequencing data evokes an urgent need to improve bioinformatics tools for large-scale proteome analysis. Over the last two decades, the foremost efforts of computer scientists were devoted to proteins with aperiodic sequences having globular 3D structures. However, a large portion of proteins contain periodic sequences representing arrays of repeats that are directly adjacent to each other (so called tandem repeats or TRs). These proteins frequently fold into elongated fibrous structures carrying different fundamental functions. Algorithms specific to the analysis of these regions are urgently required since the conventional approaches developed for globular domains have had limited success when applied to the TR regions. The protein TRs are frequently not perfect, containing a number of mutations, and some of them cannot be easily identified. To detect such "hidden" repeats several algorithms have been developed. However, the most sensitive among them are time-consuming and, therefore, inappropriate for large scale proteome analysis. To speed up the TR detection we developed a rapid filter that is based on the comparison of composition and order of short strings in the adjacent sequence motifs. Tests show that our filter discards up to 22.5% of proteins which are known to be without TRs while keeping almost all (99.2%) TR-containing sequences. Thus, we are able to decrease the size of the initial sequence dataset enriching it with TR-containing proteins which allows a faster subsequent TR detection by other methods. The program is available upon request. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. TIMPs of parasitic helminths - a large-scale analysis of high-throughput sequence datasets.

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    Cantacessi, Cinzia; Hofmann, Andreas; Pickering, Darren; Navarro, Severine; Mitreva, Makedonka; Loukas, Alex

    2013-05-30

    Tissue inhibitors of metalloproteases (TIMPs) are a multifunctional family of proteins that orchestrate extracellular matrix turnover, tissue remodelling and other cellular processes. In parasitic helminths, such as hookworms, TIMPs have been proposed to play key roles in the host-parasite interplay, including invasion of and establishment in the vertebrate animal hosts. Currently, knowledge of helminth TIMPs is limited to a small number of studies on canine hookworms, whereas no information is available on the occurrence of TIMPs in other parasitic helminths causing neglected diseases. In the present study, we conducted a large-scale investigation of TIMP proteins of a range of neglected human parasites including the hookworm Necator americanus, the roundworm Ascaris suum, the liver flukes Clonorchis sinensis and Opisthorchis viverrini, as well as the schistosome blood flukes. This entailed mining available transcriptomic and/or genomic sequence datasets for the presence of homologues of known TIMPs, predicting secondary structures of defined protein sequences, systematic phylogenetic analyses and assessment of differential expression of genes encoding putative TIMPs in the developmental stages of A. suum, N. americanus and Schistosoma haematobium which infect the mammalian hosts. A total of 15 protein sequences with high homology to known eukaryotic TIMPs were predicted from the complement of sequence data available for parasitic helminths and subjected to in-depth bioinformatic analyses. Supported by the availability of gene manipulation technologies such as RNA interference and/or transgenesis, this work provides a basis for future functional explorations of helminth TIMPs and, in particular, of their role/s in fundamental biological pathways linked to long-term establishment in the vertebrate hosts, with a view towards the development of novel approaches for the control of neglected helminthiases.

  19. NGSUtils: a software suite for analyzing and manipulating next-generation sequencing datasets

    OpenAIRE

    Breese, Marcus R.; Liu, Yunlong

    2013-01-01

    Summary: NGSUtils is a suite of software tools for manipulating data common to next-generation sequencing experiments, such as FASTQ, BED and BAM format files. These tools provide a stable and modular platform for data management and analysis.

  20. Haematobia irritans dataset of raw sequence reads from Illumina-based transcriptome sequencing of specific tissues and life stages

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    Illumina HiSeq technology was used to sequence the transcriptome from various dissected tissues and life stages from the horn fly, Haematobia irritans. These samples include eggs (0, 2, 4, and 9 hours post-oviposition), adult fly gut, adult fly legs, adult fly malpighian tubule, adult fly ovary, adu...

  1. NSAMD: A new approach to discover structured contiguous substrings in sequence datasets using Next-Symbol-Array.

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    Pari, Abdolvahed; Baraani, Ahmad; Parseh, Saeed

    2016-10-01

    In many sequence data mining applications, the goal is to find frequent substrings. Some of these applications like extracting motifs in protein and DNA sequences are looking for frequently occurring approximate contiguous substrings called simple motifs. By approximate we mean that some mismatches are allowed during similarity test between substrings, and it helps to discover unknown patterns. Structured motifs in DNA sequences are frequent structured contiguous substrings which contains two or more simple motifs. There are some works that have been done to find simple motifs but these works have problems such as low scalability, high execution time, no guarantee to find all patterns, and low flexibility in adaptation to other application. The Flame is the only algorithm that can find all unknown structured patterns in a dataset and has solved most of these problems but its scalability for very large sequences is still weak. In this research a new approach named Next-Symbol-Array based Motif Discovery (NSAMD) is represented to improve scalability in extracting all unknown simple and structured patterns. To reach this goal a new data structure has been presented called Next-Symbol-Array. This data structure makes change in how to find patterns by NSAMD in comparison with Flame and helps to find structured motif faster. Proposed algorithm is as accurate as Flame and extracts all existing patterns in dataset. Performance comparisons show that NSAMD outperforms Flame in extracting structured motifs in both execution time (51% faster) and memory usage (more than 99%). Proposed algorithm is slower in extracting simple motifs but considerable improvement in memory usage (more than 99%) makes NSAMD more scalable than Flame. This advantage of NSAMD is very important in biological applications in which very large sequences are applied. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Dataset of the HOX1 gene sequences of the wheat polyploids and their diploid relatives

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    Andrey B. Shcherban

    2018-02-01

    Full Text Available The TaHOX-1 gene of common wheat Triticum aestivum L. (BAD-genome encodes transcription factor (HD-Zip I which is characterized by the presence of a DNA-binding homeodomain (HD with an adjacent Leucine zipper (LZ motif. This gene can play a role in adapting plant to a variety of abiotic stresses, such as drought, cold, salinity etc., which strongly affect wheat production. However, it's both functional role in stress resistance and divergence during wheat evolution has not yet been elucidated. This data in brief article is associated with the research paper “Structural and functional divergence of homoeologous copies of the TaHOX-1 gene in polyploid wheats and their diploid ancestors”. The data set represents a recent survey of the primary HOX-1 gene sequences isolated from the first wheat allotetraploids (BA-genome and their corresponding Triticum and Aegilops diploid relatives. Specifically, we provide detailed information about the HOX-1 nucleotide sequences of the promoter region and both nucleotide and amino acid sequences of the gene. The sequencing data used here is available at DDBJ/EMBL/GenBank under the accession numbers MG000630-MG000698. Keywords: Wheat, Polyploid, HOX-1 gene, Homeodomain, Transcription factor, Promoter, Triticum, Aegilops

  3. Insights into SCP/TAPS proteins of liver flukes based on large-scale bioinformatic analyses of sequence datasets.

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    Cinzia Cantacessi

    Full Text Available BACKGROUND: SCP/TAPS proteins of parasitic helminths have been proposed to play key roles in fundamental biological processes linked to the invasion of and establishment in their mammalian host animals, such as the transition from free-living to parasitic stages and the modulation of host immune responses. Despite the evidence that SCP/TAPS proteins of parasitic nematodes are involved in host-parasite interactions, there is a paucity of information on this protein family for parasitic trematodes of socio-economic importance. METHODOLOGY/PRINCIPAL FINDINGS: We conducted the first large-scale study of SCP/TAPS proteins of a range of parasitic trematodes of both human and veterinary importance (including the liver flukes Clonorchis sinensis, Opisthorchis viverrini, Fasciola hepatica and F. gigantica as well as the blood flukes Schistosoma mansoni, S. japonicum and S. haematobium. We mined all current transcriptomic and/or genomic sequence datasets from public databases, predicted secondary structures of full-length protein sequences, undertook systematic phylogenetic analyses and investigated the differential transcription of SCP/TAPS genes in O. viverrini and F. hepatica, with an emphasis on those that are up-regulated in the developmental stages infecting the mammalian host. CONCLUSIONS: This work, which sheds new light on SCP/TAPS proteins, guides future structural and functional explorations of key SCP/TAPS molecules associated with diseases caused by flatworms. Future fundamental investigations of these molecules in parasites and the integration of structural and functional data could lead to new approaches for the control of parasitic diseases.

  4. Large-Scale Isolation of Microsatellites from Chinese Mitten Crab Eriocheir sinensis via a Solexa Genomic Survey

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    Qun Wang

    2012-12-01

    Full Text Available Microsatellites are simple sequence repeats with a high degree of polymorphism in the genome; they are used as DNA markers in many molecular genetic studies. Using traditional methods such as the magnetic beads enrichment method, only a few microsatellite markers have been isolated from the Chinese mitten crab Eriocheir sinensis, as the crab genome sequence information is unavailable. Here, we have identified a large number of microsatellites from the Chinese mitten crab by taking advantage of Solexa genomic surveying. A total of 141,737 SSR (simple sequence repeats motifs were identified via analysis of 883 Mb of the crab genomic DNA information, including mono-, di-, tri-, tetra-, penta- and hexa-nucleotide repeat motifs. The number of di-nucleotide repeat motifs was 82,979, making this the most abundant type of repeat motif (58.54%; the second most abundant were the tri-nucleotide repeats (42,657, 30.11%. Among di-nucleotide repeats, the most frequent repeats were AC motifs, accounting for 67.55% of the total number. AGG motifs were the most frequent (59.32% of the tri-nucleotide motifs. A total of 15,125 microsatellite loci had a flanking sequence suitable for setting the primer of a polymerase chain reaction (PCR. To verify the identified SSRs, a subset of 100 primer pairs was randomly selected for PCR. Eighty two primer sets (82% produced strong PCR products matching expected sizes, and 78% were polymorphic. In an analysis of 30 wild individuals from the Yangtze River with 20 primer sets, the number of alleles per locus ranged from 2–14 and the mean allelic richness was 7.4. No linkage disequilibrium was found between any pair of loci, indicating that the markers were independent. The Hardy-Weinberg equilibrium test showed significant deviation in four of the 20 microsatellite loci after sequential Bonferroni corrections. This method is cost- and time-effective in comparison to traditional approaches for the isolation of microsatellites.

  5. DSAP: deep-sequencing small RNA analysis pipeline.

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    Huang, Po-Jung; Liu, Yi-Chung; Lee, Chi-Ching; Lin, Wei-Chen; Gan, Richie Ruei-Chi; Lyu, Ping-Chiang; Tang, Petrus

    2010-07-01

    DSAP is an automated multiple-task web service designed to provide a total solution to analyzing deep-sequencing small RNA datasets generated by next-generation sequencing technology. DSAP uses a tab-delimited file as an input format, which holds the unique sequence reads (tags) and their corresponding number of copies generated by the Solexa sequencing platform. The input data will go through four analysis steps in DSAP: (i) cleanup: removal of adaptors and poly-A/T/C/G/N nucleotides; (ii) clustering: grouping of cleaned sequence tags into unique sequence clusters; (iii) non-coding RNA (ncRNA) matching: sequence homology mapping against a transcribed sequence library from the ncRNA database Rfam (http://rfam.sanger.ac.uk/); and (iv) known miRNA matching: detection of known miRNAs in miRBase (http://www.mirbase.org/) based on sequence homology. The expression levels corresponding to matched ncRNAs and miRNAs are summarized in multi-color clickable bar charts linked to external databases. DSAP is also capable of displaying miRNA expression levels from different jobs using a log(2)-scaled color matrix. Furthermore, a cross-species comparative function is also provided to show the distribution of identified miRNAs in different species as deposited in miRBase. DSAP is available at http://dsap.cgu.edu.tw.

  6. Metaxa: a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets.

    Science.gov (United States)

    Bengtsson, Johan; Eriksson, K Martin; Hartmann, Martin; Wang, Zheng; Shenoy, Belle Damodara; Grelet, Gwen-Aëlle; Abarenkov, Kessy; Petri, Anna; Rosenblad, Magnus Alm; Nilsson, R Henrik

    2011-10-01

    The ribosomal small subunit (SSU) rRNA gene has emerged as an important genetic marker for taxonomic identification in environmental sequencing datasets. In addition to being present in the nucleus of eukaryotes and the core genome of prokaryotes, the gene is also found in the mitochondria of eukaryotes and in the chloroplasts of photosynthetic eukaryotes. These three sets of genes are conceptually paralogous and should in most situations not be aligned and analyzed jointly. To identify the origin of SSU sequences in complex sequence datasets has hitherto been a time-consuming and largely manual undertaking. However, the present study introduces Metaxa ( http://microbiology.se/software/metaxa/ ), an automated software tool to extract full-length and partial SSU sequences from larger sequence datasets and assign them to an archaeal, bacterial, nuclear eukaryote, mitochondrial, or chloroplast origin. Using data from reference databases and from full-length organelle and organism genomes, we show that Metaxa detects and scores SSU sequences for origin with very low proportions of false positives and negatives. We believe that this tool will be useful in microbial and evolutionary ecology as well as in metagenomics.

  7. Sequence-function-stability relationships in proteins from datasets of functionally annotated variants: The case of TEM beta-lactamases

    NARCIS (Netherlands)

    Abriata, L.A.; Salverda, M.L.M.; Tomatis, P.E.

    2012-01-01

    A dataset of TEM lactamase variants with different substrate and inhibition profiles was compiled and analyzed. Trends show that loops are the main evolvable regions in these enzymes, gradually accumulating mutations to generate increasingly complex functions. Notably, many mutations present in

  8. Rhipicephalus microplus dataset of nonredundant raw sequence reads from 454 GS FLX sequencing of Cot-selected (Cot = 660) genomic DNA

    Science.gov (United States)

    A reassociation kinetics-based approach was used to reduce the complexity of genomic DNA from the Deutsch laboratory strain of the cattle tick, Rhipicephalus microplus, to facilitate genome sequencing. Selected genomic DNA (Cot value = 660) was sequenced using 454 GS FLX technology, resulting in 356...

  9. Batch-processing of imaging or liquid-chromatography mass spectrometry datasets and De Novo sequencing of polyketide siderophores

    Czech Academy of Sciences Publication Activity Database

    Novák, Jiří; Sokolová, Lucie; Lemr, Karel; Pluháček, Tomáš; Palyzová, Andrea; Havlíček, Vladimír

    2017-01-01

    Roč. 1865, č. 7 (2017), s. 768-775 ISSN 1570-9639 R&D Projects: GA ČR(CZ) GA16-20229S; GA MŠk(CZ) LO1509 Institutional support: RVO:61388971 Keywords : Mass spectrometry imaging * De novo sequencing * Siderophores Subject RIV: EE - Microbiology, Virology OBOR OECD: Microbiology Impact factor: 2.773, year: 2016

  10. viRome: an R package for the visualization and analysis of viral small RNA sequence datasets.

    Science.gov (United States)

    Watson, Mick; Schnettler, Esther; Kohl, Alain

    2013-08-01

    RNA interference (RNAi) is known to play an important part in defence against viruses in a range of species. Second-generation sequencing technologies allow us to assay these systems and the small RNAs that play a key role with unprecedented depth. However, scientists need access to tools that can condense, analyse and display the resulting data. Here, we present viRome, a package for R that takes aligned sequence data and produces a range of essential plots and reports. viRome is released under the BSD license as a package for R available for both Windows and Linux http://virome.sf.net. Additional information and a tutorial is available on the ARK-Genomics website: http://www.ark-genomics.org/bioinformatics/virome. mick.watson@roslin.ed.ac.uk.

  11. Nested PCR Biases in Interpreting Microbial Community Structure in 16S rRNA Gene Sequence Datasets.

    Science.gov (United States)

    Yu, Guoqin; Fadrosh, Doug; Goedert, James J; Ravel, Jacques; Goldstein, Alisa M

    2015-01-01

    Sequencing of the PCR-amplified 16S rRNA gene has become a common approach to microbial community investigations in the fields of human health and environmental sciences. This approach, however, is difficult when the amount of DNA is too low to be amplified by standard PCR. Nested PCR can be employed as it can amplify samples with DNA concentration several-fold lower than standard PCR. However, potential biases with nested PCRs that could affect measurement of community structure have received little attention. In this study, we used 17 DNAs extracted from vaginal swabs and 12 DNAs extracted from stool samples to study the influence of nested PCR amplification of the 16S rRNA gene on the estimation of microbial community structure using Illumina MiSeq sequencing. Nested and standard PCR methods were compared on alpha- and beta-diversity metrics and relative abundances of bacterial genera. The effects of number of cycles in the first round of PCR (10 vs. 20) and microbial diversity (relatively low in vagina vs. high in stool) were also investigated. Vaginal swab samples showed no significant difference in alpha diversity or community structure between nested PCR and standard PCR (one round of 40 cycles). Stool samples showed significant differences in alpha diversity (except Shannon's index) and relative abundance of 13 genera between nested PCR with 20 cycles in the first round and standard PCR (Pnested PCR with 10 cycles in the first round and standard PCR. Operational taxonomic units (OTUs) that had low relative abundance (sum of relative abundance 27% of total OTUs in stool). Nested PCR introduced bias in estimated diversity and community structure. The bias was more significant for communities with relatively higher diversity and when more cycles were applied in the first round of PCR. We conclude that nested PCR could be used when standard PCR does not work. However, rare taxa detected by nested PCR should be validated by other technologies.

  12. Detection of a Usp-like gene in Calotropis procera plant from the de novo assembled genome contigs of the high-throughput sequencing dataset

    KAUST Repository

    Shokry, Ahmed M.

    2014-02-01

    The wild plant species Calotropis procera (C. procera) has many potential applications and beneficial uses in medicine, industry and ornamental field. It also represents an excellent source of genes for drought and salt tolerance. Genes encoding proteins that contain the conserved universal stress protein (USP) domain are known to provide organisms like bacteria, archaea, fungi, protozoa and plants with the ability to respond to a plethora of environmental stresses. However, information on the possible occurrence of Usp in C. procera is not available. In this study, we uncovered and characterized a one-class A Usp-like (UspA-like, NCBI accession No. KC954274) gene in this medicinal plant from the de novo assembled genome contigs of the high-throughput sequencing dataset. A number of GenBank accessions for Usp sequences were blasted with the recovered de novo assembled contigs. Homology modelling of the deduced amino acids (NCBI accession No. AGT02387) was further carried out using Swiss-Model, accessible via the EXPASY. Superimposition of C. procera USPA-like full sequence model on Thermus thermophilus USP UniProt protein (PDB accession No. Q5SJV7) was constructed using RasMol and Deep-View programs. The functional domains of the novel USPA-like amino acids sequence were identified from the NCBI conserved domain database (CDD) that provide insights into sequence structure/function relationships, as well as domain models imported from a number of external source databases (Pfam, SMART, COG, PRK, TIGRFAM). © 2014 Académie des sciences.

  13. A comparison of genotyping-by-sequencing analysis methods on low-coverage crop datasets shows advantages of a new workflow, GB-eaSy.

    Science.gov (United States)

    Wickland, Daniel P; Battu, Gopal; Hudson, Karen A; Diers, Brian W; Hudson, Matthew E

    2017-12-28

    . While GB-eaSy outperformed other individual methods on the datasets analyzed, our findings suggest that a comprehensive approach integrating the results from multiple GBS bioinformatics pipelines may be the optimal strategy to obtain the largest, most highly accurate SNP yield possible from low-coverage polyploid sequence data.

  14. Maximum likelihood and Bayesian analyses of a combined nucleotide sequence dataset for genetic characterization of a novel pestivirus, SVA/cont-08.

    Science.gov (United States)

    Liu, Lihong; Xia, Hongyan; Baule, Claudia; Belák, Sándor

    2009-01-01

    Bovine viral diarrhoea virus 1 (BVDV-1) and Bovine viral diarrhoea virus 2 (BVDV-2) are two recognised bovine pestivirus species of the genus Pestivirus. Recently, a pestivirus, termed SVA/cont-08, was detected in a batch of contaminated foetal calf serum originating from South America. Comparative sequence analysis showed that the SVA/cont-08 virus shares 15-28% higher sequence identity to pestivirus D32/00_'HoBi' than to members of BVDV-1 and BVDV-2. In order to reveal the phylogenetic relationship of SVA/cont-08 with other pestiviruses, a molecular dataset of 30 pestiviruses and 1,896 characters, comprising the 5'UTR, N(pro) and E2 gene regions, was analysed by two methods: maximum likelihood and Bayesian approach. An identical, well-supported tree topology was observed, where four pestiviruses (SVA/cont-08, D32/00_'HoBi', CH-KaHo/cont, and Th/04_KhonKaen) formed a monophyletic clade that is closely related to the BVDV-1 and BVDV-2 clades. The strategy applied in this study is useful for classifying novel pestiviruses in the future.

  15. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    The datasets presented in this article are related to the research articles entitled “Neutrophil Extracellular Traps in Ulcerative Colitis: A Proteome Analysis of Intestinal Biopsies” (Bennike et al., 2015 [1]), and “Proteome Analysis of Rheumatoid Arthritis Gut Mucosa” (Bennike et al., 2017 [2])...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  16. A practical comparison of de novo genome assembly software tools for next-generation sequencing technologies.

    Directory of Open Access Journals (Sweden)

    Wenyu Zhang

    Full Text Available The advent of next-generation sequencing technologies is accompanied with the development of many whole-genome sequence assembly methods and software, especially for de novo fragment assembly. Due to the poor knowledge about the applicability and performance of these software tools, choosing a befitting assembler becomes a tough task. Here, we provide the information of adaptivity for each program, then above all, compare the performance of eight distinct tools against eight groups of simulated datasets from Solexa sequencing platform. Considering the computational time, maximum random access memory (RAM occupancy, assembly accuracy and integrity, our study indicate that string-based assemblers, overlap-layout-consensus (OLC assemblers are well-suited for very short reads and longer reads of small genomes respectively. For large datasets of more than hundred millions of short reads, De Bruijn graph-based assemblers would be more appropriate. In terms of software implementation, string-based assemblers are superior to graph-based ones, of which SOAPdenovo is complex for the creation of configuration file. Our comparison study will assist researchers in selecting a well-suited assembler and offer essential information for the improvement of existing assemblers or the developing of novel assemblers.

  17. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    patients (Morgan et al., 2012; Abraham and Medzhitov, 2011; Bennike, 2014) [8–10. Therefore, we characterized the proteome of colon mucosa biopsies from 10 inflammatory bowel disease ulcerative colitis (UC) patients, 11 gastrointestinal healthy rheumatoid arthritis (RA) patients, and 10 controls. We...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  18. Digital PCR provides sensitive and absolute calibration for high throughput sequencing

    Directory of Open Access Journals (Sweden)

    Fan H Christina

    2009-03-01

    Full Text Available Abstract Background Next-generation DNA sequencing on the 454, Solexa, and SOLiD platforms requires absolute calibration of the number of molecules to be sequenced. This requirement has two unfavorable consequences. First, large amounts of sample-typically micrograms-are needed for library preparation, thereby limiting the scope of samples which can be sequenced. For many applications, including metagenomics and the sequencing of ancient, forensic, and clinical samples, the quantity of input DNA can be critically limiting. Second, each library requires a titration sequencing run, thereby increasing the cost and lowering the throughput of sequencing. Results We demonstrate the use of digital PCR to accurately quantify 454 and Solexa sequencing libraries, enabling the preparation of sequencing libraries from nanogram quantities of input material while eliminating costly and time-consuming titration runs of the sequencer. We successfully sequenced low-nanogram scale bacterial and mammalian DNA samples on the 454 FLX and Solexa DNA sequencing platforms. This study is the first to definitively demonstrate the successful sequencing of picogram quantities of input DNA on the 454 platform, reducing the sample requirement more than 1000-fold without pre-amplification and the associated bias and reduction in library depth. Conclusion The digital PCR assay allows absolute quantification of sequencing libraries, eliminates uncertainties associated with the construction and application of standard curves to PCR-based quantification, and with a coefficient of variation close to 10%, is sufficiently precise to enable direct sequencing without titration runs.

  19. Detection of a Usp-like gene in Calotropis procera plant from the de novo assembled genome contigs of the high-throughput sequencing dataset

    KAUST Repository

    Shokry, Ahmed M.; Al-Karim, Saleh; Ramadan, Ahmed M Ali; Gadallah, Nour; Al-Attas, Sanaa G.; Sabir, Jamal Sabir M; Hassan, Sabah Mohammed; Madkour, Loutfy H.; Bressan, Ray Anthony; Mahfouz, Magdy M.; Bahieldin, Ahmed M.

    2014-01-01

    acids sequence were identified from the NCBI conserved domain database (CDD) that provide insights into sequence structure/function relationships, as well as domain models imported from a number of external source databases (Pfam, SMART, COG, PRK

  20. A viral metagenomic approach on a non-metagenomic experiment: Mining next generation sequencing datasets from pig DNA identified several porcine parvoviruses for a retrospective evaluation of viral infections.

    Directory of Open Access Journals (Sweden)

    Samuele Bovo

    Full Text Available Shot-gun next generation sequencing (NGS on whole DNA extracted from specimens collected from mammals often produces reads that are not mapped (i.e. unmapped reads on the host reference genome and that are usually discarded as by-products of the experiments. In this study, we mined Ion Torrent reads obtained by sequencing DNA isolated from archived blood samples collected from 100 performance tested Italian Large White pigs. Two reduced representation libraries were prepared from two DNA pools constructed each from 50 equimolar DNA samples. Bioinformatic analyses were carried out to mine unmapped reads on the reference pig genome that were obtained from the two NGS datasets. In silico analyses included read mapping and sequence assembly approaches for a viral metagenomic analysis using the NCBI Viral Genome Resource. Our approach identified sequences matching several viruses of the Parvoviridae family: porcine parvovirus 2 (PPV2, PPV4, PPV5 and PPV6 and porcine bocavirus 1-H18 isolate (PBoV1-H18. The presence of these viruses was confirmed by PCR and Sanger sequencing of individual DNA samples. PPV2, PPV4, PPV5, PPV6 and PBoV1-H18 were all identified in samples collected in 1998-2007, 1998-2000, 1997-2000, 1998-2004 and 2003, respectively. For most of these viruses (PPV4, PPV5, PPV6 and PBoV1-H18 previous studies reported their first occurrence much later (from 5 to more than 10 years than our identification period and in different geographic areas. Our study provided a retrospective evaluation of apparently asymptomatic parvovirus infected pigs providing information that could be important to define occurrence and prevalence of different parvoviruses in South Europe. This study demonstrated the potential of mining NGS datasets non-originally derived by metagenomics experiments for viral metagenomics analyses in a livestock species.

  1. Experimental evolution, genetic analysis and genome re-sequencing reveal the mutation conferring artemisinin resistance in an isogenic lineage of malaria parasites

    KAUST Repository

    Hunt, Paul; Martinelli, Axel; Modrzynska, Katarzyna; Borges, Sofia; Creasey, Alison; Rodrigues, Louise; Beraldi, Dario; Loewe, Laurence; Fawcett, Richard; Kumar, Sujai; Thomson, Marian; Trivedi, Urmi; Otto, Thomas D; Pain, Arnab; Blaxter, Mark; Cravo, Pedro

    2010-01-01

    was mapped to a region of chromosome 2 by Linkage Group Selection in two different genetic crosses. Whole-genome deep coverage short-read re-sequencing (IlluminaSolexa) defined the point mutations, insertions, deletions and copy-number variations arising

  2. Genome Sequence Databases (Overview): Sequencing and Assembly

    Energy Technology Data Exchange (ETDEWEB)

    Lapidus, Alla L.

    2009-01-01

    From the date its role in heredity was discovered, DNA has been generating interest among scientists from different fields of knowledge: physicists have studied the three dimensional structure of the DNA molecule, biologists tried to decode the secrets of life hidden within these long molecules, and technologists invent and improve methods of DNA analysis. The analysis of the nucleotide sequence of DNA occupies a special place among the methods developed. Thanks to the variety of sequencing technologies available, the process of decoding the sequence of genomic DNA (or whole genome sequencing) has become robust and inexpensive. Meanwhile the assembly of whole genome sequences remains a challenging task. In addition to the need to assemble millions of DNA fragments of different length (from 35 bp (Solexa) to 800 bp (Sanger)), great interest in analysis of microbial communities (metagenomes) of different complexities raises new problems and pushes some new requirements for sequence assembly tools to the forefront. The genome assembly process can be divided into two steps: draft assembly and assembly improvement (finishing). Despite the fact that automatically performed assembly (or draft assembly) is capable of covering up to 98% of the genome, in most cases, it still contains incorrectly assembled reads. The error rate of the consensus sequence produced at this stage is about 1/2000 bp. A finished genome represents the genome assembly of much higher accuracy (with no gaps or incorrectly assembled areas) and quality ({approx}1 error/10,000 bp), validated through a number of computer and laboratory experiments.

  3. Genomics dataset of unidentified disclosed isolates

    Directory of Open Access Journals (Sweden)

    Bhagwan N. Rekadwad

    2016-09-01

    Full Text Available Analysis of DNA sequences is necessary for higher hierarchical classification of the organisms. It gives clues about the characteristics of organisms and their taxonomic position. This dataset is chosen to find complexities in the unidentified DNA in the disclosed patents. A total of 17 unidentified DNA sequences were thoroughly analyzed. The quick response codes were generated. AT/GC content of the DNA sequences analysis was carried out. The QR is helpful for quick identification of isolates. AT/GC content is helpful for studying their stability at different temperatures. Additionally, a dataset on cleavage code and enzyme code studied under the restriction digestion study, which helpful for performing studies using short DNA sequences was reported. The dataset disclosed here is the new revelatory data for exploration of unique DNA sequences for evaluation, identification, comparison and analysis. Keywords: BioLABs, Blunt ends, Genomics, NEB cutter, Restriction digestion, Short DNA sequences, Sticky ends

  4. EPA Nanorelease Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — EPA Nanorelease Dataset. This dataset is associated with the following publication: Wohlleben, W., C. Kingston, J. Carter, E. Sahle-Demessie, S. Vazquez-Campos, B....

  5. Low-pass shotgun sequencing of the barley genome facilitates rapid identification of genes, conserved non-coding sequences and novel repeats

    Directory of Open Access Journals (Sweden)

    Graner Andreas

    2008-10-01

    Full Text Available Abstract Background Barley has one of the largest and most complex genomes of all economically important food crops. The rise of new short read sequencing technologies such as Illumina/Solexa permits such large genomes to be effectively sampled at relatively low cost. Based on the corresponding sequence reads a Mathematically Defined Repeat (MDR index can be generated to map repetitive regions in genomic sequences. Results We have generated 574 Mbp of Illumina/Solexa sequences from barley total genomic DNA, representing about 10% of a genome equivalent. From these sequences we generated an MDR index which was then used to identify and mark repetitive regions in the barley genome. Comparison of the MDR plots with expert repeat annotation drawing on the information already available for known repetitive elements revealed a significant correspondence between the two methods. MDR-based annotation allowed for the identification of dozens of novel repeat sequences, though, which were not recognised by hand-annotation. The MDR data was also used to identify gene-containing regions by masking of repetitive sequences in eight de-novo sequenced bacterial artificial chromosome (BAC clones. For half of the identified candidate gene islands indeed gene sequences could be identified. MDR data were only of limited use, when mapped on genomic sequences from the closely related species Triticum monococcum as only a fraction of the repetitive sequences was recognised. Conclusion An MDR index for barley, which was obtained by whole-genome Illumina/Solexa sequencing, proved as efficient in repeat identification as manual expert annotation. Circumventing the labour-intensive step of producing a specific repeat library for expert annotation, an MDR index provides an elegant and efficient resource for the identification of repetitive and low-copy (i.e. potentially gene-containing sequences regions in uncharacterised genomic sequences. The restriction that a particular

  6. Special Issue: Next Generation DNA Sequencing

    Directory of Open Access Journals (Sweden)

    Paul Richardson

    2010-10-01

    Full Text Available Next Generation Sequencing (NGS refers to technologies that do not rely on traditional dideoxy-nucleotide (Sanger sequencing where labeled DNA fragments are physically resolved by electrophoresis. These new technologies rely on different strategies, but essentially all of them make use of real-time data collection of a base level incorporation event across a massive number of reactions (on the order of millions versus 96 for capillary electrophoresis for instance. The major commercial NGS platforms available to researchers are the 454 Genome Sequencer (Roche, Illumina (formerly Solexa Genome analyzer, the SOLiD system (Applied Biosystems/Life Technologies and the Heliscope (Helicos Corporation. The techniques and different strategies utilized by these platforms are reviewed in a number of the papers in this special issue. These technologies are enabling new applications that take advantage of the massive data produced by this next generation of sequencing instruments. [...

  7. Aaron Journal article datasets

    Data.gov (United States)

    U.S. Environmental Protection Agency — All figures used in the journal article are in netCDF format. This dataset is associated with the following publication: Sims, A., K. Alapaty , and S. Raman....

  8. Integrated Surface Dataset (Global)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Integrated Surface (ISD) Dataset (ISD) is composed of worldwide surface weather observations from over 35,000 stations, though the best spatial coverage is...

  9. Control Measure Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EPA Control Measure Dataset is a collection of documents describing air pollution control available to regulated facilities for the control and abatement of air...

  10. National Hydrography Dataset (NHD)

    Data.gov (United States)

    Kansas Data Access and Support Center — The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that comprise the...

  11. Market Squid Ecology Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains ecological information collected on the major adult spawning and juvenile habitats of market squid off California and the US Pacific Northwest....

  12. Tables and figure datasets

    Data.gov (United States)

    U.S. Environmental Protection Agency — Soil and air concentrations of asbestos in Sumas study. This dataset is associated with the following publication: Wroble, J., T. Frederick, A. Frame, and D....

  13. Isfahan MISP Dataset.

    Science.gov (United States)

    Kashefpur, Masoud; Kafieh, Rahele; Jorjandi, Sahar; Golmohammadi, Hadis; Khodabande, Zahra; Abbasi, Mohammadreza; Teifuri, Nilufar; Fakharzadeh, Ali Akbar; Kashefpoor, Maryam; Rabbani, Hossein

    2017-01-01

    An online depository was introduced to share clinical ground truth with the public and provide open access for researchers to evaluate their computer-aided algorithms. PHP was used for web programming and MySQL for database managing. The website was entitled "biosigdata.com." It was a fast, secure, and easy-to-use online database for medical signals and images. Freely registered users could download the datasets and could also share their own supplementary materials while maintaining their privacies (citation and fee). Commenting was also available for all datasets, and automatic sitemap and semi-automatic SEO indexing have been set for the site. A comprehensive list of available websites for medical datasets is also presented as a Supplementary (http://journalonweb.com/tempaccess/4800.584.JMSS_55_16I3253.pdf).

  14. Mridangam stroke dataset

    OpenAIRE

    CompMusic

    2014-01-01

    The audio examples were recorded from a professional Carnatic percussionist in a semi-anechoic studio conditions by Akshay Anantapadmanabhan using SM-58 microphones and an H4n ZOOM recorder. The audio was sampled at 44.1 kHz and stored as 16 bit wav files. The dataset can be used for training models for each Mridangam stroke. /n/nA detailed description of the Mridangam and its strokes can be found in the paper below. A part of the dataset was used in the following paper. /nAkshay Anantapadman...

  15. The GTZAN dataset

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    The GTZAN dataset appears in at least 100 published works, and is the most-used public dataset for evaluation in machine listening research for music genre recognition (MGR). Our recent work, however, shows GTZAN has several faults (repetitions, mislabelings, and distortions), which challenge...... of GTZAN, and provide a catalog of its faults. We review how GTZAN has been used in MGR research, and find few indications that its faults have been known and considered. Finally, we rigorously study the effects of its faults on evaluating five different MGR systems. The lesson is not to banish GTZAN...

  16. Comparison of recent SnIa datasets

    International Nuclear Information System (INIS)

    Sanchez, J.C. Bueno; Perivolaropoulos, L.; Nesseris, S.

    2009-01-01

    We rank the six latest Type Ia supernova (SnIa) datasets (Constitution (C), Union (U), ESSENCE (Davis) (E), Gold06 (G), SNLS 1yr (S) and SDSS-II (D)) in the context of the Chevalier-Polarski-Linder (CPL) parametrization w(a) = w 0 +w 1 (1−a), according to their Figure of Merit (FoM), their consistency with the cosmological constant (ΛCDM), their consistency with standard rulers (Cosmic Microwave Background (CMB) and Baryon Acoustic Oscillations (BAO)) and their mutual consistency. We find a significant improvement of the FoM (defined as the inverse area of the 95.4% parameter contour) with the number of SnIa of these datasets ((C) highest FoM, (U), (G), (D), (E), (S) lowest FoM). Standard rulers (CMB+BAO) have a better FoM by about a factor of 3, compared to the highest FoM SnIa dataset (C). We also find that the ranking sequence based on consistency with ΛCDM is identical with the corresponding ranking based on consistency with standard rulers ((S) most consistent, (D), (C), (E), (U), (G) least consistent). The ranking sequence of the datasets however changes when we consider the consistency with an expansion history corresponding to evolving dark energy (w 0 ,w 1 ) = (−1.4,2) crossing the phantom divide line w = −1 (it is practically reversed to (G), (U), (E), (S), (D), (C)). The SALT2 and MLCS2k2 fitters are also compared and some peculiar features of the SDSS-II dataset when standardized with the MLCS2k2 fitter are pointed out. Finally, we construct a statistic to estimate the internal consistency of a collection of SnIa datasets. We find that even though there is good consistency among most samples taken from the above datasets, this consistency decreases significantly when the Gold06 (G) dataset is included in the sample

  17. Dataset - Adviesregel PPL 2010

    NARCIS (Netherlands)

    Evert, van F.K.; Schans, van der D.A.; Geel, van W.C.A.; Slabbekoorn, J.J.; Booij, R.; Jukema, J.N.; Meurs, E.J.J.; Uenk, D.

    2011-01-01

    This dataset contains experimental data from a number of field experiments with potato in The Netherlands (Van Evert et al., 2011). The data are presented as an SQL dump of a PostgreSQL database (version 8.4.4). An outline of the entity-relationship diagram of the database is given in an

  18. De novo assembly of a 40 Mb eukaryotic genome from short sequence reads: Sordaria macrospora, a model organism for fungal morphogenesis.

    Science.gov (United States)

    Nowrousian, Minou; Stajich, Jason E; Chu, Meiling; Engh, Ines; Espagne, Eric; Halliday, Karen; Kamerewerd, Jens; Kempken, Frank; Knab, Birgit; Kuo, Hsiao-Che; Osiewacz, Heinz D; Pöggeler, Stefanie; Read, Nick D; Seiler, Stephan; Smith, Kristina M; Zickler, Denise; Kück, Ulrich; Freitag, Michael

    2010-04-08

    Filamentous fungi are of great importance in ecology, agriculture, medicine, and biotechnology. Thus, it is not surprising that genomes for more than 100 filamentous fungi have been sequenced, most of them by Sanger sequencing. While next-generation sequencing techniques have revolutionized genome resequencing, e.g. for strain comparisons, genetic mapping, or transcriptome and ChIP analyses, de novo assembly of eukaryotic genomes still presents significant hurdles, because of their large size and stretches of repetitive sequences. Filamentous fungi contain few repetitive regions in their 30-90 Mb genomes and thus are suitable candidates to test de novo genome assembly from short sequence reads. Here, we present a high-quality draft sequence of the Sordaria macrospora genome that was obtained by a combination of Illumina/Solexa and Roche/454 sequencing. Paired-end Solexa sequencing of genomic DNA to 85-fold coverage and an additional 10-fold coverage by single-end 454 sequencing resulted in approximately 4 Gb of DNA sequence. Reads were assembled to a 40 Mb draft version (N50 of 117 kb) with the Velvet assembler. Comparative analysis with Neurospora genomes increased the N50 to 498 kb. The S. macrospora genome contains even fewer repeat regions than its closest sequenced relative, Neurospora crassa. Comparison with genomes of other fungi showed that S. macrospora, a model organism for morphogenesis and meiosis, harbors duplications of several genes involved in self/nonself-recognition. Furthermore, S. macrospora contains more polyketide biosynthesis genes than N. crassa. Phylogenetic analyses suggest that some of these genes may have been acquired by horizontal gene transfer from a distantly related ascomycete group. Our study shows that, for typical filamentous fungi, de novo assembly of genomes from short sequence reads alone is feasible, that a mixture of Solexa and 454 sequencing substantially improves the assembly, and that the resulting data can be used for

  19. De novo assembly of a 40 Mb eukaryotic genome from short sequence reads: Sordaria macrospora, a model organism for fungal morphogenesis.

    Directory of Open Access Journals (Sweden)

    Minou Nowrousian

    2010-04-01

    Full Text Available Filamentous fungi are of great importance in ecology, agriculture, medicine, and biotechnology. Thus, it is not surprising that genomes for more than 100 filamentous fungi have been sequenced, most of them by Sanger sequencing. While next-generation sequencing techniques have revolutionized genome resequencing, e.g. for strain comparisons, genetic mapping, or transcriptome and ChIP analyses, de novo assembly of eukaryotic genomes still presents significant hurdles, because of their large size and stretches of repetitive sequences. Filamentous fungi contain few repetitive regions in their 30-90 Mb genomes and thus are suitable candidates to test de novo genome assembly from short sequence reads. Here, we present a high-quality draft sequence of the Sordaria macrospora genome that was obtained by a combination of Illumina/Solexa and Roche/454 sequencing. Paired-end Solexa sequencing of genomic DNA to 85-fold coverage and an additional 10-fold coverage by single-end 454 sequencing resulted in approximately 4 Gb of DNA sequence. Reads were assembled to a 40 Mb draft version (N50 of 117 kb with the Velvet assembler. Comparative analysis with Neurospora genomes increased the N50 to 498 kb. The S. macrospora genome contains even fewer repeat regions than its closest sequenced relative, Neurospora crassa. Comparison with genomes of other fungi showed that S. macrospora, a model organism for morphogenesis and meiosis, harbors duplications of several genes involved in self/nonself-recognition. Furthermore, S. macrospora contains more polyketide biosynthesis genes than N. crassa. Phylogenetic analyses suggest that some of these genes may have been acquired by horizontal gene transfer from a distantly related ascomycete group. Our study shows that, for typical filamentous fungi, de novo assembly of genomes from short sequence reads alone is feasible, that a mixture of Solexa and 454 sequencing substantially improves the assembly, and that the resulting data

  20. MIPS bacterial genomes functional annotation benchmark dataset.

    Science.gov (United States)

    Tetko, Igor V; Brauner, Barbara; Dunger-Kaltenbach, Irmtraud; Frishman, Goar; Montrone, Corinna; Fobo, Gisela; Ruepp, Andreas; Antonov, Alexey V; Surmeli, Dimitrij; Mewes, Hans-Wernen

    2005-05-15

    Any development of new methods for automatic functional annotation of proteins according to their sequences requires high-quality data (as benchmark) as well as tedious preparatory work to generate sequence parameters required as input data for the machine learning methods. Different program settings and incompatible protocols make a comparison of the analyzed methods difficult. The MIPS Bacterial Functional Annotation Benchmark dataset (MIPS-BFAB) is a new, high-quality resource comprising four bacterial genomes manually annotated according to the MIPS functional catalogue (FunCat). These resources include precalculated sequence parameters, such as sequence similarity scores, InterPro domain composition and other parameters that could be used to develop and benchmark methods for functional annotation of bacterial protein sequences. These data are provided in XML format and can be used by scientists who are not necessarily experts in genome annotation. BFAB is available at http://mips.gsf.de/proj/bfab

  1. Sequencing of BAC pools by different next generation sequencing platforms and strategies

    Directory of Open Access Journals (Sweden)

    Scholz Uwe

    2011-10-01

    Full Text Available Abstract Background Next generation sequencing of BACs is a viable option for deciphering the sequence of even large and highly repetitive genomes. In order to optimize this strategy, we examined the influence of read length on the quality of Roche/454 sequence assemblies, to what extent Illumina/Solexa mate pairs (MPs improve the assemblies by scaffolding and whether barcoding of BACs is dispensable. Results Sequencing four BACs with both FLX and Titanium technologies revealed similar sequencing accuracy, but showed that the longer Titanium reads produce considerably less misassemblies and gaps. The 454 assemblies of 96 barcoded BACs were improved by scaffolding 79% of the total contig length with MPs from a non-barcoded library. Assembly of the unmasked 454 sequences without separation by barcodes revealed chimeric contig formation to be a major problem, encompassing 47% of the total contig length. Masking the sequences reduced this fraction to 24%. Conclusion Optimal BAC pool sequencing should be based on the longest available reads, with barcoding essential for a comprehensive assessment of both repetitive and non-repetitive sequence information. When interest is restricted to non-repetitive regions and repeats are masked prior to assembly, barcoding is non-essential. In any case, the assemblies can be improved considerably by scaffolding with non-barcoded BAC pool MPs.

  2. National Elevation Dataset

    Science.gov (United States)

    ,

    2002-01-01

    The National Elevation Dataset (NED) is a new raster product assembled by the U.S. Geological Survey. NED is designed to provide National elevation data in a seamless form with a consistent datum, elevation unit, and projection. Data corrections were made in the NED assembly process to minimize artifacts, perform edge matching, and fill sliver areas of missing data. NED has a resolution of one arc-second (approximately 30 meters) for the conterminous United States, Hawaii, Puerto Rico and the island territories and a resolution of two arc-seconds for Alaska. NED data sources have a variety of elevation units, horizontal datums, and map projections. In the NED assembly process the elevation values are converted to decimal meters as a consistent unit of measure, NAD83 is consistently used as horizontal datum, and all the data are recast in a geographic projection. Older DEM's produced by methods that are now obsolete have been filtered during the NED assembly process to minimize artifacts that are commonly found in data produced by these methods. Artifact removal greatly improves the quality of the slope, shaded-relief, and synthetic drainage information that can be derived from the elevation data. Figure 2 illustrates the results of this artifact removal filtering. NED processing also includes steps to adjust values where adjacent DEM's do not match well, and to fill sliver areas of missing data between DEM's. These processing steps ensure that NED has no void areas and artificial discontinuities have been minimized. The artifact removal filtering process does not eliminate all of the artifacts. In areas where the only available DEM is produced by older methods, then "striping" may still occur.

  3. Evaluation of PET and MR datasets in integrated 18F-FDG PET/MRI: A comparison of different MR sequences for whole-body restaging of breast cancer patients

    Energy Technology Data Exchange (ETDEWEB)

    Grueneisen, Johannes, E-mail: Johannes.grueneisen@uk-essen.de [Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University of Duisburg-Essen, D-45147 Essen (Germany); Sawicki, Lino Morris [Department of Diagnostic and Interventional Radiology, University Hospital, Dusseldorf, University of Dusseldorf, D-40225 Dusseldorf (Germany); Wetter, Axel [Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University of Duisburg-Essen, D-45147 Essen (Germany); Kirchner, Julian [Department of Diagnostic and Interventional Radiology, University Hospital, Dusseldorf, University of Dusseldorf, D-40225 Dusseldorf (Germany); Kinner, Sonja [Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University of Duisburg-Essen, D-45147 Essen (Germany); Aktas, Bahriye [Department of Obstetrics and Gynecology, University Hospital Essen, University of Duisburg-Essen, D-45147 Essen (Germany); Forsting, Michael [Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University of Duisburg-Essen, D-45147 Essen (Germany); Ruhlmann, Verena [Department of Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, D-45147 Essen (Germany); Umutlu, Lale [Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University of Duisburg-Essen, D-45147 Essen (Germany)

    2017-04-15

    Objectives: To investigate the diagnostic value of different MR sequences and 18F-FDG PET data for whole-body restaging of breast cancer patients utilizing PET/MRI. Methods: A total of 36 patients with suspected tumor recurrence of breast cancer based on clinical follow-up or abnormal findings in follow-up examinations (e.g. CT, MRI) were prospectively enrolled in this study. All patients underwent a PET/CT and subsequently an additional PET/MR scan. Two readers were instructed to identify the occurrence of a tumor relapse in subsequent MR and PET/MR readings, utilizing different MR sequence constellations for each session. The diagnostic confidence for the determination of a malignant or benign lesion was qualitatively rated (3-point ordinal scale) for each lesion in the different reading sessions and the lesion conspicuity (4-point ordinal scale) for the three different MR sequences was additionally evaluated. Results: Tumor recurrence was present in 25/36 (69%) patients. All three PET/MRI readings showed a significantly higher accuracy as well as higher confidence levels for the detection of recurrent breast cancer lesions when compared to MRI alone (p < 0.05). Furthermore, all three PET/MR sequence constellations showed comparable diagnostic accuracy for the identification of a breast cancer recurrence (p > 0.05), yet the highest confidence levels were obtained, when all three MR sequences were used for image interpretation. Moreover, contrast-enhanced T1-weighted VIBE imaging showed significantly higher values for the delineation of malignant and benign lesions when compared to T2 w HASTE and diffusion-weighted imaging. Conclusion: Integrated PET/MRI provides superior restaging of breast cancer patients over MRI alone. Facing the need for appropriate and efficient whole-body PET/MR protocols, our results show the feasibility of fast and morphologically adequate PET/MR protocols. However, considering an equivalent accuracy for the detection of breast cancer

  4. Evaluation of PET and MR datasets in integrated 18F-FDG PET/MRI: A comparison of different MR sequences for whole-body restaging of breast cancer patients

    International Nuclear Information System (INIS)

    Grueneisen, Johannes; Sawicki, Lino Morris; Wetter, Axel; Kirchner, Julian; Kinner, Sonja; Aktas, Bahriye; Forsting, Michael; Ruhlmann, Verena; Umutlu, Lale

    2017-01-01

    Objectives: To investigate the diagnostic value of different MR sequences and 18F-FDG PET data for whole-body restaging of breast cancer patients utilizing PET/MRI. Methods: A total of 36 patients with suspected tumor recurrence of breast cancer based on clinical follow-up or abnormal findings in follow-up examinations (e.g. CT, MRI) were prospectively enrolled in this study. All patients underwent a PET/CT and subsequently an additional PET/MR scan. Two readers were instructed to identify the occurrence of a tumor relapse in subsequent MR and PET/MR readings, utilizing different MR sequence constellations for each session. The diagnostic confidence for the determination of a malignant or benign lesion was qualitatively rated (3-point ordinal scale) for each lesion in the different reading sessions and the lesion conspicuity (4-point ordinal scale) for the three different MR sequences was additionally evaluated. Results: Tumor recurrence was present in 25/36 (69%) patients. All three PET/MRI readings showed a significantly higher accuracy as well as higher confidence levels for the detection of recurrent breast cancer lesions when compared to MRI alone (p < 0.05). Furthermore, all three PET/MR sequence constellations showed comparable diagnostic accuracy for the identification of a breast cancer recurrence (p > 0.05), yet the highest confidence levels were obtained, when all three MR sequences were used for image interpretation. Moreover, contrast-enhanced T1-weighted VIBE imaging showed significantly higher values for the delineation of malignant and benign lesions when compared to T2 w HASTE and diffusion-weighted imaging. Conclusion: Integrated PET/MRI provides superior restaging of breast cancer patients over MRI alone. Facing the need for appropriate and efficient whole-body PET/MR protocols, our results show the feasibility of fast and morphologically adequate PET/MR protocols. However, considering an equivalent accuracy for the detection of breast cancer

  5. NP-PAH Interaction Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Dataset presents concentrations of organic pollutants, such as polyaromatic hydrocarbon compounds, in water samples. Water samples of known volume and concentration...

  6. Evaluation of PET and MR datasets in integrated 18F-FDG PET/MRI: A comparison of different MR sequences for whole-body restaging of breast cancer patients.

    Science.gov (United States)

    Grueneisen, Johannes; Sawicki, Lino Morris; Wetter, Axel; Kirchner, Julian; Kinner, Sonja; Aktas, Bahriye; Forsting, Michael; Ruhlmann, Verena; Umutlu, Lale

    2017-04-01

    To investigate the diagnostic value of different MR sequences and 18F-FDG PET data for whole-body restaging of breast cancer patients utilizing PET/MRI. A total of 36 patients with suspected tumor recurrence of breast cancer based on clinical follow-up or abnormal findings in follow-up examinations (e.g. CT, MRI) were prospectively enrolled in this study. All patients underwent a PET/CT and subsequently an additional PET/MR scan. Two readers were instructed to identify the occurrence of a tumor relapse in subsequent MR and PET/MR readings, utilizing different MR sequence constellations for each session. The diagnostic confidence for the determination of a malignant or benign lesion was qualitatively rated (3-point ordinal scale) for each lesion in the different reading sessions and the lesion conspicuity (4-point ordinal scale) for the three different MR sequences was additionally evaluated. Tumor recurrence was present in 25/36 (69%) patients. All three PET/MRI readings showed a significantly higher accuracy as well as higher confidence levels for the detection of recurrent breast cancer lesions when compared to MRI alone (psequence constellations showed comparable diagnostic accuracy for the identification of a breast cancer recurrence (p>0.05), yet the highest confidence levels were obtained, when all three MR sequences were used for image interpretation. Moreover, contrast-enhanced T1-weighted VIBE imaging showed significantly higher values for the delineation of malignant and benign lesions when compared to T2w HASTE and diffusion-weighted imaging. Integrated PET/MRI provides superior restaging of breast cancer patients over MRI alone. Facing the need for appropriate and efficient whole-body PET/MR protocols, our results show the feasibility of fast and morphologically adequate PET/MR protocols. However, considering an equivalent accuracy for the detection of breast cancer recurrences in the three PET/MR readings, the application of contrast-agent and the

  7. Discovery and profiling of novel and conserved microRNAs during flower development in Carya cathayensis via deep sequencing.

    Science.gov (United States)

    Wang, Zheng Jia; Huang, Jian Qin; Huang, You Jun; Li, Zheng; Zheng, Bing Song

    2012-08-01

    Hickory (Carya cathayensis Sarg.) is an economically important woody plant in China, but its long juvenile phase delays yield. MicroRNAs (miRNAs) are critical regulators of genes and important for normal plant development and physiology, including flower development. We used Solexa technology to sequence two small RNA libraries from two floral differentiation stages in hickory to identify miRNAs related to flower development. We identified 39 conserved miRNA sequences from 114 loci belonging to 23 families as well as two novel and ten potential novel miRNAs belonging to nine families. Moreover, 35 conserved miRNA*s and two novel miRNA*s were detected. Twenty miRNA sequences from 49 loci belonging to 11 families were differentially expressed; all were up-regulated at the later stage of flower development in hickory. Quantitative real-time PCR of 12 conserved miRNA sequences, five novel miRNA families, and two novel miRNA*s validated that all were expressed during hickory flower development, and the expression patterns were similar to those detected with Solexa sequencing. Finally, a total of 146 targets of the novel and conserved miRNAs were predicted. This study identified a diverse set of miRNAs that were closely related to hickory flower development and that could help in plant floral induction.

  8. Gomphid DNA sequence data

    Data.gov (United States)

    U.S. Environmental Protection Agency — DNA sequence data for several genetic loci. This dataset is not publicly accessible because: It's already publicly available on GenBank. It can be accessed through...

  9. Editorial: Datasets for Learning Analytics

    NARCIS (Netherlands)

    Dietze, Stefan; George, Siemens; Davide, Taibi; Drachsler, Hendrik

    2018-01-01

    The European LinkedUp and LACE (Learning Analytics Community Exchange) project have been responsible for setting up a series of data challenges at the LAK conferences 2013 and 2014 around the LAK dataset. The LAK datasets consists of a rich collection of full text publications in the domain of

  10. Open University Learning Analytics dataset.

    Science.gov (United States)

    Kuzilek, Jakub; Hlosta, Martin; Zdrahal, Zdenek

    2017-11-28

    Learning Analytics focuses on the collection and analysis of learners' data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students' interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license.

  11. Management of High-Throughput DNA Sequencing Projects: Alpheus.

    Science.gov (United States)

    Miller, Neil A; Kingsmore, Stephen F; Farmer, Andrew; Langley, Raymond J; Mudge, Joann; Crow, John A; Gonzalez, Alvaro J; Schilkey, Faye D; Kim, Ryan J; van Velkinburgh, Jennifer; May, Gregory D; Black, C Forrest; Myers, M Kathy; Utsey, John P; Frost, Nicholas S; Sugarbaker, David J; Bueno, Raphael; Gullans, Stephen R; Baxter, Susan M; Day, Steve W; Retzel, Ernest F

    2008-12-26

    High-throughput DNA sequencing has enabled systems biology to begin to address areas in health, agricultural and basic biological research. Concomitant with the opportunities is an absolute necessity to manage significant volumes of high-dimensional and inter-related data and analysis. Alpheus is an analysis pipeline, database and visualization software for use with massively parallel DNA sequencing technologies that feature multi-gigabase throughput characterized by relatively short reads, such as Illumina-Solexa (sequencing-by-synthesis), Roche-454 (pyrosequencing) and Applied Biosystem's SOLiD (sequencing-by-ligation). Alpheus enables alignment to reference sequence(s), detection of variants and enumeration of sequence abundance, including expression levels in transcriptome sequence. Alpheus is able to detect several types of variants, including non-synonymous and synonymous single nucleotide polymorphisms (SNPs), insertions/deletions (indels), premature stop codons, and splice isoforms. Variant detection is aided by the ability to filter variant calls based on consistency, expected allele frequency, sequence quality, coverage, and variant type in order to minimize false positives while maximizing the identification of true positives. Alpheus also enables comparisons of genes with variants between cases and controls or bulk segregant pools. Sequence-based differential expression comparisons can be developed, with data export to SAS JMP Genomics for statistical analysis.

  12. High-precision, whole-genome sequencing of laboratory strains facilitates genetic studies.

    Directory of Open Access Journals (Sweden)

    Anjana Srivatsan

    2008-08-01

    Full Text Available Whole-genome sequencing is a powerful technique for obtaining the reference sequence information of multiple organisms. Its use can be dramatically expanded to rapidly identify genomic variations, which can be linked with phenotypes to obtain biological insights. We explored these potential applications using the emerging next-generation sequencing platform Solexa Genome Analyzer, and the well-characterized model bacterium Bacillus subtilis. Combining sequencing with experimental verification, we first improved the accuracy of the published sequence of the B. subtilis reference strain 168, then obtained sequences of multiple related laboratory strains and different isolates of each strain. This provides a framework for comparing the divergence between different laboratory strains and between their individual isolates. We also demonstrated the power of Solexa sequencing by using its results to predict a defect in the citrate signal transduction pathway of a common laboratory strain, which we verified experimentally. Finally, we examined the molecular nature of spontaneously generated mutations that suppress the growth defect caused by deletion of the stringent response mediator relA. Using whole-genome sequencing, we rapidly mapped these suppressor mutations to two small homologs of relA. Interestingly, stable suppressor strains had mutations in both genes, with each mutation alone partially relieving the relA growth defect. This supports an intriguing three-locus interaction module that is not easily identifiable through traditional suppressor mapping. We conclude that whole-genome sequencing can drastically accelerate the identification of suppressor mutations and complex genetic interactions, and it can be applied as a standard tool to investigate the genetic traits of model organisms.

  13. Turkey Run Landfill Emissions Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — landfill emissions measurements for the Turkey run landfill in Georgia. This dataset is associated with the following publication: De la Cruz, F., R. Green, G....

  14. Dataset of NRDA emission data

    Data.gov (United States)

    U.S. Environmental Protection Agency — Emissions data from open air oil burns. This dataset is associated with the following publication: Gullett, B., J. Aurell, A. Holder, B. Mitchell, D. Greenwell, M....

  15. Chemical product and function dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Merged product weight fraction and chemical function data. This dataset is associated with the following publication: Isaacs , K., M. Goldsmith, P. Egeghy , K....

  16. The NOAA Dataset Identifier Project

    Science.gov (United States)

    de la Beaujardiere, J.; Mccullough, H.; Casey, K. S.

    2013-12-01

    The US National Oceanic and Atmospheric Administration (NOAA) initiated a project in 2013 to assign persistent identifiers to datasets archived at NOAA and to create informational landing pages about those datasets. The goals of this project are to enable the citation of datasets used in products and results in order to help provide credit to data producers, to support traceability and reproducibility, and to enable tracking of data usage and impact. A secondary goal is to encourage the submission of datasets for long-term preservation, because only archived datasets will be eligible for a NOAA-issued identifier. A team was formed with representatives from the National Geophysical, Oceanographic, and Climatic Data Centers (NGDC, NODC, NCDC) to resolve questions including which identifier scheme to use (answer: Digital Object Identifier - DOI), whether or not to embed semantics in identifiers (no), the level of granularity at which to assign identifiers (as coarsely as reasonable), how to handle ongoing time-series data (do not break into chunks), creation mechanism for the landing page (stylesheet from formal metadata record preferred), and others. Decisions made and implementation experience gained will inform the writing of a Data Citation Procedural Directive to be issued by the Environmental Data Management Committee in 2014. Several identifiers have been issued as of July 2013, with more on the way. NOAA is now reporting the number as a metric to federal Open Government initiatives. This paper will provide further details and status of the project.

  17. Dataset of mitochondrial genome variants in oncocytic tumors

    Directory of Open Access Journals (Sweden)

    Lihua Lyu

    2018-04-01

    Full Text Available This dataset presents the mitochondrial genome variants associated with oncocytic tumors. These data were obtained by Sanger sequencing of the whole mitochondrial genomes of oncocytic tumors and the adjacent normal tissues from 32 patients. The mtDNA variants are identified after compared with the revised Cambridge sequence, excluding those defining haplogroups of our patients. The pathogenic prediction for the novel missense variants found in this study was performed with the Mitimpact 2 program.

  18. The Harvard organic photovoltaic dataset.

    Science.gov (United States)

    Lopez, Steven A; Pyzer-Knapp, Edward O; Simm, Gregor N; Lutzow, Trevor; Li, Kewei; Seress, Laszlo R; Hachmann, Johannes; Aspuru-Guzik, Alán

    2016-09-27

    The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications.

  19. The Harvard organic photovoltaic dataset

    Science.gov (United States)

    Lopez, Steven A.; Pyzer-Knapp, Edward O.; Simm, Gregor N.; Lutzow, Trevor; Li, Kewei; Seress, Laszlo R.; Hachmann, Johannes; Aspuru-Guzik, Alán

    2016-01-01

    The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications. PMID:27676312

  20. NCBI Mass Sequence Downloader–Large dataset downloading made easy

    Directory of Open Access Journals (Sweden)

    F. Pina-Martins

    2016-01-01

    Source code is licensed under the GPLv3, and is supported on Linux, Windows and Mac OSX. Available at https://github.com/ElsevierSoftwareX/SOFTX-D-15-00072.git, https://github.com/StuntsPT/NCBI_Mass_Downloader

  1. Querying Large Biological Network Datasets

    Science.gov (United States)

    Gulsoy, Gunhan

    2013-01-01

    New experimental methods has resulted in increasing amount of genetic interaction data to be generated every day. Biological networks are used to store genetic interaction data gathered. Increasing amount of data available requires fast large scale analysis methods. Therefore, we address the problem of querying large biological network datasets.…

  2. Fluxnet Synthesis Dataset Collaboration Infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Deborah A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Humphrey, Marty [Univ. of Virginia, Charlottesville, VA (United States); van Ingen, Catharine [Microsoft. San Francisco, CA (United States); Beekwilder, Norm [Univ. of Virginia, Charlottesville, VA (United States); Goode, Monte [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jackson, Keith [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rodriguez, Matt [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Weber, Robin [Univ. of California, Berkeley, CA (United States)

    2008-02-06

    The Fluxnet synthesis dataset originally compiled for the La Thuile workshop contained approximately 600 site years. Since the workshop, several additional site years have been added and the dataset now contains over 920 site years from over 240 sites. A data refresh update is expected to increase those numbers in the next few months. The ancillary data describing the sites continues to evolve as well. There are on the order of 120 site contacts and 60proposals have been approved to use thedata. These proposals involve around 120 researchers. The size and complexity of the dataset and collaboration has led to a new approach to providing access to the data and collaboration support and the support team attended the workshop and worked closely with the attendees and the Fluxnet project office to define the requirements for the support infrastructure. As a result of this effort, a new website (http://www.fluxdata.org) has been created to provide access to the Fluxnet synthesis dataset. This new web site is based on a scientific data server which enables browsing of the data on-line, data download, and version tracking. We leverage database and data analysis tools such as OLAP data cubes and web reports to enable browser and Excel pivot table access to the data.

  3. CERC Dataset (Full Hadza Data)

    DEFF Research Database (Denmark)

    2016-01-01

    The dataset includes demographic, behavioral, and religiosity data from eight different populations from around the world. The samples were drawn from: (1) Coastal and (2) Inland Tanna, Vanuatu; (3) Hadzaland, Tanzania; (4) Lovu, Fiji; (5) Pointe aux Piment, Mauritius; (6) Pesqueiro, Brazil; (7......) Kyzyl, Tyva Republic; and (8) Yasawa, Fiji. Related publication: Purzycki, et al. (2016). Moralistic Gods, Supernatural Punishment and the Expansion of Human Sociality. Nature, 530(7590): 327-330....

  4. Viking Seismometer PDS Archive Dataset

    Science.gov (United States)

    Lorenz, R. D.

    2016-12-01

    The Viking Lander 2 seismometer operated successfully for over 500 Sols on the Martian surface, recording at least one likely candidate Marsquake. The Viking mission, in an era when data handling hardware (both on board and on the ground) was limited in capability, predated modern planetary data archiving, and ad-hoc repositories of the data, and the very low-level record at NSSDC, were neither convenient to process nor well-known. In an effort supported by the NASA Mars Data Analysis Program, we have converted the bulk of the Viking dataset (namely the 49,000 and 270,000 records made in High- and Event- modes at 20 and 1 Hz respectively) into a simple ASCII table format. Additionally, since wind-generated lander motion is a major component of the signal, contemporaneous meteorological data are included in summary records to facilitate correlation. These datasets are being archived at the PDS Geosciences Node. In addition to brief instrument and dataset descriptions, the archive includes code snippets in the freely-available language 'R' to demonstrate plotting and analysis. Further, we present examples of lander-generated noise, associated with the sampler arm, instrument dumps and other mechanical operations.

  5. PHYSICS PERFORMANCE AND DATASET (PPD)

    CERN Multimedia

    L. Silvestris

    2013-01-01

    The first part of the Long Shutdown period has been dedicated to the preparation of the samples for the analysis targeting the summer conferences. In particular, the 8 TeV data acquired in 2012, including most of the “parked datasets”, have been reconstructed profiting from improved alignment and calibration conditions for all the sub-detectors. A careful planning of the resources was essential in order to deliver the datasets well in time to the analysts, and to schedule the update of all the conditions and calibrations needed at the analysis level. The newly reprocessed data have undergone detailed scrutiny by the Dataset Certification team allowing to recover some of the data for analysis usage and further improving the certification efficiency, which is now at 91% of the recorded luminosity. With the aim of delivering a consistent dataset for 2011 and 2012, both in terms of conditions and release (53X), the PPD team is now working to set up a data re-reconstruction and a new MC pro...

  6. RARD: The Related-Article Recommendation Dataset

    OpenAIRE

    Beel, Joeran; Carevic, Zeljko; Schaible, Johann; Neusch, Gabor

    2017-01-01

    Recommender-system datasets are used for recommender-system evaluations, training machine-learning algorithms, and exploring user behavior. While there are many datasets for recommender systems in the domains of movies, books, and music, there are rather few datasets from research-paper recommender systems. In this paper, we introduce RARD, the Related-Article Recommendation Dataset, from the digital library Sowiport and the recommendation-as-a-service provider Mr. DLib. The dataset contains ...

  7. FASTQSim: platform-independent data characterization and in silico read generation for NGS datasets.

    Science.gov (United States)

    Shcherbina, Anna

    2014-08-15

    High-throughput next generation sequencing technologies have enabled rapid characterization of clinical and environmental samples. Consequently, the largest bottleneck to actionable data has become sample processing and bioinformatics analysis, creating a need for accurate and rapid algorithms to process genetic data. Perfectly characterized in silico datasets are a useful tool for evaluating the performance of such algorithms. Background contaminating organisms are observed in sequenced mixtures of organisms. In silico samples provide exact truth. To create the best value for evaluating algorithms, in silico data should mimic actual sequencer data as closely as possible. FASTQSim is a tool that provides the dual functionality of NGS dataset characterization and metagenomic data generation. FASTQSim is sequencing platform-independent, and computes distributions of read length, quality scores, indel rates, single point mutation rates, indel size, and similar statistics for any sequencing platform. To create training or testing datasets, FASTQSim has the ability to convert target sequences into in silico reads with specific error profiles obtained in the characterization step. FASTQSim enables users to assess the quality of NGS datasets. The tool provides information about read length, read quality, repetitive and non-repetitive indel profiles, and single base pair substitutions. FASTQSim allows the user to simulate individual read datasets that can be used as standardized test scenarios for planning sequencing projects or for benchmarking metagenomic software. In this regard, in silico datasets generated with the FASTQsim tool hold several advantages over natural datasets: they are sequencing platform independent, extremely well characterized, and less expensive to generate. Such datasets are valuable in a number of applications, including the training of assemblers for multiple platforms, benchmarking bioinformatics algorithm performance, and creating challenge

  8. High-throughput sequence alignment using Graphics Processing Units

    Directory of Open Access Journals (Sweden)

    Trapnell Cole

    2007-12-01

    Full Text Available Abstract Background The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies. Results This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies. Conclusion MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU.

  9. Passive Containment DataSet

    Science.gov (United States)

    This data is for Figures 6 and 7 in the journal article. The data also includes the two EPANET input files used for the analysis described in the paper, one for the looped system and one for the block system.This dataset is associated with the following publication:Grayman, W., R. Murray , and D. Savic. Redesign of Water Distribution Systems for Passive Containment of Contamination. JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 108(7): 381-391, (2016).

  10. BLAST-EXPLORER helps you building datasets for phylogenetic analysis

    Directory of Open Access Journals (Sweden)

    Claverie Jean-Michel

    2010-01-01

    Full Text Available Abstract Background The right sampling of homologous sequences for phylogenetic or molecular evolution analyses is a crucial step, the quality of which can have a significant impact on the final interpretation of the study. There is no single way for constructing datasets suitable for phylogenetic analysis, because this task intimately depends on the scientific question we want to address, Moreover, database mining softwares such as BLAST which are routinely used for searching homologous sequences are not specifically optimized for this task. Results To fill this gap, we designed BLAST-Explorer, an original and friendly web-based application that combines a BLAST search with a suite of tools that allows interactive, phylogenetic-oriented exploration of the BLAST results and flexible selection of homologous sequences among the BLAST hits. Once the selection of the BLAST hits is done using BLAST-Explorer, the corresponding sequence can be imported locally for external analysis or passed to the phylogenetic tree reconstruction pipelines available on the Phylogeny.fr platform. Conclusions BLAST-Explorer provides a simple, intuitive and interactive graphical representation of the BLAST results and allows selection and retrieving of the BLAST hit sequences based a wide range of criterions. Although BLAST-Explorer primarily aims at helping the construction of sequence datasets for further phylogenetic study, it can also be used as a standard BLAST server with enriched output. BLAST-Explorer is available at http://www.phylogeny.fr

  11. The CMS dataset bookkeeping service

    Science.gov (United States)

    Afaq, A.; Dolgert, A.; Guo, Y.; Jones, C.; Kosyakov, S.; Kuznetsov, V.; Lueking, L.; Riley, D.; Sekhri, V.

    2008-07-01

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems.

  12. The CMS dataset bookkeeping service

    Energy Technology Data Exchange (ETDEWEB)

    Afaq, A; Guo, Y; Kosyakov, S; Lueking, L; Sekhri, V [Fermilab, Batavia, Illinois 60510 (United States); Dolgert, A; Jones, C; Kuznetsov, V; Riley, D [Cornell University, Ithaca, New York 14850 (United States)

    2008-07-15

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems.

  13. The CMS dataset bookkeeping service

    International Nuclear Information System (INIS)

    Afaq, A; Guo, Y; Kosyakov, S; Lueking, L; Sekhri, V; Dolgert, A; Jones, C; Kuznetsov, V; Riley, D

    2008-01-01

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems

  14. The CMS dataset bookkeeping service

    International Nuclear Information System (INIS)

    Afaq, Anzar; Dolgert, Andrew; Guo, Yuyi; Jones, Chris; Kosyakov, Sergey; Kuznetsov, Valentin; Lueking, Lee; Riley, Dan; Sekhri, Vijay

    2007-01-01

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems

  15. Genome-wide identification and comparative analysis of conserved and novel microRNAs in grafted watermelon by high-throughput sequencing.

    Science.gov (United States)

    Liu, Na; Yang, Jinghua; Guo, Shaogui; Xu, Yong; Zhang, Mingfang

    2013-01-01

    MicroRNAs (miRNAs) are a class of endogenous small non-coding RNAs involved in the post-transcriptional gene regulation and play a critical role in plant growth, development and stresses response. However less is known about miRNAs involvement in grafting behaviors, especially with the watermelon (Citrullus lanatus L.) crop, which is one of the most important agricultural crops worldwide. Grafting method is commonly used in watermelon production in attempts to improve its adaptation to abiotic and biotic stresses, in particular to the soil-borne fusarium wilt disease. In this study, Solexa sequencing has been used to discover small RNA populations and compare miRNAs on genome-wide scale in watermelon grafting system. A total of 11,458,476, 11,614,094 and 9,339,089 raw reads representing 2,957,751, 2,880,328 and 2,964,990 unique sequences were obtained from the scions of self-grafted watermelon and watermelon grafted on-to bottle gourd and squash at two true-leaf stage, respectively. 39 known miRNAs belonging to 30 miRNA families and 80 novel miRNAs were identified in our small RNA dataset. Compared with self-grafted watermelon, 20 (5 known miRNA families and 15 novel miRNAs) and 47 (17 known miRNA families and 30 novel miRNAs) miRNAs were expressed significantly different in watermelon grafted on to bottle gourd and squash, respectively. MiRNAs expressed differentially when watermelon was grafted onto different rootstocks, suggesting that miRNAs might play an important role in diverse biological and metabolic processes in watermelon and grafting may possibly by changing miRNAs expressions to regulate plant growth and development as well as adaptation to stresses. The small RNA transcriptomes obtained in this study provided insights into molecular aspects of miRNA-mediated regulation in grafted watermelon. Obviously, this result would provide a basis for further unravelling the mechanism on how miRNAs information is exchanged between scion and rootstock in grafted

  16. Deep sequencing-based transcriptome analysis of chicken spleen in response to avian pathogenic Escherichia coli (APEC infection.

    Directory of Open Access Journals (Sweden)

    Qinghua Nie

    Full Text Available Avian pathogenic Escherichia coli (APEC leads to economic losses in poultry production and is also a threat to human health. The goal of this study was to characterize the chicken spleen transcriptome and to identify candidate genes for response and resistance to APEC infection using Solexa sequencing. We obtained 14422935, 14104324, and 14954692 Solexa read pairs for non-challenged (NC, challenged-mild pathology (MD, and challenged-severe pathology (SV, respectively. A total of 148197 contigs and 98461 unigenes were assembled, of which 134949 contigs and 91890 unigenes match the chicken genome. In total, 12272 annotated unigenes take part in biological processes (11664, cellular components (11927, and molecular functions (11963. Summing three specific contrasts, 13650 significantly differentially expressed unigenes were found in NC Vs. MD (6844, NC Vs. SV (7764, and MD Vs. SV (2320. Some unigenes (e.g. CD148, CD45 and LCK were involved in crucial pathways, such as the T cell receptor (TCR signaling pathway and microbial metabolism in diverse environments. This study facilitates understanding of the genetic architecture of the chicken spleen transcriptome, and has identified candidate genes for host response to APEC infection.

  17. Comparison of next generation sequencing technologies for transcriptome characterization

    Directory of Open Access Journals (Sweden)

    Soltis Douglas E

    2009-08-01

    Full Text Available Abstract Background We have developed a simulation approach to help determine the optimal mixture of sequencing methods for most complete and cost effective transcriptome sequencing. We compared simulation results for traditional capillary sequencing with "Next Generation" (NG ultra high-throughput technologies. The simulation model was parameterized using mappings of 130,000 cDNA sequence reads to the Arabidopsis genome (NCBI Accession SRA008180.19. We also generated 454-GS20 sequences and de novo assemblies for the basal eudicot California poppy (Eschscholzia californica and the magnoliid avocado (Persea americana using a variety of methods for cDNA synthesis. Results The Arabidopsis reads tagged more than 15,000 genes, including new splice variants and extended UTR regions. Of the total 134,791 reads (13.8 MB, 119,518 (88.7% mapped exactly to known exons, while 1,117 (0.8% mapped to introns, 11,524 (8.6% spanned annotated intron/exon boundaries, and 3,066 (2.3% extended beyond the end of annotated UTRs. Sequence-based inference of relative gene expression levels correlated significantly with microarray data. As expected, NG sequencing of normalized libraries tagged more genes than non-normalized libraries, although non-normalized libraries yielded more full-length cDNA sequences. The Arabidopsis data were used to simulate additional rounds of NG and traditional EST sequencing, and various combinations of each. Our simulations suggest a combination of FLX and Solexa sequencing for optimal transcriptome coverage at modest cost. We have also developed ESTcalc http://fgp.huck.psu.edu/NG_Sims/ngsim.pl, an online webtool, which allows users to explore the results of this study by specifying individualized costs and sequencing characteristics. Conclusion NG sequencing technologies are a highly flexible set of platforms that can be scaled to suit different project goals. In terms of sequence coverage alone, the NG sequencing is a dramatic advance

  18. 2008 TIGER/Line Nationwide Dataset

    Data.gov (United States)

    California Natural Resource Agency — This dataset contains a nationwide build of the 2008 TIGER/Line datasets from the US Census Bureau downloaded in April 2009. The TIGER/Line Shapefiles are an extract...

  19. Satellite-Based Precipitation Datasets

    Science.gov (United States)

    Munchak, S. J.; Huffman, G. J.

    2017-12-01

    Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

  20. Genomics dataset on unclassified published organism (patent US 7547531

    Directory of Open Access Journals (Sweden)

    Mohammad Mahfuz Ali Khan Shawan

    2016-12-01

    Full Text Available Nucleotide (DNA sequence analysis provides important clues regarding the characteristics and taxonomic position of an organism. With the intention that, DNA sequence analysis is very crucial to learn about hierarchical classification of that particular organism. This dataset (patent US 7547531 is chosen to simplify all the complex raw data buried in undisclosed DNA sequences which help to open doors for new collaborations. In this data, a total of 48 unidentified DNA sequences from patent US 7547531 were selected and their complete sequences were retrieved from NCBI BioSample database. Quick response (QR code of those DNA sequences was constructed by DNA BarID tool. QR code is useful for the identification and comparison of isolates with other organisms. AT/GC content of the DNA sequences was determined using ENDMEMO GC Content Calculator, which indicates their stability at different temperature. The highest GC content was observed in GP445188 (62.5% which was followed by GP445198 (61.8% and GP445189 (59.44%, while lowest was in GP445178 (24.39%. In addition, New England BioLabs (NEB database was used to identify cleavage code indicating the 5, 3 and blunt end and enzyme code indicating the methylation site of the DNA sequences was also shown. These data will be helpful for the construction of the organisms’ hierarchical classification, determination of their phylogenetic and taxonomic position and revelation of their molecular characteristics.

  1. PHYSICS PERFORMANCE AND DATASET (PPD)

    CERN Multimedia

    L. Silvestris

    2012-01-01

      Introduction The first part of the year presented an important test for the new Physics Performance and Dataset (PPD) group (cf. its mandate: http://cern.ch/go/8f77). The activity was focused on the validation of the new releases meant for the Monte Carlo (MC) production and the data-processing in 2012 (CMSSW 50X and 52X), and on the preparation of the 2012 operations. In view of the Chamonix meeting, the PPD and physics groups worked to understand the impact of the higher pile-up scenario on some of the flagship Higgs analyses to better quantify the impact of the high luminosity on the CMS physics potential. A task force is working on the optimisation of the reconstruction algorithms and on the code to cope with the performance requirements imposed by the higher event occupancy as foreseen for 2012. Concerning the preparation for the analysis of the new data, a new MC production has been prepared. The new samples, simulated at 8 TeV, are already being produced and the digitisation and recons...

  2. Pattern Analysis On Banking Dataset

    Directory of Open Access Journals (Sweden)

    Amritpal Singh

    2015-06-01

    Full Text Available Abstract Everyday refinement and development of technology has led to an increase in the competition between the Tech companies and their going out of way to crack the system andbreak down. Thus providing Data mining a strategically and security-wise important area for many business organizations including banking sector. It allows the analyzes of important information in the data warehouse and assists the banks to look for obscure patterns in a group and discover unknown relationship in the data.Banking systems needs to process ample amount of data on daily basis related to customer information their credit card details limit and collateral details transaction details risk profiles Anti Money Laundering related information trade finance data. Thousands of decisionsbased on the related data are taken in a bank daily. This paper analyzes the banking dataset in the weka environment for the detection of interesting patterns based on its applications ofcustomer acquisition customer retention management and marketing and management of risk fraudulence detections.

  3. PHYSICS PERFORMANCE AND DATASET (PPD)

    CERN Multimedia

    L. Silvestris

    2013-01-01

    The PPD activities, in the first part of 2013, have been focused mostly on the final physics validation and preparation for the data reprocessing of the full 8 TeV datasets with the latest calibrations. These samples will be the basis for the preliminary results for summer 2013 but most importantly for the final publications on the 8 TeV Run 1 data. The reprocessing involves also the reconstruction of a significant fraction of “parked data” that will allow CMS to perform a whole new set of precision analyses and searches. In this way the CMSSW release 53X is becoming the legacy release for the 8 TeV Run 1 data. The regular operation activities have included taking care of the prolonged proton-proton data taking and the run with proton-lead collisions that ended in February. The DQM and Data Certification team has deployed a continuous effort to promptly certify the quality of the data. The luminosity-weighted certification efficiency (requiring all sub-detectors to be certified as usab...

  4. GenHtr: a tool for comparative assessment of genetic heterogeneity in microbial genomes generated by massive short-read sequencing

    Directory of Open Access Journals (Sweden)

    Yu GongXin

    2010-10-01

    Full Text Available Abstract Background Microevolution is the study of short-term changes of alleles within a population and their effects on the phenotype of organisms. The result of the below-species-level evolution is heterogeneity, where populations consist of subpopulations with a large number of structural variations. Heterogeneity analysis is thus essential to our understanding of how selective and neutral forces shape bacterial populations over a short period of time. The Solexa Genome Analyzer, a next-generation sequencing platform, allows millions of short sequencing reads to be obtained with great accuracy, allowing for the ability to study the dynamics of the bacterial population at the whole genome level. The tool referred to as GenHtr was developed for genome-wide heterogeneity analysis. Results For particular bacterial strains, GenHtr relies on a set of Solexa short reads on given bacteria pathogens and their isogenic reference genome to identify heterogeneity sites, the chromosomal positions with multiple variants of genes in the bacterial population, and variations that occur in large gene families. GenHtr accomplishes this by building and comparatively analyzing genome-wide heterogeneity genotypes for both the newly sequenced genomes (using massive short-read sequencing and their isogenic reference (using simulated data. As proof of the concept, this approach was applied to SRX007711, the Solexa sequencing data for a newly sequenced Staphylococcus aureus subsp. USA300 cell line, and demonstrated that it could predict such multiple variants. They include multiple variants of genes critical in pathogenesis, e.g. genes encoding a LysR family transcriptional regulator, 23 S ribosomal RNA, and DNA mismatch repair protein MutS. The heterogeneity results in non-synonymous and nonsense mutations, leading to truncated proteins for both LysR and MutS. Conclusion GenHtr was developed for genome-wide heterogeneity analysis. Although it is much more time

  5. The Geometry of Finite Equilibrium Datasets

    DEFF Research Database (Denmark)

    Balasko, Yves; Tvede, Mich

    We investigate the geometry of finite datasets defined by equilibrium prices, income distributions, and total resources. We show that the equilibrium condition imposes no restrictions if total resources are collinear, a property that is robust to small perturbations. We also show that the set...... of equilibrium datasets is pathconnected when the equilibrium condition does impose restrictions on datasets, as for example when total resources are widely non collinear....

  6. IPCC Socio-Economic Baseline Dataset

    Data.gov (United States)

    National Aeronautics and Space Administration — The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land...

  7. Veterans Affairs Suicide Prevention Synthetic Dataset

    Data.gov (United States)

    Department of Veterans Affairs — The VA's Veteran Health Administration, in support of the Open Data Initiative, is providing the Veterans Affairs Suicide Prevention Synthetic Dataset (VASPSD). The...

  8. Nanoparticle-organic pollutant interaction dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Dataset presents concentrations of organic pollutants, such as polyaromatic hydrocarbon compounds, in water samples. Water samples of known volume and concentration...

  9. An Annotated Dataset of 14 Meat Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2002-01-01

    This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given.......This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given....

  10. Orthology detection combining clustering and synteny for very large datasets.

    Science.gov (United States)

    Lechner, Marcus; Hernandez-Rosales, Maribel; Doerr, Daniel; Wieseke, Nicolas; Thévenin, Annelyse; Stoye, Jens; Hartmann, Roland K; Prohaska, Sonja J; Stadler, Peter F

    2014-01-01

    The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance) was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets.

  11. Orthology detection combining clustering and synteny for very large datasets.

    Directory of Open Access Journals (Sweden)

    Marcus Lechner

    Full Text Available The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets.

  12. SIMADL: Simulated Activities of Daily Living Dataset

    Directory of Open Access Journals (Sweden)

    Talal Alshammari

    2018-04-01

    Full Text Available With the realisation of the Internet of Things (IoT paradigm, the analysis of the Activities of Daily Living (ADLs, in a smart home environment, is becoming an active research domain. The existence of representative datasets is a key requirement to advance the research in smart home design. Such datasets are an integral part of the visualisation of new smart home concepts as well as the validation and evaluation of emerging machine learning models. Machine learning techniques that can learn ADLs from sensor readings are used to classify, predict and detect anomalous patterns. Such techniques require data that represent relevant smart home scenarios, for training, testing and validation. However, the development of such machine learning techniques is limited by the lack of real smart home datasets, due to the excessive cost of building real smart homes. This paper provides two datasets for classification and anomaly detection. The datasets are generated using OpenSHS, (Open Smart Home Simulator, which is a simulation software for dataset generation. OpenSHS records the daily activities of a participant within a virtual environment. Seven participants simulated their ADLs for different contexts, e.g., weekdays, weekends, mornings and evenings. Eighty-four files in total were generated, representing approximately 63 days worth of activities. Forty-two files of classification of ADLs were simulated in the classification dataset and the other forty-two files are for anomaly detection problems in which anomalous patterns were simulated and injected into the anomaly detection dataset.

  13. ASSISTments Dataset from Multiple Randomized Controlled Experiments

    Science.gov (United States)

    Selent, Douglas; Patikorn, Thanaporn; Heffernan, Neil

    2016-01-01

    In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…

  14. Synthetic and Empirical Capsicum Annuum Image Dataset

    NARCIS (Netherlands)

    Barth, R.

    2016-01-01

    This dataset consists of per-pixel annotated synthetic (10500) and empirical images (50) of Capsicum annuum, also known as sweet or bell pepper, situated in a commercial greenhouse. Furthermore, the source models to generate the synthetic images are included. The aim of the datasets are to

  15. Design of an audio advertisement dataset

    Science.gov (United States)

    Fu, Yutao; Liu, Jihong; Zhang, Qi; Geng, Yuting

    2015-12-01

    Since more and more advertisements swarm into radios, it is necessary to establish an audio advertising dataset which could be used to analyze and classify the advertisement. A method of how to establish a complete audio advertising dataset is presented in this paper. The dataset is divided into four different kinds of advertisements. Each advertisement's sample is given in *.wav file format, and annotated with a txt file which contains its file name, sampling frequency, channel number, broadcasting time and its class. The classifying rationality of the advertisements in this dataset is proved by clustering the different advertisements based on Principal Component Analysis (PCA). The experimental results show that this audio advertisement dataset offers a reliable set of samples for correlative audio advertisement experimental studies.

  16. CoVennTree: A new method for the comparative analysis of large datasets

    Directory of Open Access Journals (Sweden)

    Steffen C. Lott

    2015-02-01

    Full Text Available The visualization of massive datasets, such as those resulting from comparative metatranscriptome analyses or the analysis of microbial population structures using ribosomal RNA sequences, is a challenging task. We developed a new method called CoVennTree (Comparative weighted Venn Tree that simultaneously compares up to three multifarious datasets by aggregating and propagating information from the bottom to the top level and produces a graphical output in Cytoscape. With the introduction of weighted Venn structures, the contents and relationships of various datasets can be correlated and simultaneously aggregated without losing information. We demonstrate the suitability of this approach using a dataset of 16S rDNA sequences obtained from microbial populations at three different depths of the Gulf of Aqaba in the Red Sea. CoVennTree has been integrated into the Galaxy ToolShed and can be directly downloaded and integrated into the user instance.

  17. The Kinetics Human Action Video Dataset

    OpenAIRE

    Kay, Will; Carreira, Joao; Simonyan, Karen; Zhang, Brian; Hillier, Chloe; Vijayanarasimhan, Sudheendra; Viola, Fabio; Green, Tim; Back, Trevor; Natsev, Paul; Suleyman, Mustafa; Zisserman, Andrew

    2017-01-01

    We describe the DeepMind Kinetics human action video dataset. The dataset contains 400 human action classes, with at least 400 video clips for each action. Each clip lasts around 10s and is taken from a different YouTube video. The actions are human focussed and cover a broad range of classes including human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands. We describe the statistics of the dataset, how it was collected, and give some ...

  18. Discovery of precursor and mature microRNAs and their putative gene targets using high-throughput sequencing in pineapple (Ananas comosus var. comosus).

    Science.gov (United States)

    Yusuf, Noor Hydayaty Md; Ong, Wen Dee; Redwan, Raimi Mohamed; Latip, Mariam Abd; Kumar, S Vijay

    2015-10-15

    MicroRNAs (miRNAs) are a class of small, endogenous non-coding RNAs that negatively regulate gene expression, resulting in the silencing of target mRNA transcripts through mRNA cleavage or translational inhibition. MiRNAs play significant roles in various biological and physiological processes in plants. However, the miRNA-mediated gene regulatory network in pineapple, the model tropical non-climacteric fruit, remains largely unexplored. Here, we report a complete list of pineapple mature miRNAs obtained from high-throughput small RNA sequencing and precursor miRNAs (pre-miRNAs) obtained from ESTs. Two small RNA libraries were constructed from pineapple fruits and leaves, respectively, using Illumina's Solexa technology. Sequence similarity analysis using miRBase revealed 579,179 reads homologous to 153 miRNAs from 41 miRNA families. In addition, a pineapple fruit transcriptome library consisting of approximately 30,000 EST contigs constructed using Solexa sequencing was used for the discovery of pre-miRNAs. In all, four pre-miRNAs were identified (MIR156, MIR399, MIR444 and MIR2673). Furthermore, the same pineapple transcriptome was used to dissect the function of the miRNAs in pineapple by predicting their putative targets in conjunction with their regulatory networks. In total, 23 metabolic pathways were found to be regulated by miRNAs in pineapple. The use of high-throughput sequencing in pineapples to unveil the presence of miRNAs and their regulatory pathways provides insight into the repertoire of miRNA regulation used exclusively in this non-climacteric model plant. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. BASE MAP DATASET, LOS ANGELES COUNTY, CALIFORNIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  20. BASE MAP DATASET, CHEROKEE COUNTY, SOUTH CAROLINA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  1. SIAM 2007 Text Mining Competition dataset

    Data.gov (United States)

    National Aeronautics and Space Administration — Subject Area: Text Mining Description: This is the dataset used for the SIAM 2007 Text Mining competition. This competition focused on developing text mining...

  2. Harvard Aging Brain Study : Dataset and accessibility

    NARCIS (Netherlands)

    Dagley, Alexander; LaPoint, Molly; Huijbers, Willem; Hedden, Trey; McLaren, Donald G.; Chatwal, Jasmeer P.; Papp, Kathryn V.; Amariglio, Rebecca E.; Blacker, Deborah; Rentz, Dorene M.; Johnson, Keith A.; Sperling, Reisa A.; Schultz, Aaron P.

    2017-01-01

    The Harvard Aging Brain Study is sharing its data with the global research community. The longitudinal dataset consists of a 284-subject cohort with the following modalities acquired: demographics, clinical assessment, comprehensive neuropsychological testing, clinical biomarkers, and neuroimaging.

  3. BASE MAP DATASET, HONOLULU COUNTY, HAWAII, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  4. BASE MAP DATASET, EDGEFIELD COUNTY, SOUTH CAROLINA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  5. Simulation of Smart Home Activity Datasets

    Directory of Open Access Journals (Sweden)

    Jonathan Synnott

    2015-06-01

    Full Text Available A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

  6. Simulation of Smart Home Activity Datasets.

    Science.gov (United States)

    Synnott, Jonathan; Nugent, Chris; Jeffers, Paul

    2015-06-16

    A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

  7. Environmental Dataset Gateway (EDG) REST Interface

    Data.gov (United States)

    U.S. Environmental Protection Agency — Use the Environmental Dataset Gateway (EDG) to find and access EPA's environmental resources. Many options are available for easily reusing EDG content in other...

  8. BASE MAP DATASET, INYO COUNTY, OKLAHOMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  9. BASE MAP DATASET, JACKSON COUNTY, OKLAHOMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  10. BASE MAP DATASET, SANTA CRIZ COUNTY, CALIFORNIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  11. Climate Prediction Center IR 4km Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CPC IR 4km dataset was created from all available individual geostationary satellite data which have been merged to form nearly seamless global (60N-60S) IR...

  12. BASE MAP DATASET, MAYES COUNTY, OKLAHOMA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications: cadastral, geodetic control,...

  13. BASE MAP DATASET, KINGFISHER COUNTY, OKLAHOMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme,...

  14. High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

    Science.gov (United States)

    Greub, Gilbert; Kebbi-Beghdadi, Carole; Bertelli, Claire; Collyn, François; Riederer, Beat M; Yersin, Camille; Croxatto, Antony; Raoult, Didier

    2009-12-23

    With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.

  15. Comparison of Shallow Survey 2012 Multibeam Datasets

    Science.gov (United States)

    Ramirez, T. M.

    2012-12-01

    The purpose of the Shallow Survey common dataset is a comparison of the different technologies utilized for data acquisition in the shallow survey marine environment. The common dataset consists of a series of surveys conducted over a common area of seabed using a variety of systems. It provides equipment manufacturers the opportunity to showcase their latest systems while giving hydrographic researchers and scientists a chance to test their latest algorithms on the dataset so that rigorous comparisons can be made. Five companies collected data for the Common Dataset in the Wellington Harbor area in New Zealand between May 2010 and May 2011; including Kongsberg, Reson, R2Sonic, GeoAcoustics, and Applied Acoustics. The Wellington harbor and surrounding coastal area was selected since it has a number of well-defined features, including the HMNZS South Seas and HMNZS Wellington wrecks, an armored seawall constructed of Tetrapods and Akmons, aquifers, wharves and marinas. The seabed inside the harbor basin is largely fine-grained sediment, with gravel and reefs around the coast. The area outside the harbor on the southern coast is an active environment, with moving sand and exposed reefs. A marine reserve is also in this area. For consistency between datasets, the coastal research vessel R/V Ikatere and crew were used for all surveys conducted for the common dataset. Using Triton's Perspective processing software multibeam datasets collected for the Shallow Survey were processed for detail analysis. Datasets from each sonar manufacturer were processed using the CUBE algorithm developed by the Center for Coastal and Ocean Mapping/Joint Hydrographic Center (CCOM/JHC). Each dataset was gridded at 0.5 and 1.0 meter resolutions for cross comparison and compliance with International Hydrographic Organization (IHO) requirements. Detailed comparisons were made of equipment specifications (transmit frequency, number of beams, beam width), data density, total uncertainty, and

  16. 3DSEM: A 3D microscopy dataset

    Directory of Open Access Journals (Sweden)

    Ahmad P. Tafti

    2016-03-01

    Full Text Available The Scanning Electron Microscope (SEM as a 2D imaging instrument has been widely used in many scientific disciplines including biological, mechanical, and materials sciences to determine the surface attributes of microscopic objects. However the SEM micrographs still remain 2D images. To effectively measure and visualize the surface properties, we need to truly restore the 3D shape model from 2D SEM images. Having 3D surfaces would provide anatomic shape of micro-samples which allows for quantitative measurements and informative visualization of the specimens being investigated. The 3DSEM is a dataset for 3D microscopy vision which is freely available at [1] for any academic, educational, and research purposes. The dataset includes both 2D images and 3D reconstructed surfaces of several real microscopic samples. Keywords: 3D microscopy dataset, 3D microscopy vision, 3D SEM surface reconstruction, Scanning Electron Microscope (SEM

  17. Data Mining for Imbalanced Datasets: An Overview

    Science.gov (United States)

    Chawla, Nitesh V.

    A dataset is imbalanced if the classification categories are not approximately equally represented. Recent years brought increased interest in applying machine learning techniques to difficult "real-world" problems, many of which are characterized by imbalanced data. Additionally the distribution of the testing data may differ from that of the training data, and the true misclassification costs may be unknown at learning time. Predictive accuracy, a popular choice for evaluating performance of a classifier, might not be appropriate when the data is imbalanced and/or the costs of different errors vary markedly. In this Chapter, we discuss some of the sampling techniques used for balancing the datasets, and the performance measures more appropriate for mining imbalanced datasets.

  18. Harvard Aging Brain Study: Dataset and accessibility.

    Science.gov (United States)

    Dagley, Alexander; LaPoint, Molly; Huijbers, Willem; Hedden, Trey; McLaren, Donald G; Chatwal, Jasmeer P; Papp, Kathryn V; Amariglio, Rebecca E; Blacker, Deborah; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Schultz, Aaron P

    2017-01-01

    The Harvard Aging Brain Study is sharing its data with the global research community. The longitudinal dataset consists of a 284-subject cohort with the following modalities acquired: demographics, clinical assessment, comprehensive neuropsychological testing, clinical biomarkers, and neuroimaging. To promote more extensive analyses, imaging data was designed to be compatible with other publicly available datasets. A cloud-based system enables access to interested researchers with blinded data available contingent upon completion of a data usage agreement and administrative approval. Data collection is ongoing and currently in its fifth year. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. De novo transcriptome sequencing of axolotl blastema for identification of differentially expressed genes during limb regeneration

    Science.gov (United States)

    2013-01-01

    Background Salamanders are unique among vertebrates in their ability to completely regenerate amputated limbs through the mediation of blastema cells located at the stump ends. This regeneration is nerve-dependent because blastema formation and regeneration does not occur after limb denervation. To obtain the genomic information of blastema tissues, de novo transcriptomes from both blastema tissues and denervated stump ends of Ambystoma mexicanum (axolotls) 14 days post-amputation were sequenced and compared using Solexa DNA sequencing. Results The sequencing done for this study produced 40,688,892 reads that were assembled into 307,345 transcribed sequences. The N50 of transcribed sequence length was 562 bases. A similarity search with known proteins identified 39,200 different genes to be expressed during limb regeneration with a cut-off E-value exceeding 10-5. We annotated assembled sequences by using gene descriptions, gene ontology, and clusters of orthologous group terms. Targeted searches using these annotations showed that the majority of the genes were in the categories of essential metabolic pathways, transcription factors and conserved signaling pathways, and novel candidate genes for regenerative processes. We discovered and confirmed numerous sequences of the candidate genes by using quantitative polymerase chain reaction and in situ hybridization. Conclusion The results of this study demonstrate that de novo transcriptome sequencing allows gene expression analysis in a species lacking genome information and provides the most comprehensive mRNA sequence resources for axolotls. The characterization of the axolotl transcriptome can help elucidate the molecular mechanisms underlying blastema formation during limb regeneration. PMID:23815514

  20. Random Coefficient Logit Model for Large Datasets

    NARCIS (Netherlands)

    C. Hernández-Mireles (Carlos); D. Fok (Dennis)

    2010-01-01

    textabstractWe present an approach for analyzing market shares and products price elasticities based on large datasets containing aggregate sales data for many products, several markets and for relatively long time periods. We consider the recently proposed Bayesian approach of Jiang et al [Jiang,

  1. Thesaurus Dataset of Educational Technology in Chinese

    Science.gov (United States)

    Wu, Linjing; Liu, Qingtang; Zhao, Gang; Huang, Huan; Huang, Tao

    2015-01-01

    The thesaurus dataset of educational technology is a knowledge description of educational technology in Chinese. The aims of this thesaurus were to collect the subject terms in the domain of educational technology, facilitate the standardization of terminology and promote the communication between Chinese researchers and scholars from various…

  2. Identification and characterization of novel and differentially expressed microRNAs in peripheral blood from healthy and mastitis Holstein cattle by deep sequencing.

    Science.gov (United States)

    Li, Zhixiong; Wang, Hongliang; Chen, Ling; Wang, Lijun; Liu, Xiaolin; Ru, Caixia; Song, Ailong

    2014-02-01

    MicroRNA (miRNA) mediates post-transcriptional gene regulation and plays an important role in regulating the development of immune cells and in modulating innate and adaptive immune responses in mammals, including cattle. In the present study, we identified novel and differentially expressed miRNAs in peripheral blood from healthy and mastitis Holstein cattle by Solexa sequencing and bioinformatics. In total, 608 precursor hairpins (pre-miRNAs) encoding for 753 mature miRNAs were detected. Statistically, 173 unique miRNAs (of 753, 22.98%) were identified that had significant differential expression between healthy and mastitis Holstein cattle (P mastitis Holstein cattle, which provide important information on mastitis in miRNAs expression. Diverse miRNAs may play an important role in the treatment of mastitis in Holstein cattle. © 2013 Stichting International Foundation for Animal Genetics.

  3. BayesMotif: de novo protein sorting motif discovery from impure datasets.

    Science.gov (United States)

    Hu, Jianjun; Zhang, Fan

    2010-01-18

    Protein sorting is the process that newly synthesized proteins are transported to their target locations within or outside of the cell. This process is precisely regulated by protein sorting signals in different forms. A major category of sorting signals are amino acid sub-sequences usually located at the N-terminals or C-terminals of protein sequences. Genome-wide experimental identification of protein sorting signals is extremely time-consuming and costly. Effective computational algorithms for de novo discovery of protein sorting signals is needed to improve the understanding of protein sorting mechanisms. We formulated the protein sorting motif discovery problem as a classification problem and proposed a Bayesian classifier based algorithm (BayesMotif) for de novo identification of a common type of protein sorting motifs in which a highly conserved anchor is present along with a less conserved motif regions. A false positive removal procedure is developed to iteratively remove sequences that are unlikely to contain true motifs so that the algorithm can identify motifs from impure input sequences. Experiments on both implanted motif datasets and real-world datasets showed that the enhanced BayesMotif algorithm can identify anchored sorting motifs from pure or impure protein sequence dataset. It also shows that the false positive removal procedure can help to identify true motifs even when there is only 20% of the input sequences containing true motif instances. We proposed BayesMotif, a novel Bayesian classification based algorithm for de novo discovery of a special category of anchored protein sorting motifs from impure datasets. Compared to conventional motif discovery algorithms such as MEME, our algorithm can find less-conserved motifs with short highly conserved anchors. Our algorithm also has the advantage of easy incorporation of additional meta-sequence features such as hydrophobicity or charge of the motifs which may help to overcome the limitations of

  4. MicroRNA repertoire for functional genome research in tilapia identified by deep sequencing.

    Science.gov (United States)

    Yan, Biao; Wang, Zhen-Hua; Zhu, Chang-Dong; Guo, Jin-Tao; Zhao, Jin-Liang

    2014-08-01

    The Nile tilapia (Oreochromis niloticus; Cichlidae) is an economically important species in aquaculture and occupies a prominent position in the aquaculture industry. MicroRNAs (miRNAs) are a class of noncoding RNAs that post-transcriptionally regulate gene expression involved in diverse biological and metabolic processes. To increase the repertoire of miRNAs characterized in tilapia, we used the Illumina/Solexa sequencing technology to sequence a small RNA library using pooled RNA sample isolated from the different developmental stages of tilapia. Bioinformatic analyses suggest that 197 conserved and 27 novel miRNAs are expressed in tilapia. Sequence alignments indicate that all tested miRNAs and miRNAs* are highly conserved across many species. In addition, we characterized the tissue expression patterns of five miRNAs using real-time quantitative PCR. We found that miR-1/206, miR-7/9, and miR-122 is abundantly expressed in muscle, brain, and liver, respectively, implying a potential role in the regulation of tissue differentiation or the maintenance of tissue identity. Overall, our results expand the number of tilapia miRNAs, and the discovery of miRNAs in tilapia genome contributes to a better understanding the role of miRNAs in regulating diverse biological processes.

  5. Robust computational analysis of rRNA hypervariable tag datasets.

    Directory of Open Access Journals (Sweden)

    Maksim Sipos

    Full Text Available Next-generation DNA sequencing is increasingly being utilized to probe microbial communities, such as gastrointestinal microbiomes, where it is important to be able to quantify measures of abundance and diversity. The fragmented nature of the 16S rRNA datasets obtained, coupled with their unprecedented size, has led to the recognition that the results of such analyses are potentially contaminated by a variety of artifacts, both experimental and computational. Here we quantify how multiple alignment and clustering errors contribute to overestimates of abundance and diversity, reflected by incorrect OTU assignment, corrupted phylogenies, inaccurate species diversity estimators, and rank abundance distribution functions. We show that straightforward procedural optimizations, combining preexisting tools, are effective in handling large (10(5-10(6 16S rRNA datasets, and we describe metrics to measure the effectiveness and quality of the estimators obtained. We introduce two metrics to ascertain the quality of clustering of pyrosequenced rRNA data, and show that complete linkage clustering greatly outperforms other widely used methods.

  6. Sharing Video Datasets in Design Research

    DEFF Research Database (Denmark)

    Christensen, Bo; Abildgaard, Sille Julie Jøhnk

    2017-01-01

    This paper examines how design researchers, design practitioners and design education can benefit from sharing a dataset. We present the Design Thinking Research Symposium 11 (DTRS11) as an exemplary project that implied sharing video data of design processes and design activity in natural settings...... with a large group of fellow academics from the international community of Design Thinking Research, for the purpose of facilitating research collaboration and communication within the field of Design and Design Thinking. This approach emphasizes the social and collaborative aspects of design research, where...... a multitude of appropriate perspectives and methods may be utilized in analyzing and discussing the singular dataset. The shared data is, from this perspective, understood as a design object in itself, which facilitates new ways of working, collaborating, studying, learning and educating within the expanding...

  7. Automatic processing of multimodal tomography datasets.

    Science.gov (United States)

    Parsons, Aaron D; Price, Stephen W T; Wadeson, Nicola; Basham, Mark; Beale, Andrew M; Ashton, Alun W; Mosselmans, J Frederick W; Quinn, Paul D

    2017-01-01

    With the development of fourth-generation high-brightness synchrotrons on the horizon, the already large volume of data that will be collected on imaging and mapping beamlines is set to increase by orders of magnitude. As such, an easy and accessible way of dealing with such large datasets as quickly as possible is required in order to be able to address the core scientific problems during the experimental data collection. Savu is an accessible and flexible big data processing framework that is able to deal with both the variety and the volume of data of multimodal and multidimensional scientific datasets output such as those from chemical tomography experiments on the I18 microfocus scanning beamline at Diamond Light Source.

  8. Interpolation of diffusion weighted imaging datasets

    DEFF Research Database (Denmark)

    Dyrby, Tim B; Lundell, Henrik; Burke, Mark W

    2014-01-01

    anatomical details and signal-to-noise-ratio for reliable fibre reconstruction. We assessed the potential benefits of interpolating DWI datasets to a higher image resolution before fibre reconstruction using a diffusion tensor model. Simulations of straight and curved crossing tracts smaller than or equal......Diffusion weighted imaging (DWI) is used to study white-matter fibre organisation, orientation and structural connectivity by means of fibre reconstruction algorithms and tractography. For clinical settings, limited scan time compromises the possibilities to achieve high image resolution for finer...... interpolation methods fail to disentangle fine anatomical details if PVE is too pronounced in the original data. As for validation we used ex-vivo DWI datasets acquired at various image resolutions as well as Nissl-stained sections. Increasing the image resolution by a factor of eight yielded finer geometrical...

  9. Data assimilation and model evaluation experiment datasets

    Science.gov (United States)

    Lai, Chung-Cheng A.; Qian, Wen; Glenn, Scott M.

    1994-01-01

    The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

  10. A hybrid organic-inorganic perovskite dataset

    Science.gov (United States)

    Kim, Chiho; Huan, Tran Doan; Krishnan, Sridevi; Ramprasad, Rampi

    2017-05-01

    Hybrid organic-inorganic perovskites (HOIPs) have been attracting a great deal of attention due to their versatility of electronic properties and fabrication methods. We prepare a dataset of 1,346 HOIPs, which features 16 organic cations, 3 group-IV cations and 4 halide anions. Using a combination of an atomic structure search method and density functional theory calculations, the optimized structures, the bandgap, the dielectric constant, and the relative energies of the HOIPs are uniformly prepared and validated by comparing with relevant experimental and/or theoretical data. We make the dataset available at Dryad Digital Repository, NoMaD Repository, and Khazana Repository (http://khazana.uconn.edu/), hoping that it could be useful for future data-mining efforts that can explore possible structure-property relationships and phenomenological models. Progressive extension of the dataset is expected as new organic cations become appropriate within the HOIP framework, and as additional properties are calculated for the new compounds found.

  11. Identifying driver mutations in sequenced cancer genomes

    DEFF Research Database (Denmark)

    Raphael, Benjamin J; Dobson, Jason R; Oesper, Layla

    2014-01-01

    High-throughput DNA sequencing is revolutionizing the study of cancer and enabling the measurement of the somatic mutations that drive cancer development. However, the resulting sequencing datasets are large and complex, obscuring the clinically important mutations in a background of errors, nois...... patterns of mutual exclusivity. These techniques, coupled with advances in high-throughput DNA sequencing, are enabling precision medicine approaches to the diagnosis and treatment of cancer....

  12. Quantifying uncertainty in observational rainfall datasets

    Science.gov (United States)

    Lennard, Chris; Dosio, Alessandro; Nikulin, Grigory; Pinto, Izidine; Seid, Hussen

    2015-04-01

    The CO-ordinated Regional Downscaling Experiment (CORDEX) has to date seen the publication of at least ten journal papers that examine the African domain during 2012 and 2013. Five of these papers consider Africa generally (Nikulin et al. 2012, Kim et al. 2013, Hernandes-Dias et al. 2013, Laprise et al. 2013, Panitz et al. 2013) and five have regional foci: Tramblay et al. (2013) on Northern Africa, Mariotti et al. (2014) and Gbobaniyi el al. (2013) on West Africa, Endris et al. (2013) on East Africa and Kalagnoumou et al. (2013) on southern Africa. There also are a further three papers that the authors know about under review. These papers all use an observed rainfall and/or temperature data to evaluate/validate the regional model output and often proceed to assess projected changes in these variables due to climate change in the context of these observations. The most popular reference rainfall data used are the CRU, GPCP, GPCC, TRMM and UDEL datasets. However, as Kalagnoumou et al. (2013) point out there are many other rainfall datasets available for consideration, for example, CMORPH, FEWS, TAMSAT & RIANNAA, TAMORA and the WATCH & WATCH-DEI data. They, with others (Nikulin et al. 2012, Sylla et al. 2012) show that the observed datasets can have a very wide spread at a particular space-time coordinate. As more ground, space and reanalysis-based rainfall products become available, all which use different methods to produce precipitation data, the selection of reference data is becoming an important factor in model evaluation. A number of factors can contribute to a uncertainty in terms of the reliability and validity of the datasets such as radiance conversion algorithims, the quantity and quality of available station data, interpolation techniques and blending methods used to combine satellite and guage based products. However, to date no comprehensive study has been performed to evaluate the uncertainty in these observational datasets. We assess 18 gridded

  13. Phylogenetic factorization of compositional data yields lineage-level associations in microbiome datasets.

    Science.gov (United States)

    Washburne, Alex D; Silverman, Justin D; Leff, Jonathan W; Bennett, Dominic J; Darcy, John L; Mukherjee, Sayan; Fierer, Noah; David, Lawrence A

    2017-01-01

    Marker gene sequencing of microbial communities has generated big datasets of microbial relative abundances varying across environmental conditions, sample sites and treatments. These data often come with putative phylogenies, providing unique opportunities to investigate how shared evolutionary history affects microbial abundance patterns. Here, we present a method to identify the phylogenetic factors driving patterns in microbial community composition. We use the method, "phylofactorization," to re-analyze datasets from the human body and soil microbial communities, demonstrating how phylofactorization is a dimensionality-reducing tool, an ordination-visualization tool, and an inferential tool for identifying edges in the phylogeny along which putative functional ecological traits may have arisen.

  14. Characterization and Development of EST-SSRs by Deep Transcriptome Sequencing in Chinese Cabbage (Brassica rapa L. ssp. pekinensis

    Directory of Open Access Journals (Sweden)

    Qian Ding

    2015-01-01

    Full Text Available Simple sequence repeats (SSRs are among the most important markers for population analysis and have been widely used in plant genetic mapping and molecular breeding. Expressed sequence tag-SSR (EST-SSR markers, located in the coding regions, are potentially more efficient for QTL mapping, gene targeting, and marker-assisted breeding. In this study, we investigated 51,694 nonredundant unigenes, assembled from clean reads from deep transcriptome sequencing with a Solexa/Illumina platform, for identification and development of EST-SSRs in Chinese cabbage. In total, 10,420 EST-SSRs with over 12 bp were identified and characterized, among which 2744 EST-SSRs are new and 2317 are known ones showing polymorphism with previously reported SSRs. A total of 7877 PCR primer pairs for 1561 EST-SSR loci were designed, and primer pairs for twenty-four EST-SSRs were selected for primer evaluation. In nineteen EST-SSR loci (79.2%, amplicons were successfully generated with high quality. Seventeen (89.5% showed polymorphism in twenty-four cultivars of Chinese cabbage. The polymorphic alleles of each polymorphic locus were sequenced, and the results showed that most polymorphisms were due to variations of SSR repeat motifs. The EST-SSRs identified and characterized in this study have important implications for developing new tools for genetics and molecular breeding in Chinese cabbage.

  15. Development of a SPARK Training Dataset

    Energy Technology Data Exchange (ETDEWEB)

    Sayre, Amanda M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Olson, Jarrod R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-03-01

    In its first five years, the National Nuclear Security Administration’s (NNSA) Next Generation Safeguards Initiative (NGSI) sponsored more than 400 undergraduate, graduate, and post-doctoral students in internships and research positions (Wyse 2012). In the past seven years, the NGSI program has, and continues to produce a large body of scientific, technical, and policy work in targeted core safeguards capabilities and human capital development activities. Not only does the NGSI program carry out activities across multiple disciplines, but also across all U.S. Department of Energy (DOE)/NNSA locations in the United States. However, products are not readily shared among disciplines and across locations, nor are they archived in a comprehensive library. Rather, knowledge of NGSI-produced literature is localized to the researchers, clients, and internal laboratory/facility publication systems such as the Electronic Records and Information Capture Architecture (ERICA) at the Pacific Northwest National Laboratory (PNNL). There is also no incorporated way of analyzing existing NGSI literature to determine whether the larger NGSI program is achieving its core safeguards capabilities and activities. A complete library of NGSI literature could prove beneficial to a cohesive, sustainable, and more economical NGSI program. The Safeguards Platform for Automated Retrieval of Knowledge (SPARK) has been developed to be a knowledge storage, retrieval, and analysis capability to capture safeguards knowledge to exist beyond the lifespan of NGSI. During the development process, it was necessary to build a SPARK training dataset (a corpus of documents) for initial entry into the system and for demonstration purposes. We manipulated these data to gain new information about the breadth of NGSI publications, and they evaluated the science-policy interface at PNNL as a practical demonstration of SPARK’s intended analysis capability. The analysis demonstration sought to answer the

  16. Development of a SPARK Training Dataset

    International Nuclear Information System (INIS)

    Sayre, Amanda M.; Olson, Jarrod R.

    2015-01-01

    In its first five years, the National Nuclear Security Administration's (NNSA) Next Generation Safeguards Initiative (NGSI) sponsored more than 400 undergraduate, graduate, and post-doctoral students in internships and research positions (Wyse 2012). In the past seven years, the NGSI program has, and continues to produce a large body of scientific, technical, and policy work in targeted core safeguards capabilities and human capital development activities. Not only does the NGSI program carry out activities across multiple disciplines, but also across all U.S. Department of Energy (DOE)/NNSA locations in the United States. However, products are not readily shared among disciplines and across locations, nor are they archived in a comprehensive library. Rather, knowledge of NGSI-produced literature is localized to the researchers, clients, and internal laboratory/facility publication systems such as the Electronic Records and Information Capture Architecture (ERICA) at the Pacific Northwest National Laboratory (PNNL). There is also no incorporated way of analyzing existing NGSI literature to determine whether the larger NGSI program is achieving its core safeguards capabilities and activities. A complete library of NGSI literature could prove beneficial to a cohesive, sustainable, and more economical NGSI program. The Safeguards Platform for Automated Retrieval of Knowledge (SPARK) has been developed to be a knowledge storage, retrieval, and analysis capability to capture safeguards knowledge to exist beyond the lifespan of NGSI. During the development process, it was necessary to build a SPARK training dataset (a corpus of documents) for initial entry into the system and for demonstration purposes. We manipulated these data to gain new information about the breadth of NGSI publications, and they evaluated the science-policy interface at PNNL as a practical demonstration of SPARK's intended analysis capability. The analysis demonstration sought to answer

  17. Developing a Data-Set for Stereopsis

    Directory of Open Access Journals (Sweden)

    D.W Hunter

    2014-08-01

    Full Text Available Current research on binocular stereopsis in humans and non-human primates has been limited by a lack of available data-sets. Current data-sets fall into two categories; stereo-image sets with vergence but no ranging information (Hibbard, 2008, Vision Research, 48(12, 1427-1439 or combinations of depth information with binocular images and video taken from cameras in fixed fronto-parallel configurations exhibiting neither vergence or focus effects (Hirschmuller & Scharstein, 2007, IEEE Conf. Computer Vision and Pattern Recognition. The techniques for generating depth information are also imperfect. Depth information is normally inaccurate or simply missing near edges and on partially occluded surfaces. For many areas of vision research these are the most interesting parts of the image (Goutcher, Hunter, Hibbard, 2013, i-Perception, 4(7, 484; Scarfe & Hibbard, 2013, Vision Research. Using state-of-the-art open-source ray-tracing software (PBRT as a back-end, our intention is to release a set of tools that will allow researchers in this field to generate artificial binocular stereoscopic data-sets. Although not as realistic as photographs, computer generated images have significant advantages in terms of control over the final output and ground-truth information about scene depth is easily calculated at all points in the scene, even partially occluded areas. While individual researchers have been developing similar stimuli by hand for many decades, we hope that our software will greatly reduce the time and difficulty of creating naturalistic binocular stimuli. Our intension in making this presentation is to elicit feedback from the vision community about what sort of features would be desirable in such software.

  18. Sequence assembly

    DEFF Research Database (Denmark)

    Scheibye-Alsing, Karsten; Hoffmann, S.; Frankel, Annett Maria

    2009-01-01

    Despite the rapidly increasing number of sequenced and re-sequenced genomes, many issues regarding the computational assembly of large-scale sequencing data have remain unresolved. Computational assembly is crucial in large genome projects as well for the evolving high-throughput technologies and...... in genomic DNA, highly expressed genes and alternative transcripts in EST sequences. We summarize existing comparisons of different assemblers and provide a detailed descriptions and directions for download of assembly programs at: http://genome.ku.dk/resources/assembly/methods.html....

  19. Genome Sequencing

    DEFF Research Database (Denmark)

    Sato, Shusei; Andersen, Stig Uggerhøj

    2014-01-01

    The current Lotus japonicus reference genome sequence is based on a hybrid assembly of Sanger TAC/BAC, Sanger shotgun and Illumina shotgun sequencing data generated from the Miyakojima-MG20 accession. It covers nearly all expressed L. japonicus genes and has been annotated mainly based on transcr......The current Lotus japonicus reference genome sequence is based on a hybrid assembly of Sanger TAC/BAC, Sanger shotgun and Illumina shotgun sequencing data generated from the Miyakojima-MG20 accession. It covers nearly all expressed L. japonicus genes and has been annotated mainly based...

  20. Quality Controlling CMIP datasets at GFDL

    Science.gov (United States)

    Horowitz, L. W.; Radhakrishnan, A.; Balaji, V.; Adcroft, A.; Krasting, J. P.; Nikonov, S.; Mason, E. E.; Schweitzer, R.; Nadeau, D.

    2017-12-01

    As GFDL makes the switch from model development to production in light of the Climate Model Intercomparison Project (CMIP), GFDL's efforts are shifted to testing and more importantly establishing guidelines and protocols for Quality Controlling and semi-automated data publishing. Every CMIP cycle introduces key challenges and the upcoming CMIP6 is no exception. The new CMIP experimental design comprises of multiple MIPs facilitating research in different focus areas. This paradigm has implications not only for the groups that develop the models and conduct the runs, but also for the groups that monitor, analyze and quality control the datasets before data publishing, before their knowledge makes its way into reports like the IPCC (Intergovernmental Panel on Climate Change) Assessment Reports. In this talk, we discuss some of the paths taken at GFDL to quality control the CMIP-ready datasets including: Jupyter notebooks, PrePARE, LAMP (Linux, Apache, MySQL, PHP/Python/Perl): technology-driven tracker system to monitor the status of experiments qualitatively and quantitatively, provide additional metadata and analysis services along with some in-built controlled-vocabulary validations in the workflow. In addition to this, we also discuss the integration of community-based model evaluation software (ESMValTool, PCMDI Metrics Package, and ILAMB) as part of our CMIP6 workflow.

  1. Integrated remotely sensed datasets for disaster management

    Science.gov (United States)

    McCarthy, Timothy; Farrell, Ronan; Curtis, Andrew; Fotheringham, A. Stewart

    2008-10-01

    Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, routecorridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North America's NTSC and European SECAM and PAL television systems that are then recorded using various video formats. This technology has recently being employed as a front-line, remote sensing technology for damage assessment post-disaster. This paper traces the development of spatial video as a remote sensing tool from the early 1980s to the present day. The background to a new spatial-video research initiative based at National University of Ireland, Maynooth, (NUIM) is described. New improvements are proposed and include; low-cost encoders, easy to use software decoders, timing issues and interoperability. These developments will enable specialists and non-specialists collect, process and integrate these datasets within minimal support. This integrated approach will enable decision makers to access relevant remotely sensed datasets quickly and so, carry out rapid damage assessment during and post-disaster.

  2. Common integration sites of published datasets identified using a graph-based framework

    Directory of Open Access Journals (Sweden)

    Alessandro Vasciaveo

    2016-01-01

    Full Text Available With next-generation sequencing, the genomic data available for the characterization of integration sites (IS has dramatically increased. At present, in a single experiment, several thousand viral integration genome targets can be investigated to define genomic hot spots. In a previous article, we renovated a formal CIS analysis based on a rigid fixed window demarcation into a more stretchy definition grounded on graphs. Here, we present a selection of supporting data related to the graph-based framework (GBF from our previous article, in which a collection of common integration sites (CIS was identified on six published datasets. In this work, we will focus on two datasets, ISRTCGD and ISHIV, which have been previously discussed. Moreover, we show in more detail the workflow design that originates the datasets.

  3. Assignment tests for variety identification compared to genetic similarity-based methods using experimental datasets from different marker systems in sugar beet

    NARCIS (Netherlands)

    Riek, de J.; Everaert, I.; Esselink, D.; Calsyn, E.; Smulders, M.J.M.; Vosman, B.

    2007-01-01

    High genetic variation within sugar beet (Beta vulgaris L.) varieties hampers reliable classification procedures independent of the type of marker technique applied. Datasets on amplified fragment length polymorphisms, sequence tagged microsatellite sites, and cleaved amplified polymorphic sites

  4. Sequence based polymorphic (SBP marker technology for targeted genomic regions: its application in generating a molecular map of the Arabidopsis thaliana genome

    Directory of Open Access Journals (Sweden)

    Sahu Binod B

    2012-01-01

    Full Text Available Abstract Background Molecular markers facilitate both genotype identification, essential for modern animal and plant breeding, and the isolation of genes based on their map positions. Advancements in sequencing technology have made possible the identification of single nucleotide polymorphisms (SNPs for any genomic regions. Here a sequence based polymorphic (SBP marker technology for generating molecular markers for targeted genomic regions in Arabidopsis is described. Results A ~3X genome coverage sequence of the Arabidopsis thaliana ecotype, Niederzenz (Nd-0 was obtained by applying Illumina's sequencing by synthesis (Solexa technology. Comparison of the Nd-0 genome sequence with the assembled Columbia-0 (Col-0 genome sequence identified putative single nucleotide polymorphisms (SNPs throughout the entire genome. Multiple 75 base pair Nd-0 sequence reads containing SNPs and originating from individual genomic DNA molecules were the basis for developing co-dominant SBP markers. SNPs containing Col-0 sequences, supported by transcript sequences or sequences from multiple BAC clones, were compared to the respective Nd-0 sequences to identify possible restriction endonuclease enzyme site variations. Small amplicons, PCR amplified from both ecotypes, were digested with suitable restriction enzymes and resolved on a gel to reveal the sequence based polymorphisms. By applying this technology, 21 SBP markers for the marker poor regions of the Arabidopsis map representing polymorphisms between Col-0 and Nd-0 ecotypes were generated. Conclusions The SBP marker technology described here allowed the development of molecular markers for targeted genomic regions of Arabidopsis. It should facilitate isolation of co-dominant molecular markers for targeted genomic regions of any animal or plant species, whose genomic sequences have been assembled. This technology will particularly facilitate the development of high density molecular marker maps, essential for

  5. A comparison of 454 sequencing and clonal sequencing for the characterization of hepatitis C virus NS3 variants

    NARCIS (Netherlands)

    Ho, Cynthia K. Y.; Welkers, Matthijs R. A.; Thomas, Xiomara V.; Sullivan, James C.; Kieffer, Tara L.; Reesink, Henk W.; Rebers, Sjoerd P. H.; de Jong, Menno D.; Schinkel, Janke; Molenkamp, Richard

    2015-01-01

    We compared 454 amplicon sequencing with clonal sequencing for the characterization of intra-host hepatitis C virus (HCV) NS3 variants. Clonal and 454 sequences were obtained from 12 patients enrolled in a clinical phase I study for telaprevir, an NS3-4a protease inhibitor. Thirty-nine datasets were

  6. An improved filtering algorithm for big read datasets and its application to single-cell assembly.

    Science.gov (United States)

    Wedemeyer, Axel; Kliemann, Lasse; Srivastav, Anand; Schielke, Christian; Reusch, Thorsten B; Rosenstiel, Philip

    2017-07-03

    For single-cell or metagenomic sequencing projects, it is necessary to sequence with a very high mean coverage in order to make sure that all parts of the sample DNA get covered by the reads produced. This leads to huge datasets with lots of redundant data. A filtering of this data prior to assembly is advisable. Brown et al. (2012) presented the algorithm Diginorm for this purpose, which filters reads based on the abundance of their k-mers. We present Bignorm, a faster and quality-conscious read filtering algorithm. An important new algorithmic feature is the use of phred quality scores together with a detailed analysis of the k-mer counts to decide which reads to keep. We qualify and recommend parameters for our new read filtering algorithm. Guided by these parameters, we remove in terms of median 97.15% of the reads while keeping the mean phred score of the filtered dataset high. Using the SDAdes assembler, we produce assemblies of high quality from these filtered datasets in a fraction of the time needed for an assembly from the datasets filtered with Diginorm. We conclude that read filtering is a practical and efficient method for reducing read data and for speeding up the assembly process. This applies not only for single cell assembly, as shown in this paper, but also to other projects with high mean coverage datasets like metagenomic sequencing projects. Our Bignorm algorithm allows assemblies of competitive quality in comparison to Diginorm, while being much faster. Bignorm is available for download at https://git.informatik.uni-kiel.de/axw/Bignorm .

  7. Strontium removal jar test dataset for all figures and tables.

    Data.gov (United States)

    U.S. Environmental Protection Agency — The datasets where used to generate data to demonstrate strontium removal under various water quality and treatment conditions. This dataset is associated with the...

  8. Discovery of Teleconnections Using Data Mining Technologies in Global Climate Datasets

    Directory of Open Access Journals (Sweden)

    Fan Lin

    2007-10-01

    Full Text Available In this paper, we apply data mining technologies to a 100-year global land precipitation dataset and a 100-year Sea Surface Temperature (SST dataset. Some interesting teleconnections are discovered, including well-known patterns and unknown patterns (to the best of our knowledge, such as teleconnections between the abnormally low temperature events of the North Atlantic and floods in Northern Bolivia, abnormally low temperatures of the Venezuelan Coast and floods in Northern Algeria and Tunisia, etc. In particular, we use a high dimensional clustering method and a method that mines episode association rules in event sequences. The former is used to cluster the original time series datasets into higher spatial granularity, and the later is used to discover teleconnection patterns among events sequences that are generated by the clustering method. In order to verify our method, we also do experiments on the SOI index and a 100-year global land precipitation dataset and find many well-known teleconnections, such as teleconnections between SOI lower events and drought events of Eastern Australia, South Africa, and North Brazil; SOI lower events and flood events of the middle-lower reaches of Yangtze River; etc. We also do explorative experiments to help domain scientists discover new knowledge.

  9. Predicting dataset popularity for the CMS experiment

    CERN Document Server

    INSPIRE-00005122; Li, Ting; Giommi, Luca; Bonacorsi, Daniele; Wildish, Tony

    2016-01-01

    The CMS experiment at the LHC accelerator at CERN relies on its computing infrastructure to stay at the frontier of High Energy Physics, searching for new phenomena and making discoveries. Even though computing plays a significant role in physics analysis we rarely use its data to predict the system behavior itself. A basic information about computing resources, user activities and site utilization can be really useful for improving the throughput of the system and its management. In this paper, we discuss a first CMS analysis of dataset popularity based on CMS meta-data which can be used as a model for dynamic data placement and provide the foundation of data-driven approach for the CMS computing infrastructure.

  10. Predicting dataset popularity for the CMS experiment

    International Nuclear Information System (INIS)

    Kuznetsov, V.; Li, T.; Giommi, L.; Bonacorsi, D.; Wildish, T.

    2016-01-01

    The CMS experiment at the LHC accelerator at CERN relies on its computing infrastructure to stay at the frontier of High Energy Physics, searching for new phenomena and making discoveries. Even though computing plays a significant role in physics analysis we rarely use its data to predict the system behavior itself. A basic information about computing resources, user activities and site utilization can be really useful for improving the throughput of the system and its management. In this paper, we discuss a first CMS analysis of dataset popularity based on CMS meta-data which can be used as a model for dynamic data placement and provide the foundation of data-driven approach for the CMS computing infrastructure. (paper)

  11. Internationally coordinated glacier monitoring: strategy and datasets

    Science.gov (United States)

    Hoelzle, Martin; Armstrong, Richard; Fetterer, Florence; Gärtner-Roer, Isabelle; Haeberli, Wilfried; Kääb, Andreas; Kargel, Jeff; Nussbaumer, Samuel; Paul, Frank; Raup, Bruce; Zemp, Michael

    2014-05-01

    (c) the Randolph Glacier Inventory (RGI), a new and globally complete digital dataset of outlines from about 180,000 glaciers with some meta-information, which has been used for many applications relating to the IPCC AR5 report. Concerning glacier changes, a database (Fluctuations of Glaciers) exists containing information about mass balance, front variations including past reconstructed time series, geodetic changes and special events. Annual mass balance reporting contains information for about 125 glaciers with a subset of 37 glaciers with continuous observational series since 1980 or earlier. Front variation observations of around 1800 glaciers are available from most of the mountain ranges world-wide. This database was recently updated with 26 glaciers having an unprecedented dataset of length changes from from reconstructions of well-dated historical evidence going back as far as the 16th century. Geodetic observations of about 430 glaciers are available. The database is completed by a dataset containing information on special events including glacier surges, glacier lake outbursts, ice avalanches, eruptions of ice-clad volcanoes, etc. related to about 200 glaciers. A special database of glacier photographs contains 13,000 pictures from around 500 glaciers, some of them dating back to the 19th century. A key challenge is to combine and extend the traditional observations with fast evolving datasets from new technologies.

  12. 2006 Fynmeet sea clutter measurement trial: Datasets

    CSIR Research Space (South Africa)

    Herselman, PLR

    2007-09-06

    Full Text Available -011............................................................................................................................................................................................. 25 iii Dataset CAD14-001 0 5 10 15 20 25 30 35 10 20 30 40 50 60 70 80 90 R an ge G at e # Time [s] A bs ol ut e R an ge [m ] RCS [dBm2] vs. time and range for f1 = 9.000 GHz - CAD14-001 2400 2600 2800... 40 10 20 30 40 50 60 70 80 90 R an ge G at e # Time [s] A bs ol ut e R an ge [m ] RCS [dBm2] vs. time and range for f1 = 9.000 GHz - CAD14-002 2400 2600 2800 3000 3200 3400 3600 -30 -25 -20 -15 -10 -5 0 5 10...

  13. A new bed elevation dataset for Greenland

    Directory of Open Access Journals (Sweden)

    J. L. Bamber

    2013-03-01

    Full Text Available We present a new bed elevation dataset for Greenland derived from a combination of multiple airborne ice thickness surveys undertaken between the 1970s and 2012. Around 420 000 line kilometres of airborne data were used, with roughly 70% of this having been collected since the year 2000, when the last comprehensive compilation was undertaken. The airborne data were combined with satellite-derived elevations for non-glaciated terrain to produce a consistent bed digital elevation model (DEM over the entire island including across the glaciated–ice free boundary. The DEM was extended to the continental margin with the aid of bathymetric data, primarily from a compilation for the Arctic. Ice thickness was determined where an ice shelf exists from a combination of surface elevation and radar soundings. The across-track spacing between flight lines warranted interpolation at 1 km postings for significant sectors of the ice sheet. Grids of ice surface elevation, error estimates for the DEM, ice thickness and data sampling density were also produced alongside a mask of land/ocean/grounded ice/floating ice. Errors in bed elevation range from a minimum of ±10 m to about ±300 m, as a function of distance from an observation and local topographic variability. A comparison with the compilation published in 2001 highlights the improvement in resolution afforded by the new datasets, particularly along the ice sheet margin, where ice velocity is highest and changes in ice dynamics most marked. We estimate that the volume of ice included in our land-ice mask would raise mean sea level by 7.36 m, excluding any solid earth effects that would take place during ice sheet decay.

  14. Transcriptome sequencing and differential gene expression analysis in Viola yedoensis Makino (Fam. Violaceae) responsive to cadmium (Cd) pollution

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Jian [Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, Maize Research Institute of Sichuan Agricultural University, Wenjiang, Sichuan (China); Luo, Mao [Drug Discovery Research Center of Luzhou Medical College, Luzhou, Sichuan (China); Zhu, Ye; He, Ying; Wang, Qin [Department of Pharmacy of Luzhou Medical College, Luzhou, Sichuan (China); Zhang, Chun, E-mail: zc83good@126.com [Department of Pharmacy of Luzhou Medical College, Luzhou, Sichuan (China)

    2015-03-27

    Viola yedoensis Makino is an important Chinese traditional medicine plant adapted to cadmium (Cd) pollution regions. Illumina sequencing technology was used to sequence the transcriptome of V. yedoensis Makino. We sequenced Cd-treated (VIYCd) and untreated (VIYCK) samples of V. yedoensis, and obtained 100,410,834 and 83,587,676 high quality reads, respectively. After de novo assembly and quantitative assessment, 109,800 unigenes were finally generated with an average length of 661 bp. We then obtained functional annotations by aligning unigenes with public protein databases including NR, NT, SwissProt, KEGG and COG. In addition, 892 differentially expressed genes (DEGs) were investigated between the two libraries of untreated (VIYCK) and Cd-treated (VIYCd) plants. Moreover, 15 randomly selected DEGs were further validated with qRT-PCR and the results were highly accordant with the Solexa analysis. This study firstly generated a successful global analysis of the V. yedoensis transcriptome and it will provide for further studies on gene expression, genomics, and functional genomics in Violaceae. - Highlights: • A de novo assembly generated 109,800 unigenes and 5,4479 of them were annotated. • 31,285 could be classified into 26 COG categories. • 263 biosynthesis pathways were predicted and classified into five categories. • 892 DEGs were detected and 15 of them were validated by qRT-PCR.

  15. Transcriptome sequencing and differential gene expression analysis in Viola yedoensis Makino (Fam. Violaceae) responsive to cadmium (Cd) pollution

    International Nuclear Information System (INIS)

    Gao, Jian; Luo, Mao; Zhu, Ye; He, Ying; Wang, Qin; Zhang, Chun

    2015-01-01

    Viola yedoensis Makino is an important Chinese traditional medicine plant adapted to cadmium (Cd) pollution regions. Illumina sequencing technology was used to sequence the transcriptome of V. yedoensis Makino. We sequenced Cd-treated (VIYCd) and untreated (VIYCK) samples of V. yedoensis, and obtained 100,410,834 and 83,587,676 high quality reads, respectively. After de novo assembly and quantitative assessment, 109,800 unigenes were finally generated with an average length of 661 bp. We then obtained functional annotations by aligning unigenes with public protein databases including NR, NT, SwissProt, KEGG and COG. In addition, 892 differentially expressed genes (DEGs) were investigated between the two libraries of untreated (VIYCK) and Cd-treated (VIYCd) plants. Moreover, 15 randomly selected DEGs were further validated with qRT-PCR and the results were highly accordant with the Solexa analysis. This study firstly generated a successful global analysis of the V. yedoensis transcriptome and it will provide for further studies on gene expression, genomics, and functional genomics in Violaceae. - Highlights: • A de novo assembly generated 109,800 unigenes and 5,4479 of them were annotated. • 31,285 could be classified into 26 COG categories. • 263 biosynthesis pathways were predicted and classified into five categories. • 892 DEGs were detected and 15 of them were validated by qRT-PCR

  16. Draft genome sequence of Streptomyces coelicoflavus ZG0656 reveals the putative biosynthetic gene cluster of acarviostatin family α-amylase inhibitors.

    Science.gov (United States)

    Guo, X; Geng, P; Bai, F; Bai, G; Sun, T; Li, X; Shi, L; Zhong, Q

    2012-08-01

    The aims of this study are to obtain the draft genome sequence of Streptomyces coelicoflavus ZG0656, which produces novel acarviostatin family α-amylase inhibitors, and then to reveal the putative acarviostatin-related gene cluster and the biosynthetic pathway. The draft genome sequence of S. coelicoflavus ZG0656 was generated using a shotgun approach employing a combination of 454 and Solexa sequencing technologies. Genome analysis revealed a putative gene cluster for acarviostatin biosynthesis, termed sct-cluster. The cluster contains 13 acarviostatin synthetic genes, six transporter genes, four starch degrading or transglycosylation enzyme genes and two regulator genes. On the basis of bioinformatic analysis, we proposed a putative biosynthetic pathway of acarviostatins. The intracellular steps produce a structural core, acarviostatin I00-7-P, and the extracellular assemblies lead to diverse acarviostatin end products. The draft genome sequence of S. coelicoflavus ZG0656 revealed the putative biosynthetic gene cluster of acarviostatins and a putative pathway of acarviostatin production. To our knowledge, S. coelicoflavus ZG0656 is the first strain in this species for which a genome sequence has been reported. The analysis of sct-cluster provided important insights into the biosynthesis of acarviostatins. This work will be a platform for producing novel variants and yield improvement. © 2012 The Authors. Letters in Applied Microbiology © 2012 The Society for Applied Microbiology.

  17. Wind Integration National Dataset Toolkit | Grid Modernization | NREL

    Science.gov (United States)

    Integration National Dataset Toolkit Wind Integration National Dataset Toolkit The Wind Integration National Dataset (WIND) Toolkit is an update and expansion of the Eastern Wind Integration Data Set and Western Wind Integration Data Set. It supports the next generation of wind integration studies. WIND

  18. Solar Integration National Dataset Toolkit | Grid Modernization | NREL

    Science.gov (United States)

    Solar Integration National Dataset Toolkit Solar Integration National Dataset Toolkit NREL is working on a Solar Integration National Dataset (SIND) Toolkit to enable researchers to perform U.S . regional solar generation integration studies. It will provide modeled, coherent subhourly solar power data

  19. Technical note: An inorganic water chemistry dataset (1972–2011 ...

    African Journals Online (AJOL)

    A national dataset of inorganic chemical data of surface waters (rivers, lakes, and dams) in South Africa is presented and made freely available. The dataset comprises more than 500 000 complete water analyses from 1972 up to 2011, collected from more than 2 000 sample monitoring stations in South Africa. The dataset ...

  20. QSAR ligand dataset for modelling mutagenicity, genotoxicity, and rodent carcinogenicity

    Directory of Open Access Journals (Sweden)

    Davy Guan

    2018-04-01

    Full Text Available Five datasets were constructed from ligand and bioassay result data from the literature. These datasets include bioassay results from the Ames mutagenicity assay, Greenscreen GADD-45a-GFP assay, Syrian Hamster Embryo (SHE assay, and 2 year rat carcinogenicity assay results. These datasets provide information about chemical mutagenicity, genotoxicity and carcinogenicity.

  1. Bellerophon: a program to detect chimeric sequences in multiple sequence alignments.

    Science.gov (United States)

    Huber, Thomas; Faulkner, Geoffrey; Hugenholtz, Philip

    2004-09-22

    Bellerophon is a program for detecting chimeric sequences in multiple sequence datasets by an adaption of partial treeing analysis. Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments. Bellerophon is available as an interactive web server at http://foo.maths.uq.edu.au/~huber/bellerophon.pl

  2. Chameleon sequences in neurodegenerative diseases

    International Nuclear Information System (INIS)

    Bahramali, Golnaz; Goliaei, Bahram; Minuchehr, Zarrin; Salari, Ali

    2016-01-01

    Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to “helix to strand (HE)”, “helix to coil (HC)” and “strand to coil (CE)” alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases.

  3. Chameleon sequences in neurodegenerative diseases.

    Science.gov (United States)

    Bahramali, Golnaz; Goliaei, Bahram; Minuchehr, Zarrin; Salari, Ali

    2016-03-25

    Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to "helix to strand (HE)", "helix to coil (HC)" and "strand to coil (CE)" alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Chameleon sequences in neurodegenerative diseases

    Energy Technology Data Exchange (ETDEWEB)

    Bahramali, Golnaz [Institute of Biochemistry and Biophysics, University of Tehran, Tehran (Iran, Islamic Republic of); Goliaei, Bahram, E-mail: goliaei@ut.ac.ir [Institute of Biochemistry and Biophysics, University of Tehran, Tehran (Iran, Islamic Republic of); Minuchehr, Zarrin, E-mail: minuchehr@nigeb.ac.ir [Department of Systems Biotechnology, National Institute of Genetic Engineering and Biotechnology, (NIGEB), Tehran (Iran, Islamic Republic of); Salari, Ali [Department of Systems Biotechnology, National Institute of Genetic Engineering and Biotechnology, (NIGEB), Tehran (Iran, Islamic Republic of)

    2016-03-25

    Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to “helix to strand (HE)”, “helix to coil (HC)” and “strand to coil (CE)” alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases.

  5. annot8r: GO, EC and KEGG annotation of EST datasets

    Directory of Open Access Journals (Sweden)

    Schmid Ralf

    2008-04-01

    Full Text Available Abstract Background The expressed sequence tag (EST methodology is an attractive option for the generation of sequence data for species for which no completely sequenced genome is available. The annotation and comparative analysis of such datasets poses a formidable challenge for research groups that do not have the bioinformatics infrastructure of major genome sequencing centres. Therefore, there is a need for user-friendly tools to facilitate the annotation of non-model species EST datasets with well-defined ontologies that enable meaningful cross-species comparisons. To address this, we have developed annot8r, a platform for the rapid annotation of EST datasets with GO-terms, EC-numbers and KEGG-pathways. Results annot8r automatically downloads all files relevant for the annotation process and generates a reference database that stores UniProt entries, their associated Gene Ontology (GO, Enzyme Commission (EC and Kyoto Encyclopaedia of Genes and Genomes (KEGG annotation and additional relevant data. For each of GO, EC and KEGG, annot8r extracts a specific sequence subset from the UniProt dataset based on the information stored in the reference database. These three subsets are then formatted for BLAST searches. The user provides the protein or nucleotide sequences to be annotated and annot8r runs BLAST searches against these three subsets. The BLAST results are parsed and the corresponding annotations retrieved from the reference database. The annotations are saved both as flat files and also in a relational postgreSQL results database to facilitate more advanced searches within the results. annot8r is integrated with the PartiGene suite of EST analysis tools. Conclusion annot8r is a tool that assigns GO, EC and KEGG annotations for data sets resulting from EST sequencing projects both rapidly and efficiently. The benefits of an underlying relational database, flexibility and the ease of use of the program make it ideally suited for non

  6. “Controlled, cross-species dataset for exploring biases in genome annotation and modification profiles”

    Directory of Open Access Journals (Sweden)

    Alison McAfee

    2015-12-01

    Full Text Available Since the sequencing of the honey bee genome, proteomics by mass spectrometry has become increasingly popular for biological analyses of this insect; but we have observed that the number of honey bee protein identifications is consistently low compared to other organisms [1]. In this dataset, we use nanoelectrospray ionization-coupled liquid chromatography–tandem mass spectrometry (nLC–MS/MS to systematically investigate the root cause of low honey bee proteome coverage. To this end, we present here data from three key experiments: a controlled, cross-species analyses of samples from Apis mellifera, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Mus musculus and Homo sapiens; a proteomic analysis of an individual honey bee whose genome was also sequenced; and a cross-tissue honey bee proteome comparison. The cross-species dataset was interrogated to determine relative proteome coverages between species, and the other two datasets were used to search for polymorphic sequences and to compare protein cleavage profiles, respectively.

  7. HLA diversity in the 1000 genomes dataset.

    Directory of Open Access Journals (Sweden)

    Pierre-Antoine Gourraud

    Full Text Available The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation by sequencing at a level that should allow the genome-wide detection of most variants with frequencies as low as 1%. However, in the major histocompatibility complex (MHC, only the top 10 most frequent haplotypes are in the 1% frequency range whereas thousands of haplotypes are present at lower frequencies. Given the limitation of both the coverage and the read length of the sequences generated by the 1000 Genomes Project, the highly variable positions that define HLA alleles may be difficult to identify. We used classical Sanger sequencing techniques to type the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 genes in the available 1000 Genomes samples and combined the results with the 103,310 variants in the MHC region genotyped by the 1000 Genomes Project. Using pairwise identity-by-descent distances between individuals and principal component analysis, we established the relationship between ancestry and genetic diversity in the MHC region. As expected, both the MHC variants and the HLA phenotype can identify the major ancestry lineage, informed mainly by the most frequent HLA haplotypes. To some extent, regions of the genome with similar genetic or similar recombination rate have similar properties. An MHC-centric analysis underlines departures between the ancestral background of the MHC and the genome-wide picture. Our analysis of linkage disequilibrium (LD decay in these samples suggests that overestimation of pairwise LD occurs due to a limited sampling of the MHC diversity. This collection of HLA-specific MHC variants, available on the dbMHC portal, is a valuable resource for future analyses of the role of MHC in population and disease studies.

  8. Statistical segmentation of multidimensional brain datasets

    Science.gov (United States)

    Desco, Manuel; Gispert, Juan D.; Reig, Santiago; Santos, Andres; Pascau, Javier; Malpica, Norberto; Garcia-Barreno, Pedro

    2001-07-01

    This paper presents an automatic segmentation procedure for MRI neuroimages that overcomes part of the problems involved in multidimensional clustering techniques like partial volume effects (PVE), processing speed and difficulty of incorporating a priori knowledge. The method is a three-stage procedure: 1) Exclusion of background and skull voxels using threshold-based region growing techniques with fully automated seed selection. 2) Expectation Maximization algorithms are used to estimate the probability density function (PDF) of the remaining pixels, which are assumed to be mixtures of gaussians. These pixels can then be classified into cerebrospinal fluid (CSF), white matter and grey matter. Using this procedure, our method takes advantage of using the full covariance matrix (instead of the diagonal) for the joint PDF estimation. On the other hand, logistic discrimination techniques are more robust against violation of multi-gaussian assumptions. 3) A priori knowledge is added using Markov Random Field techniques. The algorithm has been tested with a dataset of 30 brain MRI studies (co-registered T1 and T2 MRI). Our method was compared with clustering techniques and with template-based statistical segmentation, using manual segmentation as a gold-standard. Our results were more robust and closer to the gold-standard.

  9. ASSESSING SMALL SAMPLE WAR-GAMING DATASETS

    Directory of Open Access Journals (Sweden)

    W. J. HURLEY

    2013-10-01

    Full Text Available One of the fundamental problems faced by military planners is the assessment of changes to force structure. An example is whether to replace an existing capability with an enhanced system. This can be done directly with a comparison of measures such as accuracy, lethality, survivability, etc. However this approach does not allow an assessment of the force multiplier effects of the proposed change. To gauge these effects, planners often turn to war-gaming. For many war-gaming experiments, it is expensive, both in terms of time and dollars, to generate a large number of sample observations. This puts a premium on the statistical methodology used to examine these small datasets. In this paper we compare the power of three tests to assess population differences: the Wald-Wolfowitz test, the Mann-Whitney U test, and re-sampling. We employ a series of Monte Carlo simulation experiments. Not unexpectedly, we find that the Mann-Whitney test performs better than the Wald-Wolfowitz test. Resampling is judged to perform slightly better than the Mann-Whitney test.

  10. High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

    Directory of Open Access Journals (Sweden)

    Gilbert Greub

    Full Text Available BACKGROUND: With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. METHODS/PRINCIPAL FINDINGS: We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. CONCLUSIONS/SIGNIFICANCE: This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.

  11. Whole-Genome Sequencing of Sordaria macrospora Mutants Identifies Developmental Genes.

    Science.gov (United States)

    Nowrousian, Minou; Teichert, Ines; Masloff, Sandra; Kück, Ulrich

    2012-02-01

    The study of mutants to elucidate gene functions has a long and successful history; however, to discover causative mutations in mutants that were generated by random mutagenesis often takes years of laboratory work and requires previously generated genetic and/or physical markers, or resources like DNA libraries for complementation. Here, we present an alternative method to identify defective genes in developmental mutants of the filamentous fungus Sordaria macrospora through Illumina/Solexa whole-genome sequencing. We sequenced pooled DNA from progeny of crosses of three mutants and the wild type and were able to pinpoint the causative mutations in the mutant strains through bioinformatics analysis. One mutant is a spore color mutant, and the mutated gene encodes a melanin biosynthesis enzyme. The causative mutation is a G to A change in the first base of an intron, leading to a splice defect. The second mutant carries an allelic mutation in the pro41 gene encoding a protein essential for sexual development. In the mutant, we detected a complex pattern of deletion/rearrangements at the pro41 locus. In the third mutant, a point mutation in the stop codon of a transcription factor-encoding gene leads to the production of immature fruiting bodies. For all mutants, transformation with a wild type-copy of the affected gene restored the wild-type phenotype. Our data demonstrate that whole-genome sequencing of mutant strains is a rapid method to identify developmental genes in an organism that can be genetically crossed and where a reference genome sequence is available, even without prior mapping information.

  12. Identification of microRNAs from Eugenia uniflora by high-throughput sequencing and bioinformatics analysis.

    Science.gov (United States)

    Guzman, Frank; Almerão, Mauricio P; Körbes, Ana P; Loss-Morais, Guilherme; Margis, Rogerio

    2012-01-01

    microRNAs or miRNAs are small non-coding regulatory RNAs that play important functions in the regulation of gene expression at the post-transcriptional level by targeting mRNAs for degradation or inhibiting protein translation. Eugenia uniflora is a plant native to tropical America with pharmacological and ecological importance, and there have been no previous studies concerning its gene expression and regulation. To date, no miRNAs have been reported in Myrtaceae species. Small RNA and RNA-seq libraries were constructed to identify miRNAs and pre-miRNAs in Eugenia uniflora. Solexa technology was used to perform high throughput sequencing of the library, and the data obtained were analyzed using bioinformatics tools. From 14,489,131 small RNA clean reads, we obtained 1,852,722 mature miRNA sequences representing 45 conserved families that have been identified in other plant species. Further analysis using contigs assembled from RNA-seq allowed the prediction of secondary structures of 25 known and 17 novel pre-miRNAs. The expression of twenty-seven identified miRNAs was also validated using RT-PCR assays. Potential targets were predicted for the most abundant mature miRNAs in the identified pre-miRNAs based on sequence homology. This study is the first large scale identification of miRNAs and their potential targets from a species of the Myrtaceae family without genomic sequence resources. Our study provides more information about the evolutionary conservation of the regulatory network of miRNAs in plants and highlights species-specific miRNAs.

  13. Analysis of Litopenaeus vannamei transcriptome using the next-generation DNA sequencing technique.

    Directory of Open Access Journals (Sweden)

    Chaozheng Li

    Full Text Available BACKGROUND: Pacific white shrimp (Litopenaeus vannamei, the major species of farmed shrimps in the world, has been attracting extensive studies, which require more and more genome background knowledge. The now available transcriptome data of L. vannamei are insufficient for research requirements, and have not been adequately assembled and annotated. METHODOLOGY/PRINCIPAL FINDINGS: This is the first study that used a next-generation high-throughput DNA sequencing technique, the Solexa/Illumina GA II method, to analyze the transcriptome from whole bodies of L. vannamei larvae. More than 2.4 Gb of raw data were generated, and 109,169 unigenes with a mean length of 396 bp were assembled using the SOAP denovo software. 73,505 unigenes (>200 bp with good quality sequences were selected and subjected to annotation analysis, among which 37.80% can be matched in NCBI Nr database, 37.3% matched in Swissprot, and 44.1% matched in TrEMBL. Using BLAST and BLAST2Go softwares, 11,153 unigenes were classified into 25 Clusters of Orthologous Groups of proteins (COG categories, 8171 unigenes were assigned into 51 Gene ontology (GO functional groups, and 18,154 unigenes were divided into 220 Kyoto Encyclopedia of Genes and Genomes (KEGG pathways. To primarily verify part of the results of assembly and annotations, 12 assembled unigenes that are homologous to many embryo development-related genes were chosen and subjected to RT-PCR for electrophoresis and Sanger sequencing analyses, and to real-time PCR for expression profile analyses during embryo development. CONCLUSIONS/SIGNIFICANCE: The L. vannamei transcriptome analyzed using the next-generation sequencing technique enriches the information of L. vannamei genes, which will facilitate our understanding of the genome background of crustaceans, and promote the studies on L. vannamei.

  14. Bacterial whole genome-based phylogeny: construction of a new benchmarking dataset and assessment of some existing methods

    DEFF Research Database (Denmark)

    Ahrenfeldt, Johanne; Skaarup, Carina; Hasman, Henrik

    2017-01-01

    from sequencing reads. In the present study we describe a new dataset that we have created for the purpose of benchmarking such WGS-based methods for epidemiological data, and also present an analysis where we use the data to compare the performance of some current methods. Results Our aim...

  15. Dataset of cocoa aspartic protease cleavage sites

    Directory of Open Access Journals (Sweden)

    Katharina Janek

    2016-09-01

    Full Text Available The data provide information in support of the research article, “The cleavage specificity of the aspartic protease of cocoa beans involved in the generation of the cocoa-specific aroma precursors” (Janek et al., 2016 [1]. Three different protein substrates were partially digested with the aspartic protease isolated from cocoa beans and commercial pepsin, respectively. The obtained peptide fragments were analyzed by matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/TOF-MS/MS and identified using the MASCOT server. The N- and C-terminal ends of the peptide fragments were used to identify the corresponding in-vitro cleavage sites by comparison with the amino acid sequences of the substrate proteins. The same procedure was applied to identify the cleavage sites used by the cocoa aspartic protease during cocoa fermentation starting from the published amino acid sequences of oligopeptides isolated from fermented cocoa beans. Keywords: Aspartic protease, Cleavage sites, Cocoa, In-vitro proteolysis, Mass spectrometry, Peptides

  16. Model-based quality assessment and base-calling for second-generation sequencing data.

    Science.gov (United States)

    Bravo, Héctor Corrada; Irizarry, Rafael A

    2010-09-01

    Second-generation sequencing (sec-gen) technology can sequence millions of short fragments of DNA in parallel, making it capable of assembling complex genomes for a small fraction of the price and time of previous technologies. In fact, a recently formed international consortium, the 1000 Genomes Project, plans to fully sequence the genomes of approximately 1200 people. The prospect of comparative analysis at the sequence level of a large number of samples across multiple populations may be achieved within the next five years. These data present unprecedented challenges in statistical analysis. For instance, analysis operates on millions of short nucleotide sequences, or reads-strings of A,C,G, or T's, between 30 and 100 characters long-which are the result of complex processing of noisy continuous fluorescence intensity measurements known as base-calling. The complexity of the base-calling discretization process results in reads of widely varying quality within and across sequence samples. This variation in processing quality results in infrequent but systematic errors that we have found to mislead downstream analysis of the discretized sequence read data. For instance, a central goal of the 1000 Genomes Project is to quantify across-sample variation at the single nucleotide level. At this resolution, small error rates in sequencing prove significant, especially for rare variants. Sec-gen sequencing is a relatively new technology for which potential biases and sources of obscuring variation are not yet fully understood. Therefore, modeling and quantifying the uncertainty inherent in the generation of sequence reads is of utmost importance. In this article, we present a simple model to capture uncertainty arising in the base-calling procedure of the Illumina/Solexa GA platform. Model parameters have a straightforward interpretation in terms of the chemistry of base-calling allowing for informative and easily interpretable metrics that capture the variability in

  17. Mapsembler, targeted and micro assembly of large NGS datasets on a desktop computer

    Directory of Open Access Journals (Sweden)

    Peterlongo Pierre

    2012-03-01

    Full Text Available Abstract Background The analysis of next-generation sequencing data from large genomes is a timely research topic. Sequencers are producing billions of short sequence fragments from newly sequenced organisms. Computational methods for reconstructing whole genomes/transcriptomes (de novo assemblers are typically employed to process such data. However, these methods require large memory resources and computation time. Many basic biological questions could be answered targeting specific information in the reads, thus avoiding complete assembly. Results We present Mapsembler, an iterative micro and targeted assembler which processes large datasets of reads on commodity hardware. Mapsembler checks for the presence of given regions of interest that can be constructed from reads and builds a short assembly around it, either as a plain sequence or as a graph, showing contextual structure. We introduce new algorithms to retrieve approximate occurrences of a sequence from reads and construct an extension graph. Among other results presented in this paper, Mapsembler enabled to retrieve previously described human breast cancer candidate fusion genes, and to detect new ones not previously known. Conclusions Mapsembler is the first software that enables de novo discovery around a region of interest of repeats, SNPs, exon skipping, gene fusion, as well as other structural events, directly from raw sequencing reads. As indexing is localized, the memory footprint of Mapsembler is negligible. Mapsembler is released under the CeCILL license and can be freely downloaded from http://alcovna.genouest.org/mapsembler/.

  18. Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients.

    Science.gov (United States)

    Juan, Li; Tong, Hong-li; Zhang, Pengjun; Guo, Guanghong; Wang, Zi; Wen, Xinyu; Dong, Zhennan; Tian, Ya-ping

    2014-09-03

    Small non-coding microRNAs (miRNAs) are involved in cancer development and progression, and serum profiles of cervical cancer patients may be useful for identifying novel miRNAs. We performed deep sequencing on serum pools of cervical cancer patients and healthy controls with 3 replicates and constructed a small RNA library. We used MIREAP to predict novel miRNAs and identified 2 putative novel miRNAs between serum pools of cervical cancer patients and healthy controls after filtering out pseudo-pre-miRNAs using Triplet-SVM analysis. The 2 putative novel miRNAs were validated by real time PCR and were significantly decreased in cervical cancer patients compared with healthy controls. One novel miRNA had an area under curve (AUC) of 0.921 (95% CI: 0.883, 0.959) with a sensitivity of 85.7% and a specificity of 88.2% when discriminating between cervical cancer patients and healthy controls. Our results suggest that characterizing serum profiles of cervical cancers by Solexa sequencing may be a good method for identifying novel miRNAs and that the validated novel miRNAs described here may be cervical cancer-associated biomarkers.

  19. The Dataset of Countries at Risk of Electoral Violence

    OpenAIRE

    Birch, Sarah; Muchlinski, David

    2017-01-01

    Electoral violence is increasingly affecting elections around the world, yet researchers have been limited by a paucity of granular data on this phenomenon. This paper introduces and describes a new dataset of electoral violence – the Dataset of Countries at Risk of Electoral Violence (CREV) – that provides measures of 10 different types of electoral violence across 642 elections held around the globe between 1995 and 2013. The paper provides a detailed account of how and why the dataset was ...

  20. Norwegian Hydrological Reference Dataset for Climate Change Studies

    Energy Technology Data Exchange (ETDEWEB)

    Magnussen, Inger Helene; Killingland, Magnus; Spilde, Dag

    2012-07-01

    Based on the Norwegian hydrological measurement network, NVE has selected a Hydrological Reference Dataset for studies of hydrological change. The dataset meets international standards with high data quality. It is suitable for monitoring and studying the effects of climate change on the hydrosphere and cryosphere in Norway. The dataset includes streamflow, groundwater, snow, glacier mass balance and length change, lake ice and water temperature in rivers and lakes.(Author)

  1. ProDaMa: an open source Python library to generate protein structure datasets.

    Science.gov (United States)

    Armano, Giuliano; Manconi, Andrea

    2009-10-02

    The huge difference between the number of known sequences and known tertiary structures has justified the use of automated methods for protein analysis. Although a general methodology to solve these problems has not been yet devised, researchers are engaged in developing more accurate techniques and algorithms whose training plays a relevant role in determining their performance. From this perspective, particular importance is given to the training data used in experiments, and researchers are often engaged in the generation of specialized datasets that meet their requirements. To facilitate the task of generating specialized datasets we devised and implemented ProDaMa, an open source Python library than provides classes for retrieving, organizing, updating, analyzing, and filtering protein data. ProDaMa has been used to generate specialized datasets useful for secondary structure prediction and to develop a collaborative web application aimed at generating and sharing protein structure datasets. The library, the related database, and the documentation are freely available at the URL http://iasc.diee.unica.it/prodama.

  2. ProDaMa: an open source Python library to generate protein structure datasets

    Directory of Open Access Journals (Sweden)

    Manconi Andrea

    2009-10-01

    Full Text Available Abstract Background The huge difference between the number of known sequences and known tertiary structures has justified the use of automated methods for protein analysis. Although a general methodology to solve these problems has not been yet devised, researchers are engaged in developing more accurate techniques and algorithms whose training plays a relevant role in determining their performance. From this perspective, particular importance is given to the training data used in experiments, and researchers are often engaged in the generation of specialized datasets that meet their requirements. Findings To facilitate the task of generating specialized datasets we devised and implemented ProDaMa, an open source Python library than provides classes for retrieving, organizing, updating, analyzing, and filtering protein data. Conclusion ProDaMa has been used to generate specialized datasets useful for secondary structure prediction and to develop a collaborative web application aimed at generating and sharing protein structure datasets. The library, the related database, and the documentation are freely available at the URL http://iasc.diee.unica.it/prodama.

  3. Public Availability to ECS Collected Datasets

    Science.gov (United States)

    Henderson, J. F.; Warnken, R.; McLean, S. J.; Lim, E.; Varner, J. D.

    2013-12-01

    Coastal nations have spent considerable resources exploring the limits of their extended continental shelf (ECS) beyond 200 nm. Although these studies are funded to fulfill requirements of the UN Convention on the Law of the Sea, the investments are producing new data sets in frontier areas of Earth's oceans that will be used to understand, explore, and manage the seafloor and sub-seafloor for decades to come. Although many of these datasets are considered proprietary until a nation's potential ECS has become 'final and binding' an increasing amount of data are being released and utilized by the public. Data sets include multibeam, seismic reflection/refraction, bottom sampling, and geophysical data. The U.S. ECS Project, a multi-agency collaboration whose mission is to establish the full extent of the continental shelf of the United States consistent with international law, relies heavily on data and accurate, standard metadata. The United States has made it a priority to make available to the public all data collected with ECS-funding as quickly as possible. The National Oceanic and Atmospheric Administration's (NOAA) National Geophysical Data Center (NGDC) supports this objective by partnering with academia and other federal government mapping agencies to archive, inventory, and deliver marine mapping data in a coordinated, consistent manner. This includes ensuring quality, standard metadata and developing and maintaining data delivery capabilities built on modern digital data archives. Other countries, such as Ireland, have submitted their ECS data for public availability and many others have made pledges to participate in the future. The data services provided by NGDC support the U.S. ECS effort as well as many developing nation's ECS effort through the U.N. Environmental Program. Modern discovery, visualization, and delivery of scientific data and derived products that span national and international sources of data ensure the greatest re-use of data and

  4. BIA Indian Lands Dataset (Indian Lands of the United States)

    Data.gov (United States)

    Federal Geographic Data Committee — The American Indian Reservations / Federally Recognized Tribal Entities dataset depicts feature location, selected demographics and other associated data for the 561...

  5. Framework for Interactive Parallel Dataset Analysis on the Grid

    Energy Technology Data Exchange (ETDEWEB)

    Alexander, David A.; Ananthan, Balamurali; /Tech-X Corp.; Johnson, Tony; Serbo, Victor; /SLAC

    2007-01-10

    We present a framework for use at a typical Grid site to facilitate custom interactive parallel dataset analysis targeting terabyte-scale datasets of the type typically produced by large multi-institutional science experiments. We summarize the needs for interactive analysis and show a prototype solution that satisfies those needs. The solution consists of desktop client tool and a set of Web Services that allow scientists to sign onto a Grid site, compose analysis script code to carry out physics analysis on datasets, distribute the code and datasets to worker nodes, collect the results back to the client, and to construct professional-quality visualizations of the results.

  6. Socioeconomic Data and Applications Center (SEDAC) Treaty Status Dataset

    Data.gov (United States)

    National Aeronautics and Space Administration — The Socioeconomic Data and Application Center (SEDAC) Treaty Status Dataset contains comprehensive treaty information for multilateral environmental agreements,...

  7. H-Metric: Characterizing Image Datasets via Homogenization Based on KNN-Queries

    Directory of Open Access Journals (Sweden)

    Welington M da Silva

    2012-01-01

    Full Text Available Precision-Recall is one of the main metrics for evaluating content-based image retrieval techniques. However, it does not provide an ample perception of the properties of an image dataset immersed in a metric space. In this work, we describe an alternative metric named H-Metric, which is determined along a sequence of controlled modifications in the image dataset. The process is named homogenization and works by altering the homogeneity characteristics of the classes of the images. The result is a process that measures how hard it is to deal with a set of images in respect to content-based retrieval, offering support in the task of analyzing configurations of distance functions and of features extractors.

  8. Phylogenetic factorization of compositional data yields lineage-level associations in microbiome datasets

    Directory of Open Access Journals (Sweden)

    Alex D. Washburne

    2017-02-01

    Full Text Available Marker gene sequencing of microbial communities has generated big datasets of microbial relative abundances varying across environmental conditions, sample sites and treatments. These data often come with putative phylogenies, providing unique opportunities to investigate how shared evolutionary history affects microbial abundance patterns. Here, we present a method to identify the phylogenetic factors driving patterns in microbial community composition. We use the method, “phylofactorization,” to re-analyze datasets from the human body and soil microbial communities, demonstrating how phylofactorization is a dimensionality-reducing tool, an ordination-visualization tool, and an inferential tool for identifying edges in the phylogeny along which putative functional ecological traits may have arisen.

  9. RNA sequencing reveals differential expression of mitochondrial and oxidation reduction genes in the long-lived naked mole-rat when compared to mice.

    Science.gov (United States)

    Yu, Chuanfei; Li, Yang; Holmes, Andrew; Szafranski, Karol; Faulkes, Chris G; Coen, Clive W; Buffenstein, Rochelle; Platzer, Matthias; de Magalhães, João Pedro; Church, George M

    2011-01-01

    The naked mole-rat (Heterocephalus glaber) is a long-lived, cancer resistant rodent and there is a great interest in identifying the adaptations responsible for these and other of its unique traits. We employed RNA sequencing to compare liver gene expression profiles between naked mole-rats and wild-derived mice. Our results indicate that genes associated with oxidoreduction and mitochondria were expressed at higher relative levels in naked mole-rats. The largest effect is nearly 300-fold higher expression of epithelial cell adhesion molecule (Epcam), a tumour-associated protein. Also of interest are the protease inhibitor, alpha2-macroglobulin (A2m), and the mitochondrial complex II subunit Sdhc, both ageing-related genes found strongly over-expressed in the naked mole-rat. These results hint at possible candidates for specifying species differences in ageing and cancer, and in particular suggest complex alterations in mitochondrial and oxidation reduction pathways in the naked mole-rat. Our differential gene expression analysis obviated the need for a reference naked mole-rat genome by employing a combination of Illumina/Solexa and 454 platforms for transcriptome sequencing and assembling transcriptome contigs of the non-sequenced species. Overall, our work provides new research foci and methods for studying the naked mole-rat's fascinating characteristics.

  10. RNA sequencing reveals differential expression of mitochondrial and oxidation reduction genes in the long-lived naked mole-rat when compared to mice.

    Directory of Open Access Journals (Sweden)

    Chuanfei Yu

    Full Text Available The naked mole-rat (Heterocephalus glaber is a long-lived, cancer resistant rodent and there is a great interest in identifying the adaptations responsible for these and other of its unique traits. We employed RNA sequencing to compare liver gene expression profiles between naked mole-rats and wild-derived mice. Our results indicate that genes associated with oxidoreduction and mitochondria were expressed at higher relative levels in naked mole-rats. The largest effect is nearly 300-fold higher expression of epithelial cell adhesion molecule (Epcam, a tumour-associated protein. Also of interest are the protease inhibitor, alpha2-macroglobulin (A2m, and the mitochondrial complex II subunit Sdhc, both ageing-related genes found strongly over-expressed in the naked mole-rat. These results hint at possible candidates for specifying species differences in ageing and cancer, and in particular suggest complex alterations in mitochondrial and oxidation reduction pathways in the naked mole-rat. Our differential gene expression analysis obviated the need for a reference naked mole-rat genome by employing a combination of Illumina/Solexa and 454 platforms for transcriptome sequencing and assembling transcriptome contigs of the non-sequenced species. Overall, our work provides new research foci and methods for studying the naked mole-rat's fascinating characteristics.

  11. An Analysis of the GTZAN Music Genre Dataset

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2012-01-01

    Most research in automatic music genre recognition has used the dataset assembled by Tzanetakis et al. in 2001. The composition and integrity of this dataset, however, has never been formally analyzed. For the first time, we provide an analysis of its composition, and create a machine...

  12. Really big data: Processing and analysis of large datasets

    Science.gov (United States)

    Modern animal breeding datasets are large and getting larger, due in part to the recent availability of DNA data for many animals. Computational methods for efficiently storing and analyzing those data are under development. The amount of storage space required for such datasets is increasing rapidl...

  13. An Annotated Dataset of 14 Cardiac MR Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2002-01-01

    This note describes a dataset consisting of 14 annotated cardiac MR images. Points of correspondence are placed on each image at the left ventricle (LV). As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given....

  14. A New Outlier Detection Method for Multidimensional Datasets

    KAUST Repository

    Abdel Messih, Mario A.

    2012-07-01

    This study develops a novel hybrid method for outlier detection (HMOD) that combines the idea of distance based and density based methods. The proposed method has two main advantages over most of the other outlier detection methods. The first advantage is that it works well on both dense and sparse datasets. The second advantage is that, unlike most other outlier detection methods that require careful parameter setting and prior knowledge of the data, HMOD is not very sensitive to small changes in parameter values within certain parameter ranges. The only required parameter to set is the number of nearest neighbors. In addition, we made a fully parallelized implementation of HMOD that made it very efficient in applications. Moreover, we proposed a new way of using the outlier detection for redundancy reduction in datasets where the confidence level that evaluates how accurate the less redundant dataset can be used to represent the original dataset can be specified by users. HMOD is evaluated on synthetic datasets (dense and mixed “dense and sparse”) and a bioinformatics problem of redundancy reduction of dataset of position weight matrices (PWMs) of transcription factor binding sites. In addition, in the process of assessing the performance of our redundancy reduction method, we developed a simple tool that can be used to evaluate the confidence level of reduced dataset representing the original dataset. The evaluation of the results shows that our method can be used in a wide range of problems.

  15. ReRep: Computational detection of repetitive sequences in genome survey sequences (GSS

    Directory of Open Access Journals (Sweden)

    Alves-Ferreira Marcelo

    2008-09-01

    Full Text Available Abstract Background Genome survey sequences (GSS offer a preliminary global view of a genome since, unlike ESTs, they cover coding as well as non-coding DNA and include repetitive regions of the genome. A more precise estimation of the nature, quantity and variability of repetitive sequences very early in a genome sequencing project is of considerable importance, as such data strongly influence the estimation of genome coverage, library quality and progress in scaffold construction. Also, the elimination of repetitive sequences from the initial assembly process is important to avoid errors and unnecessary complexity. Repetitive sequences are also of interest in a variety of other studies, for instance as molecular markers. Results We designed and implemented a straightforward pipeline called ReRep, which combines bioinformatics tools for identifying repetitive structures in a GSS dataset. In a case study, we first applied the pipeline to a set of 970 GSSs, sequenced in our laboratory from the human pathogen Leishmania braziliensis, the causative agent of leishmaniosis, an important public health problem in Brazil. We also verified the applicability of ReRep to new sequencing technologies using a set of 454-reads of an Escheria coli. The behaviour of several parameters in the algorithm is evaluated and suggestions are made for tuning of the analysis. Conclusion The ReRep approach for identification of repetitive elements in GSS datasets proved to be straightforward and efficient. Several potential repetitive sequences were found in a L. braziliensis GSS dataset generated in our laboratory, and further validated by the analysis of a more complete genomic dataset from the EMBL and Sanger Centre databases. ReRep also identified most of the E. coli K12 repeats prior to assembly in an example dataset obtained by automated sequencing using 454 technology. The parameters controlling the algorithm behaved consistently and may be tuned to the properties

  16. Deep sequencing discovery of novel and conserved microRNAs in trifoliate orange (Citrus trifoliata

    Directory of Open Access Journals (Sweden)

    Yu Huaping

    2010-07-01

    Full Text Available Abstract Background MicroRNAs (miRNAs play a critical role in post-transcriptional gene regulation and have been shown to control many genes involved in various biological and metabolic processes. There have been extensive studies to discover miRNAs and analyze their functions in model plant species, such as Arabidopsis and rice. Deep sequencing technologies have facilitated identification of species-specific or lowly expressed as well as conserved or highly expressed miRNAs in plants. Results In this research, we used Solexa sequencing to discover new microRNAs in trifoliate orange (Citrus trifoliata which is an important rootstock of citrus. A total of 13,106,753 reads representing 4,876,395 distinct sequences were obtained from a short RNA library generated from small RNA extracted from C. trifoliata flower and fruit tissues. Based on sequence similarity and hairpin structure prediction, we found that 156,639 reads representing 63 sequences from 42 highly conserved miRNA families, have perfect matches to known miRNAs. We also identified 10 novel miRNA candidates whose precursors were all potentially generated from citrus ESTs. In addition, five miRNA* sequences were also sequenced. These sequences had not been earlier described in other plant species and accumulation of the 10 novel miRNAs were confirmed by qRT-PCR analysis. Potential target genes were predicted for most conserved and novel miRNAs. Moreover, four target genes including one encoding IRX12 copper ion binding/oxidoreductase and three genes encoding NB-LRR disease resistance protein have been experimentally verified by detection of the miRNA-mediated mRNA cleavage in C. trifoliata. Conclusion Deep sequencing of short RNAs from C. trifoliata flowers and fruits identified 10 new potential miRNAs and 42 highly conserved miRNA families, indicating that specific miRNAs exist in C. trifoliata. These results show that regulatory miRNAs exist in agronomically important trifoliate orange

  17. ATLAS File and Dataset Metadata Collection and Use

    CERN Document Server

    Albrand, S; The ATLAS collaboration; Lambert, F; Gallas, E J

    2012-01-01

    The ATLAS Metadata Interface (“AMI”) was designed as a generic cataloguing system, and as such it has found many uses in the experiment including software release management, tracking of reconstructed event sizes and control of dataset nomenclature. The primary use of AMI is to provide a catalogue of datasets (file collections) which is searchable using physics criteria. In this paper we discuss the various mechanisms used for filling the AMI dataset and file catalogues. By correlating information from different sources we can derive aggregate information which is important for physics analysis; for example the total number of events contained in dataset, and possible reasons for missing events such as a lost file. Finally we will describe some specialized interfaces which were developed for the Data Preparation and reprocessing coordinators. These interfaces manipulate information from both the dataset domain held in AMI, and the run-indexed information held in the ATLAS COMA application (Conditions and ...

  18. A dataset on tail risk of commodities markets.

    Science.gov (United States)

    Powell, Robert J; Vo, Duc H; Pham, Thach N; Singh, Abhay K

    2017-12-01

    This article contains the datasets related to the research article "The long and short of commodity tails and their relationship to Asian equity markets"(Powell et al., 2017) [1]. The datasets contain the daily prices (and price movements) of 24 different commodities decomposed from the S&P GSCI index and the daily prices (and price movements) of three share market indices including World, Asia, and South East Asia for the period 2004-2015. Then, the dataset is divided into annual periods, showing the worst 5% of price movements for each year. The datasets are convenient to examine the tail risk of different commodities as measured by Conditional Value at Risk (CVaR) as well as their changes over periods. The datasets can also be used to investigate the association between commodity markets and share markets.

  19. Next generation sequencing based transcriptome analysis of septic-injury responsive genes in the beetle Tribolium castaneum.

    Directory of Open Access Journals (Sweden)

    Boran Altincicek

    Full Text Available Beetles (Coleoptera are the most diverse animal group on earth and interact with numerous symbiotic or pathogenic microbes in their environments. The red flour beetle Tribolium castaneum is a genetically tractable model beetle species and its whole genome sequence has recently been determined. To advance our understanding of the molecular basis of beetle immunity here we analyzed the whole transcriptome of T. castaneum by high-throughput next generation sequencing technology. Here, we demonstrate that the Illumina/Solexa sequencing approach of cDNA samples from T. castaneum including over 9.7 million reads with 72 base pairs (bp length (approximately 700 million bp sequence information with about 30× transcriptome coverage confirms the expression of most predicted genes and enabled subsequent qualitative and quantitative transcriptome analysis. This approach recapitulates our recent quantitative real-time PCR studies of immune-challenged and naïve T. castaneum beetles, validating our approach. Furthermore, this sequencing analysis resulted in the identification of 73 differentially expressed genes upon immune-challenge with statistical significance by comparing expression data to calculated values derived by fitting to generalized linear models. We identified up regulation of diverse immune-related genes (e.g. Toll receptor, serine proteinases, DOPA decarboxylase and thaumatin and of numerous genes encoding proteins with yet unknown functions. Of note, septic-injury resulted also in the elevated expression of genes encoding heat-shock proteins or cytochrome P450s supporting the view that there is crosstalk between immune and stress responses in T. castaneum. The present study provides a first comprehensive overview of septic-injury responsive genes in T. castaneum beetles. Identified genes advance our understanding of T. castaneum specific gene expression alteration upon immune-challenge in particular and may help to understand beetle immunity

  20. SAR image dataset of military ground targets with multiple poses for ATR

    Science.gov (United States)

    Belloni, Carole; Balleri, Alessio; Aouf, Nabil; Merlet, Thomas; Le Caillec, Jean-Marc

    2017-10-01

    Automatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability. Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset.1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden,2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques are currently challenging due to the lack of publicly available data in the SAR domain. In this paper, we present a high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm.3 A total of 1480 images are produced using a 20° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithms.

  1. Argo_CUDA: Exhaustive GPU based approach for motif discovery in large DNA datasets.

    Science.gov (United States)

    Vishnevsky, Oleg V; Bocharnikov, Andrey V; Kolchanov, Nikolay A

    2018-02-01

    The development of chromatin immunoprecipitation sequencing (ChIP-seq) technology has revolutionized the genetic analysis of the basic mechanisms underlying transcription regulation and led to accumulation of information about a huge amount of DNA sequences. There are a lot of web services which are currently available for de novo motif discovery in datasets containing information about DNA/protein binding. An enormous motif diversity makes their finding challenging. In order to avoid the difficulties, researchers use different stochastic approaches. Unfortunately, the efficiency of the motif discovery programs dramatically declines with the query set size increase. This leads to the fact that only a fraction of top "peak" ChIP-Seq segments can be analyzed or the area of analysis should be narrowed. Thus, the motif discovery in massive datasets remains a challenging issue. Argo_Compute Unified Device Architecture (CUDA) web service is designed to process the massive DNA data. It is a program for the detection of degenerate oligonucleotide motifs of fixed length written in 15-letter IUPAC code. Argo_CUDA is a full-exhaustive approach based on the high-performance GPU technologies. Compared with the existing motif discovery web services, Argo_CUDA shows good prediction quality on simulated sets. The analysis of ChIP-Seq sequences revealed the motifs which correspond to known transcription factor binding sites.

  2. Comparative and Joint Analysis of Two Metagenomic Datasets from a Biogas Fermenter Obtained by 454-Pyrosequencing

    Science.gov (United States)

    Jaenicke, Sebastian; Ander, Christina; Bekel, Thomas; Bisdorf, Regina; Dröge, Marcus; Gartemann, Karl-Heinz; Jünemann, Sebastian; Kaiser, Olaf; Krause, Lutz; Tille, Felix; Zakrzewski, Martha; Pühler, Alfred

    2011-01-01

    Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on the GS FLX platform. Taxonomic profiling based on 16S rRNA-specific sequences and an Environmental Gene Tag (EGT) analysis employing CARMA demonstrated that both approaches benefit from the longer read lengths obtained on the Titanium platform. Results confirmed Clostridia as the most prevalent taxonomic class, whereas species of the order Methanomicrobiales are dominant among methanogenic Archaea. However, the analyses also identified additional taxa that were missed by the previous study, including members of the genera Streptococcus, Acetivibrio, Garciella, Tissierella, and Gelria, which might also play a role in the fermentation process leading to the formation of methane. Taking advantage of the CARMA feature to correlate taxonomic information of sequences with their assigned functions, it appeared that Firmicutes, followed by Bacteroidetes and Proteobacteria, dominate within the functional context of polysaccharide degradation whereas Methanomicrobiales represent the most abundant taxonomic group responsible for methane production. Clostridia is the most important class involved in the reductive CoA pathway (Wood-Ljungdahl pathway) that is characteristic for acetogenesis. Based on binning of 16S rRNA-specific sequences allocated to the dominant genus Methanoculleus, it could be shown that this genus is represented by several different species. Phylogenetic analysis of these sequences placed them in close proximity to the hydrogenotrophic methanogen Methanoculleus

  3. Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space.

    Science.gov (United States)

    Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

    2008-07-01

    UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request.

  4. Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing.

    Directory of Open Access Journals (Sweden)

    Sebastian Jaenicke

    Full Text Available Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on the GS FLX platform. Taxonomic profiling based on 16S rRNA-specific sequences and an Environmental Gene Tag (EGT analysis employing CARMA demonstrated that both approaches benefit from the longer read lengths obtained on the Titanium platform. Results confirmed Clostridia as the most prevalent taxonomic class, whereas species of the order Methanomicrobiales are dominant among methanogenic Archaea. However, the analyses also identified additional taxa that were missed by the previous study, including members of the genera Streptococcus, Acetivibrio, Garciella, Tissierella, and Gelria, which might also play a role in the fermentation process leading to the formation of methane. Taking advantage of the CARMA feature to correlate taxonomic information of sequences with their assigned functions, it appeared that Firmicutes, followed by Bacteroidetes and Proteobacteria, dominate within the functional context of polysaccharide degradation whereas Methanomicrobiales represent the most abundant taxonomic group responsible for methane production. Clostridia is the most important class involved in the reductive CoA pathway (Wood-Ljungdahl pathway that is characteristic for acetogenesis. Based on binning of 16S rRNA-specific sequences allocated to the dominant genus Methanoculleus, it could be shown that this genus is represented by several different species. Phylogenetic analysis of these sequences placed them in close proximity to the hydrogenotrophic methanogen

  5. VarB Plus: An Integrated Tool for Visualization of Genome Variation Datasets

    KAUST Repository

    Hidayah, Lailatul

    2012-07-01

    Research on genomic sequences has been improving significantly as more advanced technology for sequencing has been developed. This opens enormous opportunities for sequence analysis. Various analytical tools have been built for purposes such as sequence assembly, read alignments, genome browsing, comparative genomics, and visualization. From the visualization perspective, there is an increasing trend towards use of large-scale computation. However, more than power is required to produce an informative image. This is a challenge that we address by providing several ways of representing biological data in order to advance the inference endeavors of biologists. This thesis focuses on visualization of variations found in genomic sequences. We develop several visualization functions and embed them in an existing variation visualization tool as extensions. The tool we improved is named VarB, hence the nomenclature for our enhancement is VarB Plus. To the best of our knowledge, besides VarB, there is no tool that provides the capability of dynamic visualization of genome variation datasets as well as statistical analysis. Dynamic visualization allows users to toggle different parameters on and off and see the results on the fly. The statistical analysis includes Fixation Index, Relative Variant Density, and Tajima’s D. Hence we focused our efforts on this tool. The scope of our work includes plots of per-base genome coverage, Principal Coordinate Analysis (PCoA), integration with a read alignment viewer named LookSeq, and visualization of geo-biological data. In addition to description of embedded functionalities, significance, and limitations, future improvements are discussed. The result is four extensions embedded successfully in the original tool, which is built on the Qt framework in C++. Hence it is portable to numerous platforms. Our extensions have shown acceptable execution time in a beta testing with various high-volume published datasets, as well as positive

  6. RAMBO-K: Rapid and Sensitive Removal of Background Sequences from Next Generation Sequencing Data.

    Directory of Open Access Journals (Sweden)

    Simon H Tausch

    Full Text Available The assembly of viral or endosymbiont genomes from Next Generation Sequencing (NGS data is often hampered by the predominant abundance of reads originating from the host organism. These reads increase the memory and CPU time usage of the assembler and can lead to misassemblies.We developed RAMBO-K (Read Assignment Method Based On K-mers, a tool which allows rapid and sensitive removal of unwanted host sequences from NGS datasets. Reaching a speed of 10 Megabases/s on 4 CPU cores and a standard hard drive, RAMBO-K is faster than any tool we tested, while showing a consistently high sensitivity and specificity across different datasets.RAMBO-K rapidly and reliably separates reads from different species without data preprocessing. It is suitable as a straightforward standard solution for workflows dealing with mixed datasets. Binaries and source code (java and python are available from http://sourceforge.net/projects/rambok/.

  7. Discovery and Reuse of Open Datasets: An Exploratory Study

    Directory of Open Access Journals (Sweden)

    Sara

    2016-07-01

    Full Text Available Objective: This article analyzes twenty cited or downloaded datasets and the repositories that house them, in order to produce insights that can be used by academic libraries to encourage discovery and reuse of research data in institutional repositories. Methods: Using Thomson Reuters’ Data Citation Index and repository download statistics, we identified twenty cited/downloaded datasets. We documented the characteristics of the cited/downloaded datasets and their corresponding repositories in a self-designed rubric. The rubric includes six major categories: basic information; funding agency and journal information; linking and sharing; factors to encourage reuse; repository characteristics; and data description. Results: Our small-scale study suggests that cited/downloaded datasets generally comply with basic recommendations for facilitating reuse: data are documented well; formatted for use with a variety of software; and shared in established, open access repositories. Three significant factors also appear to contribute to dataset discovery: publishing in discipline-specific repositories; indexing in more than one location on the web; and using persistent identifiers. The cited/downloaded datasets in our analysis came from a few specific disciplines, and tended to be funded by agencies with data publication mandates. Conclusions: The results of this exploratory research provide insights that can inform academic librarians as they work to encourage discovery and reuse of institutional datasets. Our analysis also suggests areas in which academic librarians can target open data advocacy in their communities in order to begin to build open data success stories that will fuel future advocacy efforts.

  8. Viability of Controlling Prosthetic Hand Utilizing Electroencephalograph (EEG) Dataset Signal

    Science.gov (United States)

    Miskon, Azizi; A/L Thanakodi, Suresh; Raihan Mazlan, Mohd; Mohd Haziq Azhar, Satria; Nooraya Mohd Tawil, Siti

    2016-11-01

    This project presents the development of an artificial hand controlled by Electroencephalograph (EEG) signal datasets for the prosthetic application. The EEG signal datasets were used as to improvise the way to control the prosthetic hand compared to the Electromyograph (EMG). The EMG has disadvantages to a person, who has not used the muscle for a long time and also to person with degenerative issues due to age factor. Thus, the EEG datasets found to be an alternative for EMG. The datasets used in this work were taken from Brain Computer Interface (BCI) Project. The datasets were already classified for open, close and combined movement operations. It served the purpose as an input to control the prosthetic hand by using an Interface system between Microsoft Visual Studio and Arduino. The obtained results reveal the prosthetic hand to be more efficient and faster in response to the EEG datasets with an additional LiPo (Lithium Polymer) battery attached to the prosthetic. Some limitations were also identified in terms of the hand movements, weight of the prosthetic, and the suggestions to improve were concluded in this paper. Overall, the objective of this paper were achieved when the prosthetic hand found to be feasible in operation utilizing the EEG datasets.

  9. Sparse Group Penalized Integrative Analysis of Multiple Cancer Prognosis Datasets

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Xie, Yang; Ma, Shuangge

    2014-01-01

    SUMMARY In cancer research, high-throughput profiling studies have been extensively conducted, searching for markers associated with prognosis. Because of the “large d, small n” characteristic, results generated from the analysis of a single dataset can be unsatisfactory. Recent studies have shown that integrative analysis, which simultaneously analyzes multiple datasets, can be more effective than single-dataset analysis and classic meta-analysis. In most of existing integrative analysis, the homogeneity model has been assumed, which postulates that different datasets share the same set of markers. Several approaches have been designed to reinforce this assumption. In practice, different datasets may differ in terms of patient selection criteria, profiling techniques, and many other aspects. Such differences may make the homogeneity model too restricted. In this study, we assume the heterogeneity model, under which different datasets are allowed to have different sets of markers. With multiple cancer prognosis datasets, we adopt the AFT (accelerated failure time) model to describe survival. This model may have the lowest computational cost among popular semiparametric survival models. For marker selection, we adopt a sparse group MCP (minimax concave penalty) approach. This approach has an intuitive formulation and can be computed using an effective group coordinate descent algorithm. Simulation study shows that it outperforms the existing approaches under both the homogeneity and heterogeneity models. Data analysis further demonstrates the merit of heterogeneity model and proposed approach. PMID:23938111

  10. PROVIDING GEOGRAPHIC DATASETS AS LINKED DATA IN SDI

    Directory of Open Access Journals (Sweden)

    E. Hietanen

    2016-06-01

    Full Text Available In this study, a prototype service to provide data from Web Feature Service (WFS as linked data is implemented. At first, persistent and unique Uniform Resource Identifiers (URI are created to all spatial objects in the dataset. The objects are available from those URIs in Resource Description Framework (RDF data format. Next, a Web Ontology Language (OWL ontology is created to describe the dataset information content using the Open Geospatial Consortium’s (OGC GeoSPARQL vocabulary. The existing data model is modified in order to take into account the linked data principles. The implemented service produces an HTTP response dynamically. The data for the response is first fetched from existing WFS. Then the Geographic Markup Language (GML format output of the WFS is transformed on-the-fly to the RDF format. Content Negotiation is used to serve the data in different RDF serialization formats. This solution facilitates the use of a dataset in different applications without replicating the whole dataset. In addition, individual spatial objects in the dataset can be referred with URIs. Furthermore, the needed information content of the objects can be easily extracted from the RDF serializations available from those URIs. A solution for linking data objects to the dataset URI is also introduced by using the Vocabulary of Interlinked Datasets (VoID. The dataset is divided to the subsets and each subset is given its persistent and unique URI. This enables the whole dataset to be explored with a web browser and all individual objects to be indexed by search engines.

  11. Homogenised Australian climate datasets used for climate change monitoring

    International Nuclear Information System (INIS)

    Trewin, Blair; Jones, David; Collins; Dean; Jovanovic, Branislava; Braganza, Karl

    2007-01-01

    Full text: The Australian Bureau of Meteorology has developed a number of datasets for use in climate change monitoring. These datasets typically cover 50-200 stations distributed as evenly as possible over the Australian continent, and have been subject to detailed quality control and homogenisation.The time period over which data are available for each element is largely determined by the availability of data in digital form. Whilst nearly all Australian monthly and daily precipitation data have been digitised, a significant quantity of pre-1957 data (for temperature and evaporation) or pre-1987 data (for some other elements) remains to be digitised, and is not currently available for use in the climate change monitoring datasets. In the case of temperature and evaporation, the start date of the datasets is also determined by major changes in instruments or observing practices for which no adjustment is feasible at the present time. The datasets currently available cover: Monthly and daily precipitation (most stations commence 1915 or earlier, with many extending back to the late 19th century, and a few to the mid-19th century); Annual temperature (commences 1910); Daily temperature (commences 1910, with limited station coverage pre-1957); Twice-daily dewpoint/relative humidity (commences 1957); Monthly pan evaporation (commences 1970); Cloud amount (commences 1957) (Jovanovic etal. 2007). As well as the station-based datasets listed above, an additional dataset being developed for use in climate change monitoring (and other applications) covers tropical cyclones in the Australian region. This is described in more detail in Trewin (2007). The datasets already developed are used in analyses of observed climate change, which are available through the Australian Bureau of Meteorology website (http://www.bom.gov.au/silo/products/cli_chg/). They are also used as a basis for routine climate monitoring, and in the datasets used for the development of seasonal

  12. Tension in the recent Type Ia supernovae datasets

    International Nuclear Information System (INIS)

    Wei, Hao

    2010-01-01

    In the present work, we investigate the tension in the recent Type Ia supernovae (SNIa) datasets Constitution and Union. We show that they are in tension not only with the observations of the cosmic microwave background (CMB) anisotropy and the baryon acoustic oscillations (BAO), but also with other SNIa datasets such as Davis and SNLS. Then, we find the main sources responsible for the tension. Further, we make this more robust by employing the method of random truncation. Based on the results of this work, we suggest two truncated versions of the Union and Constitution datasets, namely the UnionT and ConstitutionT SNIa samples, whose behaviors are more regular.

  13. Sequence Factorization with Multiple References.

    Directory of Open Access Journals (Sweden)

    Sebastian Wandelt

    Full Text Available The success of high-throughput sequencing has lead to an increasing number of projects which sequence large populations of a species. Storage and analysis of sequence data is a key challenge in these projects, because of the sheer size of the datasets. Compression is one simple technology to deal with this challenge. Referential factorization and compression schemes, which store only the differences between input sequence and a reference sequence, gained lots of interest in this field. Highly-similar sequences, e.g., Human genomes, can be compressed with a compression ratio of 1,000:1 and more, up to two orders of magnitude better than with standard compression techniques. Recently, it was shown that the compression against multiple references from the same species can boost the compression ratio up to 4,000:1. However, a detailed analysis of using multiple references is lacking, e.g., for main memory consumption and optimality. In this paper, we describe one key technique for the referential compression against multiple references: The factorization of sequences. Based on the notion of an optimal factorization, we propose optimization heuristics and identify parameter settings which greatly influence 1 the size of the factorization, 2 the time for factorization, and 3 the required amount of main memory. We evaluate a total of 30 setups with a varying number of references on data from three different species. Our results show a wide range of factorization sizes (optimal to an overhead of up to 300%, factorization speed (0.01 MB/s to more than 600 MB/s, and main memory usage (few dozen MB to dozens of GB. Based on our evaluation, we identify the best configurations for common use cases. Our evaluation shows that multi-reference factorization is much better than single-reference factorization.

  14. Background qualitative analysis of the European reference life cycle database (ELCD) energy datasets - part II: electricity datasets.

    Science.gov (United States)

    Garraín, Daniel; Fazio, Simone; de la Rúa, Cristina; Recchioni, Marco; Lechón, Yolanda; Mathieux, Fabrice

    2015-01-01

    The aim of this paper is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) electricity datasets. The revision is based on the data quality indicators described by the International Life Cycle Data system (ILCD) Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. Results show that ELCD electricity datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the electricity-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD electricity datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall Data Quality Requirements of databases.

  15. Peripheral blood transcriptome sequencing reveals rejection-relevant genes in long-term heart transplantation.

    Science.gov (United States)

    Chen, Yan; Zhang, Haibo; Xiao, Xue; Jia, Yixin; Wu, Weili; Liu, Licheng; Jiang, Jun; Zhu, Baoli; Meng, Xu; Chen, Weijun

    2013-10-03

    Peripheral blood-based gene expression patterns have been investigated as biomarkers to monitor the immune system and rule out rejection after heart transplantation. Recent advances in the high-throughput deep sequencing (HTS) technologies provide new leads in transcriptome analysis. By performing Solexa/Illumina's digital gene expression (DGE) profiling, we analyzed gene expression profiles of PBMCs from 6 quiescent (grade 0) and 6 rejection (grade 2R&3R) heart transplant recipients at more than 6 months after transplantation. Subsequently, quantitative real-time polymerase chain reaction (qRT-PCR) was carried out in an independent validation cohort of 47 individuals from three rejection groups (ISHLT, grade 0,1R, 2R&3R). Through DGE sequencing and qPCR validation, 10 genes were identified as informative genes for detection of cardiac transplant rejection. A further clustering analysis showed that the 10 genes were not only effective for distinguishing patients with acute cardiac allograft rejection, but also informative for discriminating patients with renal allograft rejection based on both blood and biopsy samples. Moreover, PPI network analysis revealed that the 10 genes were connected to each other within a short interaction distance. We proposed a 10-gene signature for heart transplant patients at high-risk of developing severe rejection, which was found to be effective as well in other organ transplant. Moreover, we supposed that these genes function systematically as biomarkers in long-time allograft rejection. Further validation in broad transplant population would be required before the non-invasive biomarkers can be generally utilized to predict the risk of transplant rejection. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  16. Dataset definition for CMS operations and physics analyses

    Science.gov (United States)

    Franzoni, Giovanni; Compact Muon Solenoid Collaboration

    2016-04-01

    Data recorded at the CMS experiment are funnelled into streams, integrated in the HLT menu, and further organised in a hierarchical structure of primary datasets and secondary datasets/dedicated skims. Datasets are defined according to the final-state particles reconstructed by the high level trigger, the data format and the use case (physics analysis, alignment and calibration, performance studies). During the first LHC run, new workflows have been added to this canonical scheme, to exploit at best the flexibility of the CMS trigger and data acquisition systems. The concepts of data parking and data scouting have been introduced to extend the physics reach of CMS, offering the opportunity of defining physics triggers with extremely loose selections (e.g. dijet resonance trigger collecting data at a 1 kHz). In this presentation, we review the evolution of the dataset definition during the LHC run I, and we discuss the plans for the run II.

  17. U.S. Climate Divisional Dataset (Version Superseded)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data has been superseded by a newer version of the dataset. Please refer to NOAA's Climate Divisional Database for more information. The U.S. Climate Divisional...

  18. Karna Particle Size Dataset for Tables and Figures

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset contains 1) table of bulk Pb-XAS LCF results, 2) table of bulk As-XAS LCF results, 3) figure data of particle size distribution, and 4) figure data for...

  19. NOAA Global Surface Temperature Dataset, Version 4.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is derived from two independent analyses: the Extended Reconstructed Sea Surface Temperature (ERSST)...

  20. National Hydrography Dataset (NHD) - USGS National Map Downloadable Data Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The USGS National Hydrography Dataset (NHD) Downloadable Data Collection from The National Map (TNM) is a comprehensive set of digital spatial data that encodes...

  1. Watershed Boundary Dataset (WBD) - USGS National Map Downloadable Data Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Watershed Boundary Dataset (WBD) from The National Map (TNM) defines the perimeter of drainage areas formed by the terrain and other landscape characteristics....

  2. BASE MAP DATASET, LE FLORE COUNTY, OKLAHOMA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme, orthographic...

  3. USGS National Hydrography Dataset from The National Map

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — USGS The National Map - National Hydrography Dataset (NHD) is a comprehensive set of digital spatial data that encodes information about naturally occurring and...

  4. A robust dataset-agnostic heart disease classifier from Phonocardiogram.

    Science.gov (United States)

    Banerjee, Rohan; Dutta Choudhury, Anirban; Deshpande, Parijat; Bhattacharya, Sakyajit; Pal, Arpan; Mandana, K M

    2017-07-01

    Automatic classification of normal and abnormal heart sounds is a popular area of research. However, building a robust algorithm unaffected by signal quality and patient demography is a challenge. In this paper we have analysed a wide list of Phonocardiogram (PCG) features in time and frequency domain along with morphological and statistical features to construct a robust and discriminative feature set for dataset-agnostic classification of normal and cardiac patients. The large and open access database, made available in Physionet 2016 challenge was used for feature selection, internal validation and creation of training models. A second dataset of 41 PCG segments, collected using our in-house smart phone based digital stethoscope from an Indian hospital was used for performance evaluation. Our proposed methodology yielded sensitivity and specificity scores of 0.76 and 0.75 respectively on the test dataset in classifying cardiovascular diseases. The methodology also outperformed three popular prior art approaches, when applied on the same dataset.

  5. AFSC/REFM: Seabird Necropsy dataset of North Pacific

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The seabird necropsy dataset contains information on seabird specimens that were collected under salvage and scientific collection permits primarily by...

  6. Dataset definition for CMS operations and physics analyses

    CERN Document Server

    AUTHOR|(CDS)2051291

    2016-01-01

    Data recorded at the CMS experiment are funnelled into streams, integrated in the HLT menu, and further organised in a hierarchical structure of primary datasets, secondary datasets, and dedicated skims. Datasets are defined according to the final-state particles reconstructed by the high level trigger, the data format and the use case (physics analysis, alignment and calibration, performance studies). During the first LHC run, new workflows have been added to this canonical scheme, to exploit at best the flexibility of the CMS trigger and data acquisition systems. The concept of data parking and data scouting have been introduced to extend the physics reach of CMS, offering the opportunity of defining physics triggers with extremely loose selections (e.g. dijet resonance trigger collecting data at a 1 kHz). In this presentation, we review the evolution of the dataset definition during the first run, and we discuss the plans for the second LHC run.

  7. USGS National Boundary Dataset (NBD) Downloadable Data Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The USGS Governmental Unit Boundaries dataset from The National Map (TNM) represents major civil areas for the Nation, including States or Territories, counties (or...

  8. Environmental Dataset Gateway (EDG) CS-W Interface

    Data.gov (United States)

    U.S. Environmental Protection Agency — Use the Environmental Dataset Gateway (EDG) to find and access EPA's environmental resources. Many options are available for easily reusing EDG content in other...

  9. Global Man-made Impervious Surface (GMIS) Dataset From Landsat

    Data.gov (United States)

    National Aeronautics and Space Administration — The Global Man-made Impervious Surface (GMIS) Dataset From Landsat consists of global estimates of fractional impervious cover derived from the Global Land Survey...

  10. A Comparative Analysis of Classification Algorithms on Diverse Datasets

    Directory of Open Access Journals (Sweden)

    M. Alghobiri

    2018-04-01

    Full Text Available Data mining involves the computational process to find patterns from large data sets. Classification, one of the main domains of data mining, involves known structure generalizing to apply to a new dataset and predict its class. There are various classification algorithms being used to classify various data sets. They are based on different methods such as probability, decision tree, neural network, nearest neighbor, boolean and fuzzy logic, kernel-based etc. In this paper, we apply three diverse classification algorithms on ten datasets. The datasets have been selected based on their size and/or number and nature of attributes. Results have been discussed using some performance evaluation measures like precision, accuracy, F-measure, Kappa statistics, mean absolute error, relative absolute error, ROC Area etc. Comparative analysis has been carried out using the performance evaluation measures of accuracy, precision, and F-measure. We specify features and limitations of the classification algorithms for the diverse nature datasets.

  11. Newton SSANTA Dr Water using POU filters dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset contains information about all the features extracted from the raw data files, the formulas that were assigned to some of these features, and the...

  12. Estimating parameters for probabilistic linkage of privacy-preserved datasets.

    Science.gov (United States)

    Brown, Adrian P; Randall, Sean M; Ferrante, Anna M; Semmens, James B; Boyd, James H

    2017-07-10

    Probabilistic record linkage is a process used to bring together person-based records from within the same dataset (de-duplication) or from disparate datasets using pairwise comparisons and matching probabilities. The linkage strategy and associated match probabilities are often estimated through investigations into data quality and manual inspection. However, as privacy-preserved datasets comprise encrypted data, such methods are not possible. In this paper, we present a method for estimating the probabilities and threshold values for probabilistic privacy-preserved record linkage using Bloom filters. Our method was tested through a simulation study using synthetic data, followed by an application using real-world administrative data. Synthetic datasets were generated with error rates from zero to 20% error. Our method was used to estimate parameters (probabilities and thresholds) for de-duplication linkages. Linkage quality was determined by F-measure. Each dataset was privacy-preserved using separate Bloom filters for each field. Match probabilities were estimated using the expectation-maximisation (EM) algorithm on the privacy-preserved data. Threshold cut-off values were determined by an extension to the EM algorithm allowing linkage quality to be estimated for each possible threshold. De-duplication linkages of each privacy-preserved dataset were performed using both estimated and calculated probabilities. Linkage quality using the F-measure at the estimated threshold values was also compared to the highest F-measure. Three large administrative datasets were used to demonstrate the applicability of the probability and threshold estimation technique on real-world data. Linkage of the synthetic datasets using the estimated probabilities produced an F-measure that was comparable to the F-measure using calculated probabilities, even with up to 20% error. Linkage of the administrative datasets using estimated probabilities produced an F-measure that was higher

  13. MR neurography with multiplanar reconstruction of 3D MRI datasets: an anatomical study and clinical applications

    International Nuclear Information System (INIS)

    Freund, Wolfgang; Aschoff, Andrik J.; Stuber, Gregor; Schmitz, Bernd; Brinkmann, Alexander; Wagner, Florian; Dinse, Alexander

    2007-01-01

    Extracranial MR neurography has so far mainly been used with 2D datasets. We investigated the use of 3D datasets for peripheral neurography of the sciatic nerve. A total of 40 thighs (20 healthy volunteers) were examined with a coronally oriented magnetization-prepared rapid acquisition gradient echo sequence with isotropic voxels of 1 x 1 x 1 mm and a field of view of 500 mm. Anatomical landmarks were palpated and marked with MRI markers. After MR scanning, the sciatic nerve was identified by two readers independently in the resulting 3D dataset. In every volunteer, the sciatic nerve could be identified bilaterally over the whole length of the thigh, even in areas of close contact to isointense muscles. The landmark of the greater trochanter was falsely palpated by 2.2 cm, and the knee joint by 1 cm. The mean distance between the bifurcation of the sciatic nerve and the knee-joint gap was 6 cm (±1.8 cm). The mean results of the two readers differed by 1-6%. With the described method of MR neurography, the sciatic nerve was depicted reliably and objectively in great anatomical detail over the whole length of the thigh. Important anatomical information can be obtained. The clinical applications of MR neurography for the brachial plexus and lumbosacral plexus/sciatic nerve are discussed. (orig.)

  14. Toward computational cumulative biology by combining models of biological datasets.

    Science.gov (United States)

    Faisal, Ali; Peltonen, Jaakko; Georgii, Elisabeth; Rung, Johan; Kaski, Samuel

    2014-01-01

    A main challenge of data-driven sciences is how to make maximal use of the progressively expanding databases of experimental datasets in order to keep research cumulative. We introduce the idea of a modeling-based dataset retrieval engine designed for relating a researcher's experimental dataset to earlier work in the field. The search is (i) data-driven to enable new findings, going beyond the state of the art of keyword searches in annotations, (ii) modeling-driven, to include both biological knowledge and insights learned from data, and (iii) scalable, as it is accomplished without building one unified grand model of all data. Assuming each dataset has been modeled beforehand, by the researchers or automatically by database managers, we apply a rapidly computable and optimizable combination model to decompose a new dataset into contributions from earlier relevant models. By using the data-driven decomposition, we identify a network of interrelated datasets from a large annotated human gene expression atlas. While tissue type and disease were major driving forces for determining relevant datasets, the found relationships were richer, and the model-based search was more accurate than the keyword search; moreover, it recovered biologically meaningful relationships that are not straightforwardly visible from annotations-for instance, between cells in different developmental stages such as thymocytes and T-cells. Data-driven links and citations matched to a large extent; the data-driven links even uncovered corrections to the publication data, as two of the most linked datasets were not highly cited and turned out to have wrong publication entries in the database.

  15. Testing the Neutral Theory of Biodiversity with Human Microbiome Datasets

    OpenAIRE

    Li, Lianwei; Ma, Zhanshan (Sam)

    2016-01-01

    The human microbiome project (HMP) has made it possible to test important ecological theories for arguably the most important ecosystem to human health?the human microbiome. Existing limited number of studies have reported conflicting evidence in the case of the neutral theory; the present study aims to comprehensively test the neutral theory with extensive HMP datasets covering all five major body sites inhabited by the human microbiome. Utilizing 7437 datasets of bacterial community samples...

  16. General Purpose Multimedia Dataset - GarageBand 2008

    DEFF Research Database (Denmark)

    Meng, Anders

    This document describes a general purpose multimedia data-set to be used in cross-media machine learning problems. In more detail we describe the genre taxonomy applied at http://www.garageband.com, from where the data-set was collected, and how the taxonomy have been fused into a more human...... understandable taxonomy. Finally, a description of various features extracted from both the audio and text are presented....

  17. Artificial intelligence (AI) systems for interpreting complex medical datasets.

    Science.gov (United States)

    Altman, R B

    2017-05-01

    Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. However, artificial intelligence (AI) applications in medical data have several technical challenges: complex and heterogeneous datasets, noisy medical datasets, and explaining their output to users. There are also social challenges related to intellectual property, data provenance, regulatory issues, economics, and liability. © 2017 ASCPT.

  18. GUIDEseq: a bioconductor package to analyze GUIDE-Seq datasets for CRISPR-Cas nucleases.

    Science.gov (United States)

    Zhu, Lihua Julie; Lawrence, Michael; Gupta, Ankit; Pagès, Hervé; Kucukural, Alper; Garber, Manuel; Wolfe, Scot A

    2017-05-15

    Genome editing technologies developed around the CRISPR-Cas9 nuclease system have facilitated the investigation of a broad range of biological questions. These nucleases also hold tremendous promise for treating a variety of genetic disorders. In the context of their therapeutic application, it is important to identify the spectrum of genomic sequences that are cleaved by a candidate nuclease when programmed with a particular guide RNA, as well as the cleavage efficiency of these sites. Powerful new experimental approaches, such as GUIDE-seq, facilitate the sensitive, unbiased genome-wide detection of nuclease cleavage sites within the genome. Flexible bioinformatics analysis tools for processing GUIDE-seq data are needed. Here, we describe an open source, open development software suite, GUIDEseq, for GUIDE-seq data analysis and annotation as a Bioconductor package in R. The GUIDEseq package provides a flexible platform with more than 60 adjustable parameters for the analysis of datasets associated with custom nuclease applications. These parameters allow data analysis to be tailored to different nuclease platforms with different length and complexity in their guide and PAM recognition sequences or their DNA cleavage position. They also enable users to customize sequence aggregation criteria, and vary peak calling thresholds that can influence the number of potential off-target sites recovered. GUIDEseq also annotates potential off-target sites that overlap with genes based on genome annotation information, as these may be the most important off-target sites for further characterization. In addition, GUIDEseq enables the comparison and visualization of off-target site overlap between different datasets for a rapid comparison of different nuclease configurations or experimental conditions. For each identified off-target, the GUIDEseq package outputs mapped GUIDE-Seq read count as well as cleavage score from a user specified off-target cleavage score prediction

  19. Heuristics for Relevancy Ranking of Earth Dataset Search Results

    Science.gov (United States)

    Lynnes, Christopher; Quinn, Patrick; Norton, James

    2016-01-01

    As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

  20. Identification of Differentially Expressed miRNAs between White and Black Hair Follicles by RNA-Sequencing in the Goat (Capra hircus)

    Science.gov (United States)

    Wu, Zhenyang; Fu, Yuhua; Cao, Jianhua; Yu, Mei; Tang, Xiaohui; Zhao, Shuhong

    2014-01-01

    MicroRNAs (miRNAs) play a key role in many biological processes by regulating gene expression at the post-transcriptional level. A number of miRNAs have been identified from livestock species. However, compared with other animals, such as pigs and cows, the number of miRNAs identified in goats is quite low, particularly in hair follicles. In this study, to investigate the functional roles of miRNAs in goat hair follicles of goats with different coat colors, we sequenced miRNAs from two hair follicles samples (white and black) using Solexa sequencing. A total of 35,604,016 reads were obtained, which included 30,878,637 clean reads (86.73%). MiRDeep2 software identified 214 miRNAs. Among them, 205 were conserved among species and nine were novel miRNAs. Furthermore, DESeq software identified six differentially expressed miRNAs. Quantitative PCR confirmed differential expression of two miRNAs, miR-10b and miR-211. KEGG pathways were analyzed using the DAVID website for the predicted target genes of the differentially expressed miRNAs. Several signaling pathways including Notch and MAPK pathways may affect the process of coat color formation. Our study showed that the identified miRNAs might play an essential role in black and white follicle formation in goats. PMID:24879525

  1. Identification of Differentially Expressed miRNAs between White and Black Hair Follicles by RNA-Sequencing in the Goat (Capra hircus

    Directory of Open Access Journals (Sweden)

    Zhenyang Wu

    2014-05-01

    Full Text Available MicroRNAs (miRNAs play a key role in many biological processes by regulating gene expression at the post-transcriptional level. A number of miRNAs have been identified from livestock species. However, compared with other animals, such as pigs and cows, the number of miRNAs identified in goats is quite low, particularly in hair follicles. In this study, to investigate the functional roles of miRNAs in goat hair follicles of goats with different coat colors, we sequenced miRNAs from two hair follicles samples (white and black using Solexa sequencing. A total of 35,604,016 reads were obtained, which included 30,878,637 clean reads (86.73%. MiRDeep2 software identified 214 miRNAs. Among them, 205 were conserved among species and nine were novel miRNAs. Furthermore, DESeq software identified six differentially expressed miRNAs. Quantitative PCR confirmed differential expression of two miRNAs, miR-10b and miR-211. KEGG pathways were analyzed using the DAVID website for the predicted target genes of the differentially expressed miRNAs. Several signaling pathways including Notch and MAPK pathways may affect the process of coat color formation. Our study showed that the identified miRNAs might play an essential role in black and white follicle formation in goats.

  2. Microbial Community Profiling of Human Saliva Using Shotgun Metagenomic Sequencing

    OpenAIRE

    Hasan, Nur A.; Young, Brian A.; Minard-Smith, Angela T.; Saeed, Kelly; Li, Huai; Heizer, Esley M.; McMillan, Nancy J.; Isom, Richard; Abdullah, Abdul Shakur; Bornman, Daniel M.; Faith, Seth A.; Choi, Seon Young; Dickens, Michael L.; Cebula, Thomas A.; Colwell, Rita R.

    2014-01-01

    Human saliva is clinically informative of both oral and general health. Since next generation shotgun sequencing (NGS) is now widely used to identify and quantify bacteria, we investigated the bacterial flora of saliva microbiomes of two healthy volunteers and five datasets from the Human Microbiome Project, along with a control dataset containing short NGS reads from bacterial species representative of the bacterial flora of human saliva. GENIUS, a system designed to identify and quantify ba...

  3. Sequence Quality Analysis Tool for HIV Type 1 Protease and Reverse Transcriptase

    OpenAIRE

    DeLong, Allison K.; Wu, Mingham; Bennett, Diane; Parkin, Neil; Wu, Zhijin; Hogan, Joseph W.; Kantor, Rami

    2012-01-01

    Access to antiretroviral therapy is increasing globally and drug resistance evolution is anticipated. Currently, protease (PR) and reverse transcriptase (RT) sequence generation is increasing, including the use of in-house sequencing assays, and quality assessment prior to sequence analysis is essential. We created a computational HIV PR/RT Sequence Quality Analysis Tool (SQUAT) that runs in the R statistical environment. Sequence quality thresholds are calculated from a large dataset (46,802...

  4. Mining and Utilizing Dataset Relevancy from Oceanographic Dataset Metadata, Usage Metrics, and User Feedback to Improve Data Discovery and Access

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to mine and utilize the combination of Earth Science dataset, metadata with usage metrics and user feedback to objectively extract relevance for improved...

  5. EEG datasets for motor imagery brain-computer interface.

    Science.gov (United States)

    Cho, Hohyun; Ahn, Minkyu; Ahn, Sangtae; Kwon, Moonyoung; Jun, Sung Chan

    2017-07-01

    Most investigators of brain-computer interface (BCI) research believe that BCI can be achieved through induced neuronal activity from the cortex, but not by evoked neuronal activity. Motor imagery (MI)-based BCI is one of the standard concepts of BCI, in that the user can generate induced activity by imagining motor movements. However, variations in performance over sessions and subjects are too severe to overcome easily; therefore, a basic understanding and investigation of BCI performance variation is necessary to find critical evidence of performance variation. Here we present not only EEG datasets for MI BCI from 52 subjects, but also the results of a psychological and physiological questionnaire, EMG datasets, the locations of 3D EEG electrodes, and EEGs for non-task-related states. We validated our EEG datasets by using the percentage of bad trials, event-related desynchronization/synchronization (ERD/ERS) analysis, and classification analysis. After conventional rejection of bad trials, we showed contralateral ERD and ipsilateral ERS in the somatosensory area, which are well-known patterns of MI. Finally, we showed that 73.08% of datasets (38 subjects) included reasonably discriminative information. Our EEG datasets included the information necessary to determine statistical significance; they consisted of well-discriminated datasets (38 subjects) and less-discriminative datasets. These may provide researchers with opportunities to investigate human factors related to MI BCI performance variation, and may also achieve subject-to-subject transfer by using metadata, including a questionnaire, EEG coordinates, and EEGs for non-task-related states. © The Authors 2017. Published by Oxford University Press.

  6. Comparison of CORA and EN4 in-situ datasets validation methods, toward a better quality merged dataset.

    Science.gov (United States)

    Szekely, Tanguy; Killick, Rachel; Gourrion, Jerome; Reverdin, Gilles

    2017-04-01

    CORA and EN4 are both global delayed time mode validated in-situ ocean temperature and salinity datasets distributed by the Met Office (http://www.metoffice.gov.uk/) and Copernicus (www.marine.copernicus.eu). A large part of the profiles distributed by CORA and EN4 in recent years are Argo profiles from the ARGO DAC, but profiles are also extracted from the World Ocean Database and TESAC profiles from GTSPP. In the case of CORA, data coming from the EUROGOOS Regional operationnal oserving system( ROOS) operated by European institutes no managed by National Data Centres and other datasets of profiles povided by scientific sources can also be found (Sea mammals profiles from MEOP, XBT datasets from cruises ...). (EN4 also takes data from the ASBO dataset to supplement observations in the Arctic). First advantage of this new merge product is to enhance the space and time coverage at global and european scales for the period covering 1950 till a year before the current year. This product is updated once a year and T&S gridded fields are alos generated for the period 1990-year n-1. The enhancement compared to the revious CORA product will be presented Despite the fact that the profiles distributed by both datasets are mostly the same, the quality control procedures developed by the Met Office and Copernicus teams differ, sometimes leading to different quality control flags for the same profile. Started in 2016 a new study started that aims to compare both validation procedures to move towards a Copernicus Marine Service dataset with the best features of CORA and EN4 validation.A reference data set composed of the full set of in-situ temperature and salinity measurements collected by Coriolis during 2015 is used. These measurements have been made thanks to wide range of instruments (XBTs, CTDs, Argo floats, Instrumented sea mammals,...), covering the global ocean. The reference dataset has been validated simultaneously by both teams.An exhaustive comparison of the

  7. Wind and wave dataset for Matara, Sri Lanka

    Science.gov (United States)

    Luo, Yao; Wang, Dongxiao; Priyadarshana Gamage, Tilak; Zhou, Fenghua; Madusanka Widanage, Charith; Liu, Taiwei

    2018-01-01

    We present a continuous in situ hydro-meteorology observational dataset from a set of instruments first deployed in December 2012 in the south of Sri Lanka, facing toward the north Indian Ocean. In these waters, simultaneous records of wind and wave data are sparse due to difficulties in deploying measurement instruments, although the area hosts one of the busiest shipping lanes in the world. This study describes the survey, deployment, and measurements of wind and waves, with the aim of offering future users of the dataset the most comprehensive and as much information as possible. This dataset advances our understanding of the nearshore hydrodynamic processes and wave climate, including sea waves and swells, in the north Indian Ocean. Moreover, it is a valuable resource for ocean model parameterization and validation. The archived dataset (Table 1) is examined in detail, including wave data at two locations with water depths of 20 and 10 m comprising synchronous time series of wind, ocean astronomical tide, air pressure, etc. In addition, we use these wave observations to evaluate the ERA-Interim reanalysis product. Based on Buoy 2 data, the swells are the main component of waves year-round, although monsoons can markedly alter the proportion between swell and wind sea. The dataset (Luo et al., 2017) is publicly available from Science Data Bank (https://doi.org/10.11922/sciencedb.447).

  8. The LANDFIRE Refresh strategy: updating the national dataset

    Science.gov (United States)

    Nelson, Kurtis J.; Connot, Joel A.; Peterson, Birgit E.; Martin, Charley

    2013-01-01

    The LANDFIRE Program provides comprehensive vegetation and fuel datasets for the entire United States. As with many large-scale ecological datasets, vegetation and landscape conditions must be updated periodically to account for disturbances, growth, and natural succession. The LANDFIRE Refresh effort was the first attempt to consistently update these products nationwide. It incorporated a combination of specific systematic improvements to the original LANDFIRE National data, remote sensing based disturbance detection methods, field collected disturbance information, vegetation growth and succession modeling, and vegetation transition processes. This resulted in the creation of two complete datasets for all 50 states: LANDFIRE Refresh 2001, which includes the systematic improvements, and LANDFIRE Refresh 2008, which includes the disturbance and succession updates to the vegetation and fuel data. The new datasets are comparable for studying landscape changes in vegetation type and structure over a decadal period, and provide the most recent characterization of fuel conditions across the country. The applicability of the new layers is discussed and the effects of using the new fuel datasets are demonstrated through a fire behavior modeling exercise using the 2011 Wallow Fire in eastern Arizona as an example.

  9. Interactive visualization and analysis of multimodal datasets for surgical applications.

    Science.gov (United States)

    Kirmizibayrak, Can; Yim, Yeny; Wakid, Mike; Hahn, James

    2012-12-01

    Surgeons use information from multiple sources when making surgical decisions. These include volumetric datasets (such as CT, PET, MRI, and their variants), 2D datasets (such as endoscopic videos), and vector-valued datasets (such as computer simulations). Presenting all the information to the user in an effective manner is a challenging problem. In this paper, we present a visualization approach that displays the information from various sources in a single coherent view. The system allows the user to explore and manipulate volumetric datasets, display analysis of dataset values in local regions, combine 2D and 3D imaging modalities and display results of vector-based computer simulations. Several interaction methods are discussed: in addition to traditional interfaces including mouse and trackers, gesture-based natural interaction methods are shown to control these visualizations with real-time performance. An example of a medical application (medialization laryngoplasty) is presented to demonstrate how the combination of different modalities can be used in a surgical setting with our approach.

  10. Wind and wave dataset for Matara, Sri Lanka

    Directory of Open Access Journals (Sweden)

    Y. Luo

    2018-01-01

    Full Text Available We present a continuous in situ hydro-meteorology observational dataset from a set of instruments first deployed in December 2012 in the south of Sri Lanka, facing toward the north Indian Ocean. In these waters, simultaneous records of wind and wave data are sparse due to difficulties in deploying measurement instruments, although the area hosts one of the busiest shipping lanes in the world. This study describes the survey, deployment, and measurements of wind and waves, with the aim of offering future users of the dataset the most comprehensive and as much information as possible. This dataset advances our understanding of the nearshore hydrodynamic processes and wave climate, including sea waves and swells, in the north Indian Ocean. Moreover, it is a valuable resource for ocean model parameterization and validation. The archived dataset (Table 1 is examined in detail, including wave data at two locations with water depths of 20 and 10 m comprising synchronous time series of wind, ocean astronomical tide, air pressure, etc. In addition, we use these wave observations to evaluate the ERA-Interim reanalysis product. Based on Buoy 2 data, the swells are the main component of waves year-round, although monsoons can markedly alter the proportion between swell and wind sea. The dataset (Luo et al., 2017 is publicly available from Science Data Bank (https://doi.org/10.11922/sciencedb.447.

  11. Process mining in oncology using the MIMIC-III dataset

    Science.gov (United States)

    Prima Kurniati, Angelina; Hall, Geoff; Hogg, David; Johnson, Owen

    2018-03-01

    Process mining is a data analytics approach to discover and analyse process models based on the real activities captured in information systems. There is a growing body of literature on process mining in healthcare, including oncology, the study of cancer. In earlier work we found 37 peer-reviewed papers describing process mining research in oncology with a regular complaint being the limited availability and accessibility of datasets with suitable information for process mining. Publicly available datasets are one option and this paper describes the potential to use MIMIC-III, for process mining in oncology. MIMIC-III is a large open access dataset of de-identified patient records. There are 134 publications listed as using the MIMIC dataset, but none of them have used process mining. The MIMIC-III dataset has 16 event tables which are potentially useful for process mining and this paper demonstrates the opportunities to use MIMIC-III for process mining in oncology. Our research applied the L* lifecycle method to provide a worked example showing how process mining can be used to analyse cancer pathways. The results and data quality limitations are discussed along with opportunities for further work and reflection on the value of MIMIC-III for reproducible process mining research.

  12. Recent Development on the NOAA's Global Surface Temperature Dataset

    Science.gov (United States)

    Zhang, H. M.; Huang, B.; Boyer, T.; Lawrimore, J. H.; Menne, M. J.; Rennie, J.

    2016-12-01

    Global Surface Temperature (GST) is one of the most widely used indicators for climate trend and extreme analyses. A widely used GST dataset is the NOAA merged land-ocean surface temperature dataset known as NOAAGlobalTemp (formerly MLOST). The NOAAGlobalTemp had recently been updated from version 3.5.4 to version 4. The update includes a significant improvement in the ocean surface component (Extended Reconstructed Sea Surface Temperature or ERSST, from version 3b to version 4) which resulted in an increased temperature trends in recent decades. Since then, advancements in both the ocean component (ERSST) and land component (GHCN-Monthly) have been made, including the inclusion of Argo float SSTs and expanded EOT modes in ERSST, and the use of ISTI databank in GHCN-Monthly. In this presentation, we describe the impact of those improvements on the merged global temperature dataset, in terms of global trends and other aspects.

  13. Synthetic ALSPAC longitudinal datasets for the Big Data VR project.

    Science.gov (United States)

    Avraam, Demetris; Wilson, Rebecca C; Burton, Paul

    2017-01-01

    Three synthetic datasets - of observation size 15,000, 155,000 and 1,555,000 participants, respectively - were created by simulating eleven cardiac and anthropometric variables from nine collection ages of the ALSAPC birth cohort study. The synthetic datasets retain similar data properties to the ALSPAC study data they are simulated from (co-variance matrices, as well as the mean and variance values of the variables) without including the original data itself or disclosing participant information.  In this instance, the three synthetic datasets have been utilised in an academia-industry collaboration to build a prototype virtual reality data analysis software, but they could have a broader use in method and software development projects where sensitive data cannot be freely shared.

  14. The OXL format for the exchange of integrated datasets

    Directory of Open Access Journals (Sweden)

    Taubert Jan

    2007-12-01

    Full Text Available A prerequisite for systems biology is the integration and analysis of heterogeneous experimental data stored in hundreds of life-science databases and millions of scientific publications. Several standardised formats for the exchange of specific kinds of biological information exist. Such exchange languages facilitate the integration process; however they are not designed to transport integrated datasets. A format for exchanging integrated datasets needs to i cover data from a broad range of application domains, ii be flexible and extensible to combine many different complex data structures, iii include metadata and semantic definitions, iv include inferred information, v identify the original data source for integrated entities and vi transport large integrated datasets. Unfortunately, none of the exchange formats from the biological domain (e.g. BioPAX, MAGE-ML, PSI-MI, SBML or the generic approaches (RDF, OWL fulfil these requirements in a systematic way.

  15. Dataset of transcriptional landscape of B cell early activation

    Directory of Open Access Journals (Sweden)

    Alexander S. Garruss

    2015-09-01

    Full Text Available Signaling via B cell receptors (BCR and Toll-like receptors (TLRs result in activation of B cells with distinct physiological outcomes, but transcriptional regulatory mechanisms that drive activation and distinguish these pathways remain unknown. At early time points after BCR and TLR ligand exposure, 0.5 and 2 h, RNA-seq was performed allowing observations on rapid transcriptional changes. At 2 h, ChIP-seq was performed to allow observations on important regulatory mechanisms potentially driving transcriptional change. The dataset includes RNA-seq, ChIP-seq of control (Input, RNA Pol II, H3K4me3, H3K27me3, and a separate RNA-seq for miRNA expression, which can be found at Gene Expression Omnibus Dataset GSE61608. Here, we provide details on the experimental and analysis methods used to obtain and analyze this dataset and to examine the transcriptional landscape of B cell early activation.

  16. The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Arkin, Philip; Chang, Alfred; Ferraro, Ralph; Gruber, Arnold; Janowiak, John; McNab, Alan; Rudolf, Bruno; Schneider, Udo

    1997-01-01

    The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit -satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5 deg x 2.5 deg latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

  17. A high-resolution European dataset for hydrologic modeling

    Science.gov (United States)

    Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta

    2013-04-01

    There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as

  18. Visualization of conserved structures by fusing highly variable datasets.

    Science.gov (United States)

    Silverstein, Jonathan C; Chhadia, Ankur; Dech, Fred

    2002-01-01

    Skill, effort, and time are required to identify and visualize anatomic structures in three-dimensions from radiological data. Fundamentally, automating these processes requires a technique that uses symbolic information not in the dynamic range of the voxel data. We were developing such a technique based on mutual information for automatic multi-modality image fusion (MIAMI Fuse, University of Michigan). This system previously demonstrated facility at fusing one voxel dataset with integrated symbolic structure information to a CT dataset (different scale and resolution) from the same person. The next step of development of our technique was aimed at accommodating the variability of anatomy from patient to patient by using warping to fuse our standard dataset to arbitrary patient CT datasets. A standard symbolic information dataset was created from the full color Visible Human Female by segmenting the liver parenchyma, portal veins, and hepatic veins and overwriting each set of voxels with a fixed color. Two arbitrarily selected patient CT scans of the abdomen were used for reference datasets. We used the warping functions in MIAMI Fuse to align the standard structure data to each patient scan. The key to successful fusion was the focused use of multiple warping control points that place themselves around the structure of interest automatically. The user assigns only a few initial control points to align the scans. Fusion 1 and 2 transformed the atlas with 27 points around the liver to CT1 and CT2 respectively. Fusion 3 transformed the atlas with 45 control points around the liver to CT1 and Fusion 4 transformed the atlas with 5 control points around the portal vein. The CT dataset is augmented with the transformed standard structure dataset, such that the warped structure masks are visualized in combination with the original patient dataset. This combined volume visualization is then rendered interactively in stereo on the ImmersaDesk in an immersive Virtual

  19. A cross-country Exchange Market Pressure (EMP) dataset.

    Science.gov (United States)

    Desai, Mohit; Patnaik, Ila; Felman, Joshua; Shah, Ajay

    2017-06-01

    The data presented in this article are related to the research article titled - "An exchange market pressure measure for cross country analysis" (Patnaik et al. [1]). In this article, we present the dataset for Exchange Market Pressure values (EMP) for 139 countries along with their conversion factors, ρ (rho). Exchange Market Pressure, expressed in percentage change in exchange rate, measures the change in exchange rate that would have taken place had the central bank not intervened. The conversion factor ρ can interpreted as the change in exchange rate associated with $1 billion of intervention. Estimates of conversion factor ρ allow us to calculate a monthly time series of EMP for 139 countries. Additionally, the dataset contains the 68% confidence interval (high and low values) for the point estimates of ρ 's. Using the standard errors of estimates of ρ 's, we obtain one sigma intervals around mean estimates of EMP values. These values are also reported in the dataset.

  20. cis sequence effects on gene expression

    Directory of Open Access Journals (Sweden)

    Jacobs Kevin

    2007-08-01

    Full Text Available Abstract Background Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation (genetical genomics provides insight into the role of linked sequence variation in the regulation of gene expression. We investigated the role of sequence variation in cis on gene expression (cis sequence effects in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting cis sequence effects and the proportion of gene expression variation explained by cis sequence effects using three different analytical approaches, and compared our results to the literature. Results We generated gene expression profiling data at N = 697 candidate genes from N = 30 lymphoblastoid cell lines for this study and used available candidate gene resequencing data at N = 552 candidate genes to identify N = 30 candidate genes with sufficient variance in both datasets for the investigation of cis sequence effects. We used two additive models and the haplotype phylogeny scanning approach of Templeton (Tree Scanning to evaluate association between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed gene expression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p cis sequence effects in our study, respectively. Conclusion Based on analysis of our results and the extant literature, one in four genes exhibits significant cis sequence effects, and for these genes, about 30% of gene expression variation is accounted for by cis sequence variation. Despite diverse experimental approaches, the presence or absence of significant cis sequence effects is largely supported by previously published studies.

  1. Protecting genomic sequence anonymity with generalization lattices.

    Science.gov (United States)

    Malin, B A

    2005-01-01

    Current genomic privacy technologies assume the identity of genomic sequence data is protected if personal information, such as demographics, are obscured, removed, or encrypted. While demographic features can directly compromise an individual's identity, recent research demonstrates such protections are insufficient because sequence data itself is susceptible to re-identification. To counteract this problem, we introduce an algorithm for anonymizing a collection of person-specific DNA sequences. The technique is termed DNA lattice anonymization (DNALA), and is based upon the formal privacy protection schema of k -anonymity. Under this model, it is impossible to observe or learn features that distinguish one genetic sequence from k-1 other entries in a collection. To maximize information retained in protected sequences, we incorporate a concept generalization lattice to learn the distance between two residues in a single nucleotide region. The lattice provides the most similar generalized concept for two residues (e.g. adenine and guanine are both purines). The method is tested and evaluated with several publicly available human population datasets ranging in size from 30 to 400 sequences. Our findings imply the anonymization schema is feasible for the protection of sequences privacy. The DNALA method is the first computational disclosure control technique for general DNA sequences. Given the computational nature of the method, guarantees of anonymity can be formally proven. There is room for improvement and validation, though this research provides the groundwork from which future researchers can construct genomics anonymization schemas tailored to specific datasharing scenarios.

  2. Performances of Different Fragment Sizes for Reduced Representation Bisulfite Sequencing in Pigs

    DEFF Research Database (Denmark)

    Yuan, Xiao Long; Zhang, Zhe; Pan, Rong Yang

    2017-01-01

    sizes might decrease when the dataset size was more than 70, 50 and 110 million reads for these three fragment sizes, respectively. Given a 50-million dataset size, the average sequencing depth of the detected CpG sites in the 110-220 bp fragment size appeared to be deeper than in the 40-110 bp and 40...

  3. Fast and Sequence-Adaptive Whole-Brain Segmentation Using Parametric Bayesian Modeling

    DEFF Research Database (Denmark)

    Puonti, Oula; Iglesias, Juan Eugenio; Van Leemput, Koen

    2016-01-01

    the performance of a segmentation algorithm designed to meet these requirements, building upon generative parametric models previously used in tissue classification. The method is tested on four different datasets acquired with different scanners, field strengths and pulse sequences, demonstrating comparable...

  4. SEQUENCING AND DE NOVO DRAFT ASSEMBLIES OF A FATHEAD MINNOW (Pimpehales promelas) reference genome

    Data.gov (United States)

    U.S. Environmental Protection Agency — The dataset provides the URLs for accessing the genome sequence data and two draft assemblies as well as fathead minnow genotyping data associated with estimating...

  5. Dataset of herbarium specimens of threatened vascular plants in Catalonia.

    Science.gov (United States)

    Nualart, Neus; Ibáñez, Neus; Luque, Pere; Pedrol, Joan; Vilar, Lluís; Guàrdia, Roser

    2017-01-01

    This data paper describes a specimens' dataset of the Catalonian threatened vascular plants conserved in five public Catalonian herbaria (BC, BCN, HGI, HBIL and MTTE). Catalonia is an administrative region of Spain that includes large autochthon plants diversity and 199 taxa with IUCN threatened categories (EX, EW, RE, CR, EN and VU). This dataset includes 1,618 records collected from 17 th century to nowadays. For each specimen, the species name, locality indication, collection date, collector, ecology and revision label are recorded. More than 94% of the taxa are represented in the herbaria, which evidence the paper of the botanical collections as an essential source of occurrence data.

  6. A Large-Scale 3D Object Recognition dataset

    DEFF Research Database (Denmark)

    Sølund, Thomas; Glent Buch, Anders; Krüger, Norbert

    2016-01-01

    geometric groups; concave, convex, cylindrical and flat 3D object models. The object models have varying amount of local geometric features to challenge existing local shape feature descriptors in terms of descriptiveness and robustness. The dataset is validated in a benchmark which evaluates the matching...... performance of 7 different state-of-the-art local shape descriptors. Further, we validate the dataset in a 3D object recognition pipeline. Our benchmark shows as expected that local shape feature descriptors without any global point relation across the surface have a poor matching performance with flat...

  7. Traffic sign classification with dataset augmentation and convolutional neural network

    Science.gov (United States)

    Tang, Qing; Kurnianggoro, Laksono; Jo, Kang-Hyun

    2018-04-01

    This paper presents a method for traffic sign classification using a convolutional neural network (CNN). In this method, firstly we transfer a color image into grayscale, and then normalize it in the range (-1,1) as the preprocessing step. To increase robustness of classification model, we apply a dataset augmentation algorithm and create new images to train the model. To avoid overfitting, we utilize a dropout module before the last fully connection layer. To assess the performance of the proposed method, the German traffic sign recognition benchmark (GTSRB) dataset is utilized. Experimental results show that the method is effective in classifying traffic signs.

  8. Towards interoperable and reproducible QSAR analyses: Exchange of datasets.

    Science.gov (United States)

    Spjuth, Ola; Willighagen, Egon L; Guha, Rajarshi; Eklund, Martin; Wikberg, Jarl Es

    2010-06-30

    QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML) which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join, extend, combine datasets and hence work collectively, but

  9. Towards interoperable and reproducible QSAR analyses: Exchange of datasets

    Directory of Open Access Journals (Sweden)

    Spjuth Ola

    2010-06-01

    Full Text Available Abstract Background QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. Results We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Conclusions Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join

  10. The Wind Integration National Dataset (WIND) toolkit (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Caroline Draxl: NREL

    2014-01-01

    Regional wind integration studies require detailed wind power output data at many locations to perform simulations of how the power system will operate under high penetration scenarios. The wind datasets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as being time synchronized with available load profiles.As described in this presentation, the WIND Toolkit fulfills these requirements by providing a state-of-the-art national (US) wind resource, power production and forecast dataset.

  11. Genome-wide massively parallel sequencing of formaldehyde fixed-paraffin embedded (FFPE tumor tissues for copy-number- and mutation-analysis.

    Directory of Open Access Journals (Sweden)

    Michal R Schweiger

    Full Text Available BACKGROUND: Cancer re-sequencing programs rely on DNA isolated from fresh snap frozen tissues, the preparation of which is combined with additional preservation efforts. Tissue samples at pathology departments are routinely stored as formalin-fixed and paraffin-embedded (FFPE samples and their use would open up access to a variety of clinical trials. However, FFPE preparation is incompatible with many down-stream molecular biology techniques such as PCR based amplification methods and gene expression studies. METHODOLOGY/PRINCIPAL FINDINGS: Here we investigated the sample quality requirements of FFPE tissues for massively parallel short-read sequencing approaches. We evaluated key variables of pre-fixation, fixation related and post-fixation processes that occur in routine medical service (e.g. degree of autolysis, duration of fixation and of storage. We also investigated the influence of tissue storage time on sequencing quality by using material that was up to 18 years old. Finally, we analyzed normal and tumor breast tissues using the Sequencing by Synthesis technique (Illumina Genome Analyzer, Solexa to simultaneously localize genome-wide copy number alterations and to detect genomic variations such as substitutions and point-deletions and/or insertions in FFPE tissue samples. CONCLUSIONS/SIGNIFICANCE: The application of second generation sequencing techniques on small amounts of FFPE material opens up the possibility to analyze tissue samples which have been collected during routine clinical work as well as in the context of clinical trials. This is in particular important since FFPE samples are amply available from surgical tumor resections and histopathological diagnosis, and comprise tissue from precursor lesions, primary tumors, lymphogenic and/or hematogenic metastases. Large-scale studies using this tissue material will result in a better prediction of the prognosis of cancer patients and the early identification of patients which

  12. Using Multiple Big Datasets and Machine Learning to Produce a New Global Particulate Dataset: A Technology Challenge Case Study

    Science.gov (United States)

    Lary, D. J.

    2013-12-01

    A BigData case study is described where multiple datasets from several satellites, high-resolution global meteorological data, social media and in-situ observations are combined using machine learning on a distributed cluster using an automated workflow. The global particulate dataset is relevant to global public health studies and would not be possible to produce without the use of the multiple big datasets, in-situ data and machine learning.To greatly reduce the development time and enhance the functionality a high level language capable of parallel processing has been used (Matlab). A key consideration for the system is high speed access due to the large data volume, persistence of the large data volumes and a precise process time scheduling capability.

  13. Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China

    International Nuclear Information System (INIS)

    Sun, Qiaohong; Miao, Chiyuan; Duan, Qingyun; Kong, Dongxian; Ye, Aizhong; Di, Zhenhua; Gong, Wei

    2014-01-01

    This research compared and evaluated the spatio-temporal similarities and differences of eight widely used gridded datasets. The datasets include daily precipitation over East Asia (EA), the Climate Research Unit (CRU) product, the Global Precipitation Climatology Centre (GPCC) product, the University of Delaware (UDEL) product, Precipitation Reconstruction over Land (PREC/L), the Asian Precipitation Highly Resolved Observational (APHRO) product, the Institute of Atmospheric Physics (IAP) dataset from the Chinese Academy of Sciences, and the National Meteorological Information Center dataset from the China Meteorological Administration (CN05). The meteorological variables focus on surface air temperature (SAT) or precipitation (PR) in China. All datasets presented general agreement on the whole spatio-temporal scale, but some differences appeared for specific periods and regions. On a temporal scale, EA shows the highest amount of PR, while APHRO shows the lowest. CRU and UDEL show higher SAT than IAP or CN05. On a spatial scale, the most significant differences occur in western China for PR and SAT. For PR, the difference between EA and CRU is the largest. When compared with CN05, CRU shows higher SAT in the central and southern Northwest river drainage basin, UDEL exhibits higher SAT over the Southwest river drainage system, and IAP has lower SAT in the Tibetan Plateau. The differences in annual mean PR and SAT primarily come from summer and winter, respectively. Finally, potential factors impacting agreement among gridded climate datasets are discussed, including raw data sources, quality control (QC) schemes, orographic correction, and interpolation techniques. The implications and challenges of these results for climate research are also briefly addressed. (paper)

  14. Shotgun protein sequencing.

    Energy Technology Data Exchange (ETDEWEB)

    Faulon, Jean-Loup Michel; Heffelfinger, Grant S.

    2009-06-01

    A novel experimental and computational technique based on multiple enzymatic digestion of a protein or protein mixture that reconstructs protein sequences from sequences of overlapping peptides is described in this SAND report. This approach, analogous to shotgun sequencing of DNA, is to be used to sequence alternative spliced proteins, to identify post-translational modifications, and to sequence genetically engineered proteins.

  15. Using Real Datasets for Interdisciplinary Business/Economics Projects

    Science.gov (United States)

    Goel, Rajni; Straight, Ronald L.

    2005-01-01

    The workplace's global and dynamic nature allows and requires improved approaches for providing business and economics education. In this article, the authors explore ways of enhancing students' understanding of course material by using nontraditional, real-world datasets of particular interest to them. Teaching at a historically Black university,…

  16. Dataset-driven research for improving recommender systems for learning

    NARCIS (Netherlands)

    Verbert, Katrien; Drachsler, Hendrik; Manouselis, Nikos; Wolpers, Martin; Vuorikari, Riina; Duval, Erik

    2011-01-01

    Verbert, K., Drachsler, H., Manouselis, N., Wolpers, M., Vuorikari, R., & Duval, E. (2011). Dataset-driven research for improving recommender systems for learning. In Ph. Long, & G. Siemens (Eds.), Proceedings of 1st International Conference Learning Analytics & Knowledge (pp. 44-53). February,

  17. dataTEL - Datasets for Technology Enhanced Learning

    NARCIS (Netherlands)

    Drachsler, Hendrik; Verbert, Katrien; Sicilia, Miguel-Angel; Wolpers, Martin; Manouselis, Nikos; Vuorikari, Riina; Lindstaedt, Stefanie; Fischer, Frank

    2011-01-01

    Drachsler, H., Verbert, K., Sicilia, M. A., Wolpers, M., Manouselis, N., Vuorikari, R., Lindstaedt, S., & Fischer, F. (2011). dataTEL - Datasets for Technology Enhanced Learning. STELLAR Alpine Rendez-Vous White Paper. Alpine Rendez-Vous 2011 White paper collection, Nr. 13., France (2011)

  18. A dataset of forest biomass structure for Eurasia.

    Science.gov (United States)

    Schepaschenko, Dmitry; Shvidenko, Anatoly; Usoltsev, Vladimir; Lakyda, Petro; Luo, Yunjian; Vasylyshyn, Roman; Lakyda, Ivan; Myklush, Yuriy; See, Linda; McCallum, Ian; Fritz, Steffen; Kraxner, Florian; Obersteiner, Michael

    2017-05-16

    The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above- and below ground); green forest floor (above- and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930-2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.

  19. A reanalysis dataset of the South China Sea

    Science.gov (United States)

    Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

    2014-01-01

    Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992–2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability. PMID:25977803

  20. Comparision of analysis of the QTLMAS XII common dataset

    DEFF Research Database (Denmark)

    Crooks, Lucy; Sahana, Goutam; de Koning, Dirk-Jan

    2009-01-01

    As part of the QTLMAS XII workshop, a simulated dataset was distributed and participants were invited to submit analyses of the data based on genome-wide association, fine mapping and genomic selection. We have evaluated the findings from the groups that reported fine mapping and genome-wide asso...

  1. The LAMBADA dataset: Word prediction requiring a broad discourse context

    NARCIS (Netherlands)

    Paperno, D.; Kruszewski, G.; Lazaridou, A.; Pham, Q.N.; Bernardi, R.; Pezzelle, S.; Baroni, M.; Boleda, G.; Fernández, R.; Erk, K.; Smith, N.A.

    2016-01-01

    We introduce LAMBADA, a dataset to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative passages sharing the characteristic that human subjects are able to guess their last word if they are exposed to the

  2. NEW WEB-BASED ACCESS TO NUCLEAR STRUCTURE DATASETS.

    Energy Technology Data Exchange (ETDEWEB)

    WINCHELL,D.F.

    2004-09-26

    As part of an effort to migrate the National Nuclear Data Center (NNDC) databases to a relational platform, a new web interface has been developed for the dissemination of the nuclear structure datasets stored in the Evaluated Nuclear Structure Data File and Experimental Unevaluated Nuclear Data List.

  3. Cross-Cultural Concept Mapping of Standardized Datasets

    DEFF Research Database (Denmark)

    Kano Glückstad, Fumiko

    2012-01-01

    This work compares four feature-based similarity measures derived from cognitive sciences. The purpose of the comparative analysis is to verify the potentially most effective model that can be applied for mapping independent ontologies in a culturally influenced domain [1]. Here, datasets based...

  4. Level-1 muon trigger performance with the full 2017 dataset

    CERN Document Server

    CMS Collaboration

    2018-01-01

    This document describes the performance of the CMS Level-1 Muon Trigger with the full dataset of 2017. Efficiency plots are included for each track finder (TF) individually and for the system as a whole. The efficiency is measured to be greater than 90% for all track finders.

  5. A Dataset for Visual Navigation with Neuromorphic Methods

    Directory of Open Access Journals (Sweden)

    Francisco eBarranco

    2016-02-01

    Full Text Available Standardized benchmarks in Computer Vision have greatly contributed to the advance of approaches to many problems in the field. If we want to enhance the visibility of event-driven vision and increase its impact, we will need benchmarks that allow comparison among different neuromorphic methods as well as comparison to Computer Vision conventional approaches. We present datasets to evaluate the accuracy of frame-free and frame-based approaches for tasks of visual navigation. Similar to conventional Computer Vision datasets, we provide synthetic and real scenes, with the synthetic data created with graphics packages, and the real data recorded using a mobile robotic platform carrying a dynamic and active pixel vision sensor (DAVIS and an RGB+Depth sensor. For both datasets the cameras move with a rigid motion in a static scene, and the data includes the images, events, optic flow, 3D camera motion, and the depth of the scene, along with calibration procedures. Finally, we also provide simulated event data generated synthetically from well-known frame-based optical flow datasets.

  6. Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

    Science.gov (United States)

    Besha, A. A.; Steele, C. M.; Fernald, A.

    2014-12-01

    Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

  7. Dataset: Multi Sensor-Orientation Movement Data of Goats

    NARCIS (Netherlands)

    Kamminga, Jacob Wilhelm

    2018-01-01

    This is a labeled dataset. Motion data were collected from six sensor nodes that were fixed with different orientations to a collar around the neck of goats. These six sensor nodes simultaneously, with different orientations, recorded various activities performed by the goat. We recorded the

  8. A dataset of human decision-making in teamwork management

    Science.gov (United States)

    Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang

    2017-01-01

    Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.

  9. UK surveillance: provision of quality assured information from combined datasets.

    Science.gov (United States)

    Paiba, G A; Roberts, S R; Houston, C W; Williams, E C; Smith, L H; Gibbens, J C; Holdship, S; Lysons, R

    2007-09-14

    Surveillance information is most useful when provided within a risk framework, which is achieved by presenting results against an appropriate denominator. Often the datasets are captured separately and for different purposes, and will have inherent errors and biases that can be further confounded by the act of merging. The United Kingdom Rapid Analysis and Detection of Animal-related Risks (RADAR) system contains data from several sources and provides both data extracts for research purposes and reports for wider stakeholders. Considerable efforts are made to optimise the data in RADAR during the Extraction, Transformation and Loading (ETL) process. Despite efforts to ensure data quality, the final dataset inevitably contains some data errors and biases, most of which cannot be rectified during subsequent analysis. So, in order for users to establish the 'fitness for purpose' of data merged from more than one data source, Quality Statements are produced as defined within the overarching surveillance Quality Framework. These documents detail identified data errors and biases following ETL and report construction as well as relevant aspects of the datasets from which the data originated. This paper illustrates these issues using RADAR datasets, and describes how they can be minimised.

  10. participatory development of a minimum dataset for the khayelitsha ...

    African Journals Online (AJOL)

    This dataset was integrated with data requirements at ... model for defining health information needs at district level. This participatory process has enabled health workers to appraise their .... of reproductive health, mental health, disability and community ... each chose a facilitator and met in between the forum meetings.

  11. Comparision of analysis of the QTLMAS XII common dataset

    DEFF Research Database (Denmark)

    Lund, Mogens Sandø; Sahana, Goutam; de Koning, Dirk-Jan

    2009-01-01

    A dataset was simulated and distributed to participants of the QTLMAS XII workshop who were invited to develop genomic selection models. Each contributing group was asked to describe the model development and validation as well as to submit genomic predictions for three generations of individuals...

  12. The NASA Subsonic Jet Particle Image Velocimetry (PIV) Dataset

    Science.gov (United States)

    Bridges, James; Wernet, Mark P.

    2011-01-01

    Many tasks in fluids engineering require prediction of turbulence of jet flows. The present document documents the single-point statistics of velocity, mean and variance, of cold and hot jet flows. The jet velocities ranged from 0.5 to 1.4 times the ambient speed of sound, and temperatures ranged from unheated to static temperature ratio 2.7. Further, the report assesses the accuracies of the data, e.g., establish uncertainties for the data. This paper covers the following five tasks: (1) Document acquisition and processing procedures used to create the particle image velocimetry (PIV) datasets. (2) Compare PIV data with hotwire and laser Doppler velocimetry (LDV) data published in the open literature. (3) Compare different datasets acquired at the same flow conditions in multiple tests to establish uncertainties. (4) Create a consensus dataset for a range of hot jet flows, including uncertainty bands. (5) Analyze this consensus dataset for self-consistency and compare jet characteristics to those of the open literature. The final objective was fulfilled by using the potential core length and the spread rate of the half-velocity radius to collapse of the mean and turbulent velocity fields over the first 20 jet diameters.

  13. A new dataset validation system for the Planetary Science Archive

    Science.gov (United States)

    Manaud, N.; Zender, J.; Heather, D.; Martinez, S.

    2007-08-01

    The Planetary Science Archive is the official archive for the Mars Express mission. It has received its first data by the end of 2004. These data are delivered by the PI teams to the PSA team as datasets, which are formatted conform to the Planetary Data System (PDS). The PI teams are responsible for analyzing and calibrating the instrument data as well as the production of reduced and calibrated data. They are also responsible of the scientific validation of these data. ESA is responsible of the long-term data archiving and distribution to the scientific community and must ensure, in this regard, that all archived products meet quality. To do so, an archive peer-review is used to control the quality of the Mars Express science data archiving process. However a full validation of its content is missing. An independent review board recently recommended that the completeness of the archive as well as the consistency of the delivered data should be validated following well-defined procedures. A new validation software tool is being developed to complete the overall data quality control system functionality. This new tool aims to improve the quality of data and services provided to the scientific community through the PSA, and shall allow to track anomalies in and to control the completeness of datasets. It shall ensure that the PSA end-users: (1) can rely on the result of their queries, (2) will get data products that are suitable for scientific analysis, (3) can find all science data acquired during a mission. We defined dataset validation as the verification and assessment process to check the dataset content against pre-defined top-level criteria, which represent the general characteristics of good quality datasets. The dataset content that is checked includes the data and all types of information that are essential in the process of deriving scientific results and those interfacing with the PSA database. The validation software tool is a multi-mission tool that

  14. Data Recommender: An Alternative Way to Discover Open Scientific Datasets

    Science.gov (United States)

    Klump, J. F.; Devaraju, A.; Williams, G.; Hogan, D.; Davy, R.; Page, J.; Singh, D.; Peterson, N.

    2017-12-01

    Over the past few years, institutions and government agencies have adopted policies to openly release their data, which has resulted in huge amounts of open data becoming available on the web. When trying to discover the data, users face two challenges: an overload of choice and the limitations of the existing data search tools. On the one hand, there are too many datasets to choose from, and therefore, users need to spend considerable effort to find the datasets most relevant to their research. On the other hand, data portals commonly offer keyword and faceted search, which depend fully on the user queries to search and rank relevant datasets. Consequently, keyword and faceted search may return loosely related or irrelevant results, although the results may contain the same query. They may also return highly specific results that depend more on how well metadata was authored. They do not account well for variance in metadata due to variance in author styles and preferences. The top-ranked results may also come from the same data collection, and users are unlikely to discover new and interesting datasets. These search modes mainly suits users who can express their information needs in terms of the structure and terminology of the data portals, but may pose a challenge otherwise. The above challenges reflect that we need a solution that delivers the most relevant (i.e., similar and serendipitous) datasets to users, beyond the existing search functionalities on the portals. A recommender system is an information filtering system that presents users with relevant and interesting contents based on users' context and preferences. Delivering data recommendations to users can make data discovery easier, and as a result may enhance user engagement with the portal. We developed a hybrid data recommendation approach for the CSIRO Data Access Portal. The approach leverages existing recommendation techniques (e.g., content-based filtering and item co-occurrence) to produce

  15. Comparison of global 3-D aviation emissions datasets

    Directory of Open Access Journals (Sweden)

    S. C. Olsen

    2013-01-01

    Full Text Available Aviation emissions are unique from other transportation emissions, e.g., from road transportation and shipping, in that they occur at higher altitudes as well as at the surface. Aviation emissions of carbon dioxide, soot, and water vapor have direct radiative impacts on the Earth's climate system while emissions of nitrogen oxides (NOx, sulfur oxides, carbon monoxide (CO, and hydrocarbons (HC impact air quality and climate through their effects on ozone, methane, and clouds. The most accurate estimates of the impact of aviation on air quality and climate utilize three-dimensional chemistry-climate models and gridded four dimensional (space and time aviation emissions datasets. We compare five available aviation emissions datasets currently and historically used to evaluate the impact of aviation on climate and air quality: NASA-Boeing 1992, NASA-Boeing 1999, QUANTIFY 2000, Aero2k 2002, and AEDT 2006 and aviation fuel usage estimates from the International Energy Agency. Roughly 90% of all aviation emissions are in the Northern Hemisphere and nearly 60% of all fuelburn and NOx emissions occur at cruise altitudes in the Northern Hemisphere. While these datasets were created by independent methods and are thus not strictly suitable for analyzing trends they suggest that commercial aviation fuelburn and NOx emissions increased over the last two decades while HC emissions likely decreased and CO emissions did not change significantly. The bottom-up estimates compared here are consistently lower than International Energy Agency fuelburn statistics although the gap is significantly smaller in the more recent datasets. Overall the emissions distributions are quite similar for fuelburn and NOx with regional peaks over the populated land masses of North America, Europe, and East Asia. For CO and HC there are relatively larger differences. There are however some distinct differences in the altitude distribution

  16. On sample size and different interpretations of snow stability datasets

    Science.gov (United States)

    Schirmer, M.; Mitterer, C.; Schweizer, J.

    2009-04-01

    Interpretations of snow stability variations need an assessment of the stability itself, independent of the scale investigated in the study. Studies on stability variations at a regional scale have often chosen stability tests such as the Rutschblock test or combinations of various tests in order to detect differences in aspect and elevation. The question arose: ‘how capable are such stability interpretations in drawing conclusions'. There are at least three possible errors sources: (i) the variance of the stability test itself; (ii) the stability variance at an underlying slope scale, and (iii) that the stability interpretation might not be directly related to the probability of skier triggering. Various stability interpretations have been proposed in the past that provide partly different results. We compared a subjective one based on expert knowledge with a more objective one based on a measure derived from comparing skier-triggered slopes vs. slopes that have been skied but not triggered. In this study, the uncertainties are discussed and their effects on regional scale stability variations will be quantified in a pragmatic way. An existing dataset with very large sample sizes was revisited. This dataset contained the variance of stability at a regional scale for several situations. The stability in this dataset was determined using the subjective interpretation scheme based on expert knowledge. The question to be answered was how many measurements were needed to obtain similar results (mainly stability differences in aspect or elevation) as with the complete dataset. The optimal sample size was obtained in several ways: (i) assuming a nominal data scale the sample size was determined with a given test, significance level and power, and by calculating the mean and standard deviation of the complete dataset. With this method it can also be determined if the complete dataset consists of an appropriate sample size. (ii) Smaller subsets were created with similar

  17. Multimodal sequence learning.

    Science.gov (United States)

    Kemény, Ferenc; Meier, Beat

    2016-02-01

    While sequence learning research models complex phenomena, previous studies have mostly focused on unimodal sequences. The goal of the current experiment is to put implicit sequence learning into a multimodal context: to test whether it can operate across different modalities. We used the Task Sequence Learning paradigm to test whether sequence learning varies across modalities, and whether participants are able to learn multimodal sequences. Our results show that implicit sequence learning is very similar regardless of the source modality. However, the presence of correlated task and response sequences was required for learning to take place. The experiment provides new evidence for implicit sequence learning of abstract conceptual representations. In general, the results suggest that correlated sequences are necessary for implicit sequence learning to occur. Moreover, they show that elements from different modalities can be automatically integrated into one unitary multimodal sequence. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. Sequence Read Archive (SRA)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Sequence Read Archive (SRA) stores raw sequencing data from the next generation of sequencing platforms including Roche 454 GS System®, Illumina Genome...

  19. Orthology detection combining clustering and synteny for very large datasets

    OpenAIRE

    Lechner, Marcus; Hernandez-Rosales, Maribel; Doerr, Daniel; Wieseke, Nicolas; Thévenin, Annelyse; Stoye, Jens; Hartmann, Roland K.; Prohaska, Sonja J.; Stadler, Peter F.

    2014-01-01

    The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the ...

  20. Integrated mRNA and microRNA transcriptome sequencing characterizes sequence variants and mRNA–microRNA regulatory network in nasopharyngeal carcinoma model systems

    Directory of Open Access Journals (Sweden)

    Carol Ying-Ying Szeto

    2014-01-01

    Full Text Available Nasopharyngeal carcinoma (NPC is a prevalent malignancy in Southeast Asia among the Chinese population. Aberrant regulation of transcripts has been implicated in many types of cancers including NPC. Herein, we characterized mRNA and miRNA transcriptomes by RNA sequencing (RNASeq of NPC model systems. Matched total mRNA and small RNA of undifferentiated Epstein–Barr virus (EBV-positive NPC xenograft X666 and its derived cell line C666, well-differentiated NPC cell line HK1, and the immortalized nasopharyngeal epithelial cell line NP460 were sequenced by Solexa technology. We found 2812 genes and 149 miRNAs (human and EBV to be differentially expressed in NP460, HK1, C666 and X666 with RNASeq; 533 miRNA–mRNA target pairs were inversely regulated in the three NPC cell lines compared to NP460. Integrated mRNA/miRNA expression profiling and pathway analysis show extracellular matrix organization, Beta-1 integrin cell surface interactions, and the PI3K/AKT, EGFR, ErbB, and Wnt pathways were potentially deregulated in NPC. Real-time quantitative PCR was performed on selected mRNA/miRNAs in order to validate their expression. Transcript sequence variants such as short insertions and deletions (INDEL, single nucleotide variant (SNV, and isomiRs were characterized in the NPC model systems. A novel TP53 transcript variant was identified in NP460, HK1, and C666. Detection of three previously reported novel EBV-encoded BART miRNAs and their isomiRs were also observed. Meta-analysis of a model system to a clinical system aids the choice of different cell lines in NPC studies. This comprehensive characterization of mRNA and miRNA transcriptomes in NPC cell lines and the xenograft provides insights on miRNA regulation of mRNA and valuable resources on transcript variation and regulation in NPC, which are potentially useful for mechanistic and preclinical studies.

  1. High-Throughput Sequencing Reveals Hypothalamic MicroRNAs as Novel Partners Involved in Timing the Rapid Development of Chicken (Gallus gallus) Gonads.

    Science.gov (United States)

    Han, Wei; Zou, Jianmin; Wang, Kehua; Su, Yijun; Zhu, Yunfen; Song, Chi; Li, Guohui; Qu, Liang; Zhang, Huiyong; Liu, Honglin

    2015-01-01

    Onset of the rapid gonad growth is a milestone in sexual development that comprises many genes and regulatory factors. The observations in model organisms and mammals including humans have shown a potential link between miRNAs and development timing. To determine whether miRNAs play roles in this process in the chicken (Gallus gallus), the Solexa deep sequencing was performed to analyze the profiles of miRNA expression in the hypothalamus of hens from two different pubertal stages, before onset of the rapid gonad development (BO) and after onset of the rapid gonad development (AO). 374 conserved and 46 novel miRNAs were identified as hypothalamus-expressed miRNAs in the chicken. 144 conserved miRNAs were showed to be differentially expressed (reads > 10, P time quantitative RT-PCR (qRT-PCR) method. 2013 putative genes were predicted as the targets of the 15 most differentially expressed miRNAs (fold-change > 4.0, P times by the miRNAs. qRT-PCR revealed the basic transcription levels of these clock genes were much higher (P development of chicken gonads. Considering the characteristics of miRNA functional conservation, the results will contribute to the research on puberty onset in humans.

  2. MicroRNA and piRNA profiles in normal human testis detected by next generation sequencing.

    Directory of Open Access Journals (Sweden)

    Qingling Yang

    Full Text Available BACKGROUND: MicroRNAs (miRNAs are the class of small endogenous RNAs that play an important regulatory role in cells by negatively affecting gene expression at transcriptional and post-transcriptional levels. There have been extensive studies aiming to discover miRNAs and to analyze their functions in the cells from a variety of species. However, there are no published studies of miRNA profiles in human testis using next generation sequencing (NGS technology. RESULTS: We employed Solexa sequencing technology to profile miRNAs in normal human testis. Total 770 known and 5 novel human miRNAs, and 20121 piRNAs were detected, indicating that the human testis has a complex population of small RNAs. The expression of 15 known and 5 novel detected miRNAs was validated by qRT-PCR. We have also predicted the potential target genes of the abundant known and novel miRNAs, and subjected them to GO and pathway analysis, revealing the involvement of miRNAs in many important biological phenomenon including meiosis and p53-related pathways that are implicated in the regulation of spermatogenesis. CONCLUSIONS: This study reports the first genome-wide miRNA profiles in human testis using a NGS approach. The presence of large number of miRNAs and the nature of their target genes suggested that miRNAs play important roles in spermatogenesis. Here we provide a useful resource for further elucidation of the regulatory role of miRNAs and piRNAs in the spermatogenesis. It may also facilitate the development of prophylactic strategies for male infertility.

  3. Next-generation sequencing-based transcriptome analysis of Helicoverpa armigera Larvae immune-primed with Photorhabdus luminescens TT01.

    Directory of Open Access Journals (Sweden)

    Zengyang Zhao

    Full Text Available Although invertebrates are incapable of adaptive immunity, immunal reactions which are functionally similar to the adaptive immunity of vertebrates have been described in many studies of invertebrates including insects. The phenomenon was termed immune priming. In order to understand the molecular mechanism of immune priming, we employed Illumina/Solexa platform to investigate the transcriptional changes of the hemocytes and fat body of Helicoverpa armigera larvae immune-primed with the pathogenic bacteria Photorhabdus luminescens TT01. A total of 43.6 and 65.1 million clean reads with 4.4 and 6.5 gigabase sequence data were obtained from the TT01 (the immune-primed and PBS (non-primed cDNA libraries and assembled into 35,707 all-unigenes (non-redundant transcripts, which has a length varied from 201 to 16,947 bp and a N50 length of 1,997 bp. For 35,707 all-unigenes, 20,438 were functionally annotated and 2,494 were differentially expressed after immune priming. The differentially expressed genes (DEGs are mainly related to immunity, detoxification, development and metabolism of the host insect. Analysis on the annotated immune related DEGs supported a hypothesis that we proposed previously: the immune priming phenomenon observed in H. armigera larvae was achieved by regulation of key innate immune elements. The transcriptome profiling data sets (especially the sequences of 1,022 unannotated DEGs and the clues (such as those on immune-related signal and regulatory pathways obtained from this study will facilitate immune-related novel gene discovery and provide valuable information for further exploring the molecular mechanism of immune priming of invertebrates. All these will increase our understanding of invertebrate immunity which may provide new approaches to control insect pests or prevent epidemic of infectious diseases in economic invertebrates in the future.

  4. Identification and Characterization of MicroRNAs in Small Brown Planthopper (Laodephax striatellus) by Next-Generation Sequencing

    Science.gov (United States)

    Lou, Yonggen; Cheng, Jia'an; Zhang, Hengmu; Xu, Jian-Hong

    2014-01-01

    MicroRNAs (miRNAs) are endogenous non-coding small RNAs that regulate gene expression at the post-transcriptional level and are thought to play critical roles in many metabolic activities in eukaryotes. The small brown planthopper (Laodephax striatellus Fallén), one of the most destructive agricultural pests, causes great damage to crops including rice, wheat, and maize. However, information about the genome of L. striatellus is limited. In this study, a small RNA library was constructed from a mixed L. striatellus population and sequenced by Solexa sequencing technology. A total of 501 mature miRNAs were identified, including 227 conserved and 274 novel miRNAs belonging to 125 and 250 families, respectively. Sixty-nine conserved miRNAs that are included in 38 families are predicted to have an RNA secondary structure typically found in miRNAs. Many miRNAs were validated by stem-loop RT-PCR. Comparison with the miRNAs in 84 animal species from miRBase showed that the conserved miRNA families we identified are highly conserved in the Arthropoda phylum. Furthermore, miRanda predicted 2701 target genes for 378 miRNAs, which could be categorized into 52 functional groups annotated by gene ontology. The function of miRNA target genes was found to be very similar between conserved and novel miRNAs. This study of miRNAs in L. striatellus will provide new information and enhance the understanding of the role of miRNAs in the regulation of L. striatellus metabolism and development. PMID:25057821

  5. Identification and characterization of microRNAs in small brown planthopper (Laodephax striatellus by next-generation sequencing.

    Directory of Open Access Journals (Sweden)

    Guoyan Zhou

    Full Text Available MicroRNAs (miRNAs are endogenous non-coding small RNAs that regulate gene expression at the post-transcriptional level and are thought to play critical roles in many metabolic activities in eukaryotes. The small brown planthopper (Laodephax striatellus Fallén, one of the most destructive agricultural pests, causes great damage to crops including rice, wheat, and maize. However, information about the genome of L. striatellus is limited. In this study, a small RNA library was constructed from a mixed L. striatellus population and sequenced by Solexa sequencing technology. A total of 501 mature miRNAs were identified, including 227 conserved and 274 novel miRNAs belonging to 125 and 250 families, respectively. Sixty-nine conserved miRNAs that are included in 38 families are predicted to have an RNA secondary structure typically found in miRNAs. Many miRNAs were validated by stem-loop RT-PCR. Comparison with the miRNAs in 84 animal species from miRBase showed that the conserved miRNA families we identified are highly conserved in the Arthropoda phylum. Furthermore, miRanda predicted 2701 target genes for 378 miRNAs, which could be categorized into 52 functional groups annotated by gene ontology. The function of miRNA target genes was found to be very similar between conserved and novel miRNAs. This study of miRNAs in L. striatellus will provide new information and enhance the understanding of the role of miRNAs in the regulation of L. striatellus metabolism and development.

  6. Complete genome sequence of the fire blight pathogen Erwinia pyrifoliae DSM 12163T and comparative genomic insights into plant pathogenicity

    Directory of Open Access Journals (Sweden)

    Frey Jürg E

    2010-01-01

    Full Text Available Abstract Background Erwinia pyrifoliae is a newly described necrotrophic pathogen, which causes fire blight on Asian (Nashi pear and is geographically restricted to Eastern Asia. Relatively little is known about its genetics compared to the closely related main fire blight pathogen E. amylovora. Results The genome of the type strain of E. pyrifoliae strain DSM 12163T, was sequenced using both 454 and Solexa pyrosequencing and annotated. The genome contains a circular chromosome of 4.026 Mb and four small plasmids. Based on their respective role in virulence in E. amylovora or related organisms, we identified several putative virulence factors, including type III and type VI secretion systems and their effectors, flagellar genes, sorbitol metabolism, iron uptake determinants, and quorum-sensing components. A deletion in the rpoS gene covering the most conserved region of the protein was identified which may contribute to the difference in virulence/host-range compared to E. amylovora. Comparative genomics with the pome fruit epiphyte Erwinia tasmaniensis Et1/99 showed that both species are overall highly similar, although specific differences were identified, for example the presence of some phage gene-containing regions and a high number of putative genomic islands containing transposases in the E. pyrifoliae DSM 12163T genome. Conclusions The E. pyrifoliae genome is an important addition to the published genome of E. tasmaniensis and the unfinished genome of E. amylovora providing a foundation for re-sequencing additional strains that may shed light on the evolution of the host-range and virulence/pathogenicity of this important group of plant-associated bacteria.

  7. A re-analysis of the Lake Suigetsu terrestrial radiocarbon calibration dataset

    International Nuclear Information System (INIS)

    Staff, R.A.; Bronk Ramsey, C.; Nakagawa, T.

    2010-01-01

    Lake Suigetsu, Honshu Island, Japan provides an ideal sedimentary sequence from which to derive a wholly terrestrial radiocarbon calibration curve back to the limits of radiocarbon detection (circa 60 ka bp). The presence of well-defined, annually-deposited laminae (varves) throughout the entirety of this period provides an independent, high resolution chronometer against which radiocarbon measurements of plant macrofossils from the sediment column can be directly related. However, data from the initial Lake Suigetsu project were found to diverge significantly from alternative, marine-based calibration datasets released around the same time (e.g. ). The main source of this divergence is thought to be the result of inaccuracies in the absolute age profile of the Suigetsu project, caused by both varve counting uncertainties and gaps in the sediment column of unknown duration between successively-drilled core sections. Here, a re-analysis of the previously-published Lake Suigetsu data is conducted. The most recent developments in Bayesian statistical modelling techniques (OxCal v4.1; ) are implemented to fit the Suigetsu data to the latest radiocarbon calibration datasets and thereby estimate the duration of the inter-core section gaps in the Suigetsu data. In this way, the absolute age of the Lake Suigetsu sediment profile is more accurately defined, providing significant information for both radiocarbon calibration and palaeoenvironmental reconstruction purposes.

  8. Systems genetics of complex diseases using RNA-sequencing methods

    DEFF Research Database (Denmark)

    Mazzoni, Gianluca; Kogelman, Lisette; Suravajhala, Prashanth

    2015-01-01

    Next generation sequencing technologies have enabled the generation of huge quantities of biological data, and nowadays extensive datasets at different ‘omics levels have been generated. Systems genetics is a powerful approach that allows to integrate different ‘omics level and understand the bio...

  9. A multimodal MRI dataset of professional chess players.

    Science.gov (United States)

    Li, Kaiming; Jiang, Jing; Qiu, Lihua; Yang, Xun; Huang, Xiaoqi; Lui, Su; Gong, Qiyong

    2015-01-01

    Chess is a good model to study high-level human brain functions such as spatial cognition, memory, planning, learning and problem solving. Recent studies have demonstrated that non-invasive MRI techniques are valuable for researchers to investigate the underlying neural mechanism of playing chess. For professional chess players (e.g., chess grand masters and masters or GM/Ms), what are the structural and functional alterations due to long-term professional practice, and how these alterations relate to behavior, are largely veiled. Here, we report a multimodal MRI dataset from 29 professional Chinese chess players (most of whom are GM/Ms), and 29 age matched novices. We hope that this dataset will provide researchers with new materials to further explore high-level human brain functions.

  10. Knowledge discovery with classification rules in a cardiovascular dataset.

    Science.gov (United States)

    Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

    2005-12-01

    In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

  11. Augmented Reality Prototype for Visualizing Large Sensors’ Datasets

    Directory of Open Access Journals (Sweden)

    Folorunso Olufemi A.

    2011-04-01

    Full Text Available This paper addressed the development of an augmented reality (AR based scientific visualization system prototype that supports identification, localisation, and 3D visualisation of oil leakages sensors datasets. Sensors generates significant amount of multivariate datasets during normal and leak situations which made data exploration and visualisation daunting tasks. Therefore a model to manage such data and enhance computational support needed for effective explorations are developed in this paper. A challenge of this approach is to reduce the data inefficiency. This paper presented a model for computing information gain for each data attributes and determine a lead attribute.The computed lead attribute is then used for the development of an AR-based scientific visualization interface which automatically identifies, localises and visualizes all necessary data relevant to a particularly selected region of interest (ROI on the network. Necessary architectural system supports and the interface requirements for such visualizations are also presented.

  12. An integrated dataset for in silico drug discovery

    Directory of Open Access Journals (Sweden)

    Cockell Simon J

    2010-12-01

    Full Text Available Drug development is expensive and prone to failure. It is potentially much less risky and expensive to reuse a drug developed for one condition for treating a second disease, than it is to develop an entirely new compound. Systematic approaches to drug repositioning are needed to increase throughput and find candidates more reliably. Here we address this need with an integrated systems biology dataset, developed using the Ondex data integration platform, for the in silico discovery of new drug repositioning candidates. We demonstrate that the information in this dataset allows known repositioning examples to be discovered. We also propose a means of automating the search for new treatment indications of existing compounds.

  13. Application of Density Estimation Methods to Datasets from a Glider

    Science.gov (United States)

    2014-09-30

    humpback and sperm whales as well as different dolphin species. OBJECTIVES The objective of this research is to extend existing methods for cetacean...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...estimation from single sensor datasets. Required steps for a cue counting approach, where a cue has been defined as a clicking event (Küsel et al., 2011), to

  14. A review of continent scale hydrological datasets available for Africa

    OpenAIRE

    Bonsor, H.C.

    2010-01-01

    As rainfall becomes less reliable with predicted climate change the ability to assess the spatial and seasonal variations in groundwater availability on a large-scale (catchment and continent) is becoming increasingly important (Bates, et al. 2007; MacDonald et al. 2009). The scarcity of observed hydrological data, or difficulty in obtaining such data, within Africa means remotely sensed (RS) datasets must often be used to drive large-scale hydrological models. The different ap...

  15. GLEAM version 3: Global Land Evaporation Datasets and Model

    Science.gov (United States)

    Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.

    2015-12-01

    Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ

  16. Soil chemistry in lithologically diverse datasets: the quartz dilution effect

    Science.gov (United States)

    Bern, Carleton R.

    2009-01-01

    National- and continental-scale soil geochemical datasets are likely to move our understanding of broad soil geochemistry patterns forward significantly. Patterns of chemistry and mineralogy delineated from these datasets are strongly influenced by the composition of the soil parent material, which itself is largely a function of lithology and particle size sorting. Such controls present a challenge by obscuring subtler patterns arising from subsequent pedogenic processes. Here the effect of quartz concentration is examined in moist-climate soils from a pilot dataset of the North American Soil Geochemical Landscapes Project. Due to variable and high quartz contents (6.2–81.7 wt.%), and its residual and inert nature in soil, quartz is demonstrated to influence broad patterns in soil chemistry. A dilution effect is observed whereby concentrations of various elements are significantly and strongly negatively correlated with quartz. Quartz content drives artificial positive correlations between concentrations of some elements and obscures negative correlations between others. Unadjusted soil data show the highly mobile base cations Ca, Mg, and Na to be often strongly positively correlated with intermediately mobile Al or Fe, and generally uncorrelated with the relatively immobile high-field-strength elements (HFS) Ti and Nb. Both patterns are contrary to broad expectations for soils being weathered and leached. After transforming bulk soil chemistry to a quartz-free basis, the base cations are generally uncorrelated with Al and Fe, and negative correlations generally emerge with the HFS elements. Quartz-free element data may be a useful tool for elucidating patterns of weathering or parent-material chemistry in large soil datasets.

  17. Dataset on records of Hericium erinaceus in Slovakia

    OpenAIRE

    Vladimír Kunca; Marek Čiliak

    2017-01-01

    The data presented in this article are related to the research article entitled ?Habitat preferences of Hericium erinaceus in Slovakia? (Kunca and ?iliak, 2016) [FUNECO607] [2]. The dataset include all available and unpublished data from Slovakia, besides the records from the same tree or stem. We compiled a database of records of collections by processing data from herbaria, personal records and communication with mycological activists. Data on altitude, tree species, host tree vital status,...

  18. Diffeomorphic Iterative Centroid Methods for Template Estimation on Large Datasets

    OpenAIRE

    Cury , Claire; Glaunès , Joan Alexis; Colliot , Olivier

    2014-01-01

    International audience; A common approach for analysis of anatomical variability relies on the stimation of a template representative of the population. The Large Deformation Diffeomorphic Metric Mapping is an attractive framework for that purpose. However, template estimation using LDDMM is computationally expensive, which is a limitation for the study of large datasets. This paper presents an iterative method which quickly provides a centroid of the population in the shape space. This centr...

  19. A Dataset from TIMSS to Examine the Relationship between Computer Use and Mathematics Achievement

    Science.gov (United States)

    Kadijevich, Djordje M.

    2015-01-01

    Because the relationship between computer use and achievement is still puzzling, there is a need to prepare and analyze good quality datasets on computer use and achievement. Such a dataset can be derived from TIMSS data. This paper describes how this dataset can be prepared. It also gives an example of how the dataset may be analyzed. The…

  20. An Analysis on Better Testing than Training Performances on the Iris Dataset

    NARCIS (Netherlands)

    Schutten, Marten; Wiering, Marco

    2016-01-01

    The Iris dataset is a well known dataset containing information on three different types of Iris flowers. A typical and popular method for solving classification problems on datasets such as the Iris set is the support vector machine (SVM). In order to do so the dataset is separated in a set used

  1. Identification of optimum sequencing depth especially for de novo genome assembly of small genomes using next generation sequencing data.

    Science.gov (United States)

    Desai, Aarti; Marwah, Veer Singh; Yadav, Akshay; Jha, Vineet; Dhaygude, Kishor; Bangar, Ujwala; Kulkarni, Vivek; Jere, Abhay

    2013-01-01

    Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6-40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.

  2. Parton Distributions based on a Maximally Consistent Dataset

    Science.gov (United States)

    Rojo, Juan

    2016-04-01

    The choice of data that enters a global QCD analysis can have a substantial impact on the resulting parton distributions and their predictions for collider observables. One of the main reasons for this has to do with the possible presence of inconsistencies, either internal within an experiment or external between different experiments. In order to assess the robustness of the global fit, different definitions of a conservative PDF set, that is, a PDF set based on a maximally consistent dataset, have been introduced. However, these approaches are typically affected by theory biases in the selection of the dataset. In this contribution, after a brief overview of recent NNPDF developments, we propose a new, fully objective, definition of a conservative PDF set, based on the Bayesian reweighting approach. Using the new NNPDF3.0 framework, we produce various conservative sets, which turn out to be mutually in agreement within the respective PDF uncertainties, as well as with the global fit. We explore some of their implications for LHC phenomenology, finding also good consistency with the global fit result. These results provide a non-trivial validation test of the new NNPDF3.0 fitting methodology, and indicate that possible inconsistencies in the fitted dataset do not affect substantially the global fit PDFs.

  3. New public dataset for spotting patterns in medieval document images

    Science.gov (United States)

    En, Sovann; Nicolas, Stéphane; Petitjean, Caroline; Jurie, Frédéric; Heutte, Laurent

    2017-01-01

    With advances in technology, a large part of our cultural heritage is becoming digitally available. In particular, in the field of historical document image analysis, there is now a growing need for indexing and data mining tools, thus allowing us to spot and retrieve the occurrences of an object of interest, called a pattern, in a large database of document images. Patterns may present some variability in terms of color, shape, or context, making the spotting of patterns a challenging task. Pattern spotting is a relatively new field of research, still hampered by the lack of available annotated resources. We present a new publicly available dataset named DocExplore dedicated to spotting patterns in historical document images. The dataset contains 1500 images and 1464 queries, and allows the evaluation of two tasks: image retrieval and pattern localization. A standardized benchmark protocol along with ad hoc metrics is provided for a fair comparison of the submitted approaches. We also provide some first results obtained with our baseline system on this new dataset, which show that there is room for improvement and that should encourage researchers of the document image analysis community to design new systems and submit improved results.

  4. Kernel-based discriminant feature extraction using a representative dataset

    Science.gov (United States)

    Li, Honglin; Sancho Gomez, Jose-Luis; Ahalt, Stanley C.

    2002-07-01

    Discriminant Feature Extraction (DFE) is widely recognized as an important pre-processing step in classification applications. Most DFE algorithms are linear and thus can only explore the linear discriminant information among the different classes. Recently, there has been several promising attempts to develop nonlinear DFE algorithms, among which is Kernel-based Feature Extraction (KFE). The efficacy of KFE has been experimentally verified by both synthetic data and real problems. However, KFE has some known limitations. First, KFE does not work well for strongly overlapped data. Second, KFE employs all of the training set samples during the feature extraction phase, which can result in significant computation when applied to very large datasets. Finally, KFE can result in overfitting. In this paper, we propose a substantial improvement to KFE that overcomes the above limitations by using a representative dataset, which consists of critical points that are generated from data-editing techniques and centroid points that are determined by using the Frequency Sensitive Competitive Learning (FSCL) algorithm. Experiments show that this new KFE algorithm performs well on significantly overlapped datasets, and it also reduces computational complexity. Further, by controlling the number of centroids, the overfitting problem can be effectively alleviated.

  5. Decoys Selection in Benchmarking Datasets: Overview and Perspectives

    Science.gov (United States)

    Réau, Manon; Langenfeld, Florent; Zagury, Jean-François; Lagarde, Nathalie; Montes, Matthieu

    2018-01-01

    Virtual Screening (VS) is designed to prospectively help identifying potential hits, i.e., compounds capable of interacting with a given target and potentially modulate its activity, out of large compound collections. Among the variety of methodologies, it is crucial to select the protocol that is the most adapted to the query/target system under study and that yields the most reliable output. To this aim, the performance of VS methods is commonly evaluated and compared by computing their ability to retrieve active compounds in benchmarking datasets. The benchmarking datasets contain a subset of known active compounds together with a subset of decoys, i.e., assumed non-active molecules. The composition of both the active and the decoy compounds subsets is critical to limit the biases in the evaluation of the VS methods. In this review, we focus on the selection of decoy compounds that has considerably changed over the years, from randomly selected compounds to highly customized or experimentally validated negative compounds. We first outline the evolution of decoys selection in benchmarking databases as well as current benchmarking databases that tend to minimize the introduction of biases, and secondly, we propose recommendations for the selection and the design of benchmarking datasets. PMID:29416509

  6. ENHANCED DATA DISCOVERABILITY FOR IN SITU HYPERSPECTRAL DATASETS

    Directory of Open Access Journals (Sweden)

    B. Rasaiah

    2016-06-01

    Full Text Available Field spectroscopic metadata is a central component in the quality assurance, reliability, and discoverability of hyperspectral data and the products derived from it. Cataloguing, mining, and interoperability of these datasets rely upon the robustness of metadata protocols for field spectroscopy, and on the software architecture to support the exchange of these datasets. Currently no standard for in situ spectroscopy data or metadata protocols exist. This inhibits the effective sharing of growing volumes of in situ spectroscopy datasets, to exploit the benefits of integrating with the evolving range of data sharing platforms. A core metadataset for field spectroscopy was introduced by Rasaiah et al., (2011-2015 with extended support for specific applications. This paper presents a prototype model for an OGC and ISO compliant platform-independent metadata discovery service aligned to the specific requirements of field spectroscopy. In this study, a proof-of-concept metadata catalogue has been described and deployed in a cloud-based architecture as a demonstration of an operationalized field spectroscopy metadata standard and web-based discovery service.

  7. Multiresolution persistent homology for excessively large biomolecular datasets

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Kelin; Zhao, Zhixiong [Department of Mathematics, Michigan State University, East Lansing, Michigan 48824 (United States); Wei, Guo-Wei, E-mail: wei@math.msu.edu [Department of Mathematics, Michigan State University, East Lansing, Michigan 48824 (United States); Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824 (United States); Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824 (United States)

    2015-10-07

    Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topological analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs.

  8. Tissue-Based MRI Intensity Standardization: Application to Multicentric Datasets

    Directory of Open Access Journals (Sweden)

    Nicolas Robitaille

    2012-01-01

    Full Text Available Intensity standardization in MRI aims at correcting scanner-dependent intensity variations. Existing simple and robust techniques aim at matching the input image histogram onto a standard, while we think that standardization should aim at matching spatially corresponding tissue intensities. In this study, we present a novel automatic technique, called STI for STandardization of Intensities, which not only shares the simplicity and robustness of histogram-matching techniques, but also incorporates tissue spatial intensity information. STI uses joint intensity histograms to determine intensity correspondence in each tissue between the input and standard images. We compared STI to an existing histogram-matching technique on two multicentric datasets, Pilot E-ADNI and ADNI, by measuring the intensity error with respect to the standard image after performing nonlinear registration. The Pilot E-ADNI dataset consisted in 3 subjects each scanned in 7 different sites. The ADNI dataset consisted in 795 subjects scanned in more than 50 different sites. STI was superior to the histogram-matching technique, showing significantly better intensity matching for the brain white matter with respect to the standard image.

  9. Exploring massive, genome scale datasets with the genometricorr package

    KAUST Repository

    Favorov, Alexander; Mularoni, Loris; Cope, Leslie M.; Medvedeva, Yulia; Mironov, Andrey A.; Makeev, Vsevolod J.; Wheelan, Sarah J.

    2012-01-01

    We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.

  10. Image segmentation evaluation for very-large datasets

    Science.gov (United States)

    Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

    2016-03-01

    With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

  11. Exploring massive, genome scale datasets with the genometricorr package

    KAUST Repository

    Favorov, Alexander

    2012-05-31

    We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.

  12. Principal Component Analysis of Process Datasets with Missing Values

    Directory of Open Access Journals (Sweden)

    Kristen A. Severson

    2017-07-01

    Full Text Available Datasets with missing values arising from causes such as sensor failure, inconsistent sampling rates, and merging data from different systems are common in the process industry. Methods for handling missing data typically operate during data pre-processing, but can also occur during model building. This article considers missing data within the context of principal component analysis (PCA, which is a method originally developed for complete data that has widespread industrial application in multivariate statistical process control. Due to the prevalence of missing data and the success of PCA for handling complete data, several PCA algorithms that can act on incomplete data have been proposed. Here, algorithms for applying PCA to datasets with missing values are reviewed. A case study is presented to demonstrate the performance of the algorithms and suggestions are made with respect to choosing which algorithm is most appropriate for particular settings. An alternating algorithm based on the singular value decomposition achieved the best results in the majority of test cases involving process datasets.

  13. A cross-country Exchange Market Pressure (EMP dataset

    Directory of Open Access Journals (Sweden)

    Mohit Desai

    2017-06-01

    Full Text Available The data presented in this article are related to the research article titled - “An exchange market pressure measure for cross country analysis” (Patnaik et al. [1]. In this article, we present the dataset for Exchange Market Pressure values (EMP for 139 countries along with their conversion factors, ρ (rho. Exchange Market Pressure, expressed in percentage change in exchange rate, measures the change in exchange rate that would have taken place had the central bank not intervened. The conversion factor ρ can interpreted as the change in exchange rate associated with $1 billion of intervention. Estimates of conversion factor ρ allow us to calculate a monthly time series of EMP for 139 countries. Additionally, the dataset contains the 68% confidence interval (high and low values for the point estimates of ρ’s. Using the standard errors of estimates of ρ’s, we obtain one sigma intervals around mean estimates of EMP values. These values are also reported in the dataset.

  14. The Role of Datasets on Scientific Influence within Conflict Research

    Science.gov (United States)

    Van Holt, Tracy; Johnson, Jeffery C.; Moates, Shiloh; Carley, Kathleen M.

    2016-01-01

    We inductively tested if a coherent field of inquiry in human conflict research emerged in an analysis of published research involving “conflict” in the Web of Science (WoS) over a 66-year period (1945–2011). We created a citation network that linked the 62,504 WoS records and their cited literature. We performed a critical path analysis (CPA), a specialized social network analysis on this citation network (~1.5 million works), to highlight the main contributions in conflict research and to test if research on conflict has in fact evolved to represent a coherent field of inquiry. Out of this vast dataset, 49 academic works were highlighted by the CPA suggesting a coherent field of inquiry; which means that researchers in the field acknowledge seminal contributions and share a common knowledge base. Other conflict concepts that were also analyzed—such as interpersonal conflict or conflict among pharmaceuticals, for example, did not form their own CP. A single path formed, meaning that there was a cohesive set of ideas that built upon previous research. This is in contrast to a main path analysis of conflict from 1957–1971 where ideas didn’t persist in that multiple paths existed and died or emerged reflecting lack of scientific coherence (Carley, Hummon, and Harty, 1993). The critical path consisted of a number of key features: 1) Concepts that built throughout include the notion that resource availability drives conflict, which emerged in the 1960s-1990s and continued on until 2011. More recent intrastate studies that focused on inequalities emerged from interstate studies on the democracy of peace earlier on the path. 2) Recent research on the path focused on forecasting conflict, which depends on well-developed metrics and theories to model. 3) We used keyword analysis to independently show how the CP was topically linked (i.e., through democracy, modeling, resources, and geography). Publically available conflict datasets developed early on helped

  15. The Role of Datasets on Scientific Influence within Conflict Research.

    Directory of Open Access Journals (Sweden)

    Tracy Van Holt

    Full Text Available We inductively tested if a coherent field of inquiry in human conflict research emerged in an analysis of published research involving "conflict" in the Web of Science (WoS over a 66-year period (1945-2011. We created a citation network that linked the 62,504 WoS records and their cited literature. We performed a critical path analysis (CPA, a specialized social network analysis on this citation network (~1.5 million works, to highlight the main contributions in conflict research and to test if research on conflict has in fact evolved to represent a coherent field of inquiry. Out of this vast dataset, 49 academic works were highlighted by the CPA suggesting a coherent field of inquiry; which means that researchers in the field acknowledge seminal contributions and share a common knowledge base. Other conflict concepts that were also analyzed-such as interpersonal conflict or conflict among pharmaceuticals, for example, did not form their own CP. A single path formed, meaning that there was a cohesive set of ideas that built upon previous research. This is in contrast to a main path analysis of conflict from 1957-1971 where ideas didn't persist in that multiple paths existed and died or emerged reflecting lack of scientific coherence (Carley, Hummon, and Harty, 1993. The critical path consisted of a number of key features: 1 Concepts that built throughout include the notion that resource availability drives conflict, which emerged in the 1960s-1990s and continued on until 2011. More recent intrastate studies that focused on inequalities emerged from interstate studies on the democracy of peace earlier on the path. 2 Recent research on the path focused on forecasting conflict, which depends on well-developed metrics and theories to model. 3 We used keyword analysis to independently show how the CP was topically linked (i.e., through democracy, modeling, resources, and geography. Publically available conflict datasets developed early on helped

  16. The Role of Datasets on Scientific Influence within Conflict Research.

    Science.gov (United States)

    Van Holt, Tracy; Johnson, Jeffery C; Moates, Shiloh; Carley, Kathleen M

    2016-01-01

    We inductively tested if a coherent field of inquiry in human conflict research emerged in an analysis of published research involving "conflict" in the Web of Science (WoS) over a 66-year period (1945-2011). We created a citation network that linked the 62,504 WoS records and their cited literature. We performed a critical path analysis (CPA), a specialized social network analysis on this citation network (~1.5 million works), to highlight the main contributions in conflict research and to test if research on conflict has in fact evolved to represent a coherent field of inquiry. Out of this vast dataset, 49 academic works were highlighted by the CPA suggesting a coherent field of inquiry; which means that researchers in the field acknowledge seminal contributions and share a common knowledge base. Other conflict concepts that were also analyzed-such as interpersonal conflict or conflict among pharmaceuticals, for example, did not form their own CP. A single path formed, meaning that there was a cohesive set of ideas that built upon previous research. This is in contrast to a main path analysis of conflict from 1957-1971 where ideas didn't persist in that multiple paths existed and died or emerged reflecting lack of scientific coherence (Carley, Hummon, and Harty, 1993). The critical path consisted of a number of key features: 1) Concepts that built throughout include the notion that resource availability drives conflict, which emerged in the 1960s-1990s and continued on until 2011. More recent intrastate studies that focused on inequalities emerged from interstate studies on the democracy of peace earlier on the path. 2) Recent research on the path focused on forecasting conflict, which depends on well-developed metrics and theories to model. 3) We used keyword analysis to independently show how the CP was topically linked (i.e., through democracy, modeling, resources, and geography). Publically available conflict datasets developed early on helped shape the

  17. Sequence determinants of human microsatellite variability

    Directory of Open Access Journals (Sweden)

    Jakobsson Mattias

    2009-12-01

    Full Text Available Abstract Background Microsatellite loci are frequently used in genomic studies of DNA sequence repeats and in population studies of genetic variability. To investigate the effect of sequence properties of microsatellites on their level of variability we have analyzed genotypes at 627 microsatellite loci in 1,048 worldwide individuals from the HGDP-CEPH cell line panel together with the DNA sequences of these microsatellites in the human RefSeq database. Results Calibrating PCR fragment lengths in individual genotypes by using the RefSeq sequence enabled us to infer repeat number in the HGDP-CEPH dataset and to calculate the mean number of repeats (as opposed to the mean PCR fragment length, under the assumption that differences in PCR fragment length reflect differences in the numbers of repeats in the embedded repeat sequences. We find the mean and maximum numbers of repeats across individuals to be positively correlated with heterozygosity. The size and composition of the repeat unit of a microsatellite are also important factors in predicting heterozygosity, with tetra-nucleotide repeat units high in G/C content leading to higher heterozygosity. Finally, we find that microsatellites containing more separate sets of repeated motifs generally have higher heterozygosity. Conclusions These results suggest that sequence properties of microsatellites have a significant impact in determining the features of human microsatellite variability.

  18. Inaugural Genomics Automation Congress and the coming deluge of sequencing data.

    Science.gov (United States)

    Creighton, Chad J

    2010-10-01

    Presentations at Select Biosciences's first 'Genomics Automation Congress' (Boston, MA, USA) in 2010 focused on next-generation sequencing and the platforms and methodology around them. The meeting provided an overview of sequencing technologies, both new and emerging. Speakers shared their recent work on applying sequencing to profile cells for various levels of biomolecular complexity, including DNA sequences, DNA copy, DNA methylation, mRNA and microRNA. With sequencing time and costs continuing to drop dramatically, a virtual explosion of very large sequencing datasets is at hand, which will probably present challenges and opportunities for high-level data analysis and interpretation, as well as for information technology infrastructure.

  19. Experimental evolution, genetic analysis and genome re-sequencing reveal the mutation conferring artemisinin resistance in an isogenic lineage of malaria parasites

    KAUST Repository

    Hunt, Paul

    2010-09-16

    Background: Classical and quantitative linkage analyses of genetic crosses have traditionally been used to map genes of interest, such as those conferring chloroquine or quinine resistance in malaria parasites. Next-generation sequencing technologies now present the possibility of determining genome-wide genetic variation at single base-pair resolution. Here, we combine in vivo experimental evolution, a rapid genetic strategy and whole genome re-sequencing to identify the precise genetic basis of artemisinin resistance in a lineage of the rodent malaria parasite, Plasmodium chabaudi. Such genetic markers will further the investigation of resistance and its control in natural infections of the human malaria, P. falciparum.Results: A lineage of isogenic in vivo drug-selected mutant P. chabaudi parasites was investigated. By measuring the artemisinin responses of these clones, the appearance of an in vivo artemisinin resistance phenotype within the lineage was defined. The underlying genetic locus was mapped to a region of chromosome 2 by Linkage Group Selection in two different genetic crosses. Whole-genome deep coverage short-read re-sequencing (IlluminaSolexa) defined the point mutations, insertions, deletions and copy-number variations arising in the lineage. Eight point mutations arise within the mutant lineage, only one of which appears on chromosome 2. This missense mutation arises contemporaneously with artemisinin resistance and maps to a gene encoding a de-ubiquitinating enzyme.Conclusions: This integrated approach facilitates the rapid identification of mutations conferring selectable phenotypes, without prior knowledge of biological and molecular mechanisms. For malaria, this model can identify candidate genes before resistant parasites are commonly observed in natural human malaria populations. 2010 Hunt et al; licensee BioMed Central Ltd.

  20. Deep sequencing-based transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus reveals insight into the immune-relevant genes in marine fish

    Directory of Open Access Journals (Sweden)

    Xiang Li-xin

    2010-08-01

    Full Text Available Abstract Background Systematic research on fish immunogenetics is indispensable in understanding the origin and evolution of immune systems. This has long been a challenging task because of the limited number of deep sequencing technologies and genome backgrounds of non-model fish available. The newly developed Solexa/Illumina RNA-seq and Digital gene expression (DGE are high-throughput sequencing approaches and are powerful tools for genomic studies at the transcriptome level. This study reports the transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus using RNA-seq and DGE in an attempt to gain insights into the immunogenetics of marine fish. Results RNA-seq analysis generated 169,950 non-redundant consensus sequences, among which 48,987 functional transcripts with complete or various length encoding regions were identified. More than 52% of these transcripts are possibly involved in approximately 219 known metabolic or signalling pathways, while 2,673 transcripts were associated with immune-relevant genes. In addition, approximately 8% of the transcripts appeared to be fish-specific genes that have never been described before. DGE analysis revealed that the host transcriptome profile of Vibrio harveyi-challenged L. japonicus is considerably altered, as indicated by the significant up- or down-regulation of 1,224 strong infection-responsive transcripts. Results indicated an overall conservation of the components and transcriptome alterations underlying innate and adaptive immunity in fish and other vertebrate models. Analysis suggested the acquisition of numerous fish-specific immune system components during early vertebrate evolution. Conclusion This study provided a global survey of host defence gene activities against bacterial challenge in a non-model marine fish. Results can contribute to the in-depth study of candidate genes in marine fish immunity, and help improve current understanding of host

  1. Nonparametric combinatorial sequence models.

    Science.gov (United States)

    Wauthier, Fabian L; Jordan, Michael I; Jojic, Nebojsa

    2011-11-01

    This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This article presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three biological sequence families which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution over sequence representations induced by the prior. By integrating out the posterior, our method compares favorably to leading binding predictors.

  2. Skeleton-based human action recognition using multiple sequence alignment

    Science.gov (United States)

    Ding, Wenwen; Liu, Kai; Cheng, Fei; Zhang, Jin; Li, YunSong

    2015-05-01

    Human action recognition and analysis is an active research topic in computer vision for many years. This paper presents a method to represent human actions based on trajectories consisting of 3D joint positions. This method first decompose action into a sequence of meaningful atomic actions (actionlets), and then label actionlets with English alphabets according to the Davies-Bouldin index value. Therefore, an action can be represented using a sequence of actionlet symbols, which will preserve the temporal order of occurrence of each of the actionlets. Finally, we employ sequence comparison to classify multiple actions through using string matching algorithms (Needleman-Wunsch). The effectiveness of the proposed method is evaluated on datasets captured by commodity depth cameras. Experiments of the proposed method on three challenging 3D action datasets show promising results.

  3. RUCS: Rapid identification of PCR primers for unique core sequences

    DEFF Research Database (Denmark)

    Thomsen, Martin Christen Frølund; Hasman, Henrik; Westh, Henrik

    2017-01-01

    Designing PCR primers to target a specific selection of whole genome sequenced strains can be a long, arduous, and sometimes impractical task. Such tasks would benefit greatly from an automated tool to both identify unique targets, and to validate the vast number of potential primer pairs...... for the targets in silico . Here we present RUCS, a program that will find PCR primer pairs and probes for the unique core sequences of a positive genome dataset complement to a negative genome dataset. The resulting primer pairs and probes are in addition to simple selection also validated through a complex...... in silico PCR simulation. We compared our method, which identifies the unique core sequences, against an existing tool called ssGeneFinder, and found that our method was 6.5-20 times more sensitive. We used RUCS to design primer pairs that would target a set of genomes known to contain the mcr-1 colistin...

  4. Characterising fire hazard from temporal sequences of thermal infrared modis measurements

    NARCIS (Netherlands)

    Maffei, C.; Alfieri, S.M.; Menenti, M.

    2012-01-01

    The objective of the present research was the characterisation of fire hazard using temporal sequences of land surface temperature (LST) derived from Terra-MODIS measurements. The investigation was based on a complete sequence of MODIS LST data from 2000 to 2006 on Campania (Italy) and on a dataset

  5. Flexible taxonomic assignment of ambiguous sequencing reads

    Directory of Open Access Journals (Sweden)

    Jansson Jesper

    2011-01-01

    Full Text Available Abstract Background To characterize the diversity of bacterial populations in metagenomic studies, sequencing reads need to be accurately assigned to taxonomic units in a given reference taxonomy. Reads that cannot be reliably assigned to a unique leaf in the taxonomy (ambiguous reads are typically assigned to the lowest common ancestor of the set of species that match it. This introduces a potentially severe error in the estimation of bacteria present in the sample due to false positives, since all species in the subtree rooted at the ancestor are implicitly assigned to the read even though many of them may not match it. Results We present a method that maps each read to a node in the taxonomy that minimizes a penalty score while balancing the relevance of precision and recall in the assignment through a parameter q. This mapping can be obtained in time linear in the number of matching sequences, because LCA queries to the reference taxonomy take constant time. When applied to six different metagenomic datasets, our algorithm produces different taxonomic distributions depending on whether coverage or precision is maximized. Including information on the quality of the reads reduces the number of unassigned reads but increases the number of ambiguous reads, stressing the relevance of our method. Finally, two measures of performance are described and results with a set of artificially generated datasets are discussed. Conclusions The assignment strategy of sequencing reads introduced in this paper is a versatile and a quick method to study bacterial communities. The bacterial composition of the analyzed samples can vary significantly depending on how ambiguous reads are assigned depending on the value of the q parameter. Validation of our results in an artificial dataset confirm that a combination of values of q produces the most accurate results.

  6. Animated analysis of geoscientific datasets: An interactive graphical application

    Science.gov (United States)

    Morse, Peter; Reading, Anya; Lueg, Christopher

    2017-12-01

    Geoscientists are required to analyze and draw conclusions from increasingly large volumes of data. There is a need to recognise and characterise features and changing patterns of Earth observables within such large datasets. It is also necessary to identify significant subsets of the data for more detailed analysis. We present an innovative, interactive software tool and workflow to visualise, characterise, sample and tag large geoscientific datasets from both local and cloud-based repositories. It uses an animated interface and human-computer interaction to utilise the capacity of human expert observers to identify features via enhanced visual analytics. 'Tagger' enables users to analyze datasets that are too large in volume to be drawn legibly on a reasonable number of single static plots. Users interact with the moving graphical display, tagging data ranges of interest for subsequent attention. The tool provides a rapid pre-pass process using fast GPU-based OpenGL graphics and data-handling and is coded in the Quartz Composer visual programing language (VPL) on Mac OSX. It makes use of interoperable data formats, and cloud-based (or local) data storage and compute. In a case study, Tagger was used to characterise a decade (2000-2009) of data recorded by the Cape Sorell Waverider Buoy, located approximately 10 km off the west coast of Tasmania, Australia. These data serve as a proxy for the understanding of Southern Ocean storminess, which has both local and global implications. This example shows use of the tool to identify and characterise 4 different types of storm and non-storm events during this time. Events characterised in this way are compared with conventional analysis, noting advantages and limitations of data analysis using animation and human interaction. Tagger provides a new ability to make use of humans as feature detectors in computer-based analysis of large-volume geosciences and other data.

  7. Designing the colorectal cancer core dataset in Iran

    Directory of Open Access Journals (Sweden)

    Sara Dorri

    2017-01-01

    Full Text Available Background: There is no need to explain the importance of collection, recording and analyzing the information of disease in any health organization. In this regard, systematic design of standard data sets can be helpful to record uniform and consistent information. It can create interoperability between health care systems. The main purpose of this study was design the core dataset to record colorectal cancer information in Iran. Methods: For the design of the colorectal cancer core data set, a combination of literature review and expert consensus were used. In the first phase, the draft of the data set was designed based on colorectal cancer literature review and comparative studies. Then, in the second phase, this data set was evaluated by experts from different discipline such as medical informatics, oncology and surgery. Their comments and opinion were taken. In the third phase refined data set, was evaluated again by experts and eventually data set was proposed. Results: In first phase, based on the literature review, a draft set of 85 data elements was designed. In the second phase this data set was evaluated by experts and supplementary information was offered by professionals in subgroups especially in treatment part. In this phase the number of elements totally were arrived to 93 numbers. In the third phase, evaluation was conducted by experts and finally this dataset was designed in five main parts including: demographic information, diagnostic information, treatment information, clinical status assessment information, and clinical trial information. Conclusion: In this study the comprehensive core data set of colorectal cancer was designed. This dataset in the field of collecting colorectal cancer information can be useful through facilitating exchange of health information. Designing such data set for similar disease can help providers to collect standard data from patients and can accelerate retrieval from storage systems.

  8. FTSPlot: fast time series visualization for large datasets.

    Directory of Open Access Journals (Sweden)

    Michael Riss

    Full Text Available The analysis of electrophysiological recordings often involves visual inspection of time series data to locate specific experiment epochs, mask artifacts, and verify the results of signal processing steps, such as filtering or spike detection. Long-term experiments with continuous data acquisition generate large amounts of data. Rapid browsing through these massive datasets poses a challenge to conventional data plotting software because the plotting time increases proportionately to the increase in the volume of data. This paper presents FTSPlot, which is a visualization concept for large-scale time series datasets using techniques from the field of high performance computer graphics, such as hierarchic level of detail and out-of-core data handling. In a preprocessing step, time series data, event, and interval annotations are converted into an optimized data format, which then permits fast, interactive visualization. The preprocessing step has a computational complexity of O(n x log(N; the visualization itself can be done with a complexity of O(1 and is therefore independent of the amount of data. A demonstration prototype has been implemented and benchmarks show that the technology is capable of displaying large amounts of time series data, event, and interval annotations lag-free with < 20 ms ms. The current 64-bit implementation theoretically supports datasets with up to 2(64 bytes, on the x86_64 architecture currently up to 2(48 bytes are supported, and benchmarks have been conducted with 2(40 bytes/1 TiB or 1.3 x 10(11 double precision samples. The presented software is freely available and can be included as a Qt GUI component in future software projects, providing a standard visualization method for long-term electrophysiological experiments.

  9. A synthetic dataset for evaluating soft and hard fusion algorithms

    Science.gov (United States)

    Graham, Jacob L.; Hall, David L.; Rimland, Jeffrey

    2011-06-01

    There is an emerging demand for the development of data fusion techniques and algorithms that are capable of combining conventional "hard" sensor inputs such as video, radar, and multispectral sensor data with "soft" data including textual situation reports, open-source web information, and "hard/soft" data such as image or video data that includes human-generated annotations. New techniques that assist in sense-making over a wide range of vastly heterogeneous sources are critical to improving tactical situational awareness in counterinsurgency (COIN) and other asymmetric warfare situations. A major challenge in this area is the lack of realistic datasets available for test and evaluation of such algorithms. While "soft" message sets exist, they tend to be of limited use for data fusion applications due to the lack of critical message pedigree and other metadata. They also lack corresponding hard sensor data that presents reasonable "fusion opportunities" to evaluate the ability to make connections and inferences that span the soft and hard data sets. This paper outlines the design methodologies, content, and some potential use cases of a COIN-based synthetic soft and hard dataset created under a United States Multi-disciplinary University Research Initiative (MURI) program funded by the U.S. Army Research Office (ARO). The dataset includes realistic synthetic reports from a variety of sources, corresponding synthetic hard data, and an extensive supporting database that maintains "ground truth" through logical grouping of related data into "vignettes." The supporting database also maintains the pedigree of messages and other critical metadata.

  10. Identifying frauds and anomalies in Medicare-B dataset.

    Science.gov (United States)

    Jiwon Seo; Mendelevitch, Ofer

    2017-07-01

    Healthcare industry is growing at a rapid rate to reach a market value of $7 trillion dollars world wide. At the same time, fraud in healthcare is becoming a serious problem, amounting to 5% of the total healthcare spending, or $100 billion dollars each year in US. Manually detecting healthcare fraud requires much effort. Recently, machine learning and data mining techniques are applied to automatically detect healthcare frauds. This paper proposes a novel PageRank-based algorithm to detect healthcare frauds and anomalies. We apply the algorithm to Medicare-B dataset, a real-life data with 10 million healthcare insurance claims. The algorithm successfully identifies tens of previously unreported anomalies.

  11. Power analysis dataset for QCA based multiplexer circuits

    Directory of Open Access Journals (Sweden)

    Md. Abdullah-Al-Shafi

    2017-04-01

    Full Text Available Power consumption in irreversible QCA logic circuits is a vital and a major issue; however in the practical cases, this focus is mostly omitted.The complete power depletion dataset of different QCA multiplexers have been worked out in this paper. At −271.15 °C temperature, the depletion is evaluated under three separate tunneling energy levels. All the circuits are designed with QCADesigner, a broadly used simulation engine and QCAPro tool has been applied for estimating the power dissipation.

  12. Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers

    Directory of Open Access Journals (Sweden)

    AnaM. Palacios

    2012-04-01

    Full Text Available Determining whether an imprecise dataset is imbalanced is not immediate. The vagueness in the data causes that the prior probabilities of the classes are not precisely known, and therefore the degree of imbalance can also be uncertain. In this paper we propose suitable extensions of different resampling algorithms that can be applied to interval valued, multi-labelled data. By means of these extended preprocessing algorithms, certain classification systems designed for minimizing the fraction of misclassifications are able to produce knowledge bases that are also adequate under common metrics for imbalanced classification.

  13. Scientific Datasets: Discovery and Aggregation for Semantic Interpretation.

    Science.gov (United States)

    Lopez, L. A.; Scott, S.; Khalsa, S. J. S.; Duerr, R.

    2015-12-01

    One of the biggest challenges that interdisciplinary researchers face is finding suitable datasets in order to advance their science; this problem remains consistent across multiple disciplines. A surprising number of scientists, when asked what tool they use for data discovery, reply "Google", which is an acceptable solution in some cases but not even Google can find -or cares to compile- all the data that's relevant for science and particularly geo sciences. If a dataset is not discoverable through a well known search provider it will remain dark data to the scientific world.For the past year, BCube, an EarthCube Building Block project, has been developing, testing and deploying a technology stack capable of data discovery at web-scale using the ultimate dataset: The Internet. This stack has 2 principal components, a web-scale crawling infrastructure and a semantic aggregator. The web-crawler is a modified version of Apache Nutch (the originator of Hadoop and other big data technologies) that has been improved and tailored for data and data service discovery. The second component is semantic aggregation, carried out by a python-based workflow that extracts valuable metadata and stores it in the form of triples through the use semantic technologies.While implementing the BCube stack we have run into several challenges such as a) scaling the project to cover big portions of the Internet at a reasonable cost, b) making sense of very diverse and non-homogeneous data, and lastly, c) extracting facts about these datasets using semantic technologies in order to make them usable for the geosciences community. Despite all these challenges we have proven that we can discover and characterize data that otherwise would have remained in the dark corners of the Internet. Having all this data indexed and 'triplelized' will enable scientists to access a trove of information relevant to their work in a more natural way. An important characteristic of the BCube stack is that all

  14. Dataset concerning the analytical approximation of the Ae3 temperature

    Directory of Open Access Journals (Sweden)

    B.L. Ennis

    2017-02-01

    The dataset includes the terms of the function and the values for the polynomial coefficients for major alloying elements in steel. A short description of the approximation method used to derive and validate the coefficients has also been included. For discussion and application of this model, please refer to the full length article entitled “The role of aluminium in chemical and phase segregation in a TRIP-assisted dual phase steel” 10.1016/j.actamat.2016.05.046 (Ennis et al., 2016 [1].

  15. Gene set analysis of the EADGENE chicken data-set

    DEFF Research Database (Denmark)

    Skarman, Axel; Jiang, Li; Hornshøj, Henrik

    2009-01-01

     Abstract Background: Gene set analysis is considered to be a way of improving our biological interpretation of the observed expression patterns. This paper describes different methods applied to analyse expression data from a chicken DNA microarray dataset. Results: Applying different gene set...... analyses to the chicken expression data led to different ranking of the Gene Ontology terms tested. A method for prediction of possible annotations was applied. Conclusion: Biological interpretation based on gene set analyses dependent on the statistical method used. Methods for predicting the possible...

  16. A Validation Dataset for CryoSat Sea Ice Investigators

    DEFF Research Database (Denmark)

    Julia, Gaudelli,; Baker, Steve; Haas, Christian

    Since its launch in April 2010 Cryosat has been collecting valuable sea ice data over the Arctic region. Over the same period ESA’s CryoVEx and NASA IceBridge validation campaigns have been collecting a unique set of coincident airborne measurements in the Arctic. The CryoVal-SI project has...... community. In this talk we will describe the composition of the validation dataset, summarising how it was processed and how to understand the content and format of the data. We will also explain how to access the data and the supporting documentation....

  17. Dataset of statements on policy integration of selected intergovernmental organizations

    Directory of Open Access Journals (Sweden)

    Jale Tosun

    2018-04-01

    Full Text Available This article describes data for 78 intergovernmental organizations (IGOs working on topics related to energy governance, environmental protection, and the economy. The number of IGOs covered also includes organizations active in other sectors. The point of departure for data construction was the Correlates of War dataset, from which we selected this sample of IGOs. We updated and expanded the empirical information on the IGOs selected by manual coding. Most importantly, we collected the primary law texts of the individual IGOs in order to code whether they commit themselves to environmental policy integration (EPI, climate policy integration (CPI and/or energy policy integration (EnPI.

  18. Dataset on the energy performance of atrium type hotel buildings.

    Science.gov (United States)

    Vujosevic, Milica; Krstic-Furundzic, Aleksandra

    2018-04-01

    The data presented in this article are related to the research article entitled "The Influence of Atrium on Energy Performance of Hotel Building" (Vujosevic and Krstic-Furundzic, 2017) [1], which describes the annual energy performance of atrium type hotel building in Belgrade climate conditions, with the objective to present the impact of the atrium on the hotel building's energy demands for space heating and cooling. This dataset is made publicly available to show energy performance of selected hotel design alternatives, in order to enable extended analyzes of these data for other researchers.

  19. Dataset on records of Hericium erinaceus in Slovakia.

    Science.gov (United States)

    Kunca, Vladimír; Čiliak, Marek

    2017-06-01

    The data presented in this article are related to the research article entitled "Habitat preferences of Hericium erinaceus in Slovakia" (Kunca and Čiliak, 2016) [FUNECO607] [2]. The dataset include all available and unpublished data from Slovakia, besides the records from the same tree or stem. We compiled a database of records of collections by processing data from herbaria, personal records and communication with mycological activists. Data on altitude, tree species, host tree vital status, host tree position and intensity of management of forest stands were evaluated in this study. All surveys were based on basidioma occurrence and some result from targeted searches.

  20. Dataset on records of Hericium erinaceus in Slovakia

    Directory of Open Access Journals (Sweden)

    Vladimír Kunca

    2017-06-01

    Full Text Available The data presented in this article are related to the research article entitled “Habitat preferences of Hericium erinaceus in Slovakia” (Kunca and Čiliak, 2016 [FUNECO607] [2]. The dataset include all available and unpublished data from Slovakia, besides the records from the same tree or stem. We compiled a database of records of collections by processing data from herbaria, personal records and communication with mycological activists. Data on altitude, tree species, host tree vital status, host tree position and intensity of management of forest stands were evaluated in this study. All surveys were based on basidioma occurrence and some result from targeted searches.

  1. The Transcriptome Analysis and Comparison Explorer--T-ACE: a platform-independent, graphical tool to process large RNAseq datasets of non-model organisms.

    Science.gov (United States)

    Philipp, E E R; Kraemer, L; Mountfort, D; Schilhabel, M; Schreiber, S; Rosenstiel, P

    2012-03-15

    Next generation sequencing (NGS) technologies allow a rapid and cost-effective compilation of large RNA sequence datasets in model and non-model organisms. However, the storage and analysis of transcriptome information from different NGS platforms is still a significant bottleneck, leading to a delay in data dissemination and subsequent biological understanding. Especially database interfaces with transcriptome analysis modules going beyond mere read counts are missing. Here, we present the Transcriptome Analysis and Comparison Explorer (T-ACE), a tool designed for the organization and analysis of large sequence datasets, and especially suited for transcriptome projects of non-model organisms with little or no a priori sequence information. T-ACE offers a TCL-based interface, which accesses a PostgreSQL database via a php-script. Within T-ACE, information belonging to single sequences or contigs, such as annotation or read coverage, is linked to the respective sequence and immediately accessible. Sequences and assigned information can be searched via keyword- or BLAST-search. Additionally, T-ACE provides within and between transcriptome analysis modules on the level of expression, GO terms, KEGG pathways and protein domains. Results are visualized and can be easily exported for external analysis. We developed T-ACE for laboratory environments, which have only a limited amount of bioinformatics support, and for collaborative projects in which different partners work on the same dataset from different locations or platforms (Windows/Linux/MacOS). For laboratories with some experience in bioinformatics and programming, the low complexity of the database structure and open-source code provides a framework that can be customized according to the different needs of the user and transcriptome project.

  2. CREST--classification resources for environmental sequence tags.

    Directory of Open Access Journals (Sweden)

    Anders Lanzén

    Full Text Available Sequencing of taxonomic or phylogenetic markers is becoming a fast and efficient method for studying environmental microbial communities. This has resulted in a steadily growing collection of marker sequences, most notably of the small-subunit (SSU ribosomal RNA gene, and an increased understanding of microbial phylogeny, diversity and community composition patterns. However, to utilize these large datasets together with new sequencing technologies, a reliable and flexible system for taxonomic classification is critical. We developed CREST (Classification Resources for Environmental Sequence Tags, a set of resources and tools for generating and utilizing custom taxonomies and reference datasets for classification of environmental sequences. CREST uses an alignment-based classification method with the lowest common ancestor algorithm. It also uses explicit rank similarity criteria to reduce false positives and identify novel taxa. We implemented this method in a web server, a command line tool and the graphical user interfaced program MEGAN. Further, we provide the SSU rRNA reference database and taxonomy SilvaMod, derived from the publicly available SILVA SSURef, for classification of sequences from bacteria, archaea and eukaryotes. Using cross-validation and environmental datasets, we compared the performance of CREST and SilvaMod to the RDP Classifier. We also utilized Greengenes as a reference database, both with CREST and the RDP Classifier. These analyses indicate that CREST performs better than alignment-free methods with higher recall rate (sensitivity as well as precision, and with the ability to accurately identify most sequences from novel taxa. Classification using SilvaMod performed better than with Greengenes, particularly when applied to environmental sequences. CREST is freely available under a GNU General Public License (v3 from http://apps.cbu.uib.no/crest and http://lcaclassifier.googlecode.com.

  3. Long sequence correlation coprocessor

    Science.gov (United States)

    Gage, Douglas W.

    1994-09-01

    A long sequence correlation coprocessor (LSCC) accelerates the bitwise correlation of arbitrarily long digital sequences by calculating in parallel the correlation score for 16, for example, adjacent bit alignments between two binary sequences. The LSCC integrated circuit is incorporated into a computer system with memory storage buffers and a separate general purpose computer processor which serves as its controller. Each of the LSCC's set of sequential counters simultaneously tallies a separate correlation coefficient. During each LSCC clock cycle, computer enable logic associated with each counter compares one bit of a first sequence with one bit of a second sequence to increment the counter if the bits are the same. A shift register assures that the same bit of the first sequence is simultaneously compared to different bits of the second sequence to simultaneously calculate the correlation coefficient by the different counters to represent different alignments of the two sequences.

  4. Roles of repetitive sequences

    Energy Technology Data Exchange (ETDEWEB)

    Bell, G.I.

    1991-12-31

    The DNA of higher eukaryotes contains many repetitive sequences. The study of repetitive sequences is important, not only because many have important biological function, but also because they provide information on genome organization, evolution and dynamics. In this paper, I will first discuss some generic effects that repetitive sequences will have upon genome dynamics and evolution. In particular, it will be shown that repetitive sequences foster recombination among, and turnover of, the elements of a genome. I will then consider some examples of repetitive sequences, notably minisatellite sequences and telomere sequences as examples of tandem repeats, without and with respectively known function, and Alu sequences as an example of interspersed repeats. Some other examples will also be considered in less detail.

  5. Anomaly Detection in Sequences

    Data.gov (United States)

    National Aeronautics and Space Administration — We present a set of novel algorithms which we call sequenceMiner, that detect and characterize anomalies in large sets of high-dimensional symbol sequences that...

  6. DNA sequencing conference, 2

    Energy Technology Data Exchange (ETDEWEB)

    Cook-Deegan, R.M. [Georgetown Univ., Kennedy Inst. of Ethics, Washington, DC (United States); Venter, J.C. [National Inst. of Neurological Disorders and Strokes, Bethesda, MD (United States); Gilbert, W. [Harvard Univ., Cambridge, MA (United States); Mulligan, J. [Stanford Univ., CA (United States); Mansfield, B.K. [Oak Ridge National Lab., TN (United States)

    1991-06-19

    This conference focused on DNA sequencing, genetic linkage mapping, physical mapping, informatics and bioethics. Several were used to study this sequencing and mapping. This article also discusses computer hardware and software aiding in the mapping of genes.

  7. sequenceMiner algorithm

    Data.gov (United States)

    National Aeronautics and Space Administration — Detecting and describing anomalies in large repositories of discrete symbol sequences. sequenceMiner has been open-sourced! Download the file below to try it out....

  8. Parallel Framework for Dimensionality Reduction of Large-Scale Datasets

    Directory of Open Access Journals (Sweden)

    Sai Kiranmayee Samudrala

    2015-01-01

    Full Text Available Dimensionality reduction refers to a set of mathematical techniques used to reduce complexity of the original high-dimensional data, while preserving its selected properties. Improvements in simulation strategies and experimental data collection methods are resulting in a deluge of heterogeneous and high-dimensional data, which often makes dimensionality reduction the only viable way to gain qualitative and quantitative understanding of the data. However, existing dimensionality reduction software often does not scale to datasets arising in real-life applications, which may consist of thousands of points with millions of dimensions. In this paper, we propose a parallel framework for dimensionality reduction of large-scale data. We identify key components underlying the spectral dimensionality reduction techniques, and propose their efficient parallel implementation. We show that the resulting framework can be used to process datasets consisting of millions of points when executed on a 16,000-core cluster, which is beyond the reach of currently available methods. To further demonstrate applicability of our framework we perform dimensionality reduction of 75,000 images representing morphology evolution during manufacturing of organic solar cells in order to identify how processing parameters affect morphology evolution.

  9. The Path from Large Earth Science Datasets to Information

    Science.gov (United States)

    Vicente, G. A.

    2013-12-01

    The NASA Goddard Earth Sciences Data (GES) and Information Services Center (DISC) is one of the major Science Mission Directorate (SMD) for archiving and distribution of Earth Science remote sensing data, products and services. This virtual portal provides convenient access to Atmospheric Composition and Dynamics, Hydrology, Precipitation, Ozone, and model derived datasets (generated by GSFC's Global Modeling and Assimilation Office), the North American Land Data Assimilation System (NLDAS) and the Global Land Data Assimilation System (GLDAS) data products (both generated by GSFC's Hydrological Sciences Branch). This presentation demonstrates various tools and computational technologies developed in the GES DISC to manage the huge volume of data and products acquired from various missions and programs over the years. It explores approaches to archive, document, distribute, access and analyze Earth Science data and information as well as addresses the technical and scientific issues, governance and user support problem faced by scientists in need of multi-disciplinary datasets. It also discusses data and product metrics, user distribution profiles and lessons learned through interactions with the science communities around the world. Finally it demonstrates some of the most used data and product visualization and analyses tools developed and maintained by the GES DISC.

  10. Benchmarking undedicated cloud computing providers for analysis of genomic datasets.

    Science.gov (United States)

    Yazar, Seyhan; Gooden, George E C; Mackey, David A; Hewitt, Alex W

    2014-01-01

    A major bottleneck in biological discovery is now emerging at the computational level. Cloud computing offers a dynamic means whereby small and medium-sized laboratories can rapidly adjust their computational capacity. We benchmarked two established cloud computing services, Amazon Web Services Elastic MapReduce (EMR) on Amazon EC2 instances and Google Compute Engine (GCE), using publicly available genomic datasets (E.coli CC102 strain and a Han Chinese male genome) and a standard bioinformatic pipeline on a Hadoop-based platform. Wall-clock time for complete assembly differed by 52.9% (95% CI: 27.5-78.2) for E.coli and 53.5% (95% CI: 34.4-72.6) for human genome, with GCE being more efficient than EMR. The cost of running this experiment on EMR and GCE differed significantly, with the costs on EMR being 257.3% (95% CI: 211.5-303.1) and 173.9% (95% CI: 134.6-213.1) more expensive for E.coli and human assemblies respectively. Thus, GCE was found to outperform EMR both in terms of cost and wall-clock time. Our findings confirm that cloud computing is an efficient and potentially cost-effective alternative for analysis of large genomic datasets. In addition to releasing our cost-effectiveness comparison, we present available ready-to-use scripts for establishing Hadoop instances with Ganglia monitoring on EC2 or GCE.

  11. Multiresolution comparison of precipitation datasets for large-scale models

    Science.gov (United States)

    Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

    2014-12-01

    Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

  12. Benchmarking Deep Learning Models on Large Healthcare Datasets.

    Science.gov (United States)

    Purushotham, Sanjay; Meng, Chuizheng; Che, Zhengping; Liu, Yan

    2018-06-04

    Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist which have benchmarked the performance of the deep learning models with respect to the state-of-the-art machine learning models and prognostic scoring systems on publicly available healthcare datasets. In this paper, we present the benchmarking results for several clinical prediction tasks such as mortality prediction, length of stay prediction, and ICD-9 code group prediction using Deep Learning models, ensemble of machine learning models (Super Learner algorithm), SAPS II and SOFA scores. We used the Medical Information Mart for Intensive Care III (MIMIC-III) (v1.4) publicly available dataset, which includes all patients admitted to an ICU at the Beth Israel Deaconess Medical Center from 2001 to 2012, for the benchmarking tasks. Our results show that deep learning models consistently outperform all the other approaches especially when the 'raw' clinical time series data is used as input features to the models. Copyright © 2018 Elsevier Inc. All rights reserved.

  13. Testing the Neutral Theory of Biodiversity with Human Microbiome Datasets.

    Science.gov (United States)

    Li, Lianwei; Ma, Zhanshan Sam

    2016-08-16

    The human microbiome project (HMP) has made it possible to test important ecological theories for arguably the most important ecosystem to human health-the human microbiome. Existing limited number of studies have reported conflicting evidence in the case of the neutral theory; the present study aims to comprehensively test the neutral theory with extensive HMP datasets covering all five major body sites inhabited by the human microbiome. Utilizing 7437 datasets of bacterial community samples, we discovered that only 49 communities (less than 1%) satisfied the neutral theory, and concluded that human microbial communities are not neutral in general. The 49 positive cases, although only a tiny minority, do demonstrate the existence of neutral processes. We realize that the traditional doctrine of microbial biogeography "Everything is everywhere, but the environment selects" first proposed by Baas-Becking resolves the apparent contradiction. The first part of Baas-Becking doctrine states that microbes are not dispersal-limited and therefore are neutral prone, and the second part reiterates that the freely dispersed microbes must endure selection by the environment. Therefore, in most cases, it is the host environment that ultimately shapes the community assembly and tip the human microbiome to niche regime.

  14. Overview of the CERES Edition-4 Multilayer Cloud Property Datasets

    Science.gov (United States)

    Chang, F. L.; Minnis, P.; Sun-Mack, S.; Chen, Y.; Smith, R. A.; Brown, R. R.

    2014-12-01

    Knowledge of the cloud vertical distribution is important for understanding the role of clouds on earth's radiation budget and climate change. Since high-level cirrus clouds with low emission temperatures and small optical depths can provide a positive feedback to a climate system and low-level stratus clouds with high emission temperatures and large optical depths can provide a negative feedback effect, the retrieval of multilayer cloud properties using satellite observations, like Terra and Aqua MODIS, is critically important for a variety of cloud and climate applications. For the objective of the Clouds and the Earth's Radiant Energy System (CERES), new algorithms have been developed using Terra and Aqua MODIS data to allow separate retrievals of cirrus and stratus cloud properties when the two dominant cloud types are simultaneously present in a multilayer system. In this paper, we will present an overview of the new CERES Edition-4 multilayer cloud property datasets derived from Terra as well as Aqua. Assessment of the new CERES multilayer cloud datasets will include high-level cirrus and low-level stratus cloud heights, pressures, and temperatures as well as their optical depths, emissivities, and microphysical properties.

  15. Predicting weather regime transitions in Northern Hemisphere datasets

    Energy Technology Data Exchange (ETDEWEB)

    Kondrashov, D. [University of California, Department of Atmospheric and Oceanic Sciences and Institute of Geophysics and Planetary Physics, Los Angeles, CA (United States); Shen, J. [UCLA, Department of Statistics, Los Angeles, CA (United States); Berk, R. [UCLA, Department of Statistics, Los Angeles, CA (United States); University of Pennsylvania, Department of Criminology, Philadelphia, PA (United States); D' Andrea, F.; Ghil, M. [Ecole Normale Superieure, Departement Terre-Atmosphere-Ocean and Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Paris Cedex 05 (France)

    2007-10-15

    A statistical learning method called random forests is applied to the prediction of transitions between weather regimes of wintertime Northern Hemisphere (NH) atmospheric low-frequency variability. A dataset composed of 55 winters of NH 700-mb geopotential height anomalies is used in the present study. A mixture model finds that the three Gaussian components that were statistically significant in earlier work are robust; they are the Pacific-North American (PNA) regime, its approximate reverse (the reverse PNA, or RNA), and the blocked phase of the North Atlantic Oscillation (BNAO). The most significant and robust transitions in the Markov chain generated by these regimes are PNA {yields} BNAO, PNA {yields} RNA and BNAO {yields} PNA. The break of a regime and subsequent onset of another one is forecast for these three transitions. Taking the relative costs of false positives and false negatives into account, the random-forests method shows useful forecasting skill. The calculations are carried out in the phase space spanned by a few leading empirical orthogonal functions of dataset variability. Plots of estimated response functions to a given predictor confirm the crucial influence of the exit angle on a preferred transition path. This result points to the dynamic origin of the transitions. (orig.)

  16. Digital Astronaut Photography: A Discovery Dataset for Archaeology

    Science.gov (United States)

    Stefanov, William L.

    2010-01-01

    Astronaut photography acquired from the International Space Station (ISS) using commercial off-the-shelf cameras offers a freely-accessible source for high to very high resolution (4-20 m/pixel) visible-wavelength digital data of Earth. Since ISS Expedition 1 in 2000, over 373,000 images of the Earth-Moon system (including land surface, ocean, atmospheric, and lunar images) have been added to the Gateway to Astronaut Photography of Earth online database (http://eol.jsc.nasa.gov ). Handheld astronaut photographs vary in look angle, time of acquisition, solar illumination, and spatial resolution. These attributes of digital astronaut photography result from a unique combination of ISS orbital dynamics, mission operations, camera systems, and the individual skills of the astronaut. The variable nature of astronaut photography makes the dataset uniquely useful for archaeological applications in comparison with more traditional nadir-viewing multispectral datasets acquired from unmanned orbital platforms. For example, surface features such as trenches, walls, ruins, urban patterns, and vegetation clearing and regrowth patterns may be accentuated by low sun angles and oblique viewing conditions (Fig. 1). High spatial resolution digital astronaut photographs can also be used with sophisticated land cover classification and spatial analysis approaches like Object Based Image Analysis, increasing the potential for use in archaeological characterization of landscapes and specific sites.

  17. ISC-EHB: Reconstruction of a robust earthquake dataset

    Science.gov (United States)

    Weston, J.; Engdahl, E. R.; Harris, J.; Di Giacomo, D.; Storchak, D. A.

    2018-04-01

    The EHB Bulletin of hypocentres and associated travel-time residuals was originally developed with procedures described by Engdahl, Van der Hilst and Buland (1998) and currently ends in 2008. It is a widely used seismological dataset, which is now expanded and reconstructed, partly by exploiting updated procedures at the International Seismological Centre (ISC), to produce the ISC-EHB. The reconstruction begins in the modern period (2000-2013) to which new and more rigorous procedures for event selection, data preparation, processing, and relocation are applied. The selection criteria minimise the location bias produced by unmodelled 3D Earth structure, resulting in events that are relatively well located in any given region. Depths of the selected events are significantly improved by a more comprehensive review of near station and secondary phase travel-time residuals based on ISC data, especially for the depth phases pP, pwP and sP, as well as by a rigorous review of the event depths in subduction zone cross sections. The resulting cross sections and associated maps are shown to provide details of seismicity in subduction zones in much greater detail than previously achievable. The new ISC-EHB dataset will be especially useful for global seismicity studies and high-frequency regional and global tomographic inversions.

  18. Benchmarking undedicated cloud computing providers for analysis of genomic datasets.

    Directory of Open Access Journals (Sweden)

    Seyhan Yazar

    Full Text Available A major bottleneck in biological discovery is now emerging at the computational level. Cloud computing offers a dynamic means whereby small and medium-sized laboratories can rapidly adjust their computational capacity. We benchmarked two established cloud computing services, Amazon Web Services Elastic MapReduce (EMR on Amazon EC2 instances and Google Compute Engine (GCE, using publicly available genomic datasets (E.coli CC102 strain and a Han Chinese male genome and a standard bioinformatic pipeline on a Hadoop-based platform. Wall-clock time for complete assembly differed by 52.9% (95% CI: 27.5-78.2 for E.coli and 53.5% (95% CI: 34.4-72.6 for human genome, with GCE being more efficient than EMR. The cost of running this experiment on EMR and GCE differed significantly, with the costs on EMR being 257.3% (95% CI: 211.5-303.1 and 173.9% (95% CI: 134.6-213.1 more expensive for E.coli and human assemblies respectively. Thus, GCE was found to outperform EMR both in terms of cost and wall-clock time. Our findings confirm that cloud computing is an efficient and potentially cost-effective alternative for analysis of large genomic datasets. In addition to releasing our cost-effectiveness comparison, we present available ready-to-use scripts for establishing Hadoop instances with Ganglia monitoring on EC2 or GCE.

  19. Condensing Massive Satellite Datasets For Rapid Interactive Analysis

    Science.gov (United States)

    Grant, G.; Gallaher, D. W.; Lv, Q.; Campbell, G. G.; Fowler, C.; LIU, Q.; Chen, C.; Klucik, R.; McAllister, R. A.

    2015-12-01

    Our goal is to enable users to interactively analyze massive satellite datasets, identifying anomalous data or values that fall outside of thresholds. To achieve this, the project seeks to create a derived database containing only the most relevant information, accelerating the analysis process. The database is designed to be an ancillary tool for the researcher, not an archival database to replace the original data. This approach is aimed at improving performance by reducing the overall size by way of condensing the data. The primary challenges of the project include: - The nature of the research question(s) may not be known ahead of time. - The thresholds for determining anomalies may be uncertain. - Problems associated with processing cloudy, missing, or noisy satellite imagery. - The contents and method of creation of the condensed dataset must be easily explainable to users. The architecture of the database will reorganize spatially-oriented satellite imagery into temporally-oriented columns of data (a.k.a., "data rods") to facilitate time-series analysis. The database itself is an open-source parallel database, designed to make full use of clustered server technologies. A demonstration of the system capabilities will be shown. Applications for this technology include quick-look views of the data, as well as the potential for on-board satellite processing of essential information, with the goal of reducing data latency.

  20. Identification of novel and conserved microRNAs related to drought stress in potato by deep sequencing.

    Science.gov (United States)

    Zhang, Ning; Yang, Jiangwei; Wang, Zemin; Wen, Yikai; Wang, Jie; He, Wenhui; Liu, Bailin; Si, Huaijun; Wang, Di

    2014-01-01

    MicroRNAs (miRNAs) are a group of small, non-coding RNAs that play important roles in plant growth, development and stress response. There have been an increasing number of investigations aimed at discovering miRNAs and analyzing their functions in model plants (such as Arabidopsis thaliana and rice). In this research, we constructed small RNA libraries from both polyethylene glycol (PEG 6,000) treated and control potato samples, and a large number of known and novel miRNAs were identified. Differential expression analysis showed that 100 of the known miRNAs were down-regulated and 99 were up-regulated as a result of PEG stress, while 119 of the novel miRNAs were up-regulated and 151 were down-regulated. Based on target prediction, annotation and expression analysis of the miRNAs and their putative target genes, 4 miRNAs were identified as regulating drought-related genes (miR811, miR814, miR835, miR4398). Their target genes were MYB transcription factor (CV431094), hydroxyproline-rich glycoprotein (TC225721), quaporin (TC223412) and WRKY transcription factor (TC199112), respectively. Relative expression trends of those miRNAs were the same as that predicted by Solexa sequencing and they showed a negative correlation with the expression of the target genes. The results provide molecular evidence for the possible involvement of miRNAs in the process of drought response and/or tolerance in the potato plant.

  1. High-Throughput Sequencing Reveals Circulating miRNAs as Potential Biomarkers for Measuring Puberty Onset in Chicken (Gallus gallus).

    Science.gov (United States)

    Han, Wei; Zhu, Yunfen; Su, Yijun; Li, Guohui; Qu, Liang; Zhang, Huiyong; Wang, Kehua; Zou, Jianmin; Liu, Honglin

    2016-01-01

    There are still no highly sensitive and unique biomarkers for measurement of puberty onset. Circulating miRNAs have been shown to be promising biomarkers for diagnosis of various diseases. To identify circulating miRNAs that could be served as biomarkers for measuring chicken (Gallus gallus) puberty onset, the Solexa deep sequencing was performed to analyze the miRNA expression profiles in serum and plasma of hens from two different pubertal stages, before puberty onset (BO) and after puberty onset (AO). 197 conserved and 19 novel miRNAs (reads > 10) were identified as serum/plasma-expressed miRNAs in the chicken. The common miRNA amounts and their expression changes from BO to AO between serum and plasma were very similar, indicating the different treatments to generate serum and plasma had quite small influence on the miRNAs. 130 conserved serum-miRNAs were showed to be differentially expressed (reads > 10, P 1.0, P puberty onset. Further quantitative real-time PCR (RT-qPCR) test found that a seven-miRNA panel, including miR-29c, miR-375, miR-215, miR-217, miR-19b, miR-133a and let-7a, had great potentials to serve as novel biomarkers for measuring puberty onset in chicken. Due to highly conserved nature of miRNAs, the findings could provide cues for measurement of puberty onset in other animals as well as humans.

  2. OTU analysis using metagenomic shotgun sequencing data.

    Directory of Open Access Journals (Sweden)

    Xiaolin Hao

    Full Text Available Because of technological limitations, the primer and amplification biases in targeted sequencing of 16S rRNA genes have veiled the true microbial diversity underlying environmental samples. However, the protocol of metagenomic shotgun sequencing provides 16S rRNA gene fragment data with natural immunity against the biases raised during priming and thus the potential of uncovering the true structure of microbial community by giving more accurate predictions of operational taxonomic units (OTUs. Nonetheless, the lack of statistically rigorous comparison between 16S rRNA gene fragments and other data types makes it difficult to interpret previously reported results using 16S rRNA gene fragments. Therefore, in the present work, we established a standard analysis pipeline that would help confirm if the differences in the data are true or are just due to potential technical bias. This pipeline is built by using simulated data to find optimal mapping and OTU prediction methods. The comparison between simulated datasets revealed a relationship between 16S rRNA gene fragments and full-length 16S rRNA sequences that a 16S rRNA gene fragment having a length >150 bp provides the same accuracy as a full-length 16S rRNA sequence using our proposed pipeline, which could serve as a good starting point for experimental design and making the comparison between 16S rRNA gene fragment-based and targeted 16S rRNA sequencing-based surveys possible.

  3. Utilizing the Antarctic Master Directory to find orphan datasets

    Science.gov (United States)

    Bonczkowski, J.; Carbotte, S. M.; Arko, R. A.; Grebas, S. K.

    2011-12-01

    While most Antarctic data are housed at an established disciplinary-specific data repository, there are data types for which no suitable repository exists. In some cases, these "orphan" data, without an appropriate national archive, are served from local servers by the principal investigators who produced the data. There are many pitfalls with data served privately, including the frequent lack of adequate documentation to ensure the data can be understood by others for re-use and the impermanence of personal web sites. For example, if an investigator leaves an institution and the data moves, the link published is no longer accessible. To ensure continued availability of data, submission to long-term national data repositories is needed. As stated in the National Science Foundation Office of Polar Programs (NSF/OPP) Guidelines and Award Conditions for Scientific Data, investigators are obligated to submit their data for curation and long-term preservation; this includes the registration of a dataset description into the Antarctic Master Directory (AMD), http://gcmd.nasa.gov/Data/portals/amd/. The AMD is a Web-based, searchable directory of thousands of dataset descriptions, known as DIF records, submitted by scientists from over 20 countries. It serves as a node of the International Directory Network/Global Change Master Directory (IDN/GCMD). The US Antarctic Program Data Coordination Center (USAP-DCC), http://www.usap-data.org/, funded through NSF/OPP, was established in 2007 to help streamline the process of data submission and DIF record creation. When data does not quite fit within any existing disciplinary repository, it can be registered within the USAP-DCC as the fallback data repository. Within the scope of the USAP-DCC we undertook the challenge of discovering and "rescuing" orphan datasets currently registered within the AMD. In order to find which DIF records led to data served privately, all records relating to US data within the AMD were parsed. After

  4. DNApi: A De Novo Adapter Prediction Algorithm for Small RNA Sequencing Data.

    Science.gov (United States)

    Tsuji, Junko; Weng, Zhiping

    2016-01-01

    With the rapid accumulation of publicly available small RNA sequencing datasets, third-party meta-analysis across many datasets is becoming increasingly powerful. Although removing the 3´ adapter is an essential step for small RNA sequencing analysis, the adapter sequence information is not always available in the metadata. The information can be also erroneous even when it is available. In this study, we developed DNApi, a lightweight Python software package that predicts the 3´ adapter sequence de novo and provides the user with cleansed small RNA sequences ready for down stream analysis. Tested on 539 publicly available small RNA libraries accompanied with 3´ adapter sequences in their metadata, DNApi shows near-perfect accuracy (98.5%) with fast runtime (~2.85 seconds per library) and efficient memory usage (~43 MB on average). In addition to 3´ adapter prediction, it is also important to classify whether the input small RNA libraries were already processed, i.e. the 3´ adapters were removed. DNApi perfectly judged that given another batch of datasets, 192 publicly available processed libraries were "ready-to-map" small RNA sequence. DNApi is compatible with Python 2 and 3, and is available at https://github.com/jnktsj/DNApi. The 731 small RNA libraries used for DNApi evaluation were from human tissues and were carefully and manually collected. This study also provides readers with the curated datasets that can be integrated into their studies.

  5. Resampling nucleotide sequences with closest-neighbor trimming and its comparison to other methods.

    Directory of Open Access Journals (Sweden)

    Kouki Yonezawa

    Full Text Available A large number of nucleotide sequences of various pathogens are available in public databases. The growth of the datasets has resulted in an enormous increase in computational costs. Moreover, due to differences in surveillance activities, the number of sequences found in databases varies from one country to another and from year to year. Therefore, it is important to study resampling methods to reduce the sampling bias. A novel algorithm-called the closest-neighbor trimming method-that resamples a given number of sequences from a large nucleotide sequence dataset was proposed. The performance of the proposed algorithm was compared with other algorithms by using the nucleotide sequences of human H3N2 influenza viruses. We compared the closest-neighbor trimming method with the naive hierarchical clustering algorithm and [Formula: see text]-medoids clustering algorithm. Genetic information accumulated in public databases contains sampling bias. The closest-neighbor trimming method can thin out densely sampled sequences from a given dataset. Since nucleotide sequences are among the most widely used materials for life sciences, we anticipate that our algorithm to various datasets will result in reducing sampling bias.

  6. NERIES: Seismic Data Gateways and User Composed Datasets Metadata Management

    Science.gov (United States)

    Spinuso, Alessandro; Trani, Luca; Kamb, Linus; Frobert, Laurent

    2010-05-01

    One of the NERIES EC project main objectives is to establish and improve the networking of seismic waveform data exchange and access among four main data centers in Europe: INGV, GFZ, ORFEUS and IPGP. Besides the implementation of the data backbone, several investigations and developments have been conducted in order to offer to the users the data available from this network, either programmatically or interactively. One of the challenges is to understand how to enable users` activities such as discovering, aggregating, describing and sharing datasets to obtain a decrease in the replication of similar data queries towards the network, exempting the data centers to guess and create useful pre-packed products. We`ve started to transfer this task more and more towards the users community, where the users` composed data products could be extensively re-used. The main link to the data is represented by a centralized webservice (SeismoLink) acting like a single access point to the whole data network. Users can download either waveform data or seismic station inventories directly from their own software routines by connecting to this webservice, which routes the request to the data centers. The provenance of the data is maintained and transferred to the users in the form of URIs, that identify the dataset and implicitly refer to the data provider. SeismoLink, combined with other webservices (eg EMSC-QuakeML earthquakes catalog service), is used from a community gateway such as the NERIES web portal (http://www.seismicportal.eu). Here the user interacts with a map based portlet which allows the dynamic composition of a data product, binding seismic event`s parameters with a set of seismic stations. The requested data is collected by the back-end processes of the portal, preserved and offered to the user in a personal data cart, where metadata can be generated interactively on-demand. The metadata, expressed in RDF, can also be remotely ingested. They offer rating

  7. Accuracy assessment of seven global land cover datasets over China

    Science.gov (United States)

    Yang, Yongke; Xiao, Pengfeng; Feng, Xuezhi; Li, Haixing

    2017-03-01

    Land cover (LC) is the vital foundation to Earth science. Up to now, several global LC datasets have arisen with efforts of many scientific communities. To provide guidelines for data usage over China, nine LC maps from seven global LC datasets (IGBP DISCover, UMD, GLC, MCD12Q1, GLCNMO, CCI-LC, and GlobeLand30) were evaluated in this study. First, we compared their similarities and discrepancies in both area and spatial patterns, and analysed their inherent relations to data sources and classification schemes and methods. Next, five sets of validation sample units (VSUs) were collected to calculate their accuracy quantitatively. Further, we built a spatial analysis model and depicted their spatial variation in accuracy based on the five sets of VSUs. The results show that, there are evident discrepancies among these LC maps in both area and spatial patterns. For LC maps produced by different institutes, GLC 2000 and CCI-LC 2000 have the highest overall spatial agreement (53.8%). For LC maps produced by same institutes, overall spatial agreement of CCI-LC 2000 and 2010, and MCD12Q1 2001 and 2010 reach up to 99.8% and 73.2%, respectively; while more efforts are still needed if we hope to use these LC maps as time series data for model inputting, since both CCI-LC and MCD12Q1 fail to represent the rapid changing trend of several key LC classes in the early 21st century, in particular urban and built-up, snow and ice, water bodies, and permanent wetlands. With the highest spatial resolution, the overall accuracy of GlobeLand30 2010 is 82.39%. For the other six LC datasets with coarse resolution, CCI-LC 2010/2000 has the highest overall accuracy, and following are MCD12Q1 2010/2001, GLC 2000, GLCNMO 2008, IGBP DISCover, and UMD in turn. Beside that all maps exhibit high accuracy in homogeneous regions; local accuracies in other regions are quite different, particularly in Farming-Pastoral Zone of North China, mountains in Northeast China, and Southeast Hills. Special

  8. MicroRNA discovery and analysis of pinewood nematode Bursaphelenchus xylophilus by deep sequencing.

    Directory of Open Access Journals (Sweden)

    Qi-Xing Huang

    Full Text Available BACKGROUND: MicroRNAs (miRNAs are considered to be very important in regulating the growth, development, behavior and stress response in animals and plants in post-transcriptional gene regulation. Pinewood nematode, Bursaphelenchus xylophilus, is an important invasive plant parasitic nematode in Asia. To have a comprehensive knowledge about miRNAs of the nematode is necessary for further in-depth study on roles of miRNAs in the ecological adaptation of the invasive species. METHODS AND FINDINGS: Five small RNA libraries were constructed and sequenced by Illumina/Solexa deep-sequencing technology. A total of 810 miRNA candidates (49 conserved and 761 novel were predicted by a computational pipeline, of which 57 miRNAs (20 conserved and 37 novel encoded by 53 miRNA precursors were identified by experimental methods. Ten novel miRNAs were considered to be species-specific miRNAs of B. xylophilus. Comparison of expression profiles of miRNAs in the five small RNA libraries showed that many miRNAs exhibited obviously different expression levels in the third-stage dispersal juvenile and at a cold-stressed status. Most of the miRNAs exhibited obviously down-regulated expression in the dispersal stage. But differences among the three geographic libraries were not prominent. A total of 979 genes were predicted to be targets of these authentic miRNAs. Among them, seven heat shock protein genes were targeted by 14 miRNAs, and six FMRFamide-like neuropeptides genes were targeted by 17 miRNAs. A real-time quantitative polymerase chain reaction was used to quantify the mRNA expression levels of target genes. CONCLUSIONS: Basing on the fact that a negative correlation existed between the expression profiles of miRNAs and the mRNA expression profiles of their target genes (hsp, flp by comparing those of the nematodes at a cold stressed status and a normal status, we suggested that miRNAs might participate in ecological adaptation and behavior regulation of the

  9. Field-based species identification in eukaryotes using real-time nanopore sequencing.

    OpenAIRE

    Papadopulos, Alexander; Devey, Dion; Helmstetter, Andrew; Parker, Joe

    2017-01-01

    Advances in DNA sequencing and informatics have revolutionised biology over the past four decades, but technological limitations have left many applications unexplored. Recently, portable, real-time, nanopore sequencing (RTnS) has become available. This offers opportunities to rapidly collect and analyse genomic data anywhere. However, the generation of datasets from large, complex genomes has been constrained to laboratories. The portability and long DNA sequences of RTnS offer great potenti...

  10. Gridded 5km GHCN-Daily Temperature and Precipitation Dataset, Version 1

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Gridded 5km GHCN-Daily Temperature and Precipitation Dataset (nClimGrid) consists of four climate variables derived from the GHCN-D dataset: maximum temperature,...

  11. Active Semisupervised Clustering Algorithm with Label Propagation for Imbalanced and Multidensity Datasets

    Directory of Open Access Journals (Sweden)

    Mingwei Leng

    2013-01-01

    Full Text Available The accuracy of most of the existing semisupervised clustering algorithms based on small size of labeled dataset is low when dealing with multidensity and imbalanced datasets, and labeling data is quite expensive and time consuming in many real-world applications. This paper focuses on active data selection and semisupervised clustering algorithm in multidensity and imbalanced datasets and proposes an active semisupervised clustering algorithm. The proposed algorithm uses an active mechanism for data selection to minimize the amount of labeled data, and it utilizes multithreshold to expand labeled datasets on multidensity and imbalanced datasets. Three standard datasets and one synthetic dataset are used to demonstrate the proposed algorithm, and the experimental results show that the proposed semisupervised clustering algorithm has a higher accuracy and a more stable performance in comparison to other clustering and semisupervised clustering algorithms, especially when the datasets are multidensity and imbalanced.

  12. Dataset for Probabilistic estimation of residential air exchange rates for population-based exposure modeling

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset provides the city-specific air exchange rate measurements, modeled, literature-based as well as housing characteristics. This dataset is associated with...

  13. An Affinity Propagation Clustering Algorithm for Mixed Numeric and Categorical Datasets

    Directory of Open Access Journals (Sweden)

    Kang Zhang

    2014-01-01

    Full Text Available Clustering has been widely used in different fields of science, technology, social science, and so forth. In real world, numeric as well as categorical features are usually used to describe the data objects. Accordingly, many clustering methods can process datasets that are either numeric or categorical. Recently, algorithms that can handle the mixed data clustering problems have been developed. Affinity propagation (AP algorithm is an exemplar-based clustering method which has demonstrated good performance on a wide variety of datasets. However, it has limitations on processing mixed datasets. In this paper, we propose a novel similarity measure for mixed type datasets and an adaptive AP clustering algorithm is proposed to cluster the mixed datasets. Several real world datasets are studied to evaluate the performance of the proposed algorithm. Comparisons with other clustering algorithms demonstrate that the proposed method works well not only on mixed datasets but also on pure numeric and categorical datasets.

  14. Ecohydrological Index, Native Fish, and Climate Trends and Relationships in the Kansas River Basin_dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — The dataset is an excel file that contain data for the figures in the manuscript. This dataset is associated with the following publication: Sinnathamby, S., K....

  15. Global Human Built-up And Settlement Extent (HBASE) Dataset From Landsat

    Data.gov (United States)

    National Aeronautics and Space Administration — The Global Human Built-up And Settlement Extent (HBASE) Dataset from Landsat is a global map of HBASE derived from the Global Land Survey (GLS) Landsat dataset for...

  16. Inverted temperature sequences: role of deformation partitioning

    Science.gov (United States)

    Grujic, D.; Ashley, K. T.; Coble, M. A.; Coutand, I.; Kellett, D.; Whynot, N.

    2015-12-01

    The inverted metamorphism associated with the Main Central thrust zone in the Himalaya has been historically attributed to a number of tectonic processes. Here we show that there is actually a composite peak and deformation temperature sequence that formed in succession via different tectonic processes. The deformation partitioning seems to the have played a key role, and the magnitude of each process has varied along strike of the orogen. To explain the formation of the inverted metamorphic sequence across the Lesser Himalayan Sequence (LHS) in eastern Bhutan, we used Raman spectroscopy of carbonaceous material (RSCM) to determine the peak metamorphic temperatures and Ti-in-quartz thermobarometry to determine the deformation temperatures combined with thermochronology including published apatite and zircon U-Th/He and fission-track data and new 40Ar/39Ar dating of muscovite. The dataset was inverted using 3D-thermal-kinematic modeling to constrain the ranges of geological parameters such as fault geometry and slip rates, location and rates of localized basal accretion, and thermal properties of the crust. RSCM results indicate that there are two peak temperature sequences separated by a major thrust within the LHS. The internal temperature sequence shows an inverted peak temperature gradient of 12 °C/km; in the external (southern) sequence, the peak temperatures are constant across the structural sequence. Thermo-kinematic modeling suggest that the thermochronologic and thermobarometric data are compatible with a two-stage scenario: an Early-Middle Miocene phase of fast overthrusting of a hot hanging wall over a downgoing footwall and inversion of the synkinematic isotherms, followed by the formation of the external duplex developed by dominant underthrusting and basal accretion. To reconcile our observations with the experimental data, we suggest that pervasive ductile deformation within the upper LHS and along the Main Central thrust zone at its top stopped at

  17. An Automatic Matcher and Linker for Transportation Datasets

    Directory of Open Access Journals (Sweden)

    Ali Masri

    2017-01-01

    Full Text Available Multimodality requires the integration of heterogeneous transportation data to construct a broad view of the transportation network. Many new transportation services are emerging while being isolated from previously-existing networks. This leads them to publish their data sources to the web, according to linked data principles, in order to gain visibility. Our interest is to use these data to construct an extended transportation network that links these new services to existing ones. The main problems we tackle in this article fall in the categories of automatic schema matching and data interlinking. We propose an approach that uses web services as mediators to help in automatically detecting geospatial properties and mapping them between two different schemas. On the other hand, we propose a new interlinking approach that enables the user to define rich semantic links between datasets in a flexible and customizable way.

  18. [Parallel virtual reality visualization of extreme large medical datasets].

    Science.gov (United States)

    Tang, Min

    2010-04-01

    On the basis of a brief description of grid computing, the essence and critical techniques of parallel visualization of extreme large medical datasets are discussed in connection with Intranet and common-configuration computers of hospitals. In this paper are introduced several kernel techniques, including the hardware structure, software framework, load balance and virtual reality visualization. The Maximum Intensity Projection algorithm is realized in parallel using common PC cluster. In virtual reality world, three-dimensional models can be rotated, zoomed, translated and cut interactively and conveniently through the control panel built on virtual reality modeling language (VRML). Experimental results demonstrate that this method provides promising and real-time results for playing the role in of a good assistant in making clinical diagnosis.

  19. The wildland-urban interface raster dataset of Catalonia.

    Science.gov (United States)

    Alcasena, Fermín J; Evers, Cody R; Vega-Garcia, Cristina

    2018-04-01

    We provide the wildland urban interface (WUI) map of the autonomous community of Catalonia (Northeastern Spain). The map encompasses an area of some 3.21 million ha and is presented as a 150-m resolution raster dataset. Individual housing location, structure density and vegetation cover data were used to spatially assess in detail the interface, intermix and dispersed rural WUI communities with a geographical information system. Most WUI areas concentrate in the coastal belt where suburban sprawl has occurred nearby or within unmanaged forests. This geospatial information data provides an approximation of residential housing potential for loss given a wildfire, and represents a valuable contribution to assist landscape and urban planning in the region.

  20. xarray: N-D labeled Arrays and Datasets in Python

    Directory of Open Access Journals (Sweden)

    Stephan Hoyer

    2017-04-01

    Full Text Available xarray is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays. Our approach combines an application programing interface (API inspired by pandas with the Common Data Model for self-described scientific data. Key features of the xarray package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, out-of-core computation on datasets that don’t fit into memory, a wide range of serialization and input/output (I/O options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. xarray, as a data model and analytics toolkit, has been widely adopted in the geoscience community but is also used more broadly for multi-dimensional data analysis in physics, machine learning and finance.

  1. The wildland-urban interface raster dataset of Catalonia

    Directory of Open Access Journals (Sweden)

    Fermín J. Alcasena

    2018-04-01

    Full Text Available We provide the wildland urban interface (WUI map of the autonomous community of Catalonia (Northeastern Spain. The map encompasses an area of some 3.21 million ha and is presented as a 150-m resolution raster dataset. Individual housing location, structure density and vegetation cover data were used to spatially assess in detail the interface, intermix and dispersed rural WUI communities with a geographical information system. Most WUI areas concentrate in the coastal belt where suburban sprawl has occurred nearby or within unmanaged forests. This geospatial information data provides an approximation of residential housing potential for loss given a wildfire, and represents a valuable contribution to assist landscape and urban planning in the region. Keywords: Wildland-urban interface, Wildfire risk, Urban planning, Human communities, Catalonia

  2. Reconstructing flaw image using dataset of full matrix capture technique

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Tae Hun; Kim, Yong Sik; Lee, Jeong Seok [KHNP Central Research Institute, Daejeon (Korea, Republic of)

    2017-02-15

    A conventional phased array ultrasonic system offers the ability to steer an ultrasonic beam by applying independent time delays of individual elements in the array and produce an ultrasonic image. In contrast, full matrix capture (FMC) is a data acquisition process that collects a complete matrix of A-scans from every possible independent transmit-receive combination in a phased array transducer and makes it possible to reconstruct various images that cannot be produced by conventional phased array with the post processing as well as images equivalent to a conventional phased array image. In this paper, a basic algorithm based on the LLL mode total focusing method (TFM) that can image crack type flaws is described. And this technique was applied to reconstruct flaw images from the FMC dataset obtained from the experiments and ultrasonic simulation.

  3. Survey dataset on occupational hazards on construction sites

    Directory of Open Access Journals (Sweden)

    Patience F. Tunji-Olayeni

    2018-06-01

    Full Text Available The construction site provides an unfriendly working conditions, exposing workers to one of the harshest environments at a workplace. In this dataset, a structured questionnaire was design directed to thirty-five (35 craftsmen selected through a purposive sampling technique on various construction sites in one of the most populous cities in sub-Saharan Africa. The set of descriptive statistics is presented with tables, stacked bar chats and pie charts. Common occupational health conditions affecting the cardiovascular, respiratory and musculoskeletal systems of craftsmen on construction sites were identified. The effects of occupational health hazards on craftsmen and on construction project performance can be determined when the data is analyzed. Moreover, contractors’ commitment to occupational health and safety (OHS can be obtained from the analysis of the survey data. Keywords: Accidents, Construction industry, Craftsmen, Health, Occupational hazards

  4. Feedback control in deep drawing based on experimental datasets

    Science.gov (United States)

    Fischer, P.; Heingärtner, J.; Aichholzer, W.; Hortig, D.; Hora, P.

    2017-09-01

    In large-scale production of deep drawing parts, like in automotive industry, the effects of scattering material properties as well as warming of the tools have a significant impact on the drawing result. In the scope of the work, an approach is presented to minimize the influence of these effects on part quality by optically measuring the draw-in of each part and adjusting the settings of the press to keep the strain distribution, which is represented by the draw-in, inside a certain limit. For the design of the control algorithm, a design of experiments for in-line tests is used to quantify the influence of the blank holder force as well as the force distribution on the draw-in. The results of this experimental dataset are used to model the process behavior. Based on this model, a feedback control loop is designed. Finally, the performance of the control algorithm is validated in the production line.

  5. Comprehensive comparison of large-scale tissue expression datasets

    DEFF Research Database (Denmark)

    Santos Delgado, Alberto; Tsafou, Kalliopi; Stolte, Christian

    2015-01-01

    a comprehensive evaluation of tissue expression data from a variety of experimental techniques and show that these agree surprisingly well with each other and with results from literature curation and text mining. We further found that most datasets support the assumed but not demonstrated distinction between......For tissues to carry out their functions, they rely on the right proteins to be present. Several high-throughput technologies have been used to map out which proteins are expressed in which tissues; however, the data have not previously been systematically compared and integrated. We present......://tissues.jensenlab.org), which makes all the scored and integrated data available through a single user-friendly web interface....

  6. The SAIL databank: linking multiple health and social care datasets

    Directory of Open Access Journals (Sweden)

    Ford David V

    2009-01-01

    Full Text Available Abstract Background Vast amounts of data are collected about patients and service users in the course of health and social care service delivery. Electronic data systems for patient records have the potential to revolutionise service delivery and research. But in order to achieve this, it is essential that the ability to link the data at the individual record level be retained whilst adhering to the principles of information governance. The SAIL (Secure Anonymised Information Linkage databank has been established using disparate datasets, and over 500 million records from multiple health and social care service providers have been loaded to date, with further growth in progress. Methods Having established the infrastructure of the databank, the aim of this work was to develop and implement an accurate matching process to enable the assignment of a unique Anonymous Linking Field (ALF to person-based records to make the databank ready for record-linkage research studies. An SQL-based matching algorithm (MACRAL, Matching Algorithm for Consistent Results in Anonymised Linkage was developed for this purpose. Firstly the suitability of using a valid NHS number as the basis of a unique identifier was assessed using MACRAL. Secondly, MACRAL was applied in turn to match primary care, secondary care and social services datasets to the NHS Administrative Register (NHSAR, to assess the efficacy of this process, and the optimum matching technique. Results The validation of using the NHS number yielded specificity values > 99.8% and sensitivity values > 94.6% using probabilistic record linkage (PRL at the 50% threshold, and error rates were Conclusion With the infrastructure that has been put in place, the reliable matching process that has been developed enables an ALF to be consistently allocated to records in the databank. The SAIL databank represents a research-ready platform for record-linkage studies.

  7. Analysis of Public Datasets for Wearable Fall Detection Systems.

    Science.gov (United States)

    Casilari, Eduardo; Santoyo-Ramón, José-Antonio; Cano-García, José-Manuel

    2017-06-27

    Due to the boom of wireless handheld devices such as smartwatches and smartphones, wearable Fall Detection Systems (FDSs) have become a major focus of attention among the research community during the last years. The effectiveness of a wearable FDS must be contrasted against a wide variety of measurements obtained from inertial sensors during the occurrence of falls and Activities of Daily Living (ADLs). In this regard, the access to public databases constitutes the basis for an open and systematic assessment of fall detection techniques. This paper reviews and appraises twelve existing available data repositories containing measurements of ADLs and emulated falls envisaged for the evaluation of fall detection algorithms in wearable FDSs. The analysis of the found datasets is performed in a comprehensive way, taking into account the multiple factors involved in the definition of the testbeds deployed for the generation of the mobility samples. The study of the traces brings to light the lack of a common experimental benchmarking procedure and, consequently, the large heterogeneity of the datasets from a number of perspectives (length and number of samples, typology of the emulated falls and ADLs, characteristics of the test subjects, features and positions of the sensors, etc.). Concerning this, the statistical analysis of the samples reveals the impact of the sensor range on the reliability of the traces. In addition, the study evidences the importance of the selection of the ADLs and the need of categorizing the ADLs depending on the intensity of the movements in order to evaluate the capability of a certain detection algorithm to discriminate falls from ADLs.

  8. Clusterflock: a flocking algorithm for isolating congruent phylogenomic datasets.

    Science.gov (United States)

    Narechania, Apurva; Baker, Richard; DeSalle, Rob; Mathema, Barun; Kolokotronis, Sergios-Orestis; Kreiswirth, Barry; Planet, Paul J

    2016-10-24

    Collective animal behavior, such as the flocking of birds or the shoaling of fish, has inspired a class of algorithms designed to optimize distance-based clusters in various applications, including document analysis and DNA microarrays. In a flocking model, individual agents respond only to their immediate environment and move according to a few simple rules. After several iterations the agents self-organize, and clusters emerge without the need for partitional seeds. In addition to its unsupervised nature, flocking offers several computational advantages, including the potential to reduce the number of required comparisons. In the tool presented here, Clusterflock, we have implemented a flocking algorithm designed to locate groups (flocks) of orthologous gene families (OGFs) that share an evolutionary history. Pairwise distances that measure phylogenetic incongruence between OGFs guide flock formation. We tested this approach on several simulated datasets by varying the number of underlying topologies, the proportion of missing data, and evolutionary rates, and show that in datasets containing high levels of missing data and rate heterogeneity, Clusterflock outperforms other well-established clustering techniques. We also verified its utility on a known, large-scale recombination event in Staphylococcus aureus. By isolating sets of OGFs with divergent phylogenetic signals, we were able to pinpoint the recombined region without forcing a pre-determined number of groupings or defining a pre-determined incongruence threshold. Clusterflock is an open-source tool that can be used to discover horizontally transferred genes, recombined areas of chromosomes, and the phylogenetic 'core' of a genome. Although we used it here in an evolutionary context, it is generalizable to any clustering problem. Users can write extensions to calculate any distance metric on the unit interval, and can use these distances to 'flock' any type of data.

  9. The SAIL databank: linking multiple health and social care datasets.

    Science.gov (United States)

    Lyons, Ronan A; Jones, Kerina H; John, Gareth; Brooks, Caroline J; Verplancke, Jean-Philippe; Ford, David V; Brown, Ginevra; Leake, Ken

    2009-01-16

    Vast amounts of data are collected about patients and service users in the course of health and social care service delivery. Electronic data systems for patient records have the potential to revolutionise service delivery and research. But in order to achieve this, it is essential that the ability to link the data at the individual record level be retained whilst adhering to the principles of information governance. The SAIL (Secure Anonymised Information Linkage) databank has been established using disparate datasets, and over 500 million records from multiple health and social care service providers have been loaded to date, with further growth in progress. Having established the infrastructure of the databank, the aim of this work was to develop and implement an accurate matching process to enable the assignment of a unique Anonymous Linking Field (ALF) to person-based records to make the databank ready for record-linkage research studies. An SQL-based matching algorithm (MACRAL, Matching Algorithm for Consistent Results in Anonymised Linkage) was developed for this purpose. Firstly the suitability of using a valid NHS number as the basis of a unique identifier was assessed using MACRAL. Secondly, MACRAL was applied in turn to match primary care, secondary care and social services datasets to the NHS Administrative Register (NHSAR), to assess the efficacy of this process, and the optimum matching technique. The validation of using the NHS number yielded specificity values > 99.8% and sensitivity values > 94.6% using probabilistic record linkage (PRL) at the 50% threshold, and error rates were SAIL databank represents a research-ready platform for record-linkage studies.

  10. Analysis of Public Datasets for Wearable Fall Detection Systems

    Directory of Open Access Journals (Sweden)

    Eduardo Casilari

    2017-06-01

    Full Text Available Due to the boom of wireless handheld devices such as smartwatches and smartphones, wearable Fall Detection Systems (FDSs have become a major focus of attention among the research community during the last years. The effectiveness of a wearable FDS must be contrasted against a wide variety of measurements obtained from inertial sensors during the occurrence of falls and Activities of Daily Living (ADLs. In this regard, the access to public databases constitutes the basis for an open and systematic assessment of fall detection techniques. This paper reviews and appraises twelve existing available data repositories containing measurements of ADLs and emulated falls envisaged for the evaluation of fall detection algorithms in wearable FDSs. The analysis of the found datasets is performed in a comprehensive way, taking into account the multiple factors involved in the definition of the testbeds deployed for the generation of the mobility samples. The study of the traces brings to light the lack of a common experimental benchmarking procedure and, consequently, the large heterogeneity of the datasets from a number of perspectives (length and number of samples, typology of the emulated falls and ADLs, characteristics of the test subjects, features and positions of the sensors, etc.. Concerning this, the statistical analysis of the samples reveals the impact of the sensor range on the reliability of the traces. In addition, the study evidences the importance of the selection of the ADLs and the need of categorizing the ADLs depending on the intensity of the movements in order to evaluate the capability of a certain detection algorithm to discriminate falls from ADLs.

  11. A high quality finger vascular pattern dataset collected using a custom designed capturing device

    NARCIS (Netherlands)

    Ton, B.T.; Veldhuis, Raymond N.J.

    2013-01-01

    The number of finger vascular pattern datasets available for the research community is scarce, therefore a new finger vascular pattern dataset containing 1440 images is prsented. This dataset is unique in its kind as the images are of high resolution and have a known pixel density. Furthermore this

  12. Something From Nothing (There): Collecting Global IPv6 Datasets from DNS

    NARCIS (Netherlands)

    Fiebig, T.; Borgolte, Kevin; Hao, Shuang; Kruegel, Christopher; Vigna, Giovanny; Spring, Neil; Riley, George F.

    2017-01-01

    Current large-scale IPv6 studies mostly rely on non-public datasets, asmost public datasets are domain specific. For instance, traceroute-based datasetsare biased toward network equipment. In this paper, we present a new methodologyto collect IPv6 address datasets that does not require access to

  13. An Efficient Approach to Mining Maximal Contiguous Frequent Patterns from Large DNA Sequence Databases

    Directory of Open Access Journals (Sweden)

    Md. Rezaul Karim

    2012-03-01

    Full Text Available Mining interesting patterns from DNA sequences is one of the most challenging tasks in bioinformatics and computational biology. Maximal contiguous frequent patterns are preferable for expressing the function and structure of DNA sequences and hence can capture the common data characteristics among related sequences. Biologists are interested in finding frequent orderly arrangements of motifs that are responsible for similar expression of a group of genes. In order to reduce mining time and complexity, however, most existing sequence mining algorithms either focus on finding short DNA sequences or require explicit specification of sequence lengths in advance. The challenge is to find longer sequences without specifying sequence lengths in advance. In this paper, we propose an efficient approach to mining maximal contiguous frequent patterns from large DNA sequence datasets. The experimental results show that our proposed approach is memory-efficient and mines maximal contiguous frequent patterns within a reasonable time.

  14. Bacterial whole genome-based phylogeny: construction of a new benchmarking dataset and assessment of some existing methods.

    Science.gov (United States)

    Ahrenfeldt, Johanne; Skaarup, Carina; Hasman, Henrik; Pedersen, Anders Gorm; Aarestrup, Frank Møller; Lund, Ole

    2017-01-05

    Whole genome sequencing (WGS) is increasingly used in diagnostics and surveillance of infectious diseases. A major application for WGS is to use the data for identifying outbreak clusters, and there is therefore a need for methods that can accurately and efficiently infer phylogenies from sequencing reads. In the present study we describe a new dataset that we have created for the purpose of benchmarking such WGS-based methods for epidemiological data, and also present an analysis where we use the data to compare the performance of some current methods. Our aim was to create a benchmark data set that mimics sequencing data of the sort that might be collected during an outbreak of an infectious disease. This was achieved by letting an E. coli hypermutator strain grow in the lab for 8 consecutive days, each day splitting the culture in two while also collecting samples for sequencing. The result is a data set consisting of 101 whole genome sequences with known phylogenetic relationship. Among the sequenced samples 51 correspond to internal nodes in the phylogeny because they are ancestral, while the remaining 50 correspond to leaves. We also used the newly created data set to compare three different online available methods that infer phylogenies from whole-genome sequencing reads: NDtree, CSI Phylogeny and REALPHY. One complication when comparing the output of these methods with the known phylogeny is that phylogenetic methods typically build trees where all observed sequences are placed as leafs, even though some of them are in fact ancestral. We therefore devised a method for post processing the inferred trees by collapsing short branches (thus relocating some leafs to internal nodes), and also present two new measures of tree similarity that takes into account the identity of both internal and leaf nodes. Based on this analysis we find that, among the investigated methods, CSI Phylogeny had the best performance, correctly identifying 73% of all branches in the

  15. Privacy preserving data anonymization of spontaneous ADE reporting system dataset.

    Science.gov (United States)

    Lin, Wen-Yang; Yang, Duen-Chuan; Wang, Jie-Teng

    2016-07-18

    To facilitate long-term safety surveillance of marketing drugs, many spontaneously reporting systems (SRSs) of ADR events have been established world-wide. Since the data collected by SRSs contain sensitive personal health information that should be protected to prevent the identification of individuals, it procures the issue of privacy preserving data publishing (PPDP), that is, how to sanitize (anonymize) raw data before publishing. Although much work has been done on PPDP, very few studies have focused on protecting privacy of SRS data and none of the anonymization methods is favorable for SRS datasets, due to which contain some characteristics such as rare events, multiple individual records, and multi-valued sensitive attributes. We propose a new privacy model called MS(k, θ (*) )-bounding for protecting published spontaneous ADE reporting data from privacy attacks. Our model has the flexibility of varying privacy thresholds, i.e., θ (*) , for different sensitive values and takes the characteristics of SRS data into consideration. We also propose an anonymization algorithm for sanitizing the raw data to meet the requirements specified through the proposed model. Our algorithm adopts a greedy-based clustering strategy to group the records into clusters, conforming to an innovative anonymization metric aiming to minimize the privacy risk as well as maintain the data utility for ADR detection. Empirical study was conducted using FAERS dataset from 2004Q1 to 2011Q4. We compared our model with four prevailing methods, including k-anonymity, (X, Y)-anonymity, Multi-sensitive l-diversity, and (α, k)-anonymity, evaluated via two measures, Danger Ratio (DR) and Information Loss (IL), and considered three different scenarios of threshold setting for θ (*) , including uniform setting, level-wise setting and frequency-based setting. We also conducted experiments to inspect the impact of anonymized data on the strengths of discovered ADR signals. With all three

  16. Standardization of GIS datasets for emergency preparedness of NPPs

    International Nuclear Information System (INIS)

    Saindane, Shashank S.; Suri, M.M.K.; Otari, Anil; Pradeepkumar, K.S.

    2012-01-01

    Probability of a major nuclear accident which can lead to large scale release of radioactivity into environment is extremely small by the incorporation of safety systems and defence-in-depth philosophy. Nevertheless emergency preparedness for implementation of counter measures to reduce the consequences are required for all major nuclear facilities. Iodine prophylaxis, Sheltering, evacuation etc. are protective measures to be implemented for members of public in the unlikely event of any significant releases from nuclear facilities. Bhabha Atomic Research Centre has developed a GIS supported Nuclear Emergency Preparedness Program. Preparedness for Response to Nuclear emergencies needs geographical details of the affected locations specially Nuclear Power Plant Sites and nearby public domain. Geographical information system data sets which the planners are looking for will have appropriate details in order to take decision and mobilize the resources in time and follow the Standard Operating Procedures. Maps are 2-dimensional representations of our real world and GIS makes it possible to manipulate large amounts of geo-spatially referenced data and convert it into information. This has become an integral part of the nuclear emergency preparedness and response planning. This GIS datasets consisting of layers such as village settlements, roads, hospitals, police stations, shelters etc. is standardized and effectively used during the emergency. The paper focuses on the need of standardization of GIS datasets which in turn can be used as a tool to display and evaluate the impact of standoff distances and selected zones in community planning. It will also highlight the database specifications which will help in fast processing of data and analysis to derive useful and helpful information. GIS has the capability to store, manipulate, analyze and display the large amount of required spatial and tabular data. This study intends to carry out a proper response and preparedness

  17. Forest restoration: a global dataset for biodiversity and vegetation structure.

    Science.gov (United States)

    Crouzeilles, Renato; Ferreira, Mariana S; Curran, Michael

    2016-08-01

    Restoration initiatives are becoming increasingly applied around the world. Billions of dollars have been spent on ecological restoration research and initiatives, but restoration outcomes differ widely among these initiatives in part due to variable socioeconomic and ecological contexts. Here, we present the most comprehensive dataset gathered to date on forest restoration. It encompasses 269 primary studies across 221 study landscapes in 53 countries and contains 4,645 quantitative comparisons between reference ecosystems (e.g., old-growth forest) and degraded or restored ecosystems for five taxonomic groups (mammals, birds, invertebrates, herpetofauna, and plants) and five measures of vegetation structure reflecting different ecological processes (cover, density, height, biomass, and litter). We selected studies that (1) were conducted in forest ecosystems; (2) had multiple replicate sampling sites to measure indicators of biodiversity and/or vegetation structure in reference and restored and/or degraded ecosystems; and (3) used less-disturbed forests as a reference to the ecosystem under study. We recorded (1) latitude and longitude; (2) study year; (3) country; (4) biogeographic realm; (5) past disturbance type; (6) current disturbance type; (7) forest conversion class; (8) restoration activity; (9) time that a system has been disturbed; (10) time elapsed since restoration started; (11) ecological metric used to assess biodiversity; and (12) quantitative value of the ecological metric of biodiversity and/or vegetation structure for reference and restored and/or degraded ecosystems. These were the most common data available in the selected studies. We also estimated forest cover and configuration in each study landscape using a recently developed 1 km consensus land cover dataset. We measured forest configuration as the (1) mean size of all forest patches; (2) size of the largest forest patch; and (3) edge:area ratio of forest patches. Global analyses of the

  18. BanglaLekha-Isolated: A multi-purpose comprehensive dataset of Handwritten Bangla Isolated characters

    Directory of Open Access Journals (Sweden)

    Mithun Biswas

    2017-06-01

    Full Text Available BanglaLekha-Isolated, a Bangla handwritten isolated character dataset is presented in this article. This dataset contains 84 different characters comprising of 50 Bangla basic characters, 10 Bangla numerals and 24 selected compound characters. 2000 handwriting samples for each of the 84 characters were collected, digitized and pre-processed. After discarding mistakes and scribbles, 1,66,105 handwritten character images were included in the final dataset. The dataset also includes labels indicating the age and the gender of the subjects from whom the samples were collected. This dataset could be used not only for optical handwriting recognition research but also to explore the influence of gender and age on handwriting. The dataset is publicly available at https://data.mendeley.com/datasets/hf6sf8zrkc/2.

  19. A Research Graph dataset for connecting research data repositories using RD-Switchboard.

    Science.gov (United States)

    Aryani, Amir; Poblet, Marta; Unsworth, Kathryn; Wang, Jingbo; Evans, Ben; Devaraju, Anusuriya; Hausstein, Brigitte; Klas, Claus-Peter; Zapilko, Benjamin; Kaplun, Samuele

    2018-05-29

    This paper describes the open access graph dataset that shows the connections between Dryad, CERN, ANDS and other international data repositories to publications and grants across multiple research data infrastructures. The graph dataset was created using the Research Graph data model and the Research Data Switchboard (RD-Switchboard), a collaborative project by the Research Data Alliance DDRI Working Group (DDRI WG) with the aim to discover and connect the related research datasets based on publication co-authorship or jointly funded grants. The graph dataset allows researchers to trace and follow the paths to understanding a body of work. By mapping the links between research datasets and related resources, the graph dataset improves both their discovery and visibility, while avoiding duplicate efforts in data creation. Ultimately, the linked datasets may spur novel ideas, facilitate reproducibility and re-use in new applications, stimulate combinatorial creativity, and foster collaborations across institutions.

  20. Penerapan Reverse Engineering Dalam Penentuan Pola Interaksi Sequence Diagram Pada Sampel Aplikasi Android

    Directory of Open Access Journals (Sweden)

    Vierdy Sulfianto Rahmadani

    2015-04-01

    Full Text Available The purpose of this research is to apply the application of reverse engineering to determine interaction patterns of the Sequence diagram that can be used by system analysts as a template for designing UML sequence diagrams. Sample applications from android are used as dataset for reverse engineering and pattern identification. The first step is collecting application datasets. The next stage is identifying the features and applications activity, reverse engineering to obtain a sequence diagram model, and then synthesize all of the models into an interaction pattern of sequence diagram. The final step is to test the patterns by implementing it in an application development case stud. The evaluation results concludes that interaction patterns of sequence diagram designs obtained in reverse engineering steps is able to be implemented in software development that contained similar features with the obtained features in this research.

  1. Nonlinear Synchronization for Automatic Learning of 3D Pose Variability in Human Motion Sequences

    Directory of Open Access Journals (Sweden)

    Mozerov M

    2010-01-01

    Full Text Available A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.

  2. Artificial frame filling using adaptive neural fuzzy inference system for particle image velocimetry dataset

    Science.gov (United States)

    Akdemir, Bayram; Doǧan, Sercan; Aksoy, Muharrem H.; Canli, Eyüp; Özgören, Muammer

    2015-03-01

    Liquid behaviors are very important for many areas especially for Mechanical Engineering. Fast camera is a way to observe and search the liquid behaviors. Camera traces the dust or colored markers travelling in the liquid and takes many pictures in a second as possible as. Every image has large data structure due to resolution. For fast liquid velocity, there is not easy to evaluate or make a fluent frame after the taken images. Artificial intelligence has much popularity in science to solve the nonlinear problems. Adaptive neural fuzzy inference system is a common artificial intelligence in literature. Any particle velocity in a liquid has two dimension speed and its derivatives. Adaptive Neural Fuzzy Inference System has been used to create an artificial frame between previous and post frames as offline. Adaptive neural fuzzy inference system uses velocities and vorticities to create a crossing point vector between previous and post points. In this study, Adaptive Neural Fuzzy Inference System has been used to fill virtual frames among the real frames in order to improve image continuity. So this evaluation makes the images much understandable at chaotic or vorticity points. After executed adaptive neural fuzzy inference system, the image dataset increase two times and has a sequence as virtual and real, respectively. The obtained success is evaluated using R2 testing and mean squared error. R2 testing has a statistical importance about similarity and 0.82, 0.81, 0.85 and 0.8 were obtained for velocities and derivatives, respectively.

  3. Natural history bycatch: a pipeline for identifying metagenomic sequences in RADseq data

    Directory of Open Access Journals (Sweden)

    Iris Holmes

    2018-04-01

    Full Text Available Background Reduced representation genomic datasets are increasingly becoming available from a variety of organisms. These datasets do not target specific genes, and so may contain sequences from parasites and other organisms present in the target tissue sample. In this paper, we demonstrate that (1 RADseq datasets can be used for exploratory analysis of tissue-specific metagenomes, and (2 tissue collections house complete metagenomic communities, which can be investigated and quantified by a variety of techniques. Methods We present an exploratory method for mining metagenomic “bycatch” sequences from a range of host tissue types. We use a combination of the pyRAD assembly pipeline, NCBI’s blastn software, and custom R scripts to isolate metagenomic sequences from RADseq type datasets. Results When we focus on sequences that align with existing references in NCBI’s GenBank, we find that between three and five percent of identifiable double-digest restriction site associated DNA (ddRAD sequences from host tissue samples are from phyla to contain known blood parasites. In addition to tissue samples, we examine ddRAD sequences from metagenomic DNA extracted snake and lizard hind-gut samples. We find that the sequences recovered from these samples match with expected bacterial and eukaryotic gut microbiome phyla. Discussion Our results suggest that (1 museum tissue banks originally collected for host DNA archiving are also preserving valuable parasite and microbiome communities, (2 that publicly available RADseq datasets may include metagenomic sequences that could be explored, and (3 that restriction site approaches are a useful exploratory technique to identify microbiome lineages that could be missed by primer-based approaches.

  4. ESPRIT-Forest: Parallel clustering of massive amplicon sequence data in subquadratic time.

    Science.gov (United States)

    Cai, Yunpeng; Zheng, Wei; Yao, Jin; Yang, Yujie; Mai, Volker; Mao, Qi; Sun, Yijun

    2017-04-01

    The rapid development of sequencing technology has led to an explosive accumulation of genomic sequence data. Clustering is often the first step to perform in sequence analysis, and hierarchical clustering is one of the most commonly used approaches for this purpose. However, it is currently computationally expensive to perform hierarchical clustering of extremely large sequence datasets due to its quadratic time and space complexities. In this paper we developed a new algorithm called ESPRIT-Forest for parallel hierarchical clustering of sequences. The algorithm achieves subquadratic time and space complexity and maintains a high clustering accuracy comparable to the standard method. The basic idea is to organize sequences into a pseudo-metric based partitioning tree for sub-linear time searching of nearest neighbors, and then use a new multiple-pair merging criterion to construct clusters in parallel using multiple threads. The new algorithm was tested on the human microbiome project (HMP) dataset, currently one of the largest published microbial 16S rRNA sequence dataset. Our experiment demonstrated that with the power of parallel computing it is now compu- tationally feasible to perform hierarchical clustering analysis of tens of millions of sequences. The software is available at http://www.acsu.buffalo.edu/∼yijunsun/lab/ESPRIT-Forest.html.

  5. Provenance of Earth Science Datasets - How Deep Should One Go?

    Science.gov (United States)

    Ramapriyan, H.; Manipon, G. J. M.; Aulenbach, S.; Duggan, B.; Goldstein, J.; Hua, H.; Tan, D.; Tilmes, C.; Wilson, B. D.; Wolfe, R.; Zednik, S.

    2015-12-01

    For credibility of scientific research, transparency and reproducibility are essential. This fundamental tenet has been emphasized for centuries, and has been receiving increased attention in recent years. The Office of Management and Budget (2002) addressed reproducibility and other aspects of quality and utility of information from federal agencies. Specific guidelines from NASA (2002) are derived from the above. According to these guidelines, "NASA requires a higher standard of quality for information that is considered influential. Influential scientific, financial, or statistical information is defined as NASA information that, when disseminated, will have or does have clear and substantial impact on important public policies or important private sector decisions." For information to be compliant, "the information must be transparent and reproducible to the greatest possible extent." We present how the principles of transparency and reproducibility have been applied to NASA data supporting the Third National Climate Assessment (NCA3). The depth of trace needed of provenance of data used to derive conclusions in NCA3 depends on how the data were used (e.g., qualitatively or quantitatively). Given that the information is diligently maintained in the agency archives, it is possible to trace from a figure in the publication through the datasets, specific files, algorithm versions, instruments used for data collection, and satellites, as well as the individuals and organizations involved in each step. Such trace back permits transparency and reproducibility.

  6. A dataset from bottom trawl survey around Taiwan

    Directory of Open Access Journals (Sweden)

    Kwang-tsao Shao

    2012-05-01

    Full Text Available Bottom trawl fishery is one of the most important coastal fisheries in Taiwan both in production and economic values. However, its annual production started to decline due to overfishing since the 1980s. Its bycatch problem also damages the fishery resource seriously. Thus, the government banned the bottom fishery within 3 nautical miles along the shoreline in 1989. To evaluate the effectiveness of this policy, a four year survey was conducted from 2000–2003, in the waters around Taiwan and Penghu (Pescadore Islands, one region each year respectively. All fish specimens collected from trawling were brought back to lab for identification, individual number count and body weight measurement. These raw data have been integrated and established in Taiwan Fish Database (http://fishdb.sinica.edu.tw. They have also been published through TaiBIF (http://taibif.tw, FishBase and GBIF (website see below. This dataset contains 631 fish species and 3,529 records, making it the most complete demersal fish fauna and their temporal and spatial distributional data on the soft marine habitat in Taiwan.

  7. Integrated interpretation of overlapping AEM datasets achieved through standardisation

    Science.gov (United States)

    Sørensen, Camilla C.; Munday, Tim; Heinson, Graham

    2015-12-01

    Numerous airborne electromagnetic surveys have been acquired in Australia using a variety of systems. It is not uncommon to find two or more surveys covering the same ground, but acquired using different systems and at different times. Being able to combine overlapping datasets and get a spatially coherent resistivity-depth image of the ground can assist geological interpretation, particularly when more subtle geophysical responses are important. Combining resistivity-depth models obtained from the inversion of airborne electromagnetic (AEM) data can be challenging, given differences in system configuration, geometry, flying height and preservation or monitoring of system acquisition parameters such as waveform. In this study, we define and apply an approach to overlapping AEM surveys, acquired by fixed wing and helicopter time domain electromagnetic (EM) systems flown in the vicinity of the Goulds Dam uranium deposit in the Frome Embayment, South Australia, with the aim of mapping the basement geometry and the extent of the Billeroo palaeovalley. Ground EM soundings were used to standardise the AEM data, although results indicated that only data from the REPTEM system needed to be corrected to bring the two surveys into agreement and to achieve coherent spatial resistivity-depth intervals.

  8. A global dataset of sub-daily rainfall indices

    Science.gov (United States)

    Fowler, H. J.; Lewis, E.; Blenkinsop, S.; Guerreiro, S.; Li, X.; Barbero, R.; Chan, S.; Lenderink, G.; Westra, S.

    2017-12-01

    It is still uncertain how hydrological extremes will change with global warming as we do not fully understand the processes that cause extreme precipitation under current climate variability. The INTENSE project is using a novel and fully-integrated data-modelling approach to provide a step-change in our understanding of the nature and drivers of global precipitation extremes and change on societally relevant timescales, leading to improved high-resolution climate model representation of extreme rainfall processes. The INTENSE project is in conjunction with the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges Project (GEWEX) Science questions. A new global sub-daily precipitation dataset has been constructed (data collection is ongoing). Metadata for each station has been calculated, detailing record lengths, missing data, station locations. A set of global hydroclimatic indices have been produced based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. This will provide a unique global data resource on sub-daily precipitation whose derived indices will be freely available to the wider scientific community.

  9. The Centennial Trends Greater Horn of Africa precipitation dataset

    Science.gov (United States)

    Funk, Chris; Nicholson, Sharon E.; Landsfeld, Martin F.; Klotter, Douglas; Peterson, Pete J.; Harrison, Laura

    2015-01-01

    East Africa is a drought prone, food and water insecure region with a highly variable climate. This complexity makes rainfall estimation challenging, and this challenge is compounded by low rain gauge densities and inhomogeneous monitoring networks. The dearth of observations is particularly problematic over the past decade, since the number of records in globally accessible archives has fallen precipitously. This lack of data coincides with an increasing scientific and humanitarian need to place recent seasonal and multi-annual East African precipitation extremes in a deep historic context. To serve this need, scientists from the UC Santa Barbara Climate Hazards Group and Florida State University have pooled their station archives and expertise to produce a high quality gridded ‘Centennial Trends’ precipitation dataset. Additional observations have been acquired from the national meteorological agencies and augmented with data provided by other universities. Extensive quality control of the data was carried out and seasonal anomalies interpolated using kriging. This paper documents the CenTrends methodology and data.

  10. Dataset on daytime outdoor thermal comfort for Belo Horizonte, Brazil.

    Science.gov (United States)

    Hirashima, Simone Queiroz da Silveira; Assis, Eleonora Sad de; Nikolopoulou, Marialena

    2016-12-01

    This dataset describe microclimatic parameters of two urban open public spaces in the city of Belo Horizonte, Brazil; physiological equivalent temperature (PET) index values and the related subjective responses of interviewees regarding thermal sensation perception and preference and thermal comfort evaluation. Individuals and behavioral characteristics of respondents were also presented. Data were collected at daytime, in summer and winter, 2013. Statistical treatment of this data was firstly presented in a PhD Thesis ("Percepção sonora e térmica e avaliação de conforto em espaços urbanos abertos do município de Belo Horizonte - MG, Brasil" (Hirashima, 2014) [1]), providing relevant information on thermal conditions in these locations and on thermal comfort assessment. Up to now, this data was also explored in the article "Daytime Thermal Comfort in Urban Spaces: A Field Study in Brazil" (Hirashima et al., in press) [2]. These references are recommended for further interpretation and discussion.

  11. Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets

    KAUST Repository

    Sun, Ying

    2014-11-07

    For Gaussian process models, likelihood based methods are often difficult to use with large irregularly spaced spatial datasets, because exact calculations of the likelihood for n observations require O(n3) operations and O(n2) memory. Various approximation methods have been developed to address the computational difficulties. In this paper, we propose new unbiased estimating equations based on score equation approximations that are both computationally and statistically efficient. We replace the inverse covariance matrix that appears in the score equations by a sparse matrix to approximate the quadratic forms, then set the resulting quadratic forms equal to their expected values to obtain unbiased estimating equations. The sparse matrix is constructed by a sparse inverse Cholesky approach to approximate the inverse covariance matrix. The statistical efficiency of the resulting unbiased estimating equations are evaluated both in theory and by numerical studies. Our methods are applied to nearly 90,000 satellite-based measurements of water vapor levels over a region in the Southeast Pacific Ocean.

  12. Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets

    KAUST Repository

    Sun, Ying; Stein, Michael L.

    2014-01-01

    For Gaussian process models, likelihood based methods are often difficult to use with large irregularly spaced spatial datasets, because exact calculations of the likelihood for n observations require O(n3) operations and O(n2) memory. Various approximation methods have been developed to address the computational difficulties. In this paper, we propose new unbiased estimating equations based on score equation approximations that are both computationally and statistically efficient. We replace the inverse covariance matrix that appears in the score equations by a sparse matrix to approximate the quadratic forms, then set the resulting quadratic forms equal to their expected values to obtain unbiased estimating equations. The sparse matrix is constructed by a sparse inverse Cholesky approach to approximate the inverse covariance matrix. The statistical efficiency of the resulting unbiased estimating equations are evaluated both in theory and by numerical studies. Our methods are applied to nearly 90,000 satellite-based measurements of water vapor levels over a region in the Southeast Pacific Ocean.

  13. Challenges and Experiences of Building Multidisciplinary Datasets across Cultures

    Science.gov (United States)

    Jamiyansharav, K.; Laituri, M.; Fernandez-Gimenez, M.; Fassnacht, S. R.; Venable, N. B. H.; Allegretti, A. M.; Reid, R.; Baival, B.; Jamsranjav, C.; Ulambayar, T.; Linn, S.; Angerer, J.

    2017-12-01

    Efficient data sharing and management are key challenges to multidisciplinary scientific research. These challenges are further complicated by adding a multicultural component. We address the construction of a complex database for social-ecological analysis in Mongolia. Funded by the National Science Foundation (NSF) Dynamics of Coupled Natural and Human (CNH) Systems, the Mongolian Rangelands and Resilience (MOR2) project focuses on the vulnerability of Mongolian pastoral systems to climate change and adaptive capacity. The MOR2 study spans over three years of fieldwork in 36 paired districts (Soum) from 18 provinces (Aimag) of Mongolia that covers steppe, mountain forest steppe, desert steppe and eastern steppe ecological zones. Our project team is composed of hydrologists, social scientists, geographers, and ecologists. The MOR2 database includes multiple ecological, social, meteorological, geospatial and hydrological datasets, as well as archives of original data and survey in multiple formats. Managing this complex database requires significant organizational skills, attention to detail and ability to communicate within collective team members from diverse disciplines and across multiple institutions in the US and Mongolia. We describe the database's rich content, organization, structure and complexity. We discuss lessons learned, best practices and recommendations for complex database management, sharing, and archiving in creating a cross-cultural and multi-disciplinary database.

  14. Automated Fault Interpretation and Extraction using Improved Supplementary Seismic Datasets

    Science.gov (United States)

    Bollmann, T. A.; Shank, R.

    2017-12-01

    During the interpretation of seismic volumes, it is necessary to interpret faults along with horizons of interest. With the improvement of technology, the interpretation of faults can be expedited with the aid of different algorithms that create supplementary seismic attributes, such as semblance and coherency. These products highlight discontinuities, but still need a large amount of human interaction to interpret faults and are plagued by noise and stratigraphic discontinuities. Hale (2013) presents a method to improve on these datasets by creating what is referred to as a Fault Likelihood volume. In general, these volumes contain less noise and do not emphasize stratigraphic features. Instead, planar features within a specified strike and dip range are highlighted. Once a satisfactory Fault Likelihood Volume is created, extraction of fault surfaces is much easier. The extracted fault surfaces are then exported to interpretation software for QC. Numerous software packages have implemented this methodology with varying results. After investigating these platforms, we developed a preferred Automated Fault Interpretation workflow.

  15. Privacy-preserving record linkage on large real world datasets.

    Science.gov (United States)

    Randall, Sean M; Ferrante, Anna M; Boyd, James H; Bauer, Jacqueline K; Semmens, James B

    2014-08-01

    Record linkage typically involves the use of dedicated linkage units who are supplied with personally identifying information to determine individuals from within and across datasets. The personally identifying information supplied to linkage units is separated from clinical information prior to release by data custodians. While this substantially reduces the risk of disclosure of sensitive information, some residual risks still exist and remain a concern for some custodians. In this paper we trial a method of record linkage which reduces privacy risk still further on large real world administrative data. The method uses encrypted personal identifying information (bloom filters) in a probability-based linkage framework. The privacy preserving linkage method was tested on ten years of New South Wales (NSW) and Western Australian (WA) hospital admissions data, comprising in total over 26 million records. No difference in linkage quality was found when the results were compared to traditional probabilistic methods using full unencrypted personal identifiers. This presents as a possible means of reducing privacy risks related to record linkage in population level research studies. It is hoped that through adaptations of this method or similar privacy preserving methods, risks related to information disclosure can be reduced so that the benefits of linked research taking place can be fully realised. Copyright © 2013 Elsevier Inc. All rights reserved.

  16. Structural dataset for the PPARγ V290M mutant

    Directory of Open Access Journals (Sweden)

    Ana C. Puhl

    2016-06-01

    Full Text Available Loss-of-function mutation V290M in the ligand-binding domain of the peroxisome proliferator activated receptor γ (PPARγ is associated with a ligand resistance syndrome (PLRS, characterized by partial lipodystrophy and severe insulin resistance. In this data article we discuss an X-ray diffraction dataset that yielded the structure of PPARγ LBD V290M mutant refined at 2.3 Å resolution, that allowed building of 3D model of the receptor mutant with high confidence and revealed continuous well-defined electron density for the partial agonist diclofenac bound to hydrophobic pocket of the PPARγ. These structural data provide significant insights into molecular basis of PLRS caused by V290M mutation and are correlated with the receptor disability of rosiglitazone binding and increased affinity for corepressors. Furthermore, our structural evidence helps to explain clinical observations which point out to a failure to restore receptor function by the treatment with a full agonist of PPARγ, rosiglitazone.

  17. Consed: a graphical editor for next-generation sequencing

    OpenAIRE

    Gordon, David; Green, Phil

    2013-01-01

    Summary: The rapid growth of DNA sequencing throughput in recent years implies that graphical interfaces for viewing and correcting errors must now handle large numbers of reads, efficiently pinpoint regions of interest and automate as many tasks as possible. We have adapted consed to reflect this. To allow full-feature editing of large datasets while keeping memory requirements low, we developed a viewer, bamScape, that reads billion-read BAM files, identifies and displays problem areas for ...

  18. Sequences for Student Investigation

    Science.gov (United States)

    Barton, Jeffrey; Feil, David; Lartigue, David; Mullins, Bernadette

    2004-01-01

    We describe two classes of sequences that give rise to accessible problems for undergraduate research. These problems may be understood with virtually no prerequisites and are well suited for computer-aided investigation. The first sequence is a variation of one introduced by Stephen Wolfram in connection with his study of cellular automata. The…

  19. Bayesian Correlation Analysis for Sequence Count Data.

    Directory of Open Access Journals (Sweden)

    Daniel Sánchez-Taltavull

    Full Text Available Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities' measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low-especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities' signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset.

  20. Sequence History Update Tool

    Science.gov (United States)

    Khanampompan, Teerapat; Gladden, Roy; Fisher, Forest; DelGuercio, Chris

    2008-01-01

    The Sequence History Update Tool performs Web-based sequence statistics archiving for Mars Reconnaissance Orbiter (MRO). Using a single UNIX command, the software takes advantage of sequencing conventions to automatically extract the needed statistics from multiple files. This information is then used to populate a PHP database, which is then seamlessly formatted into a dynamic Web page. This tool replaces a previous tedious and error-prone process of manually editing HTML code to construct a Web-based table. Because the tool manages all of the statistics gathering and file delivery to and from multiple data sources spread across multiple servers, there is also a considerable time and effort savings. With the use of The Sequence History Update Tool what previously took minutes is now done in less than 30 seconds, and now provides a more accurate archival record of the sequence commanding for MRO.

  1. A time warping approach to multiple sequence alignment.

    Science.gov (United States)

    Arribas-Gil, Ana; Matias, Catherine

    2017-04-25

    We propose an approach for multiple sequence alignment (MSA) derived from the dynamic time warping viewpoint and recent techniques of curve synchronization developed in the context of functional data analysis. Starting from pairwise alignments of all the sequences (viewed as paths in a certain space), we construct a median path that represents the MSA we are looking for. We establish a proof of concept that our method could be an interesting ingredient to include into refined MSA techniques. We present a simple synthetic experiment as well as the study of a benchmark dataset, together with comparisons with 2 widely used MSA softwares.

  2. Advancing analytical algorithms and pipelines for billions of microbial sequences.

    Science.gov (United States)

    Gonzalez, Antonio; Knight, Rob

    2012-02-01

    The vast number of microbial sequences resulting from sequencing efforts using new technologies require us to re-assess currently available analysis methodologies and tools. Here we describe trends in the development and distribution of software for analyzing microbial sequence data. We then focus on one widely used set of methods, dimensionality reduction techniques, which allow users to summarize and compare these vast datasets. We conclude by emphasizing the utility of formal software engineering methods for the development of computational biology tools, and the need for new algorithms for comparing microbial communities. Such large-scale comparisons will allow us to fulfill the dream of rapid integration and comparison of microbial sequence data sets, in a replicable analytical environment, in order to describe the microbial world we inhabit. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. Sequence Synopsis: Optimize Visual Summary of Temporal Event Data.

    Science.gov (United States)

    Chen, Yuanzhe; Xu, Panpan; Ren, Liu

    2018-01-01

    Event sequences analysis plays an important role in many application domains such as customer behavior analysis, electronic health record analysis and vehicle fault diagnosis. Real-world event sequence data is often noisy and complex with high event cardinality, making it a challenging task to construct concise yet comprehensive overviews for such data. In this paper, we propose a novel visualization technique based on the minimum description length (MDL) principle to construct a coarse-level overview of event sequence data while balancing the information loss in it. The method addresses a fundamental trade-off in visualization design: reducing visual clutter vs. increasing the information content in a visualization. The method enables simultaneous sequence clustering and pattern extraction and is highly tolerant to noises such as missing or additional events in the data. Based on this approach we propose a visual analytics framework with multiple levels-of-detail to facilitate interactive data exploration. We demonstrate the usability and effectiveness of our approach through case studies with two real-world datasets. One dataset showcases a new application domain for event sequence visualization, i.e., fault development path analysis in vehicles for predictive maintenance. We also discuss the strengths and limitations of the proposed method based on user feedback.

  4. Sequencing and annotation of mitochondrial genomes from individual parasitic helminths.

    Science.gov (United States)

    Jex, Aaron R; Littlewood, D Timothy; Gasser, Robin B

    2015-01-01

    Mitochondrial (mt) genomics has significant implications in a range of fundamental areas of parasitology, including evolution, systematics, and population genetics as well as explorations of mt biochemistry, physiology, and function. Mt genomes also provide a rich source of markers to aid molecular epidemiological and ecological studies of key parasites. However, there is still a paucity of information on mt genomes for many metazoan organisms, particularly parasitic helminths, which has often related to challenges linked to sequencing from tiny amounts of material. The advent of next-generation sequencing (NGS) technologies has paved the way for low cost, high-throughput mt genomic research, but there have been obstacles, particularly in relation to post-sequencing assembly and analyses of large datasets. In this chapter, we describe protocols for the efficient amplification and sequencing of mt genomes from small portions of individual helminths, and highlight the utility of NGS platforms to expedite mt genomics. In addition, we recommend approaches for manual or semi-automated bioinformatic annotation and analyses to overcome the bioinformatic "bottleneck" to research in this area. Taken together, these approaches have demonstrated applicability to a range of parasites and provide prospects for using complete mt genomic sequence datasets for large-scale molecular systematic and epidemiological studies. In addition, these methods have broader utility and might be readily adapted to a range of other medium-sized molecular regions (i.e., 10-100 kb), including large genomic operons, and other organellar (e.g., plastid) and viral genomes.

  5. Oil palm mapping for Malaysia using PALSAR-2 dataset

    Science.gov (United States)

    Gong, P.; Qi, C. Y.; Yu, L.; Cracknell, A.

    2016-12-01

    Oil palm is one of the most productive vegetable oil crops in the world. The main oil palm producing areas are distributed in humid tropical areas such as Malaysia, Indonesia, Thailand, western and central Africa, northern South America, and central America. Increasing market demands, high yields and low production costs of palm oil are the primary factors driving large-scale commercial cultivation of oil palm, especially in Malaysia and Indonesia. Global demand for palm oil has grown exponentially during the last 50 years, and the expansion of oil palm plantations is linked directly to the deforestation of natural forests. Satellite remote sensing plays an important role in monitoring expansion of oil palm. However, optical remote sensing images are difficult to acquire in the Tropics because of the frequent occurrence of thick cloud cover. This problem has led to the use of data obtained by synthetic aperture radar (SAR), which is a sensor capable of all-day/all-weather observation for studies in the Tropics. In this study, the ALOS-2 (Advanced Land Observing Satellite) PALSAR-2 (Phased Array type L-band SAR) datasets for year 2015 were used as an input to a support vector machine (SVM) based machine learning algorithm. Oil palm/non-oil palm samples were collected using a hexagonal equal-area sampling design. High-resolution images in Google Earth and PALSAR-2 imagery were used in human photo-interpretation to separate oil palm from others (i.e. cropland, forest, grassland, shrubland, water, hard surface and bareland). The characteristics of oil palms from various aspects, including PALSAR-2 backscattering coefficients (HH, HV), terrain and climate by using this sample set were further explored to post-process the SVM output. The average accuracy of oil palm type is better than 80% in the final oil palm map for Malaysia.

  6. Automatic aortic root segmentation in CTA whole-body dataset

    Science.gov (United States)

    Gao, Xinpei; Kitslaar, Pieter H.; Scholte, Arthur J. H. A.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke; Reiber, Johan H. C.

    2016-03-01

    Trans-catheter aortic valve replacement (TAVR) is an evolving technique for patients with serious aortic stenosis disease. Typically, in this application a CTA data set is obtained of the patient's arterial system from the subclavian artery to the femoral arteries, to evaluate the quality of the vascular access route and analyze the aortic root to determine if and which prosthesis should be used. In this paper, we concentrate on the automated segmentation of the aortic root. The purpose of this study was to automatically segment the aortic root in computed tomography angiography (CTA) datasets to support TAVR procedures. The method in this study includes 4 major steps. First, the patient's cardiac CTA image was resampled to reduce the computation time. Next, the cardiac CTA image was segmented using an atlas-based approach. The most similar atlas was selected from a total of 8 atlases based on its image similarity to the input CTA image. Third, the aortic root segmentation from the previous step was transferred to the patient's whole-body CTA image by affine registration and refined in the fourth step using a deformable subdivision surface model fitting procedure based on image intensity. The pipeline was applied to 20 patients. The ground truth was created by an analyst who semi-automatically corrected the contours of the automatic method, where necessary. The average Dice similarity index between the segmentations of the automatic method and the ground truth was found to be 0.965±0.024. In conclusion, the current results are very promising.

  7. HIV Sequence Compendium 2015

    Energy Technology Data Exchange (ETDEWEB)

    Foley, Brian Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Leitner, Thomas Kenneth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Apetrei, Cristian [Univ. of Pittsburgh, PA (United States); Hahn, Beatrice [Univ. of Pennsylvania, Philadelphia, PA (United States); Mizrachi, Ilene [National Center for Biotechnology Information, Bethesda, MD (United States); Mullins, James [Univ. of Washington, Seattle, WA (United States); Rambaut, Andrew [Univ. of Edinburgh, Scotland (United Kingdom); Wolinsky, Steven [Northwestern Univ., Evanston, IL (United States); Korber, Bette Tina Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-10-05

    This compendium is an annual printed summary of the data contained in the HIV sequence database. We try to present a judicious selection of the data in such a way that it is of maximum utility to HIV researchers. Each of the alignments attempts to display the genetic variability within the different species, groups and subtypes of the virus. This compendium contains sequences published before January 1, 2015. Hence, though it is published in 2015 and called the 2015 Compendium, its contents correspond to the 2014 curated alignments on our website. The number of sequences in the HIV database is still increasing. In total, at the end of 2014, there were 624,121 sequences in the HIV Sequence Database, an increase of 7% since the previous year. This is the first year that the number of new sequences added to the database has decreased compared to the previous year. The number of near complete genomes (>7000 nucleotides) increased to 5834 by end of 2014. However, as in previous years, the compendium alignments contain only a fraction of these. A more complete version of all alignments is available on our website, http://www.hiv.lanl.gov/ content/sequence/NEWALIGN/align.html As always, we are open to complaints and suggestions for improvement. Inquiries and comments regarding the compendium should be addressed to seq-info@lanl.gov.

  8. Mapping sequences by parts

    Directory of Open Access Journals (Sweden)

    Guziolowski Carito

    2007-09-01

    Full Text Available Abstract Background: We present the N-map method, a pairwise and asymmetrical approach which allows us to compare sequences by taking into account evolutionary events that produce shuffled, reversed or repeated elements. Basically, the optimal N-map of a sequence s over a sequence t is the best way of partitioning the first sequence into N parts and placing them, possibly complementary reversed, over the second sequence in order to maximize the sum of their gapless alignment scores. Results: We introduce an algorithm computing an optimal N-map with time complexity O (|s| × |t| × N using O (|s| × |t| × N memory space. Among all the numbers of parts taken in a reasonable range, we select the value N for which the optimal N-map has the most significant score. To evaluate this significance, we study the empirical distributions of the scores of optimal N-maps and show that they can be approximated by normal distributions with a reasonable accuracy. We test the functionality of the approach over random sequences on which we apply artificial evolutionary events. Practical Application: The method is illustrated with four case studies of pairs of sequences involving non-standard evolutionary events.

  9. Predictors of natively unfolded proteins: unanimous consensus score to detect a twilight zone between order and disorder in generic datasets

    Directory of Open Access Journals (Sweden)

    Deiana Antonio

    2010-04-01

    Full Text Available Abstract Background Natively unfolded proteins lack a well defined three dimensional structure but have important biological functions, suggesting a re-assignment of the structure-function paradigm. To assess that a given protein is natively unfolded requires laborious experimental investigations, then reliable sequence-only methods for predicting whether a sequence corresponds to a folded or to an unfolded protein are of interest in fundamental and applicative studies. Many proteins have amino acidic compositions compatible both with the folded and unfolded status, and belong to a twilight zone between order and disorder. This makes difficult a dichotomic classification of protein sequences into folded and natively unfolded ones. In this work we propose an operational method to identify proteins belonging to the twilight zone by combining into a consensus score good performing single predictors of folding. Results In this methodological paper dichotomic folding indexes are considered: hydrophobicity-charge, mean packing, mean pairwise energy, Poodle-W and a new global index, that is called here gVSL2, based on the local disorder predictor VSL2. The performance of these indexes is evaluated on different datasets, in particular on a new dataset composed by 2369 folded and 81 natively unfolded proteins. Poodle-W, gVSL2 and mean pairwise energy have good performance and stability in all the datasets considered and are combined into a strictly unanimous combination score SSU, that leaves proteins unclassified when the consensus of all combined indexes is not reached. The unclassified proteins: i belong to an overlap region in the vector space of amino acidic compositions occupied by both folded and unfolded proteins; ii are composed by approximately the same number of order-promoting and disorder-promoting amino acids; iii have a mean flexibility intermediate between that of folded and that of unfolded proteins. Conclusions Our results show that

  10. Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM

    Directory of Open Access Journals (Sweden)

    Yunyun Liang

    2015-01-01

    Full Text Available Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM. Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS, segmented PsePSSM, and segmented autocovariance transformation (ACT based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640 are adopted in this paper. Then a 700-dimensional (700D feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA. To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

  11. Introduction of a simple-model-based land surface dataset for Europe

    Science.gov (United States)

    Orth, Rene; Seneviratne, Sonia I.

    2015-04-01

    Land surface hydrology can play a crucial role during extreme events such as droughts, floods and even heat waves. We introduce in this study a new hydrological dataset for Europe that consists of soil moisture, runoff and evapotranspiration (ET). It is derived with a simple water balance model (SWBM) forced with precipitation, temperature and net radiation. The SWBM dataset extends over the period 1984-2013 with a daily time step and 0.5° × 0.5° resolution. We employ a novel calibration approach, in which we consider 300 random parameter sets chosen from an observation-based range. Using several independent validation datasets representing soil moisture (or terrestrial water content), ET and streamflow, we identify the best performing parameter set and hence the new dataset. To illustrate its usefulness, the SWBM dataset is compared against several state-of-the-art datasets (ERA-Interim/Land, MERRA-Land, GLDAS-2-Noah, simulations of the Community Land Model Version 4), using all validation datasets as reference. For soil moisture dynamics it outperforms the benchmarks. Therefore the SWBM soil moisture dataset constitutes a reasonable alternative to sparse measurements, little validated model results, or proxy data such as precipitation indices. Also in terms of runoff the SWBM dataset performs well, whereas the evaluation of the SWBM ET dataset is overall satisfactory, but the dynamics are less well captured for this variable. This highlights the limitations of the dataset, as it is based on a simple model that uses uniform parameter values. Hence some processes impacting ET dynamics may not be captured, and quality issues may occur in regions with complex terrain. Even though the SWBM is well calibrated, it cannot replace more sophisticated models; but as their calibration is a complex task the present dataset may serve as a benchmark in future. In addition we investigate the sources of skill of the SWBM dataset and find that the parameter set has a similar

  12. The Colliding Beams Sequencer

    International Nuclear Information System (INIS)

    Johnson, D.E.; Johnson, R.P.

    1989-01-01

    The Colliding Beam Sequencer (CBS) is a computer program used to operate the pbar-p Collider by synchronizing the applications programs and simulating the activities of the accelerator operators during filling and storage. The Sequencer acts as a meta-program, running otherwise stand alone applications programs, to do the set-up, beam transfers, acceleration, low beta turn on, and diagnostics for the transfers and storage. The Sequencer and its operational performance will be described along with its special features which include a periodic scheduler and command logger. 14 refs., 3 figs

  13. Phylogenetic Trees From Sequences

    Science.gov (United States)

    Ryvkin, Paul; Wang, Li-San

    In this chapter, we review important concepts and approaches for phylogeny reconstruction from sequence data.We first cover some basic definitions and properties of phylogenetics, and briefly explain how scientists model sequence evolution and measure sequence divergence. We then discuss three major approaches for phylogenetic reconstruction: distance-based phylogenetic reconstruction, maximum parsimony, and maximum likelihood. In the third part of the chapter, we review how multiple phylogenies are compared by consensus methods and how to assess confidence using bootstrapping. At the end of the chapter are two sections that list popular software packages and additional reading.

  14. Draft genome sequence of two Shingopyxis sp. strains H107 and H115 isolated from a chloraminated drinking water distriburion system simulator

    Data.gov (United States)

    U.S. Environmental Protection Agency — Draft genome sequence of two Shingopyxis sp. strains H107 and H115 isolated from a chloraminated drinking water distriburion system simulator. This dataset is...

  15. Phylogenetic diversity of insecticolous fusaria inferred from multilocus DNA sequence data and their molecular identification via FUSARIUM-ID and Fusarium MLST

    NARCIS (Netherlands)

    O'Donnell, K.; Humber, R.A.; Geiser, D.M.; Kang, S.; Robert, V.; Park, B.; Crous, P.W.; Johnston, P.; Aoki, T.; Rooney, A.P.; Rehner, S.A.

    2012-01-01

    We constructed several multilocus DNA sequence datasets to assess the phylogenetic diversity of insecticolous fusaria, especially focusing on those housed at the Agricultural Research Service Collection of Entomopathogenic Fungi (ARSEF), and to aid molecular identifications of unknowns via the

  16. Screening and Validation of Highly-Efficient Insecticidal Conotoxins from a Transcriptome-Based Dataset of Chinese Tubular Cone Snail

    Directory of Open Access Journals (Sweden)

    Bingmiao Gao

    2017-07-01

    Full Text Available Most previous studies have focused on analgesic and anti-cancer activities for the conotoxins identified from piscivorous and molluscivorous cone snails, but little attention has been devoted to insecticidal activity of conotoxins from the dominant vermivorous species. As a representative vermivorous cone snail, the Chinese tubular cone snail (Conus betulinus is the dominant Conus species inhabiting the South China Sea. We sequenced related venom transcriptomes from C. betulinus using both the next-generation sequencing and traditional Sanger sequencing technologies, and a comprehensive library of 215 conotoxin transcripts was constructed. In our current study, six conotoxins with potential insecticidal activity were screened out from our conotoxin library by homologous search with a reported positive control (alpha-conotoxin ImI from C. imperialis as the query. Subsequently, these conotoxins were synthesized by chemical solid-phase and oxidative folding for further insecticidal activity validation, such as MTT assay, insect bioassay and homology modeling. The final results proved insecticidal activities of our achieved six conotoxins from the transcriptome-based dataset. Interestingly, two of them presented a lot of high insecticidal activity, which supports their usefulness for a trial as insecticides in field investigations. In summary, our present work provides a good example for high throughput development of biological insecticides on basis of the accumulated genomic resources.

  17. VideoWeb Dataset for Multi-camera Activities and Non-verbal Communication

    Science.gov (United States)

    Denina, Giovanni; Bhanu, Bir; Nguyen, Hoang Thanh; Ding, Chong; Kamal, Ahmed; Ravishankar, Chinya; Roy-Chowdhury, Amit; Ivers, Allen; Varda, Brenda

    Human-activity recognition is one of the most challenging problems in computer vision. Researchers from around the world have tried to solve this problem and have come a long way in recognizing simple motions and atomic activities. As the computer vision community heads toward fully recognizing human activities, a challenging and labeled dataset is needed. To respond to that need, we collected a dataset of realistic scenarios in a multi-camera network environment (VideoWeb) involving multiple persons performing dozens of different repetitive and non-repetitive activities. This chapter describes the details of the dataset. We believe that this VideoWeb Activities dataset is unique and it is one of the most challenging datasets available today. The dataset is publicly available online at http://vwdata.ee.ucr.edu/ along with the data annotation.

  18. GuiTope: an application for mapping random-sequence peptides to protein sequences.

    Science.gov (United States)

    Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert

    2012-01-03

    Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

  19. GuiTope: an application for mapping random-sequence peptides to protein sequences

    Directory of Open Access Journals (Sweden)

    Halperin Rebecca F

    2012-01-01

    Full Text Available Abstract Background Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. Results GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. Conclusions GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

  20. USGS Watershed Boundary Dataset (WBD) Overlay Map Service from The National Map - National Geospatial Data Asset (NGDA) Watershed Boundary Dataset (WBD)

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The Watershed Boundary Dataset (WBD) from The National Map (TNM) defines the perimeter of drainage areas formed by the terrain and other landscape characteristics....

  1. The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 Catchments (Version 2.1) for the Conterminous United States: National Coal Resource Dataset System

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset represents the coal mine density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the...

  2. The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Anthropogenic Barrier Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset represents the dam density and storage volumes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the National...

  3. The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: National Elevation Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset represents the elevation values within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the National Elevation...

  4. Transcriptome datasets of oil palm pathogen Ganoderma boninense

    Directory of Open Access Journals (Sweden)

    Irene Liza Isaac

    2018-04-01

    Full Text Available Ganoderma boninense is known to be the causal agent for basal stem rot (BSR affecting the oil palm industry worldwide thus cumulating to high economic losses every year. Several reports have shown that a compatible monokaryon pair needs to mate; producing dikaryotic mycelia to initiate the infection towards the oil palm. However, the molecular events occurs during mating process are not well understood. We performed transcriptome sequencing using Illumina RNA-seq technology and de novo assembly of the transcripts from monokaryon, mating junction and dikaryon mycelia of G. boninense. Raw reads from these three libraries were deposited in the NCBI database with accession number SRR1745787, SRR1745773 and SRR1745777, respectively.

  5. Topic modeling for cluster analysis of large biological and medical datasets.

    Science.gov (United States)

    Zhao, Weizhong; Zou, Wen; Chen, James J

    2014-01-01

    The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting

  6. A new dataset and algorithm evaluation for mood estimation in music

    OpenAIRE

    Godec, Primož

    2014-01-01

    This thesis presents a new dataset of perceived and induced emotions for 200 audio clips. The gathered dataset provides users' perceived and induced emotions for each clip, the association of color, along with demographic and personal data, such as user's emotion state and emotion ratings, genre preference, music experience, among others. With an online survey we collected more than 7000 responses for a dataset of 200 audio excerpts, thus providing about 37 user responses per clip. The foc...

  7. Prediction of Protein Hotspots from Whole Protein Sequences by a Random Projection Ensemble System

    Directory of Open Access Journals (Sweden)

    Jinjian Jiang

    2017-07-01

    Full Text Available Hotspot residues are important in the determination of protein-protein interactions, and they always perform specific functions in biological processes. The determination of hotspot residues is by the commonly-used method of alanine scanning mutagenesis experiments, which is always costly and time consuming. To address this issue, computational methods have been developed. Most of them are structure based, i.e., using the information of solved protein structures. However, the number of solved protein structures is extremely less than that of sequences. Moreover, almost all of the predictors identified hotspots from the interfaces of protein complexes, seldom from the whole protein sequences. Therefore, determining hotspots from whole protein sequences by sequence information alone is urgent. To address the issue of hotspot predictions from the whole sequences of proteins, we proposed an ensemble system with random projections using statistical physicochemical properties of amino acids. First, an encoding scheme involving sequence profiles of residues and physicochemical properties from the AAindex1 dataset is developed. Then, the random projection technique was adopted to project the encoding instances into a reduced space. Then, several better random projections were obtained by training an IBk classifier based on the training dataset, which were thus applied to the test dataset. The ensemble of random projection classifiers is therefore obtained. Experimental results showed that although the performance of our method is not good enough for real applications of hotspots, it is very promising in the determination of hotspot residues from whole sequences.

  8. Yeast genome sequencing:

    DEFF Research Database (Denmark)

    Piskur, Jure; Langkjær, Rikke Breinhold

    2004-01-01

    For decades, unicellular yeasts have been general models to help understand the eukaryotic cell and also our own biology. Recently, over a dozen yeast genomes have been sequenced, providing the basis to resolve several complex biological questions. Analysis of the novel sequence data has shown...... of closely related species helps in gene annotation and to answer how many genes there really are within the genomes. Analysis of non-coding regions among closely related species has provided an example of how to determine novel gene regulatory sequences, which were previously difficult to analyse because...... they are short and degenerate and occupy different positions. Comparative genomics helps to understand the origin of yeasts and points out crucial molecular events in yeast evolutionary history, such as whole-genome duplication and horizontal gene transfer(s). In addition, the accumulating sequence data provide...

  9. Identification of microRNAs from Amur grape (Vitis amurensis Rupr.) by deep sequencing and analysis of microRNA variations with bioinformatics.

    Science.gov (United States)

    Wang, Chen; Han, Jian; Liu, Chonghuai; Kibet, Korir Nicholas; Kayesh, Emrul; Shangguan, Lingfei; Li, Xiaoying; Fang, Jinggui

    2012-03-29

    MicroRNA (miRNA) is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr.) is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs) from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR) analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Deep sequencing of short RNAs from Amur grape flowers and berries identified 72 new potential miRNAs and 34 known but non-conserved mi

  10. Identification of microRNAs from Amur grape (vitis amurensis Rupr. by deep sequencing and analysis of microRNA variations with bioinformatics

    Directory of Open Access Journals (Sweden)

    Wang Chen

    2012-03-01

    Full Text Available Abstract Background MicroRNA (miRNA is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr. is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. Results A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Conclusions Deep sequencing of short RNAs from Amur grape flowers and berries identified 72

  11. Collaborative Filtering Recommendation on Users' Interest Sequences.

    Directory of Open Access Journals (Sweden)

    Weijie Cheng

    Full Text Available As an important factor for improving recommendations, time information has been introduced to model users' dynamic preferences in many papers. However, the sequence of users' behaviour is rarely studied in recommender systems. Due to the users' unique behavior evolution patterns and personalized interest transitions among items, users' similarity in sequential dimension should be introduced to further distinguish users' preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users' interest sequences (IS that rank users' ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users' longest common sub-IS (LCSIS and the count of users' total common sub-IS (ACSIS. Then, these semantics are utilized to obtain users' IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users' preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction.

  12. Collaborative Filtering Recommendation on Users' Interest Sequences.

    Science.gov (United States)

    Cheng, Weijie; Yin, Guisheng; Dong, Yuxin; Dong, Hongbin; Zhang, Wansong

    2016-01-01

    As an important factor for improving recommendations, time information has been introduced to model users' dynamic preferences in many papers. However, the sequence of users' behaviour is rarely studied in recommender systems. Due to the users' unique behavior evolution patterns and personalized interest transitions among items, users' similarity in sequential dimension should be introduced to further distinguish users' preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users' interest sequences (IS) that rank users' ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users' longest common sub-IS (LCSIS) and the count of users' total common sub-IS (ACSIS). Then, these semantics are utilized to obtain users' IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users' preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction.

  13. Collaborative Filtering Recommendation on Users’ Interest Sequences

    Science.gov (United States)

    Cheng, Weijie; Yin, Guisheng; Dong, Yuxin; Dong, Hongbin; Zhang, Wansong

    2016-01-01

    As an important factor for improving recommendations, time information has been introduced to model users’ dynamic preferences in many papers. However, the sequence of users’ behaviour is rarely studied in recommender systems. Due to the users’ unique behavior evolution patterns and personalized interest transitions among items, users’ similarity in sequential dimension should be introduced to further distinguish users’ preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users’ interest sequences (IS) that rank users’ ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users’ longest common sub-IS (LCSIS) and the count of users’ total common sub-IS (ACSIS). Then, these semantics are utilized to obtain users’ IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users’ preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction. PMID:27195787

  14. Dynamic Sequence Assignment.

    Science.gov (United States)

    1983-12-01

    D-136 548 DYNAMIIC SEQUENCE ASSIGNMENT(U) ADVANCED INFORMATION AND 1/2 DECISION SYSTEMS MOUNTAIN YIELW CA C A 0 REILLY ET AL. UNCLSSIIED DEC 83 AI/DS...I ADVANCED INFORMATION & DECISION SYSTEMS Mountain View. CA 94040 84 u ,53 V,..’. Unclassified _____ SCURITY CLASSIFICATION OF THIS PAGE REPORT...reviews some important heuristic algorithms developed for fas- ter solution of the sequence assignment problem. 3.1. DINAMIC MOGRAMUNIG FORMULATION FOR

  15. HIV Sequence Compendium 2010

    Energy Technology Data Exchange (ETDEWEB)

    Kuiken, Carla [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Foley, Brian [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Leitner, Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Apetrei, Christian [Univ. of Pittsburgh, PA (United States); Hahn, Beatrice [Univ. of Alabama, Tuscaloosa, AL (United States); Mizrachi, Ilene [National Center for Biotechnology Information, Bethesda, MD (United States); Mullins, James [Univ. of Washington, Seattle, WA (United States); Rambaut, Andrew [Univ. of Edinburgh, Scotland (United Kingdom); Wolinsky, Steven [Northwestern Univ., Evanston, IL (United States); Korber, Bette [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2010-12-31

    This compendium is an annual printed summary of the data contained in the HIV sequence database. In these compendia we try to present a judicious selection of the data in such a way that it is of maximum utility to HIV researchers. Each of the alignments attempts to display the genetic variability within the different species, groups and subtypes of the virus. This compendium contains sequences published before January 1, 2010. Hence, though it is called the 2010 Compendium, its contents correspond to the 2009 curated alignments on our website. The number of sequences in the HIV database is still increasing exponentially. In total, at the time of printing, there were 339,306 sequences in the HIV Sequence Database, an increase of 45% since last year. The number of near complete genomes (>7000 nucleotides) increased to 2576 by end of 2009, reflecting a smaller increase than in previous years. However, as in previous years, the compendium alignments contain only a small fraction of these. Included in the alignments are a small number of sequences representing each of the subtypes and the more prevalent circulating recombinant forms (CRFs) such as 01 and 02, as well as a few outgroup sequences (group O and N and SIV-CPZ). Of the rarer CRFs we included one representative each. A more complete version of all alignments is available on our website, http://www.hiv.lanl.gov/content/sequence/NEWALIGN/align.html. Reprints are available from our website in the form of both HTML and PDF files. As always, we are open to complaints and suggestions for improvement. Inquiries and comments regarding the compendium should be addressed to seq-info@lanl.gov.

  16. General LTE Sequence

    OpenAIRE

    Billal, Masum

    2015-01-01

    In this paper,we have characterized sequences which maintain the same property described in Lifting the Exponent Lemma. Lifting the Exponent Lemma is a very powerful tool in olympiad number theory and recently it has become very popular. We generalize it to all sequences that maintain a property like it i.e. if p^{\\alpha}||a_k and p^\\b{eta}||n, then p^{{\\alpha}+\\b{eta}}||a_{nk}.

  17. LOX: Inferring level of expression from diverse methods of census sequencing

    KAUST Repository

    Zhang, Zhang

    2010-06-10

    Summary: We present LOX (Level Of eXpression) that estimates the Level Of gene eXpression from high-throughput-expressed sequence datasets with multiple treatments or samples. Unlike most analyses, LOX incorporates a gene bias model that facilitates integration of diverse transcriptomic sequencing data that arises when transcriptomic data have been produced using diverse experimental methodologies. LOX integrates overall sequence count tallies normalized by total expressed sequence count to provide expression levels for each gene relative to all treatments as well as Bayesian credible intervals. © The Author 2010. Published by Oxford University Press. All rights reserved.

  18. LOX: Inferring level of expression from diverse methods of census sequencing

    KAUST Repository

    Zhang, Zhang; Ló pez-Girá ldez, Francesc Francisco; Townsend, Jeffrey P.

    2010-01-01

    Summary: We present LOX (Level Of eXpression) that estimates the Level Of gene eXpression from high-throughput-expressed sequence datasets with multiple treatments or samples. Unlike most analyses, LOX incorporates a gene bias model that facilitates integration of diverse transcriptomic sequencing data that arises when transcriptomic data have been produced using diverse experimental methodologies. LOX integrates overall sequence count tallies normalized by total expressed sequence count to provide expression levels for each gene relative to all treatments as well as Bayesian credible intervals. © The Author 2010. Published by Oxford University Press. All rights reserved.

  19. Identification and comparative profiling of miRNAs in an early flowering mutant of trifoliate orange and its wild type by genome-wide deep sequencing.

    Directory of Open Access Journals (Sweden)

    Lei-Ming Sun

    Full Text Available MicroRNAs (miRNAs are a new class of small, endogenous RNAs that play a regulatory role in various biological and metabolic processes by negatively affecting gene expression at the post-transcriptional level. While the number of known Arabidopsis and rice miRNAs is continuously increasing, information regarding miRNAs from woody plants such as citrus remains limited. Solexa sequencing was performed at different developmental stages on both an early flowering mutant of trifoliate orange (precocious trifoliate orange, Poncirus trifoliata L. Raf. and its wild-type in this study, resulting in the obtainment of 141 known miRNAs belonging to 99 families and 75 novel miRNAs in four libraries. A total of 317 potential target genes were predicted based on the 51 novel miRNAs families, GO and KEGG annotation revealed that high ranked miRNA-target genes are those implicated in diverse cellular processes in plants, including development, transcription, protein degradation and cross adaptation. To characterize those miRNAs expressed at the juvenile and adult development stages of the mutant and its wild-type, further analysis on the expression profiles of several miRNAs through real-time PCR was performed. The results revealed that most miRNAs were down-regulated at adult stage compared with juvenile stage for both the mutant and its wild-type. These results indicate that both conserved and novel miRNAs may play important roles in citrus growth and development, stress responses and other physiological processes.

  20. Hydrological simulation of the Brahmaputra basin using global datasets

    Science.gov (United States)

    Bhattacharya, Biswa; Conway, Crystal; Craven, Joanne; Masih, Ilyas; Mazzolini, Maurizio; Shrestha, Shreedeepy; Ugay, Reyne; van Andel, Schalk Jan

    2017-04-01

    Brahmaputra River flows through China, India and Bangladesh to the Bay of Bengal and is one of the largest rivers of the world with a catchment size of 580K km2. The catchment is largely hilly and/or forested with sparse population and with limited urbanisation and economic activities. The catchment experiences heavy monsoon rainfall leading to very high flood discharges. Large inter-annual variation of discharge leading to flooding, erosion and morphological changes are among the major challenges. The catchment is largely ungauged; moreover, limited availability of hydro-meteorological data limits the possibility of carrying out evidence based research, which could provide trustworthy information for managing and when needed, controlling, the basin processes by the riparian countries for overall basin development. The paper presents initial results of a current research project on Brahmaputra basin. A set of hydrological and hydraulic models (SWAT, HMS, RAS) are developed by employing publicly available datasets of DEM, land use and soil and simulated using satellite based rainfall products, evapotranspiration and temperature estimates. Remotely sensed data are compared with sporadically available ground data. The set of models are able to produce catchment wide hydrological information that potentially can be used in the future in managing the basin's water resources. The model predications should be used with caution due to high level of uncertainty because the semi-calibrated models are developed with uncertain physical representation (e.g. cross-section) and simulated with global meteorological forcing (e.g. TRMM) with limited validation. Major scientific challenges are seen in producing robust information that can be reliably used in managing the basin. The information generated by the models are uncertain and as a result, instead of using them per se, they are used in improving the understanding of the catchment, and by running several scenarios with varying