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Sample records for big genomes facilitate

  1. Big Data: Astronomical or Genomical?

    Directory of Open Access Journals (Sweden)

    Zachary D Stephens

    2015-07-01

    Full Text Available Genomics is a Big Data science and is going to get much bigger, very soon, but it is not known whether the needs of genomics will exceed other Big Data domains. Projecting to the year 2025, we compared genomics with three other major generators of Big Data: astronomy, YouTube, and Twitter. Our estimates show that genomics is a "four-headed beast"--it is either on par with or the most demanding of the domains analyzed here in terms of data acquisition, storage, distribution, and analysis. We discuss aspects of new technologies that will need to be developed to rise up and meet the computational challenges that genomics poses for the near future. Now is the time for concerted, community-wide planning for the "genomical" challenges of the next decade.

  2. Big Data Analysis of Human Genome Variations

    KAUST Repository

    Gojobori, Takashi

    2016-01-25

    Since the human genome draft sequence was in public for the first time in 2000, genomic analyses have been intensively extended to the population level. The following three international projects are good examples for large-scale studies of human genome variations: 1) HapMap Data (1,417 individuals) (http://hapmap.ncbi.nlm.nih.gov/downloads/genotypes/2010-08_phaseII+III/forward/), 2) HGDP (Human Genome Diversity Project) Data (940 individuals) (http://www.hagsc.org/hgdp/files.html), 3) 1000 genomes Data (2,504 individuals) http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/ If we can integrate all three data into a single volume of data, we should be able to conduct a more detailed analysis of human genome variations for a total number of 4,861 individuals (= 1,417+940+2,504 individuals). In fact, we successfully integrated these three data sets by use of information on the reference human genome sequence, and we conducted the big data analysis. In particular, we constructed a phylogenetic tree of about 5,000 human individuals at the genome level. As a result, we were able to identify clusters of ethnic groups, with detectable admixture, that were not possible by an analysis of each of the three data sets. Here, we report the outcome of this kind of big data analyses and discuss evolutionary significance of human genomic variations. Note that the present study was conducted in collaboration with Katsuhiko Mineta and Kosuke Goto at KAUST.

  3. Complete Genome of Bacillus thuringiensis Myophage BigBertha

    OpenAIRE

    Ting, Jose H.; Smyth, Trinity B.; Chamakura, Karthik R.; Kuty Everett, Gabriel F.

    2013-01-01

    BigBertha is a myophage of Bacillus thuringiensis, a widely used biocontrol agent that is active against many insect pests of plants. Here, we present the complete annotated genome of BigBertha. The genome shares 85.9% sequence identity with Bacillus cereus phage B4.

  4. 'Big data', Hadoop and cloud computing in genomics.

    Science.gov (United States)

    O'Driscoll, Aisling; Daugelaite, Jurate; Sleator, Roy D

    2013-10-01

    Since the completion of the Human Genome project at the turn of the Century, there has been an unprecedented proliferation of genomic sequence data. A consequence of this is that the medical discoveries of the future will largely depend on our ability to process and analyse large genomic data sets, which continue to expand as the cost of sequencing decreases. Herein, we provide an overview of cloud computing and big data technologies, and discuss how such expertise can be used to deal with biology's big data sets. In particular, big data technologies such as the Apache Hadoop project, which provides distributed and parallelised data processing and analysis of petabyte (PB) scale data sets will be discussed, together with an overview of the current usage of Hadoop within the bioinformatics community.

  5. 'Big data', Hadoop and cloud computing in genomics.

    Science.gov (United States)

    O'Driscoll, Aisling; Daugelaite, Jurate; Sleator, Roy D

    2013-10-01

    Since the completion of the Human Genome project at the turn of the Century, there has been an unprecedented proliferation of genomic sequence data. A consequence of this is that the medical discoveries of the future will largely depend on our ability to process and analyse large genomic data sets, which continue to expand as the cost of sequencing decreases. Herein, we provide an overview of cloud computing and big data technologies, and discuss how such expertise can be used to deal with biology's big data sets. In particular, big data technologies such as the Apache Hadoop project, which provides distributed and parallelised data processing and analysis of petabyte (PB) scale data sets will be discussed, together with an overview of the current usage of Hadoop within the bioinformatics community. PMID:23872175

  6. The NIH BD2K center for big data in translational genomics.

    Science.gov (United States)

    Paten, Benedict; Diekhans, Mark; Druker, Brian J; Friend, Stephen; Guinney, Justin; Gassner, Nadine; Guttman, Mitchell; Kent, W James; Mantey, Patrick; Margolin, Adam A; Massie, Matt; Novak, Adam M; Nothaft, Frank; Pachter, Lior; Patterson, David; Smuga-Otto, Maciej; Stuart, Joshua M; Van't Veer, Laura; Wold, Barbara; Haussler, David

    2015-11-01

    The world's genomics data will never be stored in a single repository - rather, it will be distributed among many sites in many countries. No one site will have enough data to explain genotype to phenotype relationships in rare diseases; therefore, sites must share data. To accomplish this, the genetics community must forge common standards and protocols to make sharing and computing data among many sites a seamless activity. Through the Global Alliance for Genomics and Health, we are pioneering the development of shared application programming interfaces (APIs) to connect the world's genome repositories. In parallel, we are developing an open source software stack (ADAM) that uses these APIs. This combination will create a cohesive genome informatics ecosystem. Using containers, we are facilitating the deployment of this software in a diverse array of environments. Through benchmarking efforts and big data driver projects, we are ensuring ADAM's performance and utility. PMID:26174866

  7. Heterogeneous Cloud Framework for Big Data Genome Sequencing.

    Science.gov (United States)

    Wang, Chao; Li, Xi; Chen, Peng; Wang, Aili; Zhou, Xuehai; Yu, Hong

    2015-01-01

    The next generation genome sequencing problem with short (long) reads is an emerging field in numerous scientific and big data research domains. However, data sizes and ease of access for scientific researchers are growing and most current methodologies rely on one acceleration approach and so cannot meet the requirements imposed by explosive data scales and complexities. In this paper, we propose a novel FPGA-based acceleration solution with MapReduce framework on multiple hardware accelerators. The combination of hardware acceleration and MapReduce execution flow could greatly accelerate the task of aligning short length reads to a known reference genome. To evaluate the performance and other metrics, we conducted a theoretical speedup analysis on a MapReduce programming platform, which demonstrates that our proposed architecture have efficient potential to improve the speedup for large scale genome sequencing applications. Also, as a practical study, we have built a hardware prototype on the real Xilinx FPGA chip. Significant metrics on speedup, sensitivity, mapping quality, error rate, and hardware cost are evaluated, respectively. Experimental results demonstrate that the proposed platform could efficiently accelerate the next generation sequencing problem with satisfactory accuracy and acceptable hardware cost.

  8. Opportunities and challenges of big data for the social sciences: The case of genomic data.

    Science.gov (United States)

    Liu, Hexuan; Guo, Guang

    2016-09-01

    In this paper, we draw attention to one unique and valuable source of big data, genomic data, by demonstrating the opportunities they provide to social scientists. We discuss different types of large-scale genomic data and recent advances in statistical methods and computational infrastructure used to address challenges in managing and analyzing such data. We highlight how these data and methods can be used to benefit social science research. PMID:27480368

  9. Opportunities and challenges of big data for the social sciences: The case of genomic data.

    Science.gov (United States)

    Liu, Hexuan; Guo, Guang

    2016-09-01

    In this paper, we draw attention to one unique and valuable source of big data, genomic data, by demonstrating the opportunities they provide to social scientists. We discuss different types of large-scale genomic data and recent advances in statistical methods and computational infrastructure used to address challenges in managing and analyzing such data. We highlight how these data and methods can be used to benefit social science research.

  10. Nucleotide sequence and genomic organization of an ophiovirus associated with lettuce big-vein disease

    NARCIS (Netherlands)

    Wilk, van der F.; Dullemans, A.M.; Verbeek, M.; Heuvel, van den J.F.J.M.

    2002-01-01

    The complete nucleotide sequence of an ophiovirus associated with lettuce big-vein disease has been elucidated. The genome consisted of four RNA molecules of approximately 7ò8, 1ò7, 1ò5 and 1ò4 kb. Virus particles were shown to contain nearly equimolar amounts of RNA molecules of both polarities. Th

  11. The Burkholderia Genome Database: facilitating flexible queries and comparative analyses

    OpenAIRE

    Winsor, Geoffrey L.; Khaira, Bhavjinder; Van Rossum, Thea; Lo, Raymond; Whiteside, Matthew D.; Fiona S.L. Brinkman

    2008-01-01

    Summary: As the genome sequences of multiple strains of a given bacterial species are obtained, more generalized bacterial genome databases may be complemented by databases that are focused on providing more information geared for a distinct bacterial phylogenetic group and its associated research community. The Burkholderia Genome Database represents a model for such a database, providing a powerful, user-friendly search and comparative analysis interface that contains features not found in ...

  12. Mapping Our Genes: The Genome Projects: How Big, How Fast

    Science.gov (United States)

    1988-04-01

    For the past 2 years, scientific and technical journals in biology and medicine have extensively covered a debate about whether and how to determine the function and order of human genes on human chromosomes and when to determine the sequence of molecular building blocks that comprise DNA in those chromosomes. In 1987, these issues rose to become part of the public agenda. The debate involves science, technology, and politics. Congress is responsible for �writing the rules� of what various federal agencies do and for funding their work. This report surveys the points made so far in the debate, focusing on those that most directly influence the policy options facing the US Congress. Congressional interest focused on how to assess the rationales for conducting human genome projects, how to fund human genome projects (at what level and through which mechanisms), how to coordinate the scientific and technical programs of the several federal agencies and private interests already supporting various genome projects, and how to strike a balance regarding the impact of genome projects on international scientific cooperation and international economic competition in biotechnology. The Office of Technology Assessment (OTA) prepared this report with the assistance of several hundred experts throughout the world.

  13. Mapping our genes: The genome projects: How big, how fast

    Energy Technology Data Exchange (ETDEWEB)

    none,

    1988-04-01

    For the past 2 years, scientific and technical journals in biology and medicine have extensively covered a debate about whether and how to determine the function and order of human genes on human chromosomes and when to determine the sequence of molecular building blocks that comprise DNA in those chromosomes. In 1987, these issues rose to become part of the public agenda. The debate involves science, technology, and politics. Congress is responsible for /open quotes/writing the rules/close quotes/ of what various federal agencies do and for funding their work. This report surveys the points made so far in the debate, focusing on those that most directly influence the policy options facing the US Congress. Congressional interest focused on how to assess the rationales for conducting human genome projects, how to fund human genome projects (at what level and through which mechanisms), how to coordinate the scientific and technical programs of the several federal agencies and private interests already supporting various genome projects, and how to strike a balance regarding the impact of genome projects on international scientific cooperation and international economic competition in biotechnology. OTA prepared this report with the assistance of several hundred experts throughout the world. 342 refs., 26 figs., 11 tabs.

  14. MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease

    NARCIS (Netherlands)

    L. Shen (Lishuang); M.A. Diroma (Maria Angela); M. Gonzalez (Michael); D. Navarro-Gomez (Daniel); J. Leipzig (Jeremy); M.T. Lott (Marie T.); M. van Oven (Mannis); D.C. Wallace; C.C. Muraresku (Colleen Clarke); Z. Zolkipli-Cunningham (Zarazuela); P.F. Chinnery (Patrick); M. Attimonelli (Marcella); S. Zuchner (Stephan); M.J. Falk (Marni J.); X. Gai (Xiaowu)

    2016-01-01

    textabstractMSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, gene

  15. Figure 4 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

    Science.gov (United States)

    Gene-list view of genomic data. The gene-list view allows users to compare data across a set of loci. The data in this figure includes copy number, mutation, and clinical data from 202 glioblastoma samples from TCGA. Adapted from Figure 7; Thorvaldsdottir H et al. 2012

  16. Figure 5 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

    Science.gov (United States)

    Split-Screen View. The split-screen view is useful for exploring relationships of genomic features that are independent of chromosomal location. Color is used here to indicate mate pairs that map to different chromosomes, chromosomes 1 and 6, suggesting a translocation event. Adapted from Figure 8; Thorvaldsdottir H et al. 2012

  17. Figure 2 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

    Science.gov (United States)

    Grouping and sorting genomic data in IGV. The IGV user interface displaying 202 glioblastoma samples from TCGA. Samples are grouped by tumor subtype (second annotation column) and data type (first annotation column) and sorted by copy number of the EGFR locus (middle column). Adapted from Figure 1; Robinson et al. 2011

  18. Big data, open science and the brain: lessons learned from genomics

    Directory of Open Access Journals (Sweden)

    Suparna eChoudhury

    2014-05-01

    Full Text Available The BRAIN Initiative aims to break new ground in the scale and speed of data collection in neuroscience, requiring tools to handle data in the magnitude of yottabytes (1024. The scale, investment and organization of it are being compared to the Human Genome Project (HGP, which has exemplified ‘big science’ for biology. In line with the trend towards Big Data in genomic research, the promise of the BRAIN Initiative, as well as the European Human Brain Project, rests on the possibility to amass vast quantities of data to model the complex interactions between the brain and behaviour and inform the diagnosis and prevention of neurological disorders and psychiatric disease. Advocates of this ‘data driven’ paradigm in neuroscience argue that harnessing the large quantities of data generated across laboratories worldwide has numerous methodological, ethical and economic advantages, but it requires the neuroscience community to adopt a culture of data sharing and open access to benefit from them. In this article, we examine the rationale for data sharing among advocates and briefly exemplify these in terms of new ‘open neuroscience’ projects. Then, drawing on the frequently invoked model of data sharing in genomics, we go on to demonstrate the complexities of data sharing, shedding light on the sociological and ethical challenges within the realms of institutions, researchers and participants, namely dilemmas around public/private interests in data, (lack of motivation to share in the academic community, and potential loss of participant anonymity. Our paper serves to highlight some foreseeable tensions around data sharing relevant to the emergent ‘open neuroscience’ movement.

  19. The spotted gar genome illuminates vertebrate evolution and facilitates human-to-teleost comparisons

    Science.gov (United States)

    Braasch, Ingo; Gehrke, Andrew R.; Smith, Jeramiah J.; Kawasaki, Kazuhiko; Manousaki, Tereza; Pasquier, Jeremy; Amores, Angel; Desvignes, Thomas; Batzel, Peter; Catchen, Julian; Berlin, Aaron M.; Campbell, Michael S.; Barrell, Daniel; Martin, Kyle J.; Mulley, John F.; Ravi, Vydianathan; Lee, Alison P.; Nakamura, Tetsuya; Chalopin, Domitille; Fan, Shaohua; Wcisel, Dustin; Cañestro, Cristian; Sydes, Jason; Beaudry, Felix E. G.; Sun, Yi; Hertel, Jana; Beam, Michael J.; Fasold, Mario; Ishiyama, Mikio; Johnson, Jeremy; Kehr, Steffi; Lara, Marcia; Letaw, John H.; Litman, Gary W.; Litman, Ronda T.; Mikami, Masato; Ota, Tatsuya; Saha, Nil Ratan; Williams, Louise; Stadler, Peter F.; Wang, Han; Taylor, John S.; Fontenot, Quenton; Ferrara, Allyse; Searle, Stephen M. J.; Aken, Bronwen; Yandell, Mark; Schneider, Igor; Yoder, Jeffrey A.; Volff, Jean-Nicolas; Meyer, Axel; Amemiya, Chris T.; Venkatesh, Byrappa; Holland, Peter W. H.; Guiguen, Yann; Bobe, Julien; Shubin, Neil H.; Di Palma, Federica; Alföldi, Jessica; Lindblad-Toh, Kerstin; Postlethwait, John H.

    2016-01-01

    To connect human biology to fish biomedical models, we sequenced the genome of spotted gar (Lepisosteus oculatus), whose lineage diverged from teleosts before the teleost genome duplication (TGD). The slowly evolving gar genome conserved in content and size many entire chromosomes from bony vertebrate ancestors. Gar bridges teleosts to tetrapods by illuminating the evolution of immunity, mineralization, and development (e.g., Hox, ParaHox, and miRNA genes). Numerous conserved non-coding elements (CNEs, often cis-regulatory) undetectable in direct human-teleost comparisons become apparent using gar: functional studies uncovered conserved roles of such cryptic CNEs, facilitating annotation of sequences identified in human genome-wide association studies. Transcriptomic analyses revealed that the sum of expression domains and levels from duplicated teleost genes often approximate patterns and levels of gar genes, consistent with subfunctionalization. The gar genome provides a resource for understanding evolution after genome duplication, the origin of vertebrate genomes, and the function of human regulatory sequences. PMID:26950095

  20. The spotted gar genome illuminates vertebrate evolution and facilitates human-teleost comparisons.

    Science.gov (United States)

    Braasch, Ingo; Gehrke, Andrew R; Smith, Jeramiah J; Kawasaki, Kazuhiko; Manousaki, Tereza; Pasquier, Jeremy; Amores, Angel; Desvignes, Thomas; Batzel, Peter; Catchen, Julian; Berlin, Aaron M; Campbell, Michael S; Barrell, Daniel; Martin, Kyle J; Mulley, John F; Ravi, Vydianathan; Lee, Alison P; Nakamura, Tetsuya; Chalopin, Domitille; Fan, Shaohua; Wcisel, Dustin; Cañestro, Cristian; Sydes, Jason; Beaudry, Felix E G; Sun, Yi; Hertel, Jana; Beam, Michael J; Fasold, Mario; Ishiyama, Mikio; Johnson, Jeremy; Kehr, Steffi; Lara, Marcia; Letaw, John H; Litman, Gary W; Litman, Ronda T; Mikami, Masato; Ota, Tatsuya; Saha, Nil Ratan; Williams, Louise; Stadler, Peter F; Wang, Han; Taylor, John S; Fontenot, Quenton; Ferrara, Allyse; Searle, Stephen M J; Aken, Bronwen; Yandell, Mark; Schneider, Igor; Yoder, Jeffrey A; Volff, Jean-Nicolas; Meyer, Axel; Amemiya, Chris T; Venkatesh, Byrappa; Holland, Peter W H; Guiguen, Yann; Bobe, Julien; Shubin, Neil H; Di Palma, Federica; Alföldi, Jessica; Lindblad-Toh, Kerstin; Postlethwait, John H

    2016-04-01

    To connect human biology to fish biomedical models, we sequenced the genome of spotted gar (Lepisosteus oculatus), whose lineage diverged from teleosts before teleost genome duplication (TGD). The slowly evolving gar genome has conserved in content and size many entire chromosomes from bony vertebrate ancestors. Gar bridges teleosts to tetrapods by illuminating the evolution of immunity, mineralization and development (mediated, for example, by Hox, ParaHox and microRNA genes). Numerous conserved noncoding elements (CNEs; often cis regulatory) undetectable in direct human-teleost comparisons become apparent using gar: functional studies uncovered conserved roles for such cryptic CNEs, facilitating annotation of sequences identified in human genome-wide association studies. Transcriptomic analyses showed that the sums of expression domains and expression levels for duplicated teleost genes often approximate the patterns and levels of expression for gar genes, consistent with subfunctionalization. The gar genome provides a resource for understanding evolution after genome duplication, the origin of vertebrate genomes and the function of human regulatory sequences.

  1. Barriers and Facilitators to Adoption of Genomic Services for Colorectal Care within the Veterans Health Administration.

    Science.gov (United States)

    Sperber, Nina R; Andrews, Sara M; Voils, Corrine I; Green, Gregory L; Provenzale, Dawn; Knight, Sara

    2016-01-01

    We examined facilitators and barriers to adoption of genomic services for colorectal care, one of the first genomic medicine applications, within the Veterans Health Administration to shed light on areas for practice change. We conducted semi-structured interviews with 58 clinicians to understand use of the following genomic services for colorectal care: family health history documentation, molecular and genetic testing, and genetic counseling. Data collection and analysis were informed by two conceptual frameworks, the Greenhalgh Diffusion of Innovation and Andersen Behavioral Model, to allow for concurrent examination of both access and innovation factors. Specialists were more likely than primary care clinicians to obtain family history to investigate hereditary colorectal cancer (CRC), but with limited detail; clinicians suggested templates to facilitate retrieval and documentation of family history according to guidelines. Clinicians identified advantage of molecular tumor analysis prior to genetic testing, but tumor testing was infrequently used due to perceived low disease burden. Support from genetic counselors was regarded as facilitative for considering hereditary basis of CRC diagnosis, but there was variability in awareness of and access to this expertise. Our data suggest the need for tools and policies to establish and disseminate well-defined processes for accessing services and adhering to guidelines. PMID:27136589

  2. Barriers and Facilitators to Adoption of Genomic Services for Colorectal Care within the Veterans Health Administration

    Directory of Open Access Journals (Sweden)

    Nina R. Sperber

    2016-04-01

    Full Text Available We examined facilitators and barriers to adoption of genomic services for colorectal care, one of the first genomic medicine applications, within the Veterans Health Administration to shed light on areas for practice change. We conducted semi-structured interviews with 58 clinicians to understand use of the following genomic services for colorectal care: family health history documentation, molecular and genetic testing, and genetic counseling. Data collection and analysis were informed by two conceptual frameworks, the Greenhalgh Diffusion of Innovation and Andersen Behavioral Model, to allow for concurrent examination of both access and innovation factors. Specialists were more likely than primary care clinicians to obtain family history to investigate hereditary colorectal cancer (CRC, but with limited detail; clinicians suggested templates to facilitate retrieval and documentation of family history according to guidelines. Clinicians identified advantage of molecular tumor analysis prior to genetic testing, but tumor testing was infrequently used due to perceived low disease burden. Support from genetic counselors was regarded as facilitative for considering hereditary basis of CRC diagnosis, but there was variability in awareness of and access to this expertise. Our data suggest the need for tools and policies to establish and disseminate well-defined processes for accessing services and adhering to guidelines.

  3. Barriers and Facilitators to Adoption of Genomic Services for Colorectal Care within the Veterans Health Administration.

    Science.gov (United States)

    Sperber, Nina R; Andrews, Sara M; Voils, Corrine I; Green, Gregory L; Provenzale, Dawn; Knight, Sara

    2016-04-28

    We examined facilitators and barriers to adoption of genomic services for colorectal care, one of the first genomic medicine applications, within the Veterans Health Administration to shed light on areas for practice change. We conducted semi-structured interviews with 58 clinicians to understand use of the following genomic services for colorectal care: family health history documentation, molecular and genetic testing, and genetic counseling. Data collection and analysis were informed by two conceptual frameworks, the Greenhalgh Diffusion of Innovation and Andersen Behavioral Model, to allow for concurrent examination of both access and innovation factors. Specialists were more likely than primary care clinicians to obtain family history to investigate hereditary colorectal cancer (CRC), but with limited detail; clinicians suggested templates to facilitate retrieval and documentation of family history according to guidelines. Clinicians identified advantage of molecular tumor analysis prior to genetic testing, but tumor testing was infrequently used due to perceived low disease burden. Support from genetic counselors was regarded as facilitative for considering hereditary basis of CRC diagnosis, but there was variability in awareness of and access to this expertise. Our data suggest the need for tools and policies to establish and disseminate well-defined processes for accessing services and adhering to guidelines.

  4. Crowd-funded micro-grants for genomics and "big data": an actionable idea connecting small (artisan) science, infrastructure science, and citizen philanthropy.

    Science.gov (United States)

    Özdemir, Vural; Badr, Kamal F; Dove, Edward S; Endrenyi, Laszlo; Geraci, Christy Jo; Hotez, Peter J; Milius, Djims; Neves-Pereira, Maria; Pang, Tikki; Rotimi, Charles N; Sabra, Ramzi; Sarkissian, Christineh N; Srivastava, Sanjeeva; Tims, Hesther; Zgheib, Nathalie K; Kickbusch, Ilona

    2013-04-01

    Biomedical science in the 21(st) century is embedded in, and draws from, a digital commons and "Big Data" created by high-throughput Omics technologies such as genomics. Classic Edisonian metaphors of science and scientists (i.e., "the lone genius" or other narrow definitions of expertise) are ill equipped to harness the vast promises of the 21(st) century digital commons. Moreover, in medicine and life sciences, experts often under-appreciate the important contributions made by citizen scholars and lead users of innovations to design innovative products and co-create new knowledge. We believe there are a large number of users waiting to be mobilized so as to engage with Big Data as citizen scientists-only if some funding were available. Yet many of these scholars may not meet the meta-criteria used to judge expertise, such as a track record in obtaining large research grants or a traditional academic curriculum vitae. This innovation research article describes a novel idea and action framework: micro-grants, each worth $1000, for genomics and Big Data. Though a relatively small amount at first glance, this far exceeds the annual income of the "bottom one billion"-the 1.4 billion people living below the extreme poverty level defined by the World Bank ($1.25/day). We describe two types of micro-grants. Type 1 micro-grants can be awarded through established funding agencies and philanthropies that create micro-granting programs to fund a broad and highly diverse array of small artisan labs and citizen scholars to connect genomics and Big Data with new models of discovery such as open user innovation. Type 2 micro-grants can be funded by existing or new science observatories and citizen think tanks through crowd-funding mechanisms described herein. Type 2 micro-grants would also facilitate global health diplomacy by co-creating crowd-funded micro-granting programs across nation-states in regions facing political and financial instability, while sharing similar disease

  5. Genomic sequencing: assessing the health care system, policy, and big-data implications.

    Science.gov (United States)

    Phillips, Kathryn A; Trosman, Julia R; Kelley, Robin K; Pletcher, Mark J; Douglas, Michael P; Weldon, Christine B

    2014-07-01

    New genomic sequencing technologies enable the high-speed analysis of multiple genes simultaneously, including all of those in a person's genome. Sequencing is a prominent example of a "big data" technology because of the massive amount of information it produces and its complexity, diversity, and timeliness. Our objective in this article is to provide a policy primer on sequencing and illustrate how it can affect health care system and policy issues. Toward this end, we developed an easily applied classification of sequencing based on inputs, methods, and outputs. We used it to examine the implications of sequencing for three health care system and policy issues: making care more patient-centered, developing coverage and reimbursement policies, and assessing economic value. We conclude that sequencing has great promise but that policy challenges include how to optimize patient engagement as well as privacy, develop coverage policies that distinguish research from clinical uses and account for bioinformatics costs, and determine the economic value of sequencing through complex economic models that take into account multiple findings and downstream costs. PMID:25006153

  6. Parallel and Space-Efficient Construction of Burrows-Wheeler Transform and Suffix Array for Big Genome Data.

    Science.gov (United States)

    Liu, Yongchao; Hankeln, Thomas; Schmidt, Bertil

    2016-01-01

    Next-generation sequencing technologies have led to the sequencing of more and more genomes, propelling related research into the era of big data. In this paper, we present ParaBWT, a parallelized Burrows-Wheeler transform (BWT) and suffix array construction algorithm for big genome data. In ParaBWT, we have investigated a progressive construction approach to constructing the BWT of single genome sequences in linear space complexity, but with a small constant factor. This approach has been further parallelized using multi-threading based on a master-slave coprocessing model. After gaining the BWT, the suffix array is constructed in a memory-efficient manner. The performance of ParaBWT has been evaluated using two sequences generated from two human genome assemblies: the Ensembl Homo sapiens assembly and the human reference genome. Our performance comparison to FMD-index and Bwt-disk reveals that on 12 CPU cores, ParaBWT runs up to 2.2× faster than FMD-index and up to 99.0× faster than Bwt-disk. BWT construction algorithms for very long genomic sequences are time consuming and (due to their incremental nature) inherently difficult to parallelize. Thus, their parallelization is challenging and even relatively small speedups like the ones of our method over FMD-index are of high importance to research. ParaBWT is written in C++, and is freely available at http://parabwt.sourceforge.net. PMID:27295644

  7. The Widening Gulf between Genomics Data Generation and Consumption: A Practical Guide to Big Data Transfer Technology

    OpenAIRE

    Feltus, Frank A.; Joseph R. Breen III; Juan Deng; Ryan S. Izard; Christopher A. Konger; Walter B. Ligon III; Don Preuss; Kuang-Ching Wang

    2015-01-01

    In the last decade, high-throughput DNA sequencing has become a disruptive technology and pushed the life sciences into a distributed ecosystem of sequence data producers and consumers. Given the power of genomics and declining sequencing costs, biology is an emerging “Big Data” discipline that will soon enter the exabyte data range when all subdisciplines are combined. These datasets must be transferred across commercial and research networks in creative ways since sending data without thoug...

  8. Crowd-Funded Micro-Grants for Genomics and “Big Data”: An Actionable Idea Connecting Small (Artisan) Science, Infrastructure Science, and Citizen Philanthropy

    Science.gov (United States)

    Badr, Kamal F.; Dove, Edward S.; Endrenyi, Laszlo; Geraci, Christy Jo; Hotez, Peter J.; Milius, Djims; Neves-Pereira, Maria; Pang, Tikki; Rotimi, Charles N.; Sabra, Ramzi; Sarkissian, Christineh N.; Srivastava, Sanjeeva; Tims, Hesther; Zgheib, Nathalie K.; Kickbusch, Ilona

    2013-01-01

    Abstract Biomedical science in the 21st century is embedded in, and draws from, a digital commons and “Big Data” created by high-throughput Omics technologies such as genomics. Classic Edisonian metaphors of science and scientists (i.e., “the lone genius” or other narrow definitions of expertise) are ill equipped to harness the vast promises of the 21st century digital commons. Moreover, in medicine and life sciences, experts often under-appreciate the important contributions made by citizen scholars and lead users of innovations to design innovative products and co-create new knowledge. We believe there are a large number of users waiting to be mobilized so as to engage with Big Data as citizen scientists—only if some funding were available. Yet many of these scholars may not meet the meta-criteria used to judge expertise, such as a track record in obtaining large research grants or a traditional academic curriculum vitae. This innovation research article describes a novel idea and action framework: micro-grants, each worth $1000, for genomics and Big Data. Though a relatively small amount at first glance, this far exceeds the annual income of the “bottom one billion”—the 1.4 billion people living below the extreme poverty level defined by the World Bank ($1.25/day). We describe two types of micro-grants. Type 1 micro-grants can be awarded through established funding agencies and philanthropies that create micro-granting programs to fund a broad and highly diverse array of small artisan labs and citizen scholars to connect genomics and Big Data with new models of discovery such as open user innovation. Type 2 micro-grants can be funded by existing or new science observatories and citizen think tanks through crowd-funding mechanisms described herein. Type 2 micro-grants would also facilitate global health diplomacy by co-creating crowd-funded micro-granting programs across nation-states in regions facing political and financial instability, while

  9. The Widening Gulf between Genomics Data Generation and Consumption: A Practical Guide to Big Data Transfer Technology.

    Science.gov (United States)

    Feltus, Frank A; Breen, Joseph R; Deng, Juan; Izard, Ryan S; Konger, Christopher A; Ligon, Walter B; Preuss, Don; Wang, Kuang-Ching

    2015-01-01

    In the last decade, high-throughput DNA sequencing has become a disruptive technology and pushed the life sciences into a distributed ecosystem of sequence data producers and consumers. Given the power of genomics and declining sequencing costs, biology is an emerging "Big Data" discipline that will soon enter the exabyte data range when all subdisciplines are combined. These datasets must be transferred across commercial and research networks in creative ways since sending data without thought can have serious consequences on data processing time frames. Thus, it is imperative that biologists, bioinformaticians, and information technology engineers recalibrate data processing paradigms to fit this emerging reality. This review attempts to provide a snapshot of Big Data transfer across networks, which is often overlooked by many biologists. Specifically, we discuss four key areas: 1) data transfer networks, protocols, and applications; 2) data transfer security including encryption, access, firewalls, and the Science DMZ; 3) data flow control with software-defined networking; and 4) data storage, staging, archiving and access. A primary intention of this article is to orient the biologist in key aspects of the data transfer process in order to frame their genomics-oriented needs to enterprise IT professionals. PMID:26568680

  10. Big Data

    Directory of Open Access Journals (Sweden)

    Prachi More

    2013-05-01

    Full Text Available Demand and spurt in collections and accumulation of data has coined new term “Big Data” has begun. Accidently, incidentally and by interaction of people, information so called data is massively generated. This BIG DATA is to be smartly and effectively used Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists and many Variety of Intellegesia debate over the potential benefits and costs of analysing information from Twitter, Google, Facebook, Wikipedia and every space where large groups of people leave digital traces and deposit data. Given the rise of Big Data as both a phenomenon and a methodological persuasion, it is time to start critically interrogating this phenomenon, its assumptions and its biases. Big data, which refers to the data sets that are too big to be handled using the existing database management tools, are emerging in many important applications, such as Internet search, business informatics, social networks, social media, genomics, and meteorology. Big data presents a grand challenge for database and data analytics research. This paper is a blend of non-technical and introductory-level technical detail, ideal for the novice. We conclude with some technical challenges as well as the solutions that can be used to these challenges. Big Data differs from other data with five characteristics like volume, variety, value, velocity and complexity. The article will focus on some current and future cases and causes for BIG DATA.

  11. Big Data in Plant Science: Resources and Data Mining Tools for Plant Genomics and Proteomics.

    Science.gov (United States)

    Popescu, George V; Noutsos, Christos; Popescu, Sorina C

    2016-01-01

    In modern plant biology, progress is increasingly defined by the scientists' ability to gather and analyze data sets of high volume and complexity, otherwise known as "big data". Arguably, the largest increase in the volume of plant data sets over the last decade is a consequence of the application of the next-generation sequencing and mass-spectrometry technologies to the study of experimental model and crop plants. The increase in quantity and complexity of biological data brings challenges, mostly associated with data acquisition, processing, and sharing within the scientific community. Nonetheless, big data in plant science create unique opportunities in advancing our understanding of complex biological processes at a level of accuracy without precedence, and establish a base for the plant systems biology. In this chapter, we summarize the major drivers of big data in plant science and big data initiatives in life sciences with a focus on the scope and impact of iPlant, a representative cyberinfrastructure platform for plant science.

  12. Big Data in Plant Science: Resources and Data Mining Tools for Plant Genomics and Proteomics.

    Science.gov (United States)

    Popescu, George V; Noutsos, Christos; Popescu, Sorina C

    2016-01-01

    In modern plant biology, progress is increasingly defined by the scientists' ability to gather and analyze data sets of high volume and complexity, otherwise known as "big data". Arguably, the largest increase in the volume of plant data sets over the last decade is a consequence of the application of the next-generation sequencing and mass-spectrometry technologies to the study of experimental model and crop plants. The increase in quantity and complexity of biological data brings challenges, mostly associated with data acquisition, processing, and sharing within the scientific community. Nonetheless, big data in plant science create unique opportunities in advancing our understanding of complex biological processes at a level of accuracy without precedence, and establish a base for the plant systems biology. In this chapter, we summarize the major drivers of big data in plant science and big data initiatives in life sciences with a focus on the scope and impact of iPlant, a representative cyberinfrastructure platform for plant science. PMID:27115651

  13. MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease.

    Science.gov (United States)

    Shen, Lishuang; Diroma, Maria Angela; Gonzalez, Michael; Navarro-Gomez, Daniel; Leipzig, Jeremy; Lott, Marie T; van Oven, Mannis; Wallace, Douglas C; Muraresku, Colleen Clarke; Zolkipli-Cunningham, Zarazuela; Chinnery, Patrick F; Attimonelli, Marcella; Zuchner, Stephan; Falk, Marni J; Gai, Xiaowu

    2016-06-01

    MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse genome browser supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and mitochondrial disease. MSeqDR-LSDB is a locus-specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar compliant variant annotations. PhenoTips will be used for phenotypic data submission on deidentified patients using human phenotype ontology terminology. The development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources.

  14. MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease.

    Science.gov (United States)

    Shen, Lishuang; Diroma, Maria Angela; Gonzalez, Michael; Navarro-Gomez, Daniel; Leipzig, Jeremy; Lott, Marie T; van Oven, Mannis; Wallace, Douglas C; Muraresku, Colleen Clarke; Zolkipli-Cunningham, Zarazuela; Chinnery, Patrick F; Attimonelli, Marcella; Zuchner, Stephan; Falk, Marni J; Gai, Xiaowu

    2016-06-01

    MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse genome browser supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and mitochondrial disease. MSeqDR-LSDB is a locus-specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar compliant variant annotations. PhenoTips will be used for phenotypic data submission on deidentified patients using human phenotype ontology terminology. The development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources. PMID:26919060

  15. LLNL's Big Science Capabilities Help Spur Over $796 Billion in U.S. Economic Activity Sequencing the Human Genome

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, Jeffrey S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-07-28

    LLNL’s successful history of taking on big science projects spans beyond national security and has helped create billions of dollars per year in new economic activity. One example is LLNL’s role in helping sequence the human genome. Over $796 billion in new economic activity in over half a dozen fields has been documented since LLNL successfully completed this Grand Challenge.

  16. Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle

    DEFF Research Database (Denmark)

    Daetwyler, Hans D; Capitan, Aurélien; Pausch, Hubert;

    2014-01-01

    The 1000 bull genomes project supports the goal of accelerating the rates of genetic gain in domestic cattle while at the same time considering animal health and welfare by providing the annotated sequence variants and genotypes of key ancestor bulls. In the first phase of the 1000 bull genomes p...

  17. Characterizing Big Data Management

    OpenAIRE

    Rogério Rossi; Kechi Hirama

    2015-01-01

    Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: t...

  18. Facilitating a Culture of Responsible and Effective Sharing of Cancer Genome Data

    Science.gov (United States)

    Siu, Lillian L.; Lawler, Mark; Haussler, David; Knoppers, Bartha Maria; Lewin, Jeremy; Vis, Daniel J.; Liao, Rachel G.; Andre, Fabrice; Banks, Ian; Barrett, J. Carl; Caldas, Carlos; Camargo, Anamaria Aranha; Fitzgerald, Rebecca C.; Mao, Mao; Mattison, John E.; Pao, William; Sellers, William R.; Sullivan, Patrick; Teh, Bin Tean; Ward, Robyn; ZenKlusen, Jean Claude; Sawyers, Charles L; Voest, Emile E.

    2016-01-01

    Rapid and affordable tumor molecular profiling has led to an explosion of clinical and genomic data poised to enhance diagnosis, prognostication and treatment of cancer. A critical point has now been reached where analysis and storage of annotated clinical and genomic information in unconnected silos will stall the advancement of precision cancer care. Information systems must be harmonized to overcome the multiple technical and logistical barriers for data sharing. Against this backdrop, the Global Alliance for Genomic Health (GA4GH) was established in 2013 to create a common framework that enables responsible, voluntary, and secure sharing of clinical and genomic data. This Perspective from the GA4GH Clinical Working Group Cancer Task Team highlights the data aggregation challenges faced by the field, suggests potential collaborative solutions, and describes how GA4GH can catalyze a harmonized data sharing culture. PMID:27149219

  19. Bridging the gap between Big Genome Data Analysis and Database Management Systems

    NARCIS (Netherlands)

    Cijvat, C.P.

    2014-01-01

    The bioinformatics field has encountered a data deluge over the last years, due to in- creasing speed and decreasing cost of DNA sequencing technology. Today, sequencing the DNA of a single genome only takes about a week, and it can result in up to a ter- abyte of data. The sequencing data are usual

  20. Single-Cell-Genomics-Facilitated Read Binning of Candidate Phylum EM19 Genomes from Geothermal Spring Metagenomes.

    Science.gov (United States)

    Becraft, Eric D; Dodsworth, Jeremy A; Murugapiran, Senthil K; Ohlsson, J Ingemar; Briggs, Brandon R; Kanbar, Jad; De Vlaminck, Iwijn; Quake, Stephen R; Dong, Hailiang; Hedlund, Brian P; Swingley, Wesley D

    2015-12-04

    The vast majority of microbial life remains uncatalogued due to the inability to cultivate these organisms in the laboratory. This "microbial dark matter" represents a substantial portion of the tree of life and of the populations that contribute to chemical cycling in many ecosystems. In this work, we leveraged an existing single-cell genomic data set representing the candidate bacterial phylum "Calescamantes" (EM19) to calibrate machine learning algorithms and define metagenomic bins directly from pyrosequencing reads derived from Great Boiling Spring in the U.S. Great Basin. Compared to other assembly-based methods, taxonomic binning with a read-based machine learning approach yielded final assemblies with the highest predicted genome completeness of any method tested. Read-first binning subsequently was used to extract Calescamantes bins from all metagenomes with abundant Calescamantes populations, including metagenomes from Octopus Spring and Bison Pool in Yellowstone National Park and Gongxiaoshe Spring in Yunnan Province, China. Metabolic reconstruction suggests that Calescamantes are heterotrophic, facultative anaerobes, which can utilize oxidized nitrogen sources as terminal electron acceptors for respiration in the absence of oxygen and use proteins as their primary carbon source. Despite their phylogenetic divergence, the geographically separate Calescamantes populations were highly similar in their predicted metabolic capabilities and core gene content, respiring O2, or oxidized nitrogen species for energy conservation in distant but chemically similar hot springs.

  1. Facilitating genome navigation : survey sequencing and dense radiation-hybrid gene mapping

    NARCIS (Netherlands)

    Hitte, C; Madeoy, J; Kirkness, EF; Priat, C; Lorentzen, TD; Senger, F; Thomas, D; Derrien, T; Ramirez, C; Scott, C; Evanno, G; Pullar, B; Cadieu, E; Oza, [No Value; Lourgant, K; Jaffe, DB; Tacher, S; Dreano, S; Berkova, N; Andre, C; Deloukas, P; Fraser, C; Lindblad-Toh, K; Ostrander, EA; Galibert, F

    2005-01-01

    Accurate and comprehensive sequence coverage for large genomes has been restricted to only a few species of specific interest. Lower sequence coverage (survey sequencing) of related species can yield a wealth of information about gene content and putative regulatory elements. But survey sequences la

  2. Big Data

    OpenAIRE

    Eils, Jürgen

    2013-01-01

    Das weltweite Datenvolumen verdoppelt sich ca. alle zwei Jahre. Der Fortschritt bei der Auswertung ist atemberaubend. Tausende Wissenschaftlcer brauchten mehr als ein Jahrzehnt, um erstmals das vollständige menschliche Genom zu entschlüsseln. Das hat sich dramatisch geändert, meint Jürgen Eils, Leiter der Data-Management-Gruppe am Deutschen Krebsforschungszentrum in Heidelberg ... Der Beitrag über Big Data erschien in der Sendereihe "Campus-Report" - einer Beitragsreihe, in der über aktue...

  3. From functional genomics to functional immunomics: new challenges, old problems, big rewards.

    Directory of Open Access Journals (Sweden)

    Ulisses M Braga-Neto

    2006-07-01

    Full Text Available The development of DNA microarray technology a decade ago led to the establishment of functional genomics as one of the most active and successful scientific disciplines today. With the ongoing development of immunomic microarray technology-a spatially addressable, large-scale technology for measurement of specific immunological response-the new challenge of functional immunomics is emerging, which bears similarities to but is also significantly different from functional genomics. Immunonic data has been successfully used to identify biological markers involved in autoimmune diseases, allergies, viral infections such as human immunodeficiency virus (HIV, influenza, diabetes, and responses to cancer vaccines. This review intends to provide a coherent vision of this nascent scientific field, and speculate on future research directions. We discuss at some length issues such as epitope prediction, immunomic microarray technology and its applications, and computation and statistical challenges related to functional immunomics. Based on the recent discovery of regulation mechanisms in T cell responses, we envision the use of immunomic microarrays as a tool for advances in systems biology of cellular immune responses, by means of immunomic regulatory network models.

  4. Human CST Facilitates Genome-wide RAD51 Recruitment to GC-Rich Repetitive Sequences in Response to Replication Stress.

    Science.gov (United States)

    Chastain, Megan; Zhou, Qing; Shiva, Olga; Whitmore, Leanne; Jia, Pingping; Dai, Xueyu; Huang, Chenhui; Fadri-Moskwik, Maria; Ye, Ping; Chai, Weihang

    2016-08-01

    The telomeric CTC1/STN1/TEN1 (CST) complex has been implicated in promoting replication recovery under replication stress at genomic regions, yet its precise role is unclear. Here, we report that STN1 is enriched at GC-rich repetitive sequences genome-wide in response to hydroxyurea (HU)-induced replication stress. STN1 deficiency exacerbates the fragility of these sequences under replication stress, resulting in chromosome fragmentation. We find that upon fork stalling, CST proteins form distinct nuclear foci that colocalize with RAD51. Furthermore, replication stress induces physical association of CST with RAD51 in an ATR-dependent manner. Strikingly, CST deficiency diminishes HU-induced RAD51 foci formation and reduces RAD51 recruitment to telomeres and non-telomeric GC-rich fragile sequences. Collectively, our findings establish that CST promotes RAD51 recruitment to GC-rich repetitive sequences in response to replication stress to facilitate replication restart, thereby providing insights into the mechanism underlying genome stability maintenance.

  5. A central support system can facilitate implementation and sustainability of a Classroom-based Undergraduate Research Experience (CURE) in Genomics.

    Science.gov (United States)

    Lopatto, David; Hauser, Charles; Jones, Christopher J; Paetkau, Don; Chandrasekaran, Vidya; Dunbar, David; MacKinnon, Christy; Stamm, Joyce; Alvarez, Consuelo; Barnard, Daron; Bedard, James E J; Bednarski, April E; Bhalla, Satish; Braverman, John M; Burg, Martin; Chung, Hui-Min; DeJong, Randall J; DiAngelo, Justin R; Du, Chunguang; Eckdahl, Todd T; Emerson, Julia; Frary, Amy; Frohlich, Donald; Goodman, Anya L; Gosser, Yuying; Govind, Shubha; Haberman, Adam; Hark, Amy T; Hoogewerf, Arlene; Johnson, Diana; Kadlec, Lisa; Kaehler, Marian; Key, S Catherine Silver; Kokan, Nighat P; Kopp, Olga R; Kuleck, Gary A; Lopilato, Jane; Martinez-Cruzado, Juan C; McNeil, Gerard; Mel, Stephanie; Nagengast, Alexis; Overvoorde, Paul J; Parrish, Susan; Preuss, Mary L; Reed, Laura D; Regisford, E Gloria; Revie, Dennis; Robic, Srebrenka; Roecklien-Canfield, Jennifer A; Rosenwald, Anne G; Rubin, Michael R; Saville, Kenneth; Schroeder, Stephanie; Sharif, Karim A; Shaw, Mary; Skuse, Gary; Smith, Christopher D; Smith, Mary; Smith, Sheryl T; Spana, Eric P; Spratt, Mary; Sreenivasan, Aparna; Thompson, Jeffrey S; Wawersik, Matthew; Wolyniak, Michael J; Youngblom, James; Zhou, Leming; Buhler, Jeremy; Mardis, Elaine; Leung, Wilson; Shaffer, Christopher D; Threlfall, Jennifer; Elgin, Sarah C R

    2014-01-01

    In their 2012 report, the President's Council of Advisors on Science and Technology advocated "replacing standard science laboratory courses with discovery-based research courses"-a challenging proposition that presents practical and pedagogical difficulties. In this paper, we describe our collective experiences working with the Genomics Education Partnership, a nationwide faculty consortium that aims to provide undergraduates with a research experience in genomics through a scheduled course (a classroom-based undergraduate research experience, or CURE). We examine the common barriers encountered in implementing a CURE, program elements of most value to faculty, ways in which a shared core support system can help, and the incentives for and rewards of establishing a CURE on our diverse campuses. While some of the barriers and rewards are specific to a research project utilizing a genomics approach, other lessons learned should be broadly applicable. We find that a central system that supports a shared investigation can mitigate some shortfalls in campus infrastructure (such as time for new curriculum development, availability of IT services) and provides collegial support for change. Our findings should be useful for designing similar supportive programs to facilitate change in the way we teach science for undergraduates. PMID:25452493

  6. Recombination and evolution of duplicate control regions in the mitochondrial genome of the Asian big-headed turtle, Platysternon megacephalum.

    Directory of Open Access Journals (Sweden)

    Chenfei Zheng

    Full Text Available Complete mitochondrial (mt genome sequences with duplicate control regions (CRs have been detected in various animal species. In Testudines, duplicate mtCRs have been reported in the mtDNA of the Asian big-headed turtle, Platysternon megacephalum, which has three living subspecies. However, the evolutionary pattern of these CRs remains unclear. In this study, we report the completed sequences of duplicate CRs from 20 individuals belonging to three subspecies of this turtle and discuss the micro-evolutionary analysis of the evolution of duplicate CRs. Genetic distances calculated with MEGA 4.1 using the complete duplicate CR sequences revealed that within turtle subspecies, genetic distances between orthologous copies from different individuals were 0.63% for CR1 and 1.2% for CR2app:addword:respectively, and the average distance between paralogous copies of CR1 and CR2 was 4.8%. Phylogenetic relationships were reconstructed from the CR sequences, excluding the variable number of tandem repeats (VNTRs at the 3' end using three methods: neighbor-joining, maximum likelihood algorithm, and Bayesian inference. These data show that any two CRs within individuals were more genetically distant from orthologous genes in different individuals within the same subspecies. This suggests independent evolution of the two mtCRs within each P. megacephalum subspecies. Reconstruction of separate phylogenetic trees using different CR components (TAS, CD, CSB, and VNTRs suggested the role of recombination in the evolution of duplicate CRs. Consequently, recombination events were detected using RDP software with break points at ≈290 bp and ≈1,080 bp. Based on these results, we hypothesize that duplicate CRs in P. megacephalum originated from heterological ancestral recombination of mtDNA. Subsequent recombination could have resulted in homogenization during independent evolutionary events, thus maintaining the functions of duplicate CRs in the mtDNA of P

  7. De novo transcriptome sequencing facilitates genomic resource generation in Tinospora cordifolia.

    Science.gov (United States)

    Singh, Rakesh; Kumar, Rajesh; Mahato, Ajay Kumar; Paliwal, Ritu; Singh, Amit Kumar; Kumar, Sundeep; Marla, Soma S; Kumar, Ashok; Singh, Nagendra K

    2016-09-01

    Tinospora cordifolia is known for its medicinal properties owing to the presence of useful constituents such as terpenes, glycosides, steroids, alkaloids, and flavonoids belonging to secondary metabolism origin. However, there is little information available pertaining to critical genomic elements (ESTs, molecular markers) necessary for judicious exploitation of its germplasm. We employed 454 GS-FLX pyrosequencing of entire transcripts and altogether ∼25 K assembled transcripts or Expressed sequence tags (ESTs) were identified. As the interest in T. cordifolia is primarily due to its secondary metabolite constituents, the ESTs pertaining to terpenoids biosynthetic pathway were identified in the present study. Additionally, several ESTs were assigned to different transcription factor families. To validate our transcripts dataset, the novel EST-SSR markers were generated to assess the genetic diversity among germplasm of T. cordifolia. These EST-SSR markers were found to be polymorphic and the dendrogram based on dice similarity index revealed three distinct clustering of accessions. The present study demonstrates effectiveness in using both NEWBLER and MIRA sequence read assembler software for enriching transcript-dataset and thus enables better exploitation of EST resources for mining candidate genes and designing molecular markers. PMID:27465295

  8. Accurate Dna Assembly And Direct Genome Integration With Optimized Uracil Excision Cloning To Facilitate Engineering Of Escherichia Coli As A Cell Factory

    DEFF Research Database (Denmark)

    Cavaleiro, Mafalda; Kim, Se Hyeuk; Nørholm, Morten

    2015-01-01

    Plants produce a vast diversity of valuable compounds with medical properties, but these are often difficult to purify from the natural source or produce by organic synthesis. An alternative is to transfer the biosynthetic pathways to an efficient production host like the bacterium Escherichia coli......-excision-based cloning and combining it with a genome-engineering approach to allow direct integration of whole metabolic pathways into the genome of E. coli, to facilitate the advanced engineering of cell factories....

  9. Machine learning for Big Data analytics in plants.

    Science.gov (United States)

    Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

    2014-12-01

    Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences.

  10. Machine learning for Big Data analytics in plants.

    Science.gov (United States)

    Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

    2014-12-01

    Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences. PMID:25223304

  11. Polycomb repressive complex 2 facilitates the nuclear export of the influenza viral genome through the interaction with M1.

    Science.gov (United States)

    Asaka, Masamitsu N; Kawaguchi, Atsushi; Sakai, Yuri; Mori, Kotaro; Nagata, Kyosuke

    2016-01-01

    The organization of nuclear domains is crucial for biological events including virus infection. Newly synthesized influenza viral genome forms viral ribonucleoprotein (vRNP) complexes and is exported from the nucleus to the cytoplasm through a CRM1-dependent pathway mediated by viral proteins M1 and NS2. However, the spatio-temporal regulation of the progeny vRNP in the nucleus is still unclear. Here we found that polycomb repressive complex 2 (PRC2), which contains a methyltransferase subunit EZH2 and catalyzes histone H3K27me3 for the formation of facultative heterochromatin, is a positive factor for the virus production. Depletion of PRC2 complex showed the nuclear accumulation of vRNP and the reduction of M1-vRNP complex formation. We also found that PRC2 complex directly binds to M1, and facilitates the interaction of M1 with vRNP. In conclusion, we propose that the progeny vRNP could be recruited to facultative heterochromatin and assembled into the export complex mediated by PRC2 complex. PMID:27646999

  12. Genome-scale reconstruction and analysis of the Pseudomonas putida KT2440 metabolic network facilitates applications in biotechnology.

    Directory of Open Access Journals (Sweden)

    Jacek Puchałka

    2008-10-01

    Full Text Available A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, (13C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype-phenotype relationships and provides a sound framework to explore this versatile

  13. Big data for health.

    Science.gov (United States)

    Andreu-Perez, Javier; Poon, Carmen C Y; Merrifield, Robert D; Wong, Stephen T C; Yang, Guang-Zhong

    2015-07-01

    This paper provides an overview of recent developments in big data in the context of biomedical and health informatics. It outlines the key characteristics of big data and how medical and health informatics, translational bioinformatics, sensor informatics, and imaging informatics will benefit from an integrated approach of piecing together different aspects of personalized information from a diverse range of data sources, both structured and unstructured, covering genomics, proteomics, metabolomics, as well as imaging, clinical diagnosis, and long-term continuous physiological sensing of an individual. It is expected that recent advances in big data will expand our knowledge for testing new hypotheses about disease management from diagnosis to prevention to personalized treatment. The rise of big data, however, also raises challenges in terms of privacy, security, data ownership, data stewardship, and governance. This paper discusses some of the existing activities and future opportunities related to big data for health, outlining some of the key underlying issues that need to be tackled. PMID:26173222

  14. Big data for health.

    Science.gov (United States)

    Andreu-Perez, Javier; Poon, Carmen C Y; Merrifield, Robert D; Wong, Stephen T C; Yang, Guang-Zhong

    2015-07-01

    This paper provides an overview of recent developments in big data in the context of biomedical and health informatics. It outlines the key characteristics of big data and how medical and health informatics, translational bioinformatics, sensor informatics, and imaging informatics will benefit from an integrated approach of piecing together different aspects of personalized information from a diverse range of data sources, both structured and unstructured, covering genomics, proteomics, metabolomics, as well as imaging, clinical diagnosis, and long-term continuous physiological sensing of an individual. It is expected that recent advances in big data will expand our knowledge for testing new hypotheses about disease management from diagnosis to prevention to personalized treatment. The rise of big data, however, also raises challenges in terms of privacy, security, data ownership, data stewardship, and governance. This paper discusses some of the existing activities and future opportunities related to big data for health, outlining some of the key underlying issues that need to be tackled.

  15. Från data till kunskap : En kvalitativ studie om interaktiv visualisering av big data genom dashboards

    OpenAIRE

    Agerberg, David; Eriksson, Linus

    2016-01-01

    Rapid growing volumes of data demands new solutions in terms of analysing and visualizing. The growing amount of data contains valuable information which organizations in a more digitized society need to manage. It is a major challenge to visualize data, both in a static and interactive way. Through visualization of big data follows several opportunities containing risk assessment and decision basis. Previous research indicates a lack of standards and guidelines considering the development of...

  16. The DNA damage checkpoint pathway promotes extensive resection and nucleotide synthesis to facilitate homologous recombination repair and genome stability in fission yeast.

    Science.gov (United States)

    Blaikley, Elizabeth J; Tinline-Purvis, Helen; Kasparek, Torben R; Marguerat, Samuel; Sarkar, Sovan; Hulme, Lydia; Hussey, Sharon; Wee, Boon-Yu; Deegan, Rachel S; Walker, Carol A; Pai, Chen-Chun; Bähler, Jürg; Nakagawa, Takuro; Humphrey, Timothy C

    2014-05-01

    DNA double-strand breaks (DSBs) can cause chromosomal rearrangements and extensive loss of heterozygosity (LOH), hallmarks of cancer cells. Yet, how such events are normally suppressed is unclear. Here we identify roles for the DNA damage checkpoint pathway in facilitating homologous recombination (HR) repair and suppressing extensive LOH and chromosomal rearrangements in response to a DSB. Accordingly, deletion of Rad3(ATR), Rad26ATRIP, Crb2(53BP1) or Cdc25 overexpression leads to reduced HR and increased break-induced chromosome loss and rearrangements. We find the DNA damage checkpoint pathway facilitates HR, in part, by promoting break-induced Cdt2-dependent nucleotide synthesis. We also identify additional roles for Rad17, the 9-1-1 complex and Chk1 activation in facilitating break-induced extensive resection and chromosome loss, thereby suppressing extensive LOH. Loss of Rad17 or the 9-1-1 complex results in a striking increase in break-induced isochromosome formation and very low levels of chromosome loss, suggesting the 9-1-1 complex acts as a nuclease processivity factor to facilitate extensive resection. Further, our data suggest redundant roles for Rad3ATR and Exo1 in facilitating extensive resection. We propose that the DNA damage checkpoint pathway coordinates resection and nucleotide synthesis, thereby promoting efficient HR repair and genome stability. PMID:24623809

  17. Clinical research of traditional Chinese medicine in big data era.

    Science.gov (United States)

    Zhang, Junhua; Zhang, Boli

    2014-09-01

    With the advent of big data era, our thinking, technology and methodology are being transformed. Data-intensive scientific discovery based on big data, named "The Fourth Paradigm," has become a new paradigm of scientific research. Along with the development and application of the Internet information technology in the field of healthcare, individual health records, clinical data of diagnosis and treatment, and genomic data have been accumulated dramatically, which generates big data in medical field for clinical research and assessment. With the support of big data, the defects and weakness may be overcome in the methodology of the conventional clinical evaluation based on sampling. Our research target shifts from the "causality inference" to "correlativity analysis." This not only facilitates the evaluation of individualized treatment, disease prediction, prevention and prognosis, but also is suitable for the practice of preventive healthcare and symptom pattern differentiation for treatment in terms of traditional Chinese medicine (TCM), and for the post-marketing evaluation of Chinese patent medicines. To conduct clinical studies involved in big data in TCM domain, top level design is needed and should be performed orderly. The fundamental construction and innovation studies should be strengthened in the sections of data platform creation, data analysis technology and big-data professionals fostering and training.

  18. Clinical research of traditional Chinese medicine in big data era.

    Science.gov (United States)

    Zhang, Junhua; Zhang, Boli

    2014-09-01

    With the advent of big data era, our thinking, technology and methodology are being transformed. Data-intensive scientific discovery based on big data, named "The Fourth Paradigm," has become a new paradigm of scientific research. Along with the development and application of the Internet information technology in the field of healthcare, individual health records, clinical data of diagnosis and treatment, and genomic data have been accumulated dramatically, which generates big data in medical field for clinical research and assessment. With the support of big data, the defects and weakness may be overcome in the methodology of the conventional clinical evaluation based on sampling. Our research target shifts from the "causality inference" to "correlativity analysis." This not only facilitates the evaluation of individualized treatment, disease prediction, prevention and prognosis, but also is suitable for the practice of preventive healthcare and symptom pattern differentiation for treatment in terms of traditional Chinese medicine (TCM), and for the post-marketing evaluation of Chinese patent medicines. To conduct clinical studies involved in big data in TCM domain, top level design is needed and should be performed orderly. The fundamental construction and innovation studies should be strengthened in the sections of data platform creation, data analysis technology and big-data professionals fostering and training. PMID:25217972

  19. Big Data in industry

    Science.gov (United States)

    Latinović, T. S.; Preradović, D. M.; Barz, C. R.; Latinović, M. T.; Petrica, P. P.; Pop-Vadean, A.

    2016-08-01

    The amount of data at the global level has grown exponentially. Along with this phenomena, we have a need for a new unit of measure like exabyte, zettabyte, and yottabyte as the last unit measures the amount of data. The growth of data gives a situation where the classic systems for the collection, storage, processing, and visualization of data losing the battle with a large amount, speed, and variety of data that is generated continuously. Many of data that is created by the Internet of Things, IoT (cameras, satellites, cars, GPS navigation, etc.). It is our challenge to come up with new technologies and tools for the management and exploitation of these large amounts of data. Big Data is a hot topic in recent years in IT circles. However, Big Data is recognized in the business world, and increasingly in the public administration. This paper proposes an ontology of big data analytics and examines how to enhance business intelligence through big data analytics as a service by presenting a big data analytics services-oriented architecture. This paper also discusses the interrelationship between business intelligence and big data analytics. The proposed approach in this paper might facilitate the research and development of business analytics, big data analytics, and business intelligence as well as intelligent agents.

  20. Big data

    OpenAIRE

    Thomsen, Christoffer Bolvig; Steffensen, Nikolaj; Jørgensen, Frederik Thordal; Olesen, Rasmus Bjørk; Nilsson, Martin Becker; Iramdane, Souphian

    2014-01-01

    In the recent past, a new phenomenon in digital marketing, has gained more attention from companies, the phenomenon is called big data. Big data is a term in computer science that broadly covers the collection, storage, analysis and interpretation of huge amounts of data, from various sources. In the project questions are made to find answers for what companies should pay attention to when using big data. Companies use big data to marketing, inventory management and general business managemen...

  1. Expression of IMP1 enhances production of murine leukemia virus vector by facilitating viral genomic RNA packaging.

    Directory of Open Access Journals (Sweden)

    Yun Mai

    Full Text Available Murine leukemia virus (MLV-based retroviral vector is widely used for gene transfer. Efficient packaging of the genomic RNA is critical for production of high-titer virus. Here, we report that expression of the insulin-like growth factor II mRNA binding protein 1 (IMP1 enhanced the production of infectious MLV vector. Overexpression of IMP1 increased the stability of viral genomic RNA in virus producer cells and packaging of the RNA into progeny virus in a dose-dependent manner. Downregulation of IMP1 in virus producer cells resulted in reduced production of the retroviral vector. These results indicate that IMP1 plays a role in regulating the packaging of MLV genomic RNA and can be used for improving production of retroviral vectors.

  2. Discovery of Nigri/nox and Panto/pox site-specific recombinase systems facilitates advanced genome engineering.

    Science.gov (United States)

    Karimova, Madina; Splith, Victoria; Karpinski, Janet; Pisabarro, M Teresa; Buchholz, Frank

    2016-01-01

    Precise genome engineering is instrumental for biomedical research and holds great promise for future therapeutic applications. Site-specific recombinases (SSRs) are valuable tools for genome engineering due to their exceptional ability to mediate precise excision, integration and inversion of genomic DNA in living systems. The ever-increasing complexity of genome manipulations and the desire to understand the DNA-binding specificity of these enzymes are driving efforts to identify novel SSR systems with unique properties. Here, we describe two novel tyrosine site-specific recombination systems designated Nigri/nox and Panto/pox. Nigri originates from Vibrio nigripulchritudo (plasmid VIBNI_pA) and recombines its target site nox with high efficiency and high target-site selectivity, without recombining target sites of the well established SSRs Cre, Dre, Vika and VCre. Panto, derived from Pantoea sp. aB, is less specific and in addition to its native target site, pox also recombines the target site for Dre recombinase, called rox. This relaxed specificity allowed the identification of residues that are involved in target site selectivity, thereby advancing our understanding of how SSRs recognize their respective DNA targets. PMID:27444945

  3. Discovery of Nigri/nox and Panto/pox site-specific recombinase systems facilitates advanced genome engineering

    Science.gov (United States)

    Karimova, Madina; Splith, Victoria; Karpinski, Janet; Pisabarro, M. Teresa; Buchholz, Frank

    2016-01-01

    Precise genome engineering is instrumental for biomedical research and holds great promise for future therapeutic applications. Site-specific recombinases (SSRs) are valuable tools for genome engineering due to their exceptional ability to mediate precise excision, integration and inversion of genomic DNA in living systems. The ever-increasing complexity of genome manipulations and the desire to understand the DNA-binding specificity of these enzymes are driving efforts to identify novel SSR systems with unique properties. Here, we describe two novel tyrosine site-specific recombination systems designated Nigri/nox and Panto/pox. Nigri originates from Vibrio nigripulchritudo (plasmid VIBNI_pA) and recombines its target site nox with high efficiency and high target-site selectivity, without recombining target sites of the well established SSRs Cre, Dre, Vika and VCre. Panto, derived from Pantoea sp. aB, is less specific and in addition to its native target site, pox also recombines the target site for Dre recombinase, called rox. This relaxed specificity allowed the identification of residues that are involved in target site selectivity, thereby advancing our understanding of how SSRs recognize their respective DNA targets. PMID:27444945

  4. Can fat explain the human brain's big bang evolution?-Horrobin's leads for comparative and functional genomics.

    Science.gov (United States)

    Erren, T C; Erren, M

    2004-04-01

    When David Horrobin suggested that phospholipid and fatty acid metabolism played a major role in human evolution, his 'fat utilization hypothesis' unified intriguing work from paleoanthropology, evolutionary biology, genetic and nervous system research in a novel and coherent lipid-related context. Interestingly, unlike most other evolutionary concepts, the hypothesis allows specific predictions which can be empirically tested in the near future. This paper summarizes some of Horrobin's intriguing propositions and suggests as to how approaches of comparative genomics published in Cell, Nature, Science and elsewhere since 1997 may be used to examine his evolutionary hypothesis. Indeed, systematic investigations of the genomic clock in the species' mitochondrial DNA, the Y and autosomal chromosomes as evidence of evolutionary relationships and distinctions can help to scrutinize associated predictions for their validity, namely that key mutations which differentiate us from Neanderthals and from great apes are in the genes coding for proteins which regulate fat metabolism, and particularly the phospholipid metabolism of the synapses of the brain. It is concluded that beyond clues to humans' relationships with living primates and to the Neanderthals' cognitive performance and their disappearance, the suggested molecular clock analyses may provide crucial insights into the biochemical evolution-and means of possible manipulation-of our brain.

  5. Test balloons? Small signs of big events: a qualitative study on circumstances facilitating adults' awareness of children's first signs of sexual abuse.

    Science.gov (United States)

    Flåm, Anna Margrete; Haugstvedt, Eli

    2013-09-01

    This research examined caregivers' awareness of children's first signs of sexual abuse. The aim was to explore circumstances that facilitate adults' awareness of first signs in everyday natural settings. Data were obtained from a Norwegian university hospital's outpatient specialty mental health clinic. Included were all cases (N=20) referred during a two-year period for treatment after the disclosure of sexual abuse that was reported to the police and child protective service. Nonabusing caregivers' awareness of first signs were recollected in hindsight as part of therapy. Qualitative analysis was conducted to capture caregivers' experiences. As identified by caregivers, all children gave signs. Thereafter, children either stopped, delayed, or immediately disclosed sexual abuse. At first signs, each child had time and attention from trusted adults, connection to the abuser, and exhibited signs of reservation against that person or related activities. Then, if met with closed answers, first signs were rebuffed as once-occurring events. If met with open answers and follow-up questions, children continued to tell. Unambiguous messages were prompted only in settings with intimate bodily activity or sexual abuse related content. In sum, when trusted adults provided door-openings, children used them; when carefully prompted, children talked; when thoughtfully asked, children told. The study suggests that children's signs of sexual abuse can be understood as "test balloons" to explore understanding and whether anything is to be done. A disclosing continuation hinges on the trusted adult's dialogical attunement and supplementary door-openings. Divergent from an idea of behavioural markers, or purposeful versus accidental disclosures, this study calls for a broader attention: Moments of first signs are embedded in dialogue. A uniqueness at moments of first signs appears: Both to form such moments and to transform them into moments of meeting for joint exploration and

  6. Test balloons? Small signs of big events: a qualitative study on circumstances facilitating adults' awareness of children's first signs of sexual abuse.

    Science.gov (United States)

    Flåm, Anna Margrete; Haugstvedt, Eli

    2013-09-01

    This research examined caregivers' awareness of children's first signs of sexual abuse. The aim was to explore circumstances that facilitate adults' awareness of first signs in everyday natural settings. Data were obtained from a Norwegian university hospital's outpatient specialty mental health clinic. Included were all cases (N=20) referred during a two-year period for treatment after the disclosure of sexual abuse that was reported to the police and child protective service. Nonabusing caregivers' awareness of first signs were recollected in hindsight as part of therapy. Qualitative analysis was conducted to capture caregivers' experiences. As identified by caregivers, all children gave signs. Thereafter, children either stopped, delayed, or immediately disclosed sexual abuse. At first signs, each child had time and attention from trusted adults, connection to the abuser, and exhibited signs of reservation against that person or related activities. Then, if met with closed answers, first signs were rebuffed as once-occurring events. If met with open answers and follow-up questions, children continued to tell. Unambiguous messages were prompted only in settings with intimate bodily activity or sexual abuse related content. In sum, when trusted adults provided door-openings, children used them; when carefully prompted, children talked; when thoughtfully asked, children told. The study suggests that children's signs of sexual abuse can be understood as "test balloons" to explore understanding and whether anything is to be done. A disclosing continuation hinges on the trusted adult's dialogical attunement and supplementary door-openings. Divergent from an idea of behavioural markers, or purposeful versus accidental disclosures, this study calls for a broader attention: Moments of first signs are embedded in dialogue. A uniqueness at moments of first signs appears: Both to form such moments and to transform them into moments of meeting for joint exploration and

  7. Big universe, big data

    DEFF Research Database (Denmark)

    Kremer, Jan; Stensbo-Smidt, Kristoffer; Gieseke, Fabian Cristian;

    2016-01-01

    , modern astronomy requires big data know-how, in particular it demands highly efficient machine learning and image analysis algorithms. But scalability is not the only challenge: Astronomy applications touch several current machine learning research questions, such as learning from biased data and dealing......Astrophysics and cosmology are rich with data. The advent of wide-area digital cameras on large aperture telescopes has led to ever more ambitious surveys of the sky. Data volumes of entire surveys a decade ago can now be acquired in a single night and real-time analysis is often desired. Thus...... with label and measurement noise. We argue that this makes astronomy a great domain for computer science research, as it pushes the boundaries of data analysis. In the following, we will present this exciting application area for data scientists. We will focus on exemplary results, discuss main challenges...

  8. The Drosophila melanogaster PeptideAtlas facilitates the use of peptide data for improved fly proteomics and genome annotation

    Directory of Open Access Journals (Sweden)

    King Nichole L

    2009-02-01

    Full Text Available Abstract Background Crucial foundations of any quantitative systems biology experiment are correct genome and proteome annotations. Protein databases compiled from high quality empirical protein identifications that are in turn based on correct gene models increase the correctness, sensitivity, and quantitative accuracy of systems biology genome-scale experiments. Results In this manuscript, we present the Drosophila melanogaster PeptideAtlas, a fly proteomics and genomics resource of unsurpassed depth. Based on peptide mass spectrometry data collected in our laboratory the portal http://www.drosophila-peptideatlas.org allows querying fly protein data observed with respect to gene model confirmation and splice site verification as well as for the identification of proteotypic peptides suited for targeted proteomics studies. Additionally, the database provides consensus mass spectra for observed peptides along with qualitative and quantitative information about the number of observations of a particular peptide and the sample(s in which it was observed. Conclusion PeptideAtlas is an open access database for the Drosophila community that has several features and applications that support (1 reduction of the complexity inherently associated with performing targeted proteomic studies, (2 designing and accelerating shotgun proteomics experiments, (3 confirming or questioning gene models, and (4 adjusting gene models such that they are in line with observed Drosophila peptides. While the database consists of proteomic data it is not required that the user is a proteomics expert.

  9. Moleculo long-read sequencing facilitates assembly and resolves functionally active genomic bins from complex soil metagenomes

    Energy Technology Data Exchange (ETDEWEB)

    White, Richard A.; Bottos, Eric M.; Roy Chowdhury, Taniya; Zucker, Jeremy D.; Brislawn, Colin J.; Nicora, Carrie D.; Fansler, Sarah J.; Glaesemann, Kurt R.; Glass, Kevin A.; Jansson, Janet K.

    2016-07-28

    Soil metagenomics has been touted as the "grand challenge" for metagenomes, as the high microbial diversity, sample complexity, and spatial heterogeneity of soils makes them unamenable to current sequencing and assembly platforms. Here we aimed to improve soil metagenomic sequence assembly by applying a synthetic long read sequencing technology (i.e. Moleculo) from three locations within Konza native prairie station in Kansas. In total, we obtained 520 GB of raw sequence data; 239 GB of short read data from the Joint Genome Institute (JGI), an additional 97 GB from Moleculo sequencing, plus 184 GB of rapid mode sequence data. The Moleculo data alone yielded over 5,600 reads greater than 10 kbp in length, mapping over 95% of the total sequence data. Hybrid assembly of all data resulted in more than 10,000 contigs over 10 kbp in length. The Moleculo sub-assemblies captured much of the functional potential of the soil community, in that 92% of the functional enzyme commission numbers (EC) predicted from the metagenome were also detected in metatranscriptome data. The Moleculo sub-assembly enabled binning of more than 100 novel soil microbial genomic bins. Candidatus Pseudomonas janssonensis strain KNPRW21, was the first genome obtained from a native soil metagenome by direct binning. By mapping RNA-Seq (i.e. metatranscriptomic) sequence reads back to the bins, we found that several low abundance Acidobacteria bins were highly transcriptionally active, whereas the highly abundant Verruomicrobia bins were not. Using Moleculo long reads alone or combined with conventional short read metagenomic data is therefore a useful tool for resolving complex soil microbial communities.

  10. Big Data

    DEFF Research Database (Denmark)

    Madsen, Anders Koed; Flyverbom, Mikkel; Hilbert, Martin;

    2016-01-01

    The claim that big data can revolutionize strategy and governance in the context of international relations is increasingly hard to ignore. Scholars of international political sociology have mainly discussed this development through the themes of security and surveillance. The aim of this paper...... is to outline a research agenda that can be used to raise a broader set of sociological and practice-oriented questions about the increasing datafication of international relations and politics. First, it proposes a way of conceptualizing big data that is broad enough to open fruitful investigations...... into the emerging use of big data in these contexts. This conceptualization includes the identification of three moments contained in any big data practice. Second, it suggests a research agenda built around a set of subthemes that each deserve dedicated scrutiny when studying the interplay between big data...

  11. Big data

    DEFF Research Database (Denmark)

    Madsen, Anders Koed; Ruppert, Evelyn; Flyverbom, Mikkel;

    2016-01-01

    The claim that big data can revolutionize strategy and governance in the context of international relations is increasingly hard to ignore. Scholars of international political sociology have mainly discussed this development through the themes of security and surveillance. The aim of this paper...... is to outline a research agenda that can be used to raise a broader set of sociological and practice-oriented questions about the increasing datafication of international relations and politics. First, it proposes a way of conceptualizing big data that is broad enough to open fruitful investigations...... into the emerging use of big data in these contexts. This conceptualization includes the identification of three moments that is contained in any big data practice. Secondly, it suggest a research agenda built around a set of sub-themes that each deserve dedicated scrutiny when studying the interplay between big...

  12. Big Egos in Big Science

    DEFF Research Database (Denmark)

    Jeppesen, Jacob; Vaarst Andersen, Kristina; Lauto, Giancarlo;

    and locations, having a diverse knowledge set and capable of tackling more and more complex problems. This prose the question if Big Egos continues to dominate in this rising paradigm of big science. Using a dataset consisting of full bibliometric coverage from a Large Scale Research Facility, we utilize...... a stochastic actor oriented model (SAOM) to analyze both network endogeneous mechanisms and individual agency driving the collaboration network and further if being a Big Ego in Big Science translates to increasing performance. Our findings suggest that the selection of collaborators is not based...... on preferentialattachment, but more of an assortativity effect creating not merely a rich-gets-richer effect but an elitist network with high entry barriers. In this acclaimed democratic and collaborative environment of Big Science, the elite closes in on itself. We propose this tendency to be even more explicit in other...

  13. Big Data

    OpenAIRE

    Sabater Picañol, Jordi

    2013-01-01

    El proyecto se ha desarrollado en la empresa Everis y ha sido el resultado de la colaboración con otro estudiante de la Facultad de Informática de Barcelona, Robert Serrat Morros. [CASTELLÀ] El concepto Big Data está cobrando actualmente un gran interés creciente por parte de las empresas, que ven en ello una gran ventaja competitiva. Este proyecto busca justificar este interés creciente partiendo de los conceptos más básicos de Big Data. [ANGLÈS] The Big Data concept is nowadays...

  14. Big Data

    OpenAIRE

    Prachi More; Latika Chaudhary; Sangita Panmand; Prof. Nilesh Shah

    2013-01-01

    Demand and spurt in collections and accumulation of data has coined new term “Big Data” has begun. Accidently, incidentally and by interaction of people, information so called data is massively generated. This BIG DATA is to be smartly and effectively used Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists and many Variety of Intellegesia debate over the potential benefits and costs of analysing information from Twitter, Google,...

  15. Big Surveys, Big Data Centres

    Science.gov (United States)

    Schade, D.

    2016-06-01

    Well-designed astronomical surveys are powerful and have consistently been keystones of scientific progress. The Byurakan Surveys using a Schmidt telescope with an objective prism produced a list of about 3000 UV-excess Markarian galaxies but these objects have stimulated an enormous amount of further study and appear in over 16,000 publications. The CFHT Legacy Surveys used a wide-field imager to cover thousands of square degrees and those surveys are mentioned in over 1100 publications since 2002. Both ground and space-based astronomy have been increasing their investments in survey work. Survey instrumentation strives toward fair samples and large sky coverage and therefore strives to produce massive datasets. Thus we are faced with the "big data" problem in astronomy. Survey datasets require specialized approaches to data management. Big data places additional challenging requirements for data management. If the term "big data" is defined as data collections that are too large to move then there are profound implications for the infrastructure that supports big data science. The current model of data centres is obsolete. In the era of big data the central problem is how to create architectures that effectively manage the relationship between data collections, networks, processing capabilities, and software, given the science requirements of the projects that need to be executed. A stand alone data silo cannot support big data science. I'll describe the current efforts of the Canadian community to deal with this situation and our successes and failures. I'll talk about how we are planning in the next decade to try to create a workable and adaptable solution to support big data science.

  16. Big Dreams

    Science.gov (United States)

    Benson, Michael T.

    2015-01-01

    The Keen Johnson Building is symbolic of Eastern Kentucky University's historic role as a School of Opportunity. It is a place that has inspired generations of students, many from disadvantaged backgrounds, to dream big dreams. The construction of the Keen Johnson Building was inspired by a desire to create a student union facility that would not…

  17. Big Opportunities and Big Concerns of Big Data in Education

    Science.gov (United States)

    Wang, Yinying

    2016-01-01

    Against the backdrop of the ever-increasing influx of big data, this article examines the opportunities and concerns over big data in education. Specifically, this article first introduces big data, followed by delineating the potential opportunities of using big data in education in two areas: learning analytics and educational policy. Then, the…

  18. Big Data and Big Science

    OpenAIRE

    Di Meglio, Alberto

    2014-01-01

    Brief introduction to the challenges of big data in scientific research based on the work done by the HEP community at CERN and how the CERN openlab promotes collaboration among research institutes and industrial IT companies. Presented at the FutureGov 2014 conference in Singapore.

  19. Trade Facilitation

    OpenAIRE

    Ujiie, Teruo

    2006-01-01

    The issue of trade facilitation has been increasingly highlighted among business and trading communities as they would like to reduce the costs of international transactions of goods and services. Trade facilitation is a broad term: there are a number of international agreements relating to trade facilitation, and a number of international organizations involved in this area. Recognizing the importance of trade facilitation and after several years of exploratory work on government trade facil...

  20. The complete mitochondrial genome of the cryptic "lineage A" big-fin reef squid, Sepioteuthis lessoniana (Cephalopoda: Loliginidae) in Indo-West Pacific.

    Science.gov (United States)

    Hsiao, Chung-Der; Shen, Kang-Ning; Ching, Tzu-Yun; Wang, Ya-Hsien; Ye, Jeng-Jia; Tsai, Shiou-Yi; Wu, Shan-Chun; Chen, Ching-Hung; Wang, Chia-Hui

    2016-07-01

    In this study, the complete mitogenome sequence of the cryptic "lineage A" big-fin reef squid, Sepioteuthis lessoniana (Cephalopoda: Loliginidae) has been sequenced by the next-generation sequencing method. The assembled mitogenome consists of 16,605 bp, which includes 13 protein-coding genes, 22 transfer RNAs, and 2 ribosomal RNAs genes. The overall base composition of "lineage A" S. lessoniana is 37.5% for A, 17.4% for C, 9.1% for G, and 35.9% for T and shows 87% identities to "lineage C" S. lessoniana. It is also noticed by its high T + A content (73.4%), two non-coding regions with TA tandem repeats. The complete mitogenome of the cryptic "lineage A" S. lessoniana provides essential and important DNA molecular data for further phylogeography and evolutionary analysis for big-fin reef squid species complex. PMID:26016882

  1. Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance | Office of Cancer Genomics

    Science.gov (United States)

    The Cancer Target Discovery and Development (CTD^2) Network was established to accelerate the transformation of "Big Data" into novel pharmacological targets, lead compounds, and biomarkers for rapid translation into improved patient outcomes. It rapidly became clear in this collaborative network that a key central issue was to define what constitutes sufficient computational or experimental evidence to support a biologically or clinically relevant finding.

  2. Networking for big data

    CERN Document Server

    Yu, Shui; Misic, Jelena; Shen, Xuemin (Sherman)

    2015-01-01

    Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications.The book is divided into four sections: introduction to Big Data, networking theory and design for Big Data, networking security for Big Data, and platforms and systems for Big Data applications. Focusing on key networking issues in Big Data, the book explains network design and implementation for Big Data. It exa

  3. Big queues

    CERN Document Server

    Ganesh, Ayalvadi; Wischik, Damon

    2004-01-01

    Big Queues aims to give a simple and elegant account of how large deviations theory can be applied to queueing problems. Large deviations theory is a collection of powerful results and general techniques for studying rare events, and has been applied to queueing problems in a variety of ways. The strengths of large deviations theory are these: it is powerful enough that one can answer many questions which are hard to answer otherwise, and it is general enough that one can draw broad conclusions without relying on special case calculations.

  4. Big Data Analytics in Healthcare.

    Science.gov (United States)

    Belle, Ashwin; Thiagarajan, Raghuram; Soroushmehr, S M Reza; Navidi, Fatemeh; Beard, Daniel A; Najarian, Kayvan

    2015-01-01

    The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined. PMID:26229957

  5. Big Data Analytics in Healthcare

    Directory of Open Access Journals (Sweden)

    Ashwin Belle

    2015-01-01

    Full Text Available The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.

  6. Big Data Analytics in Healthcare.

    Science.gov (United States)

    Belle, Ashwin; Thiagarajan, Raghuram; Soroushmehr, S M Reza; Navidi, Fatemeh; Beard, Daniel A; Najarian, Kayvan

    2015-01-01

    The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.

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

    Science.gov (United States)

    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 costs. An MDR (Mathematically Defined Repeat)...

  8. Enhancement of β-catenin activity by BIG1 plus BIG2 via Arf activation and cAMP signals.

    Science.gov (United States)

    Li, Chun-Chun; Le, Kang; Kato, Jiro; Moss, Joel; Vaughan, Martha

    2016-05-24

    Multifunctional β-catenin, with critical roles in both cell-cell adhesion and Wnt-signaling pathways, was among HeLa cell proteins coimmunoprecipitated by antibodies against brefeldin A-inhibited guanine nucleotide-exchange factors 1 and 2 (BIG1 or BIG2) that activate ADP-ribosylation factors (Arfs) by accelerating the replacement of bound GDP with GTP. BIG proteins also contain A-kinase anchoring protein (AKAP) sequences that can act as scaffolds for multimolecular assemblies that facilitate and limit cAMP signaling temporally and spatially. Direct interaction of BIG1 N-terminal sequence with β-catenin was confirmed using yeast two-hybrid assays and in vitro synthesized proteins. Depletion of BIG1 and/or BIG2 or overexpression of guanine nucleotide-exchange factor inactive mutant, but not wild-type, proteins interfered with β-catenin trafficking, leading to accumulation at perinuclear Golgi structures. Both phospholipase D activity and vesicular trafficking were required for effects of BIG1 and BIG2 on β-catenin activation. Levels of PKA-phosphorylated β-catenin S675 and β-catenin association with PKA, BIG1, and BIG2 were also diminished after BIG1/BIG2 depletion. Inferring a requirement for BIG1 and/or BIG2 AKAP sequence in PKA modification of β-catenin and its effect on transcription activation, we confirmed dependence of S675 phosphorylation and transcription coactivator function on BIG2 AKAP-C sequence. PMID:27162341

  9. Big data analytics turning big data into big money

    CERN Document Server

    Ohlhorst, Frank J

    2012-01-01

    Unique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportuni

  10. Big Data Application in Biomedical Research and Health Care: A Literature Review.

    Science.gov (United States)

    Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

    2016-01-01

    Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care. PMID:26843812

  11. Big Data Application in Biomedical Research and Health Care: A Literature Review.

    Science.gov (United States)

    Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

    2016-01-01

    Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care.

  12. Big Data Application in Biomedical Research and Health Care: A Literature Review

    Science.gov (United States)

    Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

    2016-01-01

    Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care. PMID:26843812

  13. Databases and Web Tools for Cancer Genomics Study

    Institute of Scientific and Technical Information of China (English)

    Yadong Yang; Xunong Dong; Bingbing Xie; Nan Ding; Juan Chen; Yongjun Li; Qian Zhang; Hongzhu Qu; Xiangdong Fang

    2015-01-01

    Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data com-prehensiveness, and user experience. The resources reviewed include data repository and analysis tools;and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community.

  14. 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

  15. Big data analytics methods and applications

    CERN Document Server

    Rao, BLS; Rao, SB

    2016-01-01

    This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

  16. Big data are coming to psychiatry: a general introduction.

    Science.gov (United States)

    Monteith, Scott; Glenn, Tasha; Geddes, John; Bauer, Michael

    2015-12-01

    Big data are coming to the study of bipolar disorder and all of psychiatry. Data are coming from providers and payers (including EMR, imaging, insurance claims and pharmacy data), from omics (genomic, proteomic, and metabolomic data), and from patients and non-providers (data from smart phone and Internet activities, sensors and monitoring tools). Analysis of the big data will provide unprecedented opportunities for exploration, descriptive observation, hypothesis generation, and prediction, and the results of big data studies will be incorporated into clinical practice. Technical challenges remain in the quality, analysis and management of big data. This paper discusses some of the fundamental opportunities and challenges of big data for psychiatry.

  17. Big data are coming to psychiatry: a general introduction.

    Science.gov (United States)

    Monteith, Scott; Glenn, Tasha; Geddes, John; Bauer, Michael

    2015-12-01

    Big data are coming to the study of bipolar disorder and all of psychiatry. Data are coming from providers and payers (including EMR, imaging, insurance claims and pharmacy data), from omics (genomic, proteomic, and metabolomic data), and from patients and non-providers (data from smart phone and Internet activities, sensors and monitoring tools). Analysis of the big data will provide unprecedented opportunities for exploration, descriptive observation, hypothesis generation, and prediction, and the results of big data studies will be incorporated into clinical practice. Technical challenges remain in the quality, analysis and management of big data. This paper discusses some of the fundamental opportunities and challenges of big data for psychiatry. PMID:26440506

  18. Big Data: Overview

    OpenAIRE

    Gupta, Richa; Gupta, Sunny; Singhal, Anuradha

    2014-01-01

    Big data is data that exceeds the processing capacity of traditional databases. The data is too big to be processed by a single machine. New and innovative methods are required to process and store such large volumes of data. This paper provides an overview on big data, its importance in our live and some technologies to handle big data.

  19. The big bang of genome editing technology: development and application of the CRISPR/Cas9 system in disease animal models.

    Science.gov (United States)

    Shao, Ming; Xu, Tian-Rui; Chen, Ce-Shi

    2016-07-18

    Targeted genome editing technology has been widely used in biomedical studies. The CRISPR-associated RNA-guided endonuclease Cas9 has become a versatile genome editing tool. The CRISPR/Cas9 system is useful for studying gene function through efficient knock-out, knock-in or chromatin modification of the targeted gene loci in various cell types and organisms. It can be applied in a number of fields, such as genetic breeding, disease treatment and gene functional investigation. In this review, we introduce the most recent developments and applications, the challenges, and future directions of Cas9 in generating disease animal model. Derived from the CRISPR adaptive immune system of bacteria, the development trend of Cas9 will inevitably fuel the vital applications from basic research to biotechnology and bio-medicine. PMID:27469250

  20. The big bang of genome editing technology: development and application of the CRISPR/Cas9 system in disease animal models

    Science.gov (United States)

    SHAO, Ming; XU, Tian-Rui; CHEN, Ce-Shi

    2016-01-01

    Targeted genome editing technology has been widely used in biomedical studies. The CRISPR-associated RNA-guided endonuclease Cas9 has become a versatile genome editing tool. The CRISPR/Cas9 system is useful for studying gene function through efficient knock-out, knock-in or chromatin modification of the targeted gene loci in various cell types and organisms. It can be applied in a number of fields, such as genetic breeding, disease treatment and gene functional investigation. In this review, we introduce the most recent developments and applications, the challenges, and future directions of Cas9 in generating disease animal model. Derived from the CRISPR adaptive immune system of bacteria, the development trend of Cas9 will inevitably fuel the vital applications from basic research to biotechnology and biomedicine. PMID:27469250

  1. Comparative Genomic Analysis of Rapid Evolution of an Extreme-Drug-Resistant Acinetobacter baumannii Clone

    DEFF Research Database (Denmark)

    Tan, Sean Yang-Yi; Chua, Song Lin; Liu, Yang;

    2013-01-01

    The emergence of extreme-drug-resistant (EDR) bacterial strains in hospital and nonhospital clinical settings is a big and growing public health threat. Understanding the antibiotic resistance mechanisms at the genomic levels can facilitate the development of next-generation agents. Here, compara......The emergence of extreme-drug-resistant (EDR) bacterial strains in hospital and nonhospital clinical settings is a big and growing public health threat. Understanding the antibiotic resistance mechanisms at the genomic levels can facilitate the development of next-generation agents. Here...... that a putative porin protein was down-regulated when A. baumannii 53264 was exposed to antimicrobials, which may reduce the entry of antibiotics into the bacterial cell....

  2. Big data=Big marketing?!

    Institute of Scientific and Technical Information of China (English)

    肖明超

    2012-01-01

    <正>互联网刚刚兴起的时候,有句话很流行:"在网上,没人知道你是一条狗。"但是,在20多年后的今天,这句话已经早被扔进了历史的垃圾堆,因为在技术的推动下,随着移动互联、社交网络、电子商务等的迅速发展,消费者的"行踪"变得越来越容易被把握,消费者在互联网上的眼球、行为轨迹、谈论、喜好、购物经历等等都可能被捕捉到,消费者进入一个几乎透明化生存的"大数据时代"(Age of Big Data)。数据不仅仅正在变得更加可用,人工智能(AI)技术,包括自然语言处理、模式识别和机器学习等技术的发展,正在让数据变得更加容易被计算机所理解,

  3. True Randomness from Big Data

    Science.gov (United States)

    Papakonstantinou, Periklis A.; Woodruff, David P.; Yang, Guang

    2016-09-01

    Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests.

  4. True Randomness from Big Data

    Science.gov (United States)

    Papakonstantinou, Periklis A.; Woodruff, David P.; Yang, Guang

    2016-01-01

    Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests. PMID:27666514

  5. Facilitating Transfers

    DEFF Research Database (Denmark)

    Kjær, Poul F.

    The concept of governance has mutated into an all‐embracing buzz‐word characterised by a low degree of conceptual precision and empirical focus. This paper therefore suggests a narrower and more precise understanding of governance and the regulatory function it fulfils by advancing the argument t...... and different types of transfers between them. It will, furthermore, explore the role and “quality” of different types of regulatory governance frameworks in relation to the facilitation, stabilisation and justification of transfers....... that the essential functional and normative purpose of regulatory governance is to facilitate, stabilise and justify the transfer of condensed social components (such as economic capital and products, political decisions, legal judgements, religious beliefs and scientific knowledge) from one social contexts...

  6. Indian microchip for Big Bang research in Geneva

    CERN Multimedia

    Bhabani, Soudhriti

    2007-01-01

    "A premier nuclear physics institute here has come up with India's first indigenously designed microchip that will facilitate research on the Big Bang theory in Geneva's CERN, the world's largest particle physics laboratory." (1 page)

  7. Evaluation of a Phylogenetic Marker Based on Genomic Segment B of Infectious Bursal Disease Virus: Facilitating a Feasible Incorporation of this Segment to the Molecular Epidemiology Studies for this Viral Agent.

    Directory of Open Access Journals (Sweden)

    Abdulahi Alfonso-Morales

    Full Text Available Infectious bursal disease (IBD is a highly contagious and acute viral disease, which has caused high mortality rates in birds and considerable economic losses in different parts of the world for more than two decades and it still represents a considerable threat to poultry. The current study was designed to rigorously measure the reliability of a phylogenetic marker included into segment B. This marker can facilitate molecular epidemiology studies, incorporating this segment of the viral genome, to better explain the links between emergence, spreading and maintenance of the very virulent IBD virus (vvIBDV strains worldwide.Sequences of the segment B gene from IBDV strains isolated from diverse geographic locations were obtained from the GenBank Database; Cuban sequences were obtained in the current work. A phylogenetic marker named B-marker was assessed by different phylogenetic principles such as saturation of substitution, phylogenetic noise and high consistency. This last parameter is based on the ability of B-marker to reconstruct the same topology as the complete segment B of the viral genome. From the results obtained from B-marker, demographic history for both main lineages of IBDV regarding segment B was performed by Bayesian skyline plot analysis. Phylogenetic analysis for both segments of IBDV genome was also performed, revealing the presence of a natural reassortant strain with segment A from vvIBDV strains and segment B from non-vvIBDV strains within Cuban IBDV population.This study contributes to a better understanding of the emergence of vvIBDV strains, describing molecular epidemiology of IBDV using the state-of-the-art methodology concerning phylogenetic reconstruction. This study also revealed the presence of a novel natural reassorted strain as possible manifest of change in the genetic structure and stability of the vvIBDV strains. Therefore, it highlights the need to obtain information about both genome segments of IBDV for

  8. Social big data mining

    CERN Document Server

    Ishikawa, Hiroshi

    2015-01-01

    Social Media. Big Data and Social Data. Hypotheses in the Era of Big Data. Social Big Data Applications. Basic Concepts in Data Mining. Association Rule Mining. Clustering. Classification. Prediction. Web Structure Mining. Web Content Mining. Web Access Log Mining, Information Extraction and Deep Web Mining. Media Mining. Scalability and Outlier Detection.

  9. Big data computing

    CERN Document Server

    Akerkar, Rajendra

    2013-01-01

    Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book i

  10. Microsoft big data solutions

    CERN Document Server

    Jorgensen, Adam; Welch, John; Clark, Dan; Price, Christopher; Mitchell, Brian

    2014-01-01

    Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all,

  11. Mining "big data" using big data services

    OpenAIRE

    Reips, UD; Matzat, U Uwe

    2014-01-01

    While many colleagues within science are fed up with the “big data fad”, empirical analyses we conducted for the current editorial actually show an inconsistent picture: we use big data services to determine whether there really is an increase in writing about big data or even widespread use of the term. Google Correlate (http://www.google.com/trends/correlate/), the first free tool we are presenting here, doesn’t list the term, showing that number of searches for it are below an absolute min...

  12. Big data and visual analytics in anaesthesia and health care.

    Science.gov (United States)

    Simpao, A F; Ahumada, L M; Rehman, M A

    2015-09-01

    Advances in computer technology, patient monitoring systems, and electronic health record systems have enabled rapid accumulation of patient data in electronic form (i.e. big data). Organizations such as the Anesthesia Quality Institute and Multicenter Perioperative Outcomes Group have spearheaded large-scale efforts to collect anaesthesia big data for outcomes research and quality improvement. Analytics--the systematic use of data combined with quantitative and qualitative analysis to make decisions--can be applied to big data for quality and performance improvements, such as predictive risk assessment, clinical decision support, and resource management. Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces, and it can facilitate performance of cognitive activities involving big data. Ongoing integration of big data and analytics within anaesthesia and health care will increase demand for anaesthesia professionals who are well versed in both the medical and the information sciences.

  13. From Big Crunch to Big Bang

    OpenAIRE

    Khoury, Justin; Ovrut, Burt A.; Seiberg, Nathan; Steinhardt, Paul J.(Princeton Center for Theoretical Science, Princeton University, Princeton, NJ, 08544, USA); Turok, Neil

    2001-01-01

    We consider conditions under which a universe contracting towards a big crunch can make a transition to an expanding big bang universe. A promising example is 11-dimensional M-theory in which the eleventh dimension collapses, bounces, and re-expands. At the bounce, the model can reduce to a weakly coupled heterotic string theory and, we conjecture, it may be possible to follow the transition from contraction to expansion. The possibility opens the door to new classes of cosmological models. F...

  14. Big Data: Survey, Technologies, Opportunities, and Challenges

    Directory of Open Access Journals (Sweden)

    Nawsher Khan

    2014-01-01

    Full Text Available Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.

  15. Big data: survey, technologies, opportunities, and challenges.

    Science.gov (United States)

    Khan, Nawsher; Yaqoob, Ibrar; Hashem, Ibrahim Abaker Targio; Inayat, Zakira; Ali, Waleed Kamaleldin Mahmoud; Alam, Muhammad; Shiraz, Muhammad; Gani, Abdullah

    2014-01-01

    Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data. PMID:25136682

  16. HARNESSING BIG DATA VOLUMES

    Directory of Open Access Journals (Sweden)

    Bogdan DINU

    2014-04-01

    Full Text Available Big Data can revolutionize humanity. Hidden within the huge amounts and variety of the data we are creating we may find information, facts, social insights and benchmarks that were once virtually impossible to find or were simply inexistent. Large volumes of data allow organizations to tap in real time the full potential of all the internal or external information they possess. Big data calls for quick decisions and innovative ways to assist customers and the society as a whole. Big data platforms and product portfolio will help customers harness to the full the value of big data volumes. This paper deals with technical and technological issues related to handling big data volumes in the Big Data environment.

  17. Matrix Big Brunch

    OpenAIRE

    Bedford, J; Papageorgakis, C.; Rodriguez-Gomez, D.; Ward, J.

    2007-01-01

    Following the holographic description of linear dilaton null Cosmologies with a Big Bang in terms of Matrix String Theory put forward by Craps, Sethi and Verlinde, we propose an extended background describing a Universe including both Big Bang and Big Crunch singularities. This belongs to a class of exact string backgrounds and is perturbative in the string coupling far away from the singularities, both of which can be resolved using Matrix String Theory. We provide a simple theory capable of...

  18. ANALYSIS OF BIG DATA

    OpenAIRE

    Anshul Sharma; Preeti Gulia

    2014-01-01

    Big Data is data that either is too large, grows too fast, or does not fit into traditional architectures. Within such data can be valuable information that can be discovered through data analysis [1]. Big data is a collection of complex and large data sets that are difficult to process and mine for patterns and knowledge using traditional database management tools or data processing and mining systems. Big Data is data whose scale, diversity and complexity require new architecture, technique...

  19. Summary big data

    CERN Document Server

    2014-01-01

    This work offers a summary of Cukier the book: "Big Data: A Revolution That Will Transform How we Live, Work, and Think" by Viktor Mayer-Schonberg and Kenneth. Summary of the ideas in Viktor Mayer-Schonberg's and Kenneth Cukier's book: " Big Data " explains that big data is where we use huge quantities of data to make better predictions based on the fact we identify patters in the data rather than trying to understand the underlying causes in more detail. This summary highlights that big data will be a source of new economic value and innovation in the future. Moreover, it shows that it will

  20. Bliver big data til big business?

    DEFF Research Database (Denmark)

    Ritter, Thomas

    2015-01-01

    Danmark har en digital infrastruktur, en registreringskultur og it-kompetente medarbejdere og kunder, som muliggør en førerposition, men kun hvis virksomhederne gør sig klar til næste big data-bølge.......Danmark har en digital infrastruktur, en registreringskultur og it-kompetente medarbejdere og kunder, som muliggør en førerposition, men kun hvis virksomhederne gør sig klar til næste big data-bølge....

  1. Modeling genomic regulatory networks with big data.

    Science.gov (United States)

    Bolouri, Hamid

    2014-05-01

    High-throughput sequencing, large-scale data generation projects, and web-based cloud computing are changing how computational biology is performed, who performs it, and what biological insights it can deliver. I review here the latest developments in available data, methods, and software, focusing on the modeling and analysis of the gene regulatory interactions in cells. Three key findings are: (i) although sophisticated computational resources are increasingly available to bench biologists, tailored ongoing education is necessary to avoid the erroneous use of these resources. (ii) Current models of the regulation of gene expression are far too simplistic and need updating. (iii) Integrative computational analysis of large-scale datasets is becoming a fundamental component of molecular biology. I discuss current and near-term opportunities and challenges related to these three points.

  2. Big data integration: scalability and sustainability

    KAUST Repository

    Zhang, Zhang

    2016-01-26

    Integration of various types of omics data is critically indispensable for addressing most important and complex biological questions. In the era of big data, however, data integration becomes increasingly tedious, time-consuming and expensive, posing a significant obstacle to fully exploit the wealth of big biological data. Here we propose a scalable and sustainable architecture that integrates big omics data through community-contributed modules. Community modules are contributed and maintained by different committed groups and each module corresponds to a specific data type, deals with data collection, processing and visualization, and delivers data on-demand via web services. Based on this community-based architecture, we build Information Commons for Rice (IC4R; http://ic4r.org), a rice knowledgebase that integrates a variety of rice omics data from multiple community modules, including genome-wide expression profiles derived entirely from RNA-Seq data, resequencing-based genomic variations obtained from re-sequencing data of thousands of rice varieties, plant homologous genes covering multiple diverse plant species, post-translational modifications, rice-related literatures, and community annotations. Taken together, such architecture achieves integration of different types of data from multiple community-contributed modules and accordingly features scalable, sustainable and collaborative integration of big data as well as low costs for database update and maintenance, thus helpful for building IC4R into a comprehensive knowledgebase covering all aspects of rice data and beneficial for both basic and translational researches.

  3. Big Boss Interval Games

    NARCIS (Netherlands)

    Alparslan-Gok, S.Z.; Brânzei, R.; Tijs, S.H.

    2008-01-01

    In this paper big boss interval games are introduced and various characterizations are given. The structure of the core of a big boss interval game is explicitly described and plays an important role relative to interval-type bi-monotonic allocation schemes for such games. Specifically, each element

  4. Some experiences and opportunities for big data in translational research.

    Science.gov (United States)

    Chute, Christopher G; Ullman-Cullere, Mollie; Wood, Grant M; Lin, Simon M; He, Min; Pathak, Jyotishman

    2013-10-01

    Health care has become increasingly information intensive. The advent of genomic data, integrated into patient care, significantly accelerates the complexity and amount of clinical data. Translational research in the present day increasingly embraces new biomedical discovery in this data-intensive world, thus entering the domain of "big data." The Electronic Medical Records and Genomics consortium has taught us many lessons, while simultaneously advances in commodity computing methods enable the academic community to affordably manage and process big data. Although great promise can emerge from the adoption of big data methods and philosophy, the heterogeneity and complexity of clinical data, in particular, pose additional challenges for big data inferencing and clinical application. However, the ultimate comparability and consistency of heterogeneous clinical information sources can be enhanced by existing and emerging data standards, which promise to bring order to clinical data chaos. Meaningful Use data standards in particular have already simplified the task of identifying clinical phenotyping patterns in electronic health records. PMID:24008998

  5. Big Data in Caenorhabditis elegans: quo vadis?

    Science.gov (United States)

    Hutter, Harald; Moerman, Donald

    2015-11-01

    A clear definition of what constitutes "Big Data" is difficult to identify, but we find it most useful to define Big Data as a data collection that is complete. By this criterion, researchers on Caenorhabditis elegans have a long history of collecting Big Data, since the organism was selected with the idea of obtaining a complete biological description and understanding of development. The complete wiring diagram of the nervous system, the complete cell lineage, and the complete genome sequence provide a framework to phrase and test hypotheses. Given this history, it might be surprising that the number of "complete" data sets for this organism is actually rather small--not because of lack of effort, but because most types of biological experiments are not currently amenable to complete large-scale data collection. Many are also not inherently limited, so that it becomes difficult to even define completeness. At present, we only have partial data on mutated genes and their phenotypes, gene expression, and protein-protein interaction--important data for many biological questions. Big Data can point toward unexpected correlations, and these unexpected correlations can lead to novel investigations; however, Big Data cannot establish causation. As a result, there is much excitement about Big Data, but there is also a discussion on just what Big Data contributes to solving a biological problem. Because of its relative simplicity, C. elegans is an ideal test bed to explore this issue and at the same time determine what is necessary to build a multicellular organism from a single cell.

  6. Big Data, Big Knowledge: Big Data for Personalized Healthcare.

    OpenAIRE

    Viceconti, M.; Hunter, P.; Hose, R.

    2015-01-01

    The idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for individual patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. We propose in this position paper that big data analytics can be successfully combined with VPH technologies to produce robust and effective in silico medicine soluti...

  7. Big data, big knowledge: big data for personalized healthcare.

    Science.gov (United States)

    Viceconti, Marco; Hunter, Peter; Hose, Rod

    2015-07-01

    The idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for individual patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. We propose in this position paper that big data analytics can be successfully combined with VPH technologies to produce robust and effective in silico medicine solutions. In order to do this, big data technologies must be further developed to cope with some specific requirements that emerge from this application. Such requirements are: working with sensitive data; analytics of complex and heterogeneous data spaces, including nontextual information; distributed data management under security and performance constraints; specialized analytics to integrate bioinformatics and systems biology information with clinical observations at tissue, organ and organisms scales; and specialized analytics to define the "physiological envelope" during the daily life of each patient. These domain-specific requirements suggest a need for targeted funding, in which big data technologies for in silico medicine becomes the research priority. PMID:26218867

  8. Big data, big knowledge: big data for personalized healthcare.

    Science.gov (United States)

    Viceconti, Marco; Hunter, Peter; Hose, Rod

    2015-07-01

    The idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for individual patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. We propose in this position paper that big data analytics can be successfully combined with VPH technologies to produce robust and effective in silico medicine solutions. In order to do this, big data technologies must be further developed to cope with some specific requirements that emerge from this application. Such requirements are: working with sensitive data; analytics of complex and heterogeneous data spaces, including nontextual information; distributed data management under security and performance constraints; specialized analytics to integrate bioinformatics and systems biology information with clinical observations at tissue, organ and organisms scales; and specialized analytics to define the "physiological envelope" during the daily life of each patient. These domain-specific requirements suggest a need for targeted funding, in which big data technologies for in silico medicine becomes the research priority.

  9. Big data a primer

    CERN Document Server

    Bhuyan, Prachet; Chenthati, Deepak

    2015-01-01

    This book is a collection of chapters written by experts on various aspects of big data. The book aims to explain what big data is and how it is stored and used. The book starts from  the fundamentals and builds up from there. It is intended to serve as a review of the state-of-the-practice in the field of big data handling. The traditional framework of relational databases can no longer provide appropriate solutions for handling big data and making it available and useful to users scattered around the globe. The study of big data covers a wide range of issues including management of heterogeneous data, big data frameworks, change management, finding patterns in data usage and evolution, data as a service, service-generated data, service management, privacy and security. All of these aspects are touched upon in this book. It also discusses big data applications in different domains. The book will prove useful to students, researchers, and practicing database and networking engineers.

  10. Recht voor big data, big data voor recht

    NARCIS (Netherlands)

    Lafarre, Anne

    2016-01-01

    Big data is een niet meer weg te denken fenomeen in onze maatschappij. Het is de hype cycle voorbij en de eerste implementaties van big data-technieken worden uitgevoerd. Maar wat is nu precies big data? Wat houden de vijf V's in die vaak genoemd worden in relatie tot big data? Ter inleiding van dez

  11. Assessing Big Data

    DEFF Research Database (Denmark)

    Leimbach, Timo; Bachlechner, Daniel

    2015-01-01

    In recent years, big data has been one of the most controversially discussed technologies in terms of its possible positive and negative impact. Therefore, the need for technology assessments is obvious. This paper first provides, based on the results of a technology assessment study, an overview...... of the potential and challenges associated with big data and then describes the problems experienced during the study as well as methods found helpful to address them. The paper concludes with reflections on how the insights from the technology assessment study may have an impact on the future governance of big...... data....

  12. Big Data ethics

    Directory of Open Access Journals (Sweden)

    Andrej Zwitter

    2014-11-01

    Full Text Available The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with specific and knowable outcomes, towards actions by many unaware that they may have taken actions with unintended consequences for anyone. Responses will require a rethinking of ethical choices, the lack thereof and how this will guide scientists, governments, and corporate agencies in handling Big Data. This essay elaborates on the ways Big Data impacts on ethical conceptions.

  13. Big data for dummies

    CERN Document Server

    Hurwitz, Judith; Halper, Fern; Kaufman, Marcia

    2013-01-01

    Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it m

  14. Facilitering som styringsredskab

    OpenAIRE

    Jørgensen, Karen Overgaard

    2006-01-01

    #This thesis surveys facilitation as a new tool of steering within the public sector in Denmark. It is explored how facilitation is articulated and practiced among facilitators from the public, private and voluntary sector. Furthermore, the facilitator’s challenges by using facilitation are examined. The thesis is based on the presumption that facilitation is articulated by rationalities, which influence how facilitation is practiced and performed. Also, a facilitator is seen as a performer a...

  15. Big data opportunities and challenges

    CERN Document Server

    2014-01-01

    This ebook aims to give practical guidance for all those who want to understand big data better and learn how to make the most of it. Topics range from big data analysis, mobile big data and managing unstructured data to technologies, governance and intellectual property and security issues surrounding big data.

  16. Big Creek Pit Tags

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The BCPITTAGS database is used to store data from an Oncorhynchus mykiss (steelhead/rainbow trout) population dynamics study in Big Creek, a coastal stream along...

  17. Big Data as Governmentality

    DEFF Research Database (Denmark)

    Flyverbom, Mikkel; Klinkby Madsen, Anders; Rasche, Andreas

    This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big...... data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects...... shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact....

  18. Reframing Open Big Data

    DEFF Research Database (Denmark)

    Marton, Attila; Avital, Michel; Jensen, Tina Blegind

    2013-01-01

    Recent developments in the techniques and technologies of collecting, sharing and analysing data are challenging the field of information systems (IS) research let alone the boundaries of organizations and the established practices of decision-making. Coined ‘open data’ and ‘big data......’, these developments introduce an unprecedented level of societal and organizational engagement with the potential of computational data to generate new insights and information. Based on the commonalities shared by open data and big data, we develop a research framework that we refer to as open big data (OBD......) by employing the dimensions of ‘order’ and ‘relationality’. We argue that these dimensions offer a viable approach for IS research on open and big data because they address one of the core value propositions of IS; i.e. how to support organizing with computational data. We contrast these dimensions with two...

  19. Big Data Revisited

    DEFF Research Database (Denmark)

    Kallinikos, Jannis; Constantiou, Ioanna

    2015-01-01

    We elaborate on key issues of our paper New games, new rules: big data and the changing context of strategy as a means of addressing some of the concerns raised by the paper’s commentators. We initially deal with the issue of social data and the role it plays in the current data revolution...... and the technological recording of facts. We further discuss the significance of the very mechanisms by which big data is produced as distinct from the very attributes of big data, often discussed in the literature. In the final section of the paper, we qualify the alleged importance of algorithms and claim...... that the structures of data capture and the architectures in which data generation is embedded are fundamental to the phenomenon of big data....

  20. The Big Bang Singularity

    Science.gov (United States)

    Ling, Eric

    The big bang theory is a model of the universe which makes the striking prediction that the universe began a finite amount of time in the past at the so called "Big Bang singularity." We explore the physical and mathematical justification of this surprising result. After laying down the framework of the universe as a spacetime manifold, we combine physical observations with global symmetrical assumptions to deduce the FRW cosmological models which predict a big bang singularity. Next we prove a couple theorems due to Stephen Hawking which show that the big bang singularity exists even if one removes the global symmetrical assumptions. Lastly, we investigate the conditions one needs to impose on a spacetime if one wishes to avoid a singularity. The ideas and concepts used here to study spacetimes are similar to those used to study Riemannian manifolds, therefore we compare and contrast the two geometries throughout.

  1. Big Data as Governmentality

    DEFF Research Database (Denmark)

    Flyverbom, Mikkel; Madsen, Anders Koed; Rasche, Andreas

    data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects...... shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact.......This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big...

  2. Big Data Analytics

    Indian Academy of Sciences (India)

    2016-08-01

    The volume and variety of data being generated using computersis doubling every two years. It is estimated that in 2015,8 Zettabytes (Zetta=1021) were generated which consistedmostly of unstructured data such as emails, blogs, Twitter,Facebook posts, images, and videos. This is called big data. Itis possible to analyse such huge data collections with clustersof thousands of inexpensive computers to discover patterns inthe data that have many applications. But analysing massiveamounts of data available in the Internet has the potential ofimpinging on our privacy. Inappropriate analysis of big datacan lead to misleading conclusions. In this article, we explainwhat is big data, how it is analysed, and give some case studiesillustrating the potentials and pitfalls of big data analytics.

  3. Testing Big Bang Nucleosynthesis

    OpenAIRE

    Steigman, Gary

    1996-01-01

    Big Bang Nucleosynthesis (BBN), along with the cosmic background radiation and the Hubble expansion, is one of the pillars ofthe standard, hot, big bang cosmology since the primordial synthesis of the light nuclides (D, $^3$He, $^4$He, $^7$Li) must have occurred during the early evolution of a universe described by this model. The overall consistency between the predicted and observed abundances of the light nuclides, each of which spans a range of some nine orders of magnitude, provides impr...

  4. Sharing big biomedical data

    OpenAIRE

    Toga, Arthur W.; Dinov, Ivo D.

    2015-01-01

    Background The promise of Big Biomedical Data may be offset by the enormous challenges in handling, analyzing, and sharing it. In this paper, we provide a framework for developing practical and reasonable data sharing policies that incorporate the sociological, financial, technical and scientific requirements of a sustainable Big Data dependent scientific community. Findings Many biomedical and healthcare studies may be significantly impacted by using large, heterogeneous and incongruent data...

  5. Conociendo Big Data

    Directory of Open Access Journals (Sweden)

    Juan José Camargo-Vega

    2014-12-01

    Full Text Available Teniendo en cuenta la importancia que ha adquirido el término Big Data, la presente investigación buscó estudiar y analizar de manera exhaustiva el estado del arte del Big Data; además, y como segundo objetivo, analizó las características, las herramientas, las tecnologías, los modelos y los estándares relacionados con Big Data, y por último buscó identificar las características más relevantes en la gestión de Big Data, para que con ello se pueda conocer todo lo concerniente al tema central de la investigación.La metodología utilizada incluyó revisar el estado del arte de Big Data y enseñar su situación actual; conocer las tecnologías de Big Data; presentar algunas de las bases de datos NoSQL, que son las que permiten procesar datos con formatos no estructurados, y mostrar los modelos de datos y las tecnologías de análisis de ellos, para terminar con algunos beneficios de Big Data.El diseño metodológico usado para la investigación fue no experimental, pues no se manipulan variables, y de tipo exploratorio, debido a que con esta investigación se empieza a conocer el ambiente del Big Data.

  6. Minsky on "Big Government"

    Directory of Open Access Journals (Sweden)

    Daniel de Santana Vasconcelos

    2014-03-01

    Full Text Available This paper objective is to assess, in light of the main works of Minsky, his view and analysis of what he called the "Big Government" as that huge institution which, in parallels with the "Big Bank" was capable of ensuring stability in the capitalist system and regulate its inherently unstable financial system in mid-20th century. In this work, we analyze how Minsky proposes an active role for the government in a complex economic system flawed by financial instability.

  7. The Zen of Facilitation.

    Science.gov (United States)

    Killion, Joellen P.; Simmons, Lynn A.

    1992-01-01

    Distinguishes between training and facilitation, examines the belief system of a facilitator, and shares a process for moving from the familiar mind-set of the trainer to the zen (the practice of seeking the truth) of facilitation. (GLR)

  8. [Three applications and the challenge of the big data in otology].

    Science.gov (United States)

    Lei, Guanxiong; Li, Jianan; Shen, Weidong; Yang, Shiming

    2016-03-01

    With the expansion of human practical activities, more and more areas have suffered from big data problems. The emergence of big data requires people to update the research paradigm and develop new technical methods. This review discussed that big data might bring opportunities and challenges in the area of auditory implantation, the deafness genome, and auditory pathophysiology, and pointed out that we needed to find appropriate theories and methods to make this kind of expectation into reality. PMID:27033583

  9. Big data in biomedicine.

    Science.gov (United States)

    Costa, Fabricio F

    2014-04-01

    The increasing availability and growth rate of biomedical information, also known as 'big data', provides an opportunity for future personalized medicine programs that will significantly improve patient care. Recent advances in information technology (IT) applied to biomedicine are changing the landscape of privacy and personal information, with patients getting more control of their health information. Conceivably, big data analytics is already impacting health decisions and patient care; however, specific challenges need to be addressed to integrate current discoveries into medical practice. In this article, I will discuss the major breakthroughs achieved in combining omics and clinical health data in terms of their application to personalized medicine. I will also review the challenges associated with using big data in biomedicine and translational science. PMID:24183925

  10. Big and Small

    CERN Document Server

    Ekers, R D

    2010-01-01

    Technology leads discovery in astronomy, as in all other areas of science, so growth in technology leads to the continual stream of new discoveries which makes our field so fascinating. Derek de Solla Price had analysed the discovery process in science in the 1960s and he introduced the terms 'Little Science' and 'Big Science' as part of his discussion of the role of exponential growth in science. I will show how the development of astronomical facilities has followed this same trend from 'Little Science' to 'Big Science' as a field matures. We can see this in the discoveries resulting in Nobel Prizes in astronomy. A more detailed analysis of discoveries in radio astronomy shows the same effect. I include a digression to look at how science progresses, comparing the roles of prediction, serendipity, measurement and explanation. Finally I comment on the differences between the 'Big Science' culture in Physics and in Astronomy.

  11. Big Data and Peacebuilding

    Directory of Open Access Journals (Sweden)

    Sanjana Hattotuwa

    2013-11-01

    Full Text Available Any peace process is an exercise in the negotiation of big data. From centuries old communal hagiography to the reams of official texts, media coverage and social media updates, peace negotiations generate data. Peacebuilding and peacekeeping today are informed by, often respond and contribute to big data. This is no easy task. As recently as a few years ago, before the term big data embraced the virtual on the web, what informed peace process design and implementation was in the physical domain – from contested borders and resources to background information in the form of text. The move from analogue, face-to-face negotiations to online, asynchronous, web-mediated negotiations – which can still include real world meetings – has profound implications for how peace is strengthened in fragile democracies.

  12. Networks & big data

    OpenAIRE

    Litvak, Nelly; Meulen, van der, P.

    2015-01-01

    Once a year, the NWO cluster Stochastics – Theoretical and Applied Research (STAR) organises a STAR Outreach Day, a one-day event around a theme that is of a broad interest to the stochastics community in the Netherlands. The last Outreach Day took place at Eurandom on 12 December 2014. The theme of the day was ‘Networks & Big Data’. The topic is very timely. The Vision document 2025 of the PlatformWiskunde Nederland (PWN) mentions big data as one of the six “major societal and scientific tre...

  13. Primordial Big Bang Nucleosynthesis

    OpenAIRE

    Olive, Keith A.

    1999-01-01

    Big Bang Nucleosynthesis is the theory of the production of the the light element isotopes of D, He3, He4, and Li7. After a brief review of the essential elements of the standard Big Bang model at a temperature of about 1 MeV, the theoretical input and predictions of BBN are discussed. The theory is tested by the observational determinations of the light element abundances and the current status of these observations is reviewed. Concordance of standard model and the related observations is f...

  14. Mouse Genome Informatics (MGI)

    Data.gov (United States)

    U.S. Department of Health & Human Services — MGI is the international database resource for the laboratory mouse, providing integrated genetic, genomic, and biological data to facilitate the study of human...

  15. Big Data ethics

    NARCIS (Netherlands)

    Zwitter, Andrej

    2014-01-01

    The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with sp

  16. Space big book

    CERN Document Server

    Homer, Charlene

    2007-01-01

    Our Combined resource includes all necessary areas of Space for grades five to eight. Get the big picture about the Solar System, Galaxies and the Universe as your students become fascinated by the interesting information about the Sun, Earth, Moon, Comets, Asteroids Meteoroids, Stars and Constellations. Also, thrill your young astronomers as they connect Earth and space cycles with their daily life.

  17. A Big Bang Lab

    Science.gov (United States)

    Scheider, Walter

    2005-01-01

    The February 2005 issue of The Science Teacher (TST) reminded everyone that by learning how scientists study stars, students gain an understanding of how science measures things that can not be set up in lab, either because they are too big, too far away, or happened in a very distant past. The authors of "How Far are the Stars?" show how the…

  18. Governing Big Data

    Directory of Open Access Journals (Sweden)

    Andrej J. Zwitter

    2014-04-01

    Full Text Available 2.5 quintillion bytes of data are created every day through pictures, messages, gps-data, etc. "Big Data" is seen simultaneously as the new Philosophers Stone and Pandora's box: a source of great knowledge and power, but equally, the root of serious problems.

  19. The Big Bang

    CERN Multimedia

    Moods, Patrick

    2006-01-01

    How did the Universe begin? The favoured theory is that everything - space, time, matter - came into existence at the same moment, around 13.7 thousand million years ago. This event was scornfully referred to as the "Big Bang" by Sir Fred Hoyle, who did not believe in it and maintained that the Universe had always existed.

  20. Big Java late objects

    CERN Document Server

    Horstmann, Cay S

    2012-01-01

    Big Java: Late Objects is a comprehensive introduction to Java and computer programming, which focuses on the principles of programming, software engineering, and effective learning. It is designed for a two-semester first course in programming for computer science students.

  1. Big is beautiful

    Energy Technology Data Exchange (ETDEWEB)

    Meyer, J.P.

    2007-06-08

    Although big solar systems are both effective and architecturally pleasing, they are still not widespread in Germany. Recently, politicians reacted by improving funding conditions. In order to prevent planning errors, planners and fitters must be better trained, and standardisation of systems must be enhanced. (orig.)

  2. Big Data and Cycling

    NARCIS (Netherlands)

    Romanillos, Gustavo; Zaltz Austwick, Martin; Ettema, Dick; De Kruijf, Joost

    2016-01-01

    Big Data has begun to create significant impacts in urban and transport planning. This paper covers the explosion in data-driven research on cycling, most of which has occurred in the last ten years. We review the techniques, objectives and findings of a growing number of studies we have classified

  3. Big data in history

    CERN Document Server

    Manning, Patrick

    2013-01-01

    Big Data in History introduces the project to create a world-historical archive, tracing the last four centuries of historical dynamics and change. Chapters address the archive's overall plan, how to interpret the past through a global archive, the missions of gathering records, linking local data into global patterns, and exploring the results.

  4. The big bang

    Science.gov (United States)

    Silk, Joseph

    Our universe was born billions of years ago in a hot, violent explosion of elementary particles and radiation - the big bang. What do we know about this ultimate moment of creation, and how do we know it? Drawing upon the latest theories and technology, this new edition of The big bang, is a sweeping, lucid account of the event that set the universe in motion. Joseph Silk begins his story with the first microseconds of the big bang, on through the evolution of stars, galaxies, clusters of galaxies, quasars, and into the distant future of our universe. He also explores the fascinating evidence for the big bang model and recounts the history of cosmological speculation. Revised and updated, this new edition features all the most recent astronomical advances, including: Photos and measurements from the Hubble Space Telescope, Cosmic Background Explorer Satellite (COBE), and Infrared Space Observatory; the latest estimates of the age of the universe; new ideas in string and superstring theory; recent experiments on neutrino detection; new theories about the presence of dark matter in galaxies; new developments in the theory of the formation and evolution of galaxies; the latest ideas about black holes, worm holes, quantum foam, and multiple universes.

  5. Big ideas: innovation policy

    OpenAIRE

    Van Reenen, John

    2011-01-01

    In the last CentrePiece, John Van Reenen stressed the importance of competition and labour market flexibility for productivity growth. His latest in CEP's 'big ideas' series describes the impact of research on how policy-makers can influence innovation more directly - through tax credits for business spending on research and development.

  6. Spaces of genomics : exploring the innovation journey of genomics in research on common disease

    NARCIS (Netherlands)

    Bitsch, L.

    2013-01-01

    Genomics was introduced with big promises and expectations of its future contribution to our society. Medical genomics was introduced as that which would lay the foundation for a revolution in our management of common diseases. Genomics would lead the way towards a future of personalised medicine. D

  7. Big Data and Chemical Education

    Science.gov (United States)

    Pence, Harry E.; Williams, Antony J.

    2016-01-01

    The amount of computerized information that organizations collect and process is growing so large that the term Big Data is commonly being used to describe the situation. Accordingly, Big Data is defined by a combination of the Volume, Variety, Velocity, and Veracity of the data being processed. Big Data tools are already having an impact in…

  8. Big Data-Survey

    Directory of Open Access Journals (Sweden)

    P.S.G. Aruna Sri

    2016-03-01

    Full Text Available Big data is the term for any gathering of information sets, so expensive and complex, that it gets to be hard to process for utilizing customary information handling applications. The difficulties incorporate investigation, catch, duration, inquiry, sharing, stockpiling, Exchange, perception, and protection infringement. To reduce spot business patterns, anticipate diseases, conflict etc., we require bigger data sets when compared with the smaller data sets. Enormous information is hard to work with utilizing most social database administration frameworks and desktop measurements and perception bundles, needing rather enormously parallel programming running on tens, hundreds, or even a large number of servers. In this paper there was an observation on Hadoop architecture, different tools used for big data and its security issues.

  9. ANALYTICS OF BIG DATA

    Directory of Open Access Journals (Sweden)

    Prof. Shubhada Talegaon

    2015-10-01

    Full Text Available Big Data analytics has started to impact all types of organizations, as it carries the potential power to extract embedded knowledge from big amounts of data and react according to it in real time. The current technology enables us to efficiently store and query large datasets, the focus is now on techniques that make use of the complete data set, instead of sampling. This has tremendous implications in areas like machine learning, pattern recognition and classification, sentiment analysis, social networking analysis to name a few. Therefore, there are a number of requirements for moving beyond standard data mining technique. Purpose of this paper is to understand various techniques to analysis data.

  10. Really big numbers

    CERN Document Server

    Schwartz, Richard Evan

    2014-01-01

    In the American Mathematical Society's first-ever book for kids (and kids at heart), mathematician and author Richard Evan Schwartz leads math lovers of all ages on an innovative and strikingly illustrated journey through the infinite number system. By means of engaging, imaginative visuals and endearing narration, Schwartz manages the monumental task of presenting the complex concept of Big Numbers in fresh and relatable ways. The book begins with small, easily observable numbers before building up to truly gigantic ones, like a nonillion, a tredecillion, a googol, and even ones too huge for names! Any person, regardless of age, can benefit from reading this book. Readers will find themselves returning to its pages for a very long time, perpetually learning from and growing with the narrative as their knowledge deepens. Really Big Numbers is a wonderful enrichment for any math education program and is enthusiastically recommended to every teacher, parent and grandparent, student, child, or other individual i...

  11. Think Small Go Big

    Institute of Scientific and Technical Information of China (English)

    汤维维

    2006-01-01

    Vepoo公司在创立之前,经历了三次创业转型。用他们的话来说,从“think big go small”转到“think small go big”用了一年的时间。这期间他们耗尽了初期筹备资金,幸运的是在最后一刻迎来了黎明的曙光。

  12. DARPA's Big Mechanism program

    Science.gov (United States)

    Cohen, Paul R.

    2015-07-01

    Reductionist science produces causal models of small fragments of complicated systems. Causal models of entire systems can be hard to construct because what is known of them is distributed across a vast amount of literature. The Big Mechanism program aims to have machines read the literature and assemble the causal fragments found in individual papers into huge causal models, automatically. The current domain of the program is cell signalling associated with Ras-driven cancers.

  13. Big Bang 8

    CERN Document Server

    Apolin, Martin

    2008-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. Band 8 vermittelt auf verständliche Weise Relativitätstheorie, Kern- und Teilchenphysik (und deren Anwendungen in der Kosmologie und Astrophysik), Nanotechnologie sowie Bionik.

  14. Big Bang 7

    CERN Document Server

    Apolin, Martin

    2008-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. In Band 7 werden neben einer Einführung auch viele aktuelle Aspekte von Quantenmechanik (z. Beamen) und Elektrodynamik (zB Elektrosmog), sowie die Klimaproblematik und die Chaostheorie behandelt.

  15. Big Bang 5

    CERN Document Server

    Apolin, Martin

    2007-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. Der Band 5 RG behandelt die Grundlagen (Maßsystem, Größenordnungen) und die Mechanik (Translation, Rotation, Kraft, Erhaltungssätze).

  16. Big Bang 6

    CERN Document Server

    Apolin, Martin

    2008-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. Der Band 6 RG behandelt die Gravitation, Schwingungen und Wellen, Thermodynamik und eine Einführung in die Elektrizität anhand von Alltagsbeispielen und Querverbindungen zu anderen Disziplinen.

  17. Big Data Refinement

    OpenAIRE

    Boiten, Eerke Albert

    2016-01-01

    "Big data" has become a major area of research and associated funding, as well as a focus of utopian thinking. In the still growing research community, one of the favourite optimistic analogies for data processing is that of the oil refinery, extracting the essence out of the raw data. Pessimists look for their imagery to the other end of the petrol cycle, and talk about the "data exhausts" of our society. Obviously, the refinement community knows how to do "refining". This paper explores...

  18. The NOAA Big Data Project

    Science.gov (United States)

    de la Beaujardiere, J.

    2015-12-01

    The US National Oceanic and Atmospheric Administration (NOAA) is a Big Data producer, generating tens of terabytes per day from hundreds of sensors on satellites, radars, aircraft, ships, and buoys, and from numerical models. These data are of critical importance and value for NOAA's mission to understand and predict changes in climate, weather, oceans, and coasts. In order to facilitate extracting additional value from this information, NOAA has established Cooperative Research and Development Agreements (CRADAs) with five Infrastructure-as-a-Service (IaaS) providers — Amazon, Google, IBM, Microsoft, Open Cloud Consortium — to determine whether hosting NOAA data in publicly-accessible Clouds alongside on-demand computational capability stimulates the creation of new value-added products and services and lines of business based on the data, and if the revenue generated by these new applications can support the costs of data transmission and hosting. Each IaaS provider is the anchor of a "Data Alliance" which organizations or entrepreneurs can join to develop and test new business or research avenues. This presentation will report on progress and lessons learned during the first 6 months of the 3-year CRADAs.

  19. Vertical landscraping, a big regionalism for Dubai.

    Science.gov (United States)

    Wilson, Matthew

    2010-01-01

    Dubai's ecologic and economic complications are exacerbated by six years of accelerated expansion, a fixed top-down approach to urbanism and the construction of iconic single-phase mega-projects. With recent construction delays, project cancellations and growing landscape issues, Dubai's tower typologies have been unresponsive to changing environmental, socio-cultural and economic patterns (BBC, 2009; Gillet, 2009; Lewis, 2009). In this essay, a theory of "Big Regionalism" guides an argument for an economically and ecologically linked tower typology called the Condenser. This phased "box-to-tower" typology is part of a greater Landscape Urbanist strategy called Vertical Landscraping. Within this strategy, the Condenser's role is to densify the city, facilitating the creation of ecologic voids that order the urban region. Delineating "Big Regional" principles, the Condenser provides a time-based, global-local urban growth approach that weaves Bigness into a series of urban-regional, economic and ecological relationships, builds upon the environmental performance of the city's regional architecture and planning, promotes a continuity of Dubai's urban history, and responds to its landscape issues while condensing development. These speculations permit consideration of the overlooked opportunities embedded within Dubai's mega-projects and their long-term impact on the urban morphology.

  20. Leveraging Big Data to Transform Target Selection and Drug Discovery

    Science.gov (United States)

    Chen, B; Butte, AJ

    2016-01-01

    The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. Recent open data initiatives in basic and clinical research have dramatically increased the types of data available to the public. The past few years have witnessed successful use of big data in many sectors across the whole drug discovery pipeline. In this review, we will highlight the state of the art in leveraging big data to identify new targets, drug indications, and drug response biomarkers in this era of precision medicine. PMID:26659699

  1. Leveraging big data to transform target selection and drug discovery

    Science.gov (United States)

    Butte, AJ

    2016-01-01

    The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. Recent open data initiatives in basic and clinical research have dramatically increased the types of data available to the public. The past few years have witnessed successful use of big data in many sectors across the whole drug discovery pipeline. In this review, we will highlight the state of the art in leveraging big data to identify new targets, drug indications, and drug response biomarkers in this era of precision medicine. PMID:26659699

  2. From Big Bang to Big Crunch and Beyond

    OpenAIRE

    Elitzur, S.; Giveon, A.; Kutasov, D.; Rabinovici, E.

    2002-01-01

    We study a quotient Conformal Field Theory, which describes a 3+1 dimensional cosmological spacetime. Part of this spacetime is the Nappi-Witten (NW) universe, which starts at a ``big bang'' singularity, expands and then contracts to a ``big crunch'' singularity at a finite time. The gauged WZW model contains a number of copies of the NW spacetime, with each copy connected to the preceeding one and to the next one at the respective big bang/big crunch singularities. The sequence of NW spaceti...

  3. Single-cell Transcriptome Study as Big Data.

    Science.gov (United States)

    Yu, Pingjian; Lin, Wei

    2016-02-01

    The rapid growth of single-cell RNA-seq studies (scRNA-seq) demands efficient data storage, processing, and analysis. Big-data technology provides a framework that facilitates the comprehensive discovery of biological signals from inter-institutional scRNA-seq datasets. The strategies to solve the stochastic and heterogeneous single-cell transcriptome signal are discussed in this article. After extensively reviewing the available big-data applications of next-generation sequencing (NGS)-based studies, we propose a workflow that accounts for the unique characteristics of scRNA-seq data and primary objectives of single-cell studies. PMID:26876720

  4. Single-cell Transcriptome Study as Big Data

    Institute of Scientific and Technical Information of China (English)

    Pingjian Yu; Wei Lin

    2016-01-01

    The rapid growth of single-cell RNA-seq studies (scRNA-seq) demands efficient data storage, processing, and analysis. Big-data technology provides a framework that facilitates the comprehensive discovery of biological signals from inter-institutional scRNA-seq datasets. The strategies to solve the stochastic and heterogeneous single-cell transcriptome signal are discussed in this article. After extensively reviewing the available big-data applications of next-generation sequencing (NGS)-based studies, we propose a workflow that accounts for the unique characteris-tics of scRNA-seq data and primary objectives of single-cell studies.

  5. Single-cell Transcriptome Study as Big Data

    Science.gov (United States)

    Yu, Pingjian; Lin, Wei

    2016-01-01

    The rapid growth of single-cell RNA-seq studies (scRNA-seq) demands efficient data storage, processing, and analysis. Big-data technology provides a framework that facilitates the comprehensive discovery of biological signals from inter-institutional scRNA-seq datasets. The strategies to solve the stochastic and heterogeneous single-cell transcriptome signal are discussed in this article. After extensively reviewing the available big-data applications of next-generation sequencing (NGS)-based studies, we propose a workflow that accounts for the unique characteristics of scRNA-seq data and primary objectives of single-cell studies. PMID:26876720

  6. Asymmetric author-topic model for knowledge discovering of big data in toxicogenomics

    Directory of Open Access Journals (Sweden)

    Ming-Hua eChung

    2015-04-01

    Full Text Available The advancement of high-throughput screening technologies facilitates the generation of massive amount of biological data, a big data phenomena in biomedical science. Yet, researchers still heavily rely on keyword search and/or literature review to navigate the databases and analyses are often done in rather small-scale. As a result, the rich information of a database has not been fully utilized, particularly for the information embedded in the interactive nature between data points that are largely ignored and buried. For the past ten years, probabilistic topic modeling has been recognized as an effective machine learning algorithm to annotate the hidden thematic structure of massive collection of documents. The analogy between text corpus and large-scale genomic data enables the application of text mining tools, like probabilistic topic models, to explore hidden patterns of genomic data and to the extension of altered biological functions. In this paper, we developed a generalized probabilistic topic model to analyze a toxicogenomics dataset that consists of a large number of gene expression data from the rat livers treated with drugs in multiple dose and time-points. We discovered the hidden patterns in gene expression associated with the effect of doses and time-points of treatment. Finally, we illustrated the ability of our model to identify the evidence of potential reduction of animal use.

  7. Visual explorer facilitator's guide

    CERN Document Server

    Palus, Charles J

    2010-01-01

    Grounded in research and practice, the Visual Explorer™ Facilitator's Guide provides a method for supporting collaborative, creative conversations about complex issues through the power of images. The guide is available as a component in the Visual Explorer Facilitator's Letter-sized Set, Visual Explorer Facilitator's Post card-sized Set, Visual Explorer Playing Card-sized Set, and is also available as a stand-alone title for purchase to assist multiple tool users in an organization.

  8. How Big is Earth?

    Science.gov (United States)

    Thurber, Bonnie B.

    2015-08-01

    How Big is Earth celebrates the Year of Light. Using only the sunlight striking the Earth and a wooden dowel, students meet each other and then measure the circumference of the earth. Eratosthenes did it over 2,000 years ago. In Cosmos, Carl Sagan shared the process by which Eratosthenes measured the angle of the shadow cast at local noon when sunlight strikes a stick positioned perpendicular to the ground. By comparing his measurement to another made a distance away, Eratosthenes was able to calculate the circumference of the earth. How Big is Earth provides an online learning environment where students do science the same way Eratosthenes did. A notable project in which this was done was The Eratosthenes Project, conducted in 2005 as part of the World Year of Physics; in fact, we will be drawing on the teacher's guide developed by that project.How Big Is Earth? expands on the Eratosthenes project by providing an online learning environment provided by the iCollaboratory, www.icollaboratory.org, where teachers and students from Sweden, China, Nepal, Russia, Morocco, and the United States collaborate, share data, and reflect on their learning of science and astronomy. They are sharing their information and discussing their ideas/brainstorming the solutions in a discussion forum. There is an ongoing database of student measurements and another database to collect data on both teacher and student learning from surveys, discussions, and self-reflection done online.We will share our research about the kinds of learning that takes place only in global collaborations.The entrance address for the iCollaboratory is http://www.icollaboratory.org.

  9. Big Red Telephone, Gone

    Institute of Scientific and Technical Information of China (English)

    Toni Piech

    2006-01-01

    @@ The Chinese big red telephones looked exactly as Iimagined the ones servicing the direct emergen line between the Kreml and the White House duing the cold-war era would have look like. But here in China, every kio seemed to have such a device in t1990s, and anyone could use it for ju 0.2 yuan. The government did not juinstall public phones on street corner but they let small-business owners pa ticipate in telecommunication. Supply and demand were juggled by a kind of Hutong capitalism.

  10. A Matrix Big Bang

    OpenAIRE

    Craps, Ben; Sethi, Savdeep; Verlinde, Erik

    2005-01-01

    The light-like linear dilaton background represents a particularly simple time-dependent 1/2 BPS solution of critical type IIA superstring theory in ten dimensions. Its lift to M-theory, as well as its Einstein frame metric, are singular in the sense that the geometry is geodesically incomplete and the Riemann tensor diverges along a light-like subspace of codimension one. We study this background as a model for a big bang type singularity in string theory/M-theory. We construct the dual Matr...

  11. Big and little OER

    OpenAIRE

    Weller, Martin

    2010-01-01

    Much of the attention around OERs has been on institutional projects which make explicit learning content available. These can be classified as ‘big OER’, but another form of OER is that of small scale, individually produced resources using web 2.0 type services, which are classified as ‘little OER’. This paper examines some of the differences between the use of these two types of OER to highlight issues in open education. These include attitudes towards reputation, the intentionality of the ...

  12. Big Data Challenges

    Directory of Open Access Journals (Sweden)

    Alexandru Adrian TOLE

    2013-10-01

    Full Text Available The amount of data that is traveling across the internet today, not only that is large, but is complex as well. Companies, institutions, healthcare system etc., all of them use piles of data which are further used for creating reports in order to ensure continuity regarding the services that they have to offer. The process behind the results that these entities requests represents a challenge for software developers and companies that provide IT infrastructure. The challenge is how to manipulate an impressive volume of data that has to be securely delivered through the internet and reach its destination intact. This paper treats the challenges that Big Data creates.

  13. Big Bang Nucleosynthesis Calculation

    CERN Document Server

    Kurki-Suonio, H

    2001-01-01

    I review standard big bang nucleosynthesis and some versions of nonstandard BBN. The abundances of the primordial isotopes D, He-3, and Li-7 produced in standard BBN can be calculated as a function of the baryon density with an accuracy of about 10%. For He-4 the accuracy is better than 1%. The calculated abundances agree fairly well with observations, but the baryon density of the universe cannot be determined with high precision. Possibilities for nonstandard BBN include inhomogeneous and antimatter BBN and nonzero neutrino chemical potentials.

  14. Privacy and Big Data

    CERN Document Server

    Craig, Terence

    2011-01-01

    Much of what constitutes Big Data is information about us. Through our online activities, we leave an easy-to-follow trail of digital footprints that reveal who we are, what we buy, where we go, and much more. This eye-opening book explores the raging privacy debate over the use of personal data, with one undeniable conclusion: once data's been collected, we have absolutely no control over who uses it or how it is used. Personal data is the hottest commodity on the market today-truly more valuable than gold. We are the asset that every company, industry, non-profit, and government wants. Pri

  15. Mitochondrial Disease Sequence Data Resource (MSeqDR): A global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities

    NARCIS (Netherlands)

    M.J. Falk (Marni J.); L. Shen (Lishuang); M. Gonzalez (Michael); J. Leipzig (Jeremy); M.T. Lott (Marie T.); A.P.M. Stassen (Alphons P.M.); M.A. Diroma (Maria Angela); D. Navarro-Gomez (Daniel); P. Yeske (Philip); R. Bai (Renkui); R.G. Boles (Richard G.); V. Brilhante (Virginia); D. Ralph (David); J.T. DaRe (Jeana T.); R. Shelton (Robert); S.F. Terry (Sharon); Z. Zhang (Zhe); W.C. Copeland (William C.); M. van Oven (Mannis); H. Prokisch (Holger); D.C. Wallace; M. Attimonelli (Marcella); D. Krotoski (Danuta); S. Zuchner (Stephan); X. Gai (Xiaowu); S. Bale (Sherri); J. Bedoyan (Jirair); D.M. Behar (Doron); P. Bonnen (Penelope); L. Brooks (Lisa); C. Calabrese (Claudia); S. Calvo (Sarah); P.F. Chinnery (Patrick); J. Christodoulou (John); D. Church (Deanna); R. Clima (Rosanna); B.H. Cohen (Bruce H.); R.G.H. Cotton (Richard); I.F.M. de Coo (René); O. Derbenevoa (Olga); J.T. den Dunnen (Johan); D. Dimmock (David); G. Enns (Gregory); G. Gasparre (Giuseppe); A. Goldstein (Amy); I. Gonzalez (Iris); K. Gwinn (Katrina); S. Hahn (Sihoun); R.H. Haas (Richard H.); H. Hakonarson (Hakon); M. Hirano (Michio); D. Kerr (Douglas); D. Li (Dong); M. Lvova (Maria); F. Macrae (Finley); D. Maglott (Donna); E. McCormick (Elizabeth); G. Mitchell (Grant); V.K. Mootha (Vamsi K.); Y. Okazaki (Yasushi); A. Pujol (Aurora); M. Parisi (Melissa); J.C. Perin (Juan Carlos); E.A. Pierce (Eric A.); V. Procaccio (Vincent); S. Rahman (Shamima); H. Reddi (Honey); H. Rehm (Heidi); E. Riggs (Erin); R.J.T. Rodenburg (Richard); Y. Rubinstein (Yaffa); R. Saneto (Russell); M. Santorsola (Mariangela); C. Scharfe (Curt); C. Sheldon (Claire); E.A. Shoubridge (Eric); D. Simone (Domenico); B. Smeets (Bert); J.A.M. Smeitink (Jan); C. Stanley (Christine); A. Suomalainen (Anu); M.A. Tarnopolsky (Mark); I. Thiffault (Isabelle); D.R. Thorburn (David R.); J.V. Hove (Johan Van); L. Wolfe (Lynne); L.-J. Wong (Lee-Jun)

    2015-01-01

    textabstractSuccess rates for genomic analyses of highly heterogeneous disorders can be greatly improved if a large cohort of patient data is assembled to enhance collective capabilities for accurate sequence variant annotation, analysis, and interpretation. Indeed, molecular diagnostics requires th

  16. Genome Maps, a new generation genome browser

    Science.gov (United States)

    Medina, Ignacio; Salavert, Francisco; Sanchez, Rubén; de Maria, Alejandro; Alonso, Roberto; Escobar, Pablo; Bleda, Marta; Dopazo, Joaquín

    2013-01-01

    Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org. PMID:23748955

  17. Genome Maps, a new generation genome browser.

    Science.gov (United States)

    Medina, Ignacio; Salavert, Francisco; Sanchez, Rubén; de Maria, Alejandro; Alonso, Roberto; Escobar, Pablo; Bleda, Marta; Dopazo, Joaquín

    2013-07-01

    Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org. PMID:23748955

  18. Genome Maps, a new generation genome browser.

    Science.gov (United States)

    Medina, Ignacio; Salavert, Francisco; Sanchez, Rubén; de Maria, Alejandro; Alonso, Roberto; Escobar, Pablo; Bleda, Marta; Dopazo, Joaquín

    2013-07-01

    Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org.

  19. Training facilitators and supervisors

    DEFF Research Database (Denmark)

    Kjær, Louise Binow; O Connor, Maja; Krogh, Kristian;

    At the Master’s program in Medicine at Aarhus University, Denmark, we have developed a faculty development program for facilitators and supervisors in 4 progressing student modules in communication, cooperation, and leadership. 1) A course for module 1 and 3 facilitators inspired by the apprentic...

  20. Can Pleasant Goat and Big Big Wolf Save China's Animation Industry?

    Institute of Scientific and Technical Information of China (English)

    Guo Liqin

    2009-01-01

    "My dreamed husband is big big wolf," claimed Miss Fang, a young lady who works in KPMG Beijing Office. This big big wolf is a lovely cartoon wolf appeared in a Pleasant Goat and Big Big Wolf produced independently by Chinese.

  1. Passport to the Big Bang

    CERN Multimedia

    De Melis, Cinzia

    2013-01-01

    Le 2 juin 2013, le CERN inaugure le projet Passeport Big Bang lors d'un grand événement public. Affiche et programme. On 2 June 2013 CERN launches a scientific tourist trail through the Pays de Gex and the Canton of Geneva known as the Passport to the Big Bang. Poster and Programme.

  2. IZVEDBENI ELEMENTI U BIG BROTHERU

    OpenAIRE

    Radman, Korana

    2009-01-01

    Big Brother publici nudi "ultimativnu stvarnost" osiguranu cjelodnevnim nadzorom televizijskih kamera, o čemu je polemizirano od početka njegova prikazivanja u Europi i svijetu. Imajući to na umu, ovaj rad je pristupio Big Brotheru iz perspektive izvedbenih studija, pokušavajući u njemu prepoznati neke od mogućih izvedbi.

  3. The Rise of Big Data in Neurorehabilitation.

    Science.gov (United States)

    Faroqi-Shah, Yasmeen

    2016-02-01

    In some fields, Big Data has been instrumental in analyzing, predicting, and influencing human behavior. However, Big Data approaches have so far been less central in speech-language pathology. This article introduces the concept of Big Data and provides examples of Big Data initiatives pertaining to adult neurorehabilitation. It also discusses the potential theoretical and clinical contributions that Big Data can make. The article also recognizes some impediments in building and using Big Data for scientific and clinical inquiry.

  4. Avoiding a Big Catastrophe

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Before last October,the South China tiger had almost slipped into mythi- cal status as it had been absent for so long from the public eye.In the previous 20-plus years,these tigers could not be found in the wild in China and the number of those in captivity numbered only around 60. The species—a direct descendent of the earliest tigers thought to have originat- ed in China 2 million years ago—is functionally extinct,according to experts. The big cat’s return to the media spotlight was completely unexpected. On October 12,2007,a digital picture,showing a wild South China tiger

  5. Big Bounce Genesis

    CERN Document Server

    Li, Changhong; Cheung, Yeuk-Kwan E

    2014-01-01

    We report on the possibility to use dark matter mass and its interaction cross section as a smoking gun signal of the existence of a big bounce at the early stage in the evolution of our currently observed universe. A model independent study of dark matter production in the contraction and expansion phases of the bounce universe reveals a new venue for achieving the observed relic abundance in which a significantly smaller amount of dark matter--compared to the standard cosmology--is produced and survives until today, diluted only by the cosmic expansion since the radiation dominated era. Once DM mass and its interaction strength with ordinary matter are determined by experiments, this alternative route becomes a signature of the bounce universe scenario.

  6. BIG DATA AND STATISTICS

    Science.gov (United States)

    Rossell, David

    2016-01-01

    Big Data brings unprecedented power to address scientific, economic and societal issues, but also amplifies the possibility of certain pitfalls. These include using purely data-driven approaches that disregard understanding the phenomenon under study, aiming at a dynamically moving target, ignoring critical data collection issues, summarizing or preprocessing the data inadequately and mistaking noise for signal. We review some success stories and illustrate how statistical principles can help obtain more reliable information from data. We also touch upon current challenges that require active methodological research, such as strategies for efficient computation, integration of heterogeneous data, extending the underlying theory to increasingly complex questions and, perhaps most importantly, training a new generation of scientists to develop and deploy these strategies.

  7. The Last Big Bang

    Energy Technology Data Exchange (ETDEWEB)

    McGuire, Austin D. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Meade, Roger Allen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-09-13

    As one of the very few people in the world to give the “go/no go” decision to detonate a nuclear device, Austin “Mac” McGuire holds a very special place in the history of both the Los Alamos National Laboratory and the world. As Commander of Joint Task Force Unit 8.1.1, on Christmas Island in the spring and summer of 1962, Mac directed the Los Alamos data collection efforts for twelve of the last atmospheric nuclear detonations conducted by the United States. Since data collection was at the heart of nuclear weapon testing, it fell to Mac to make the ultimate decision to detonate each test device. He calls his experience THE LAST BIG BANG, since these tests, part of Operation Dominic, were characterized by the dramatic displays of the heat, light, and sounds unique to atmospheric nuclear detonations – never, perhaps, to be witnessed again.

  8. Big Bang Darkleosynthesis

    CERN Document Server

    Krnjaic, Gordan

    2014-01-01

    In a popular class of models, dark matter comprises an asymmetric population of composite particles with short range interactions arising from a confined nonabelian gauge group. We show that coupling this sector to a well-motivated light mediator particle yields efficient darkleosynthesis, a dark-sector version of big-bang nucleosynthesis (BBN), in generic regions of parameter space. Dark matter self-interaction bounds typically require the confinement scale to be above \\Lambda_{QCD}, which generically yields large (>>MeV/dark-nucleon) binding energies. These bounds further suggest the mediator is relatively weakly coupled, so repulsive forces between dark-sector nuclei are much weaker than coulomb repulsion between standard-model nuclei, which results in an exponential barrier-tunneling enhancement over standard BBN. Thus, dark nuclei are easier to make and harder to break than visible species with comparable mass numbers. This process can efficiently yield a dominant population of states with masses signifi...

  9. A Grey Theory Based Approach to Big Data Risk Management Using FMEA

    Directory of Open Access Journals (Sweden)

    Maisa Mendonça Silva

    2016-01-01

    Full Text Available Big data is the term used to denote enormous sets of data that differ from other classic databases in four main ways: (huge volume, (high velocity, (much greater variety, and (big value. In general, data are stored in a distributed fashion and on computing nodes as a result of which big data may be more susceptible to attacks by hackers. This paper presents a risk model for big data, which comprises Failure Mode and Effects Analysis (FMEA and Grey Theory, more precisely grey relational analysis. This approach has several advantages: it provides a structured approach in order to incorporate the impact of big data risk factors; it facilitates the assessment of risk by breaking down the overall risk to big data; and finally its efficient evaluation criteria can help enterprises reduce the risks associated with big data. In order to illustrate the applicability of our proposal in practice, a numerical example, with realistic data based on expert knowledge, was developed. The numerical example analyzes four dimensions, that is, managing identification and access, registering the device and application, managing the infrastructure, and data governance, and 20 failure modes concerning the vulnerabilities of big data. The results show that the most important aspect of risk to big data relates to data governance.

  10. Transcriptome characterization and polymorphism detection between subspecies of big sagebrush (Artemisia tridentata)

    OpenAIRE

    Cronn Richard C; Price Jared C; Richardson Bryce A; Bajgain Prabin; Udall Joshua A

    2011-01-01

    Abstract Background Big sagebrush (Artemisia tridentata) is one of the most widely distributed and ecologically important shrub species in western North America. This species serves as a critical habitat and food resource for many animals and invertebrates. Habitat loss due to a combination of disturbances followed by establishment of invasive plant species is a serious threat to big sagebrush ecosystem sustainability. Lack of genomic data has limited our understanding of the evolutionary his...

  11. From Darwin to the Census of Marine Life: Marine Biology as Big Science

    OpenAIRE

    Vermeulen, N.

    2013-01-01

    With the development of the Human Genome Project, a heated debate emerged on biology becoming ‘big science’. However, biology already has a long tradition of collaboration, as natural historians were part of the first collective scientific efforts: exploring the variety of life on earth. Such mappings of life still continue today, and if field biology is gradually becoming an important subject of studies into big science, research into life in the world's oceans is not taken into account yet....

  12. Seeking Relationships in Big Data: A Bayesian Perspective

    OpenAIRE

    Singpurwalla, Nozer

    2014-01-01

    The real purpose of collecting big data is to identify causality in the hope that this will facilitate credible predictivity . But the search for causality can trap one into infinite regress, and thus one takes refuge in seeking associations between variables in data sets. Regrettably, the mere knowledge of associations does not enable predictivity. Associations need to be embedded within the framework of probability calculus to make coherent predictions. This is so because ...

  13. BigData as a Driver for Capacity Building in Astrophysics

    Science.gov (United States)

    Shastri, Prajval

    2015-08-01

    Exciting public interest in astrophysics acquires new significance in the era of Big Data. Since Big Data involves advanced technologies of both software and hardware, astrophysics with Big Data has the potential to inspire young minds with diverse inclinations - i.e., not just those attracted to physics but also those pursuing engineering careers. Digital technologies have become steadily cheaper, which can enable expansion of the Big Data user pool considerably, especially to communities that may not yet be in the astrophysics mainstream, but have high potential because of access to thesetechnologies. For success, however, capacity building at the early stages becomes key. The development of on-line pedagogical resources in astrophysics, astrostatistics, data-mining and data visualisation that are designed around the big facilities of the future can be an important effort that drives such capacity building, especially if facilitated by the IAU.

  14. BigOP: Generating Comprehensive Big Data Workloads as a Benchmarking Framework

    OpenAIRE

    Zhu, Yuqing; Zhan, Jianfeng; Weng, Chuliang; Nambiar, Raghunath; Zhang, Jinchao; Chen, Xingzhen; Wang, Lei

    2014-01-01

    Big Data is considered proprietary asset of companies, organizations, and even nations. Turning big data into real treasure requires the support of big data systems. A variety of commercial and open source products have been unleashed for big data storage and processing. While big data users are facing the choice of which system best suits their needs, big data system developers are facing the question of how to evaluate their systems with regard to general big data processing needs. System b...

  15. Google BigQuery analytics

    CERN Document Server

    Tigani, Jordan

    2014-01-01

    How to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets Google BigQuery Analytics is the perfect guide for business and data analysts who want the latest tips on running complex queries and writing code to communicate with the BigQuery API. The book uses real-world examples to demonstrate current best practices and techniques, and also explains and demonstrates streaming ingestion, transformation via Hadoop in Google Compute engine, AppEngine datastore integration, and using GViz with Tableau to generate charts of query results. In addit

  16. Big Data: present and future

    Directory of Open Access Journals (Sweden)

    Mircea Raducu TRIFU

    2014-05-01

    Full Text Available The paper explains the importance of the Big Data concept, a concept that even now, after years of development, is for the most companies just a cool keyword. The paper also describes the level of the actual big data development and the things it can do, and also the things that can be done in the near future. The paper focuses on explaining to nontechnical and non-database related technical specialists what basically is big data, presents the three most important V's, as well as the new ones, the most important solutions used by companies like Google or Amazon, as well as some interesting perceptions based on this subject.

  17. The challenges of big data

    Science.gov (United States)

    2016-01-01

    ABSTRACT The largely untapped potential of big data analytics is a feeding frenzy that has been fueled by the production of many next-generation-sequencing-based data sets that are seeking to answer long-held questions about the biology of human diseases. Although these approaches are likely to be a powerful means of revealing new biological insights, there are a number of substantial challenges that currently hamper efforts to harness the power of big data. This Editorial outlines several such challenges as a means of illustrating that the path to big data revelations is paved with perils that the scientific community must overcome to pursue this important quest. PMID:27147249

  18. Big Data Mining: Tools & Algorithms

    Directory of Open Access Journals (Sweden)

    Adeel Shiraz Hashmi

    2016-03-01

    Full Text Available We are now in Big Data era, and there is a growing demand for tools which can process and analyze it. Big data analytics deals with extracting valuable information from that complex data which can’t be handled by traditional data mining tools. This paper surveys the available tools which can handle large volumes of data as well as evolving data streams. The data mining tools and algorithms which can handle big data have also been summarized, and one of the tools has been used for mining of large datasets using distributed algorithms.

  19. The challenges of big data.

    Science.gov (United States)

    Mardis, Elaine R

    2016-05-01

    The largely untapped potential of big data analytics is a feeding frenzy that has been fueled by the production of many next-generation-sequencing-based data sets that are seeking to answer long-held questions about the biology of human diseases. Although these approaches are likely to be a powerful means of revealing new biological insights, there are a number of substantial challenges that currently hamper efforts to harness the power of big data. This Editorial outlines several such challenges as a means of illustrating that the path to big data revelations is paved with perils that the scientific community must overcome to pursue this important quest.

  20. Transposable elements: powerful facilitators of evolution.

    Science.gov (United States)

    Oliver, Keith R; Greene, Wayne K

    2009-07-01

    Transposable elements (TEs) are powerful facilitators of genome evolution, and hence of phenotypic diversity as they can cause genetic changes of great magnitude and variety. TEs are ubiquitous and extremely ancient, and although harmful to some individuals, they can be very beneficial to lineages. TEs can build, sculpt, and reformat genomes by both active and passive means. Lineages with active TEs or with abundant homogeneous inactive populations of TEs that can act passively by causing ectopic recombination are potentially fecund, adaptable, and taxonate readily. Conversely, taxa deficient in TEs or possessing heterogeneous populations of inactive TEs may be well adapted in their niche, but tend to prolonged stasis and may risk extinction by lacking the capacity to adapt to change, or diversify. Because of recurring intermittent waves of TE infestation, available data indicate a compatibility with punctuated equilibrium, in keeping with widely accepted interpretations of evidence from the fossil record. We propose a general and holistic synthesis on how the presence of TEs within genomes makes them flexible and dynamic, so that genomes themselves are powerful facilitators of their own evolution. PMID:19415638

  1. Antigravity and the big crunch/big bang transition

    OpenAIRE

    Bars, Itzhak; Chen, Shih-Hung; Steinhardt, Paul J.(Princeton Center for Theoretical Science, Princeton University, Princeton, NJ, 08544, USA); Turok, Neil

    2011-01-01

    We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition...

  2. Quantum Fields in a Big Crunch/Big Bang Spacetime

    OpenAIRE

    Tolley, Andrew J.; Turok, Neil

    2002-01-01

    We consider quantum field theory on a spacetime representing the Big Crunch/Big Bang transition postulated in the ekpyrotic or cyclic cosmologies. We show via several independent methods that an essentially unique matching rule holds connecting the incoming state, in which a single extra dimension shrinks to zero, to the outgoing state in which it re-expands at the same rate. For free fields in our construction there is no particle production from the incoming adiabatic vacuum. When interacti...

  3. Sailing through the big crunch-big bang transition

    OpenAIRE

    Bars, Itzhak; Steinhardt, Paul; Turok, Neil

    2013-01-01

    In a recent series of papers, we have shown that theories with scalar fields coupled to gravity (e.g., the standard model) can be lifted to a Weyl-invariant equivalent theory in which it is possible to unambiguously trace the classical cosmological evolution through the transition from big crunch to big bang. The key was identifying a sufficient number of finite, Weyl-invariant conserved quantities to uniquely match the fundamental cosmological degrees of freedom across the transition. In so ...

  4. Detecting and understanding big events in big cities

    OpenAIRE

    Furletti, Barbara; Trasarti, Roberto; Gabrielli, Lorenzo; Smoreda, Zbigniew; Vanhoof, Maarten; Ziemlicki, Cezary

    2015-01-01

    Recent studies have shown the great potential of big data such as mobile phone location data to model human behavior. Big data allow to analyze people presence in a territory in a fast and effective way with respect to the classical surveys (diaries or questionnaires). One of the drawbacks of these collection systems is incompleteness of the users' traces; people are localized only when they are using their phones. In this work we define a data mining method for identifying people presence an...

  5. Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks

    Science.gov (United States)

    Lin, Shengda; Yin, Yi A.; Jiang, Xiaoqian; Sahni, Nidhi; Yi, Song

    2016-01-01

    The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative “OMICs” arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA), the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT) and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine. PMID:27403431

  6. Boosting Big National Lab Data

    Energy Technology Data Exchange (ETDEWEB)

    Kleese van Dam, Kerstin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2013-02-21

    Introduction: Big data. Love it or hate it, solving the world’s most intractable problems requires the ability to make sense of huge and complex sets of data and do it quickly. Speeding up the process – from hours to minutes or from weeks to days – is key to our success. One major source of such big data are physical experiments. As many will know, these physical experiments are commonly used to solve challenges in fields such as energy security, manufacturing, medicine, pharmacology, environmental protection and national security. Experiments use different instruments and sensor types to research for example the validity of new drugs, the base cause for diseases, more efficient energy sources, new materials for every day goods, effective methods for environmental cleanup, the optimal ingredients composition for chocolate or determine how to preserve valuable antics. This is done by experimentally determining the structure, properties and processes that govern biological systems, chemical processes and materials. The speed and quality at which we can acquire new insights from experiments directly influences the rate of scientific progress, industrial innovation and competitiveness. And gaining new groundbreaking insights, faster, is key to the economic success of our nations. Recent years have seen incredible advances in sensor technologies, from house size detector systems in large experiments such as the Large Hadron Collider and the ‘Eye of Gaia’ billion pixel camera detector to high throughput genome sequencing. These developments have led to an exponential increase in data volumes, rates and variety produced by instruments used for experimental work. This increase is coinciding with a need to analyze the experimental results at the time they are collected. This speed is required to optimize the data taking and quality, and also to enable new adaptive experiments, where the sample is manipulated as it is observed, e.g. a substance is injected into a

  7. Hey, big spender

    International Nuclear Information System (INIS)

    Business to business electronic commerce is looming large in the future of the oil industry. It is estimated that by adopting e-commerce the industry could achieve bottom line savings of between $1.8 to $ 3.4 billion a year on annual gross revenues in excess of $ 30 billion. At present there are several teething problems to overcome such as inter-operability standards, which are at least two or three years away. Tying in electronically with specific suppliers is also an expensive proposition, although the big benefits are in fact in doing business with the same suppliers on a continuing basis. Despite these problems, 14 of the world's largest energy and petrochemical companies joined forces in mid-April to create a single Internet procurement marketplace for the industry's complex supply chain. The exchange was designed by B2B (business-to-business) software provider, Commerce One Inc., ; it will leverage the buying clout of these industry giants (BP Amoco, Royal Dutch Shell Group, Conoco, Occidental Petroleum, Phillips Petroleum, Unocal Corporation and Statoil among them), currently about $ 125 billion on procurement per year; they hope to save between 5 to 30 per cent depending on the product and the region involved. Other similar schemes such as Chevron and partners' Petrocosm Marketplace, Network Oil, a Houston-based Internet portal aimed at smaller petroleum companies, are also doing business in the $ 10 billion per annum range. e-Energy, a cooperative project between IBM Ericson and Telus Advertising is another neutral, virtual marketplace targeted at the oil and gas sector. PetroTRAX, a Calgary-based website plans to take online procurement and auction sales a big step forward by establishing a portal to handle any oil company's asset management needs. There are also a number of websites targeting specific needs: IndigoPool.com (acquisitions and divestitures) and WellBid.com (products related to upstream oil and gas operators) are just two examples. All in

  8. The BigBOSS Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Schelgel, D.; Abdalla, F.; Abraham, T.; Ahn, C.; Allende Prieto, C.; Annis, J.; Aubourg, E.; Azzaro, M.; Bailey, S.; Baltay, C.; Baugh, C.; /APC, Paris /Brookhaven /IRFU, Saclay /Marseille, CPPM /Marseille, CPT /Durham U. / /IEU, Seoul /Fermilab /IAA, Granada /IAC, La Laguna

    2011-01-01

    BigBOSS will obtain observational constraints that will bear on three of the four 'science frontier' questions identified by the Astro2010 Cosmology and Fundamental Phyics Panel of the Decadal Survey: Why is the universe accelerating; what is dark matter and what are the properties of neutrinos? Indeed, the BigBOSS project was recommended for substantial immediate R and D support the PASAG report. The second highest ground-based priority from the Astro2010 Decadal Survey was the creation of a funding line within the NSF to support a 'Mid-Scale Innovations' program, and it used BigBOSS as a 'compelling' example for support. This choice was the result of the Decadal Survey's Program Priorization panels reviewing 29 mid-scale projects and recommending BigBOSS 'very highly'.

  9. Le Big Bang en laboratoire

    CERN Multimedia

    Roy, Christelle

    2006-01-01

    Physiciens have been dreaming of it for 30 years; Thanks to huge particle accelerators, they were able to observe the matter such as it was some instants after the Big Bang (three different articles in 10 pages)

  10. Big Data Technology Literature Review

    OpenAIRE

    Bar-sinai, Michael

    2015-01-01

    A short overview of various algorithms and technologies that are helpful for big data storage and manipulation. Includes pointers to papers for further reading, and, where applicable, pointers to open source projects implementing a described storage type.

  11. Genomic signal processing

    CERN Document Server

    Shmulevich, Ilya

    2007-01-01

    Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathema

  12. Big bang darkleosynthesis

    Directory of Open Access Journals (Sweden)

    Gordan Krnjaic

    2015-12-01

    Full Text Available In a popular class of models, dark matter comprises an asymmetric population of composite particles with short range interactions arising from a confined nonabelian gauge group. We show that coupling this sector to a well-motivated light mediator particle yields efficient darkleosynthesis, a dark-sector version of big-bang nucleosynthesis (BBN, in generic regions of parameter space. Dark matter self-interaction bounds typically require the confinement scale to be above ΛQCD, which generically yields large (≫MeV/dark-nucleon binding energies. These bounds further suggest the mediator is relatively weakly coupled, so repulsive forces between dark-sector nuclei are much weaker than Coulomb repulsion between standard-model nuclei, which results in an exponential barrier-tunneling enhancement over standard BBN. Thus, darklei are easier to make and harder to break than visible species with comparable mass numbers. This process can efficiently yield a dominant population of states with masses significantly greater than the confinement scale and, in contrast to dark matter that is a fundamental particle, may allow the dominant form of dark matter to have high spin (S≫3/2, whose discovery would be smoking gun evidence for dark nuclei.

  13. Array-based comparative genomic hybridization facilitates identification of breakpoints of a novel der(1)t(1;18)(p36.3;q23)dn in a child presenting with mental retardation.

    Science.gov (United States)

    Lennon, P A; Cooper, M L; Curtis, M A; Lim, C; Ou, Z; Patel, A; Cheung, S W; Bacino, C A

    2006-06-01

    Monosomy of distal 1p36 represents the most common terminal deletion in humans and results in one of the most frequently diagnosed mental retardation syndromes. This deletion is considered a contiguous gene deletion syndrome, and has been shown to vary in deletion sizes that contribute to the spectrum of phenotypic anomalies seen in patients with monosomy 1p36. We report on an 8-year-old female with characteristics of the monosomy 1p36 syndrome who demonstrated a novel der(1)t(1;18)(p36.3;q23). Initial G-banded karyotype analysis revealed a deleted chromosome 1, with a breakpoint within 1p36.3. Subsequent FISH and array-based comparative genomic hybridization not only confirmed and partially characterized the deletion of chromosome 1p36.3, but also uncovered distal trisomy for 18q23. In this patient, the duplicated 18q23 is translocated onto the deleted 1p36.3 region, suggesting telomere capture. Molecular characterization of this novel der(1)t(1;18)(p36.3;q23), guided by our clinical array-comparative genomic hybridization, demonstrated a 3.2 Mb terminal deletion of chromosome 1p36.3 and a 200 kb duplication of 18q23 onto the deleted 1p36.3, presumably stabilizing the deleted chromosome 1. DNA sequence analysis around the breakpoints demonstrated no homology, and therefore this telomere capture of distal 18q is apparently the result of a non-homologous recombination. Partial trisomy for 18q23 has not been previously reported. The importance of mapping the breakpoints of all balanced and unbalanced translocations found in the clinical laboratory, when phenotypic abnormalities are found, is discussed.

  14. Big Data and Ambulatory Care

    OpenAIRE

    Thorpe, Jane Hyatt; Gray, Elizabeth Alexandra

    2014-01-01

    Big data is heralded as having the potential to revolutionize health care by making large amounts of data available to support care delivery, population health, and patient engagement. Critics argue that big data's transformative potential is inhibited by privacy requirements that restrict health information exchange. However, there are a variety of permissible activities involving use and disclosure of patient information that support care delivery and management. This article presents an ov...

  15. Big Data Analytics in Healthcare

    OpenAIRE

    Ashwin Belle; Raghuram Thiagarajan; S. M. Reza Soroushmehr; Fatemeh Navidi; Daniel A Beard; Kayvan Najarian

    2015-01-01

    The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is sti...

  16. The role of big laboratories

    CERN Document Server

    Heuer, Rolf-Dieter

    2013-01-01

    This paper presents the role of big laboratories in their function as research infrastructures. Starting from the general definition and features of big laboratories, the paper goes on to present the key ingredients and issues, based on scientific excellence, for the successful realization of large-scale science projects at such facilities. The paper concludes by taking the example of scientific research in the field of particle physics and describing the structures and methods required to be implemented for the way forward.

  17. Challenges of Big Data Analysis.

    Science.gov (United States)

    Fan, Jianqing; Han, Fang; Liu, Han

    2014-06-01

    Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This article gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogeneous assumptions in most statistical methods for Big Data can not be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

  18. Intelligent Decisional Assistant that Facilitate the Choice of a Proper Computer System Applied in Busines

    OpenAIRE

    Nicolae MARGINEAN

    2009-01-01

    The choice of a proper computer system is not an easy task for a decider. One reason could be the present market development of computer systems applied in business. The big number of the Romanian market players determines a big number of computerized products, with a multitude of various properties. Our proposal tries to optimize and facilitate this decisional process within an e-shop where are sold IT packets applied in business, building an online decisional assistant, a special component ...

  19. Small country, big business?

    DEFF Research Database (Denmark)

    Martens, Kerstin; Starke, Peter

    2008-01-01

    This paper discusses New Zealand's role in the global market for tertiary education. The internationalisation and liberalisation of education markets is progressing rapidly in today's globalising world, as reflected by the incorporation of education as a service into the GATS framework. Through...... of education shows that this is not necessarily the case, at least not in the medium-term: New Zealand's government rather appears to be an active facilitator of the liberalisation process in education. We review its recent move towards treating education as an international export good and present data...

  20. From Teaching to Facilitation

    DEFF Research Database (Denmark)

    de Graaff, Erik

    2013-01-01

    A shift from teaching to learning is characteristic of the introduction of Problem Based Learning (PBL) in an existing school. As a consequence the teaching staff has to be trained in skills like facilitating group work and writing cases. Most importantly a change in thinking about teaching...

  1. Facilitation skills for trainers

    Directory of Open Access Journals (Sweden)

    F. Cilliers

    2000-06-01

    Full Text Available This research aims to develop the facilitation skills of trainers. Facilitation is defined form the Person-Centered approach, as providing an opportunity for the trainee to experience personal growth and learning. A facilitation skills workshop was presented to 40 trainers, focussing on enhancing selfactualisation, its intra and inter personal characteristics, and attending and responding behaviour. Measurement with the Personal Orientation Inventory and Carkhuff scales, indicate enhanced cognitive, affective and conative sensitivity and interpersonal skills. A post-interview indicates the trainers experienced empowerment in dealing with the providing of opportunities for growth amongst trainees, in all kinds of training situations. Recommendations are made to enhance facilitation development amongst trainers. Opsomming Hierdie navorsing poog om die fasiliteringsvaardighede van opieiers te ontwikkel. Fasilitering word gedefinieer vanuit die Persoonsgesentreerde benadering as die beskikbaarstelling van 'n geleentheid om persoonlike groei en leer te ervaar. 'n Fasiliteringsvaardighede werkswinkel is aangebied vir 40 opieiers, met die fokus op die stimulering van selfaktualisering, die intra en interpersoonlike kenmerke daarvan, en aandagskenk- en responderings- gedrag. Meting met die Persoonlike Orientasievraelys en die Carkhuff skale, dui op n toename in kognitiewe, affektiewe en konatiewe sensitiwiteit en interpersoonlike vaardighede. n Post-onderhoud dui op die opleier se ervaarde bemagtiging in die beskikbaarstelling van groeigeleenthede vir opleidelinge, in all tipe opleidingsituasies. Aanbevelings word gemaak om die ontwikkeling van fasiliteringsvaardighede by opleiers te verhoog.

  2. Facilitating leadership team communication

    OpenAIRE

    Hedman, Eerika

    2015-01-01

    The purpose of this study is to understand and describe how to facilitate competent communication in leadership teamwork. Grounded in the premises of social constructionism and informed by such theoretical frameworks as coordinated management of meaning theory (CMM), dialogic organization development (OD), systemic-constructionist leadership, communication competence, and reflexivity, this study seeks to produce further insights into understanding leadership team communicati...

  3. Facilitation of Adult Development

    Science.gov (United States)

    Boydell, Tom

    2016-01-01

    Taking an autobiographical approach, I tell the story of my experiences facilitating adult development, in a polytechnic and as a management consultant. I relate these to a developmental framework of Modes of Being and Learning that I created and elaborated with colleagues. I connect this picture with a number of related models, theories,…

  4. Between two fern genomes.

    Science.gov (United States)

    Sessa, Emily B; Banks, Jo Ann; Barker, Michael S; Der, Joshua P; Duffy, Aaron M; Graham, Sean W; Hasebe, Mitsuyasu; Langdale, Jane; Li, Fay-Wei; Marchant, D Blaine; Pryer, Kathleen M; Rothfels, Carl J; Roux, Stanley J; Salmi, Mari L; Sigel, Erin M; Soltis, Douglas E; Soltis, Pamela S; Stevenson, Dennis W; Wolf, Paul G

    2014-01-01

    Ferns are the only major lineage of vascular plants not represented by a sequenced nuclear genome. This lack of genome sequence information significantly impedes our ability to understand and reconstruct genome evolution not only in ferns, but across all land plants. Azolla and Ceratopteris are ideal and complementary candidates to be the first ferns to have their nuclear genomes sequenced. They differ dramatically in genome size, life history, and habit, and thus represent the immense diversity of extant ferns. Together, this pair of genomes will facilitate myriad large-scale comparative analyses across ferns and all land plants. Here we review the unique biological characteristics of ferns and describe a number of outstanding questions in plant biology that will benefit from the addition of ferns to the set of taxa with sequenced nuclear genomes. We explain why the fern clade is pivotal for understanding genome evolution across land plants, and we provide a rationale for how knowledge of fern genomes will enable progress in research beyond the ferns themselves. PMID:25324969

  5. Fungal Genomics Program

    Energy Technology Data Exchange (ETDEWEB)

    Grigoriev, Igor

    2012-03-12

    The JGI Fungal Genomics Program aims to scale up sequencing and analysis of fungal genomes to explore the diversity of fungi important for energy and the environment, and to promote functional studies on a system level. Combining new sequencing technologies and comparative genomics tools, JGI is now leading the world in fungal genome sequencing and analysis. Over 120 sequenced fungal genomes with analytical tools are available via MycoCosm (www.jgi.doe.gov/fungi), a web-portal for fungal biologists. Our model of interacting with user communities, unique among other sequencing centers, helps organize these communities, improves genome annotation and analysis work, and facilitates new larger-scale genomic projects. This resulted in 20 high-profile papers published in 2011 alone and contributing to the Genomics Encyclopedia of Fungi, which targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts). Our next grand challenges include larger scale exploration of fungal diversity (1000 fungal genomes), developing molecular tools for DOE-relevant model organisms, and analysis of complex systems and metagenomes.

  6. 大数据和物联网在国外城市治理中的前沿应用:公共价值促生的可操作化%Frontier Application of Big Data and IoT in Urban Governance of Other Countries:Operationalize of Public Value Facilitate

    Institute of Scientific and Technical Information of China (English)

    李一男

    2015-01-01

    城市的不断发展带来更高的复杂性和各方社会主体相互冲突的价值需求,对城市治理和公共决策形成新的挑战。借助大数据和物联网技术,智慧城市的兴起成为改善城市治理的有效手段。文章介绍并评析了城市治理研究的三个前沿领域,以及大数据和物联网技术的两个应用案例,在此基础上对我国发展智慧城市以提高城市治理水平,推进新型城镇化建设提出了具体建议。借助大数据和物联网技术,政府有能力识别核心公共价值,并对相互冲突的价值需求进行调解,进而将理论模型可操作化,在具体执行中实现公共价值的促生。%The continuous development of urbanization meets more complexity and conflicting value requirements from different social bodies.This is-sue becomes new challenge for urban governance and public decision.Taking technological advantages of big data and internet of things,the rises of smart city makes it possible to improve urban governance.In this paper I introduce and review three frontiers of urban governance research,and two cases of ap-plication for big data and IoT technologies.On this base I give detailed suggestions for the development of smart city in China,in order to improve urban governance and promote new round of urbanization.

  7. Programs | Office of Cancer Genomics

    Science.gov (United States)

    OCG facilitates cancer genomics research through a series of highly-focused programs. These programs generate and disseminate genomic data for use by the cancer research community. OCG programs also promote advances in technology-based infrastructure and create valuable experimental reagents and tools. OCG programs encourage collaboration by interconnecting with other genomics and cancer projects in order to accelerate translation of findings into the clinic. Below are OCG’s current, completed, and initiated programs:

  8. Facilitating functional annotation of chicken microarray data

    Directory of Open Access Journals (Sweden)

    Gresham Cathy R

    2009-10-01

    Full Text Available Abstract Background Modeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO. However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information. Results We have improved the breadth of functional annotations of the gene products associated with probesets on the Affymetrix chicken genome array by 45% and the quality of annotation by 14%. We have also identified the most significant diseases and disorders, different types of genes, and known drug targets represented on Affymetrix chicken genome array. To facilitate functional annotation of other arrays and microarray experimental datasets we developed an Array GO Mapper (AGOM tool to help researchers to quickly retrieve corresponding functional information for their dataset. Conclusion Results from this study will directly facilitate annotation of other chicken arrays and microarray experimental datasets. Researchers will be able to quickly model their microarray dataset into more reliable biological functional information by using AGOM tool. The disease, disorders, gene types and drug targets revealed in the study will allow researchers to learn more about how genes function in complex biological systems and may lead to new drug discovery and development of therapies. The GO annotation data generated will be available for public use via AgBase website and

  9. Evaluation of Operations Scenarios for Managing the Big Creek Marsh

    Science.gov (United States)

    Wilson, Ian; Rahman, Masihur; Wychreschuk, Jeremy; Lebedyk, Dan; Bolisetti, Tirupati

    2013-04-01

    Wetland management in changing climate is important for maintaining sustainable ecosystem as well as for reducing the impact of climate change on the environment as wetlands act as natural carbon sinks. The Big Creek Marsh within the Essex County is a Provincially Significant Wetland (PSW) in Ontario, Canada. The marsh is approximately 900 hectares in area and is primarily fed by streamflow from the Big Creek Watershed. The water level of this wetland has been managed by the stakeholders using a system of pumps, dykes and a controlled outlet to the Lake Erie. In order to adequately manage the Big Creek Marsh and conserve diverse aquatic plant species, Essex Region Conservation Authority (ERCA), Ontario has embarked on developing an Operations Plan to maintain desire water depths during different marsh phases, viz., Open water, Hemi and Overgrown marsh phases. The objective of the study is to evaluate the alternatives for managing water level of the Big Creek Marsh in different marsh phases. The Soil and Water Assessment Tool (SWAT), a continuous simulation model was used to simulate streamflow entering into the marsh from the Big Creek watershed. A Water Budget (WB) model was developed for the Big Creek Marsh to facilitate in operational management of the marsh. The WB model was applied to simulate the marsh level based on operations schedules, and available weather and hydrologic data aiming to attain the target water depths for the marsh phases. This paper presents the results of simulated and target water levels, streamflow entering into the marsh, water releasing from the marsh, and water pumping into and out of the marsh under different hydrologic conditions.

  10. Mindfulness for group facilitation

    DEFF Research Database (Denmark)

    Adriansen, Hanne Kirstine; Krohn, Simon

    2014-01-01

    In this paper, we argue that mindfulness techniques can be used for enhancing the outcome of group performance. The word mindfulness has different connotations in the academic literature. Broadly speaking there is ‘mindfulness without meditation’ or ‘Western’ mindfulness which involves active...... thinking and ‘Eastern’ mindfulness which refers to an open, accepting state of mind, as intended with Buddhist-inspired techniques such as meditation. In this paper, we are interested in the latter type of mindfulness and demonstrate how Eastern mindfulness techniques can be used as a tool for facilitation....... A brief introduction to the physiology and philosophy of Eastern mindfulness constitutes the basis for the arguments of the effect of mindfulness techniques. The use of mindfulness techniques for group facilitation is novel as it changes the focus from individuals’ mindfulness practice...

  11. Facilitating Learning at Conferences

    DEFF Research Database (Denmark)

    Ravn, Ib; Elsborg, Steen

    2011-01-01

    for learning, mutual inspiration and human flourishing. We offer five design principles that specify how conferences may engage participants more and hence increase their learning. In the research-and-development effort reported here, our team collaborated with conference organizers in Denmark to introduce...... and facilitate a variety of simple learning techniques at thirty one- and two-day conferences of up to 300 participants each. We present ten of these techniques and data evaluating them. We conclude that if conference organizers allocate a fraction of the total conference time to facilitated processes......The typical conference consists of a series of PowerPoint presentations that tend to render participants passive. Students of learning have long abandoned the transfer model that underlies such one-way communication. We propose an al-ternative theory of conferences that sees them as a forum...

  12. Facilitating Knowledge Sharing

    OpenAIRE

    Holdt Christensen, Peter

    2005-01-01

    Abstract This paper argues that knowledge sharing can be conceptualized as different situations of exchange in which individuals relate to each other in different ways, involving different rules, norms and traditions of reciprocity regulating the exchange. The main challenge for facilitating knowledge sharing is to ensure that the exchange is seen as equitable for the parties involved, and by viewing the problems of knowledge sharing as motivational problems situated in different organization...

  13. Big data for bipolar disorder.

    Science.gov (United States)

    Monteith, Scott; Glenn, Tasha; Geddes, John; Whybrow, Peter C; Bauer, Michael

    2016-12-01

    The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process.

  14. [Big data in official statistics].

    Science.gov (United States)

    Zwick, Markus

    2015-08-01

    The concept of "big data" stands to change the face of official statistics over the coming years, having an impact on almost all aspects of data production. The tasks of future statisticians will not necessarily be to produce new data, but rather to identify and make use of existing data to adequately describe social and economic phenomena. Until big data can be used correctly in official statistics, a lot of questions need to be answered and problems solved: the quality of data, data protection, privacy, and the sustainable availability are some of the more pressing issues to be addressed. The essential skills of official statisticians will undoubtedly change, and this implies a number of challenges to be faced by statistical education systems, in universities, and inside the statistical offices. The national statistical offices of the European Union have concluded a concrete strategy for exploring the possibilities of big data for official statistics, by means of the Big Data Roadmap and Action Plan 1.0. This is an important first step and will have a significant influence on implementing the concept of big data inside the statistical offices of Germany. PMID:26077871

  15. Big data for bipolar disorder.

    Science.gov (United States)

    Monteith, Scott; Glenn, Tasha; Geddes, John; Whybrow, Peter C; Bauer, Michael

    2016-12-01

    The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process. PMID:27068058

  16. Dual of Big-bang and Big-crunch

    OpenAIRE

    Bak, Dongsu

    2006-01-01

    Starting from the Janus solution and its gauge theory dual, we obtain the dual gauge theory description of the cosmological solution by procedure of the double anaytic continuation. The coupling is driven either to zero or to infinity at the big-bang and big-crunch singularities, which are shown to be related by the S-duality symmetry. In the dual Yang-Mills theory description, these are non singular at all as the coupling goes to zero in the N=4 Super Yang-Mills theory. The cosmological sing...

  17. The life cycle of a genome project: perspectives and guidelines inspired by insect genome projects

    OpenAIRE

    Alexie Papanicolaou

    2016-01-01

    Many research programs on non-model species biology have been empowered by genomics. In turn, genomics is underpinned by a reference sequence and ancillary information created by so-called “genome projects”. The most reliable genome projects are the ones created as part of an active research program and designed to address specific questions but their life extends past publication. In this opinion paper I outline four key insights that have facilitated maintaining genomic communities: the key...

  18. CLOUD COMPUTING WITH BIG DATA: A REVIEW

    OpenAIRE

    Anjali; Er. Amandeep Kaur; Mrs. Shakshi

    2016-01-01

    Big data is a collection of huge quantities of data. Big data is the process of examining large amounts of data. Big data and Cloud computing are the hot issues in Information Technology. Big data is the one of the main problem now a day’s. Researchers focusing how to handle huge amount of data with cloud computing and how to gain a perfect security for big data in cloud computing. To handle the Big Data problem Hadoop framework is used in which data is fragmented and executed parallel....

  19. 淀粉Big Bang!

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    Big Bang,也叫"大爆炸",指的是宇宙诞生时期从密度极大且温度极高的太初状态开始发生不断膨胀的过程。换句话说,从Big Bang开始,我们现在的宇宙慢慢形成了。0K,从本期开始,"少电"将在微博引发Big Bang!——淀粉大爆炸!具体怎么爆呢?我想,看到本页版式的你已经明白了七八分了吧?

  20. Multiwavelength astronomy and big data

    Science.gov (United States)

    Mickaelian, A. M.

    2016-09-01

    Two major characteristics of modern astronomy are multiwavelength (MW) studies (fromγ-ray to radio) and big data (data acquisition, storage and analysis). Present astronomical databases and archives contain billions of objects observed at various wavelengths, both galactic and extragalactic, and the vast amount of data on them allows new studies and discoveries. Astronomers deal with big numbers. Surveys are the main source for discovery of astronomical objects and accumulation of observational data for further analysis, interpretation, and achieving scientific results. We review the main characteristics of astronomical surveys, compare photographic and digital eras of astronomical studies (including the development of wide-field observations), describe the present state of MW surveys, and discuss the Big Data in astronomy and related topics of Virtual Observatories and Computational Astrophysics. The review includes many numbers and data that can be compared to have a possibly overall understanding on the Universe, cosmic numbers and their relationship to modern computational facilities.

  1. Expert and novice facilitated modelling

    DEFF Research Database (Denmark)

    Tavella, Elena; Papadopoulos, Thanos

    2015-01-01

    the behaviour of one expert and two novice facilitators during a Viable System Model workshop. The findings suggest common facilitation patterns in the behaviour of experts and novices. This contrasts literature claiming that experts and novices behave and use their available knowledge differently......This paper provides an empirical study based on action research in which expert and novice facilitators in facilitated modelling workshops are compared. There is limited empirical research analysing the differences between expert and novice facilitators. Aiming to address this gap we study...... and facilitation strategies in contexts in which external, expert facilitation is not always possible are also discussed, and limitations of this study are provided....

  2. A draft sequence of the rice(Oryza sativa ssp. indica) genome

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The sequence of the rice genome holds fundamental information for its biology, including physiology, genetics, development, and evolution, as well as information on many beneficial phenotypes of economic significance. Using a "whole genome shotgun" approach, we have produced a draft rice genome sequence of Oryza sativa ssp. indica, the major crop rice subspecies in China and many other regions of Asia. The draft genome sequence is constructed from over 4.3 million successful sequencing traces with an accumulative total length of 2214.9 Mb. The initial assembly of the non-redundant sequences reached 409.76 Mb in length, based on 3.30 million successful sequencing traces with a total length of 1797.4 Mb from an indica variant cultivar 93-11, giving an estimated coverage of 95.29% of the rice genome with an average base accuracy of higher than 99%. The coverage of the draft sequence, the randomness of the sequence distribution, and the consistency of BIG-ASSEM- BLER, a custom-designed software package used for the initial assembly, were verified rigorously by comparisons against finished BAC clone sequences from both indica and japanica strains, available from the public databases. Over all, 96.3% of full-length cDNAs, 96.4% of STS, STR, RFLP markers, 94.0% of ESTs and 94.9% unigene clusters were identified from the draft sequence. Our preliminary analysis on the data set shows that our rice draft sequence is consistent with the comman standard accepted by the genome sequencing community. The unconditional release of the draft to the public also undoubtedly provides a fundamental resource to the international scientific communities to facilitate genomic and genetic studies on rice biology.

  3. Facilitation as a teaching strategy : experiences of facilitators.

    Science.gov (United States)

    Lekalakala-Mokgele, E

    2006-08-01

    Changes in nursing education involve the move from traditional teaching approaches that are teacher-centred to facilitation, a student centred approach. The student-centred approach is based on a philosophy of teaching and learning that puts the learner on centre-stage. The aim of this study was to identify the challenges of facilitators of learning using facilitation as a teaching method and recommend strategies for their (facilitators) development and support. A qualitative, explorative and contextual design was used. Four (4) universities in South Africa which utilize facilitation as a teaching/ learning process were identified and the facilitators were selected to be the sample of the study. The main question posed during in-depth group interviews was: How do you experience facilitation as a teaching/learning method?. Facilitators indicated different experiences and emotions when they first had to facilitate learning. All of them indicated that it was difficult to facilitate at the beginning as they were trained to lecture and that no format for facilitation was available. They experienced frustrations and anxieties as a result. The lack of knowledge of facilitation instilled fear in them. However they indicated that facilitation had many benefits for them and for the students. Amongst the ones mentioned were personal and professional growth. Challenges mentioned were the fear that they waste time and that they do not cover the content. It is therefore important that facilitation be included in the training of nurse educators. PMID:17131610

  4. Facilitation as a teaching strategy : experiences of facilitators

    Directory of Open Access Journals (Sweden)

    E Lekalakala-Mokgele

    2006-09-01

    Full Text Available Changes in nursing education involve the move from traditional teaching approaches that are teacher-centred to facilitation, a student centred approach. The studentcentred approach is based on a philosophy of teaching and learning that puts the learner on centre-stage. The aim of this study was to identify the challenges of facilitators of learning using facilitation as a teaching method and recommend strategies for their (facilitators development and support. A qualitative, explorative and contextual design was used. Four (4 universities in South Africa which utilize facilitation as a teaching/ learning process were identified and the facilitators were selected to be the sample of the study. The main question posed during in-depth group interviews was: How do you experience facilitation as a teaching/learning method?. Facilitators indicated different experiences and emotions when they first had to facilitate learning. All of them indicated that it was difficult to facilitate at the beginning as they were trained to lecture and that no format for facilitation was available. They experienced frustrations and anxieties as a result. The lack of knowledge of facilitation instilled fear in them. However they indicated that facilitation had many benefits for them and for the students. Amongst the ones mentioned were personal and professional growth. Challenges mentioned were the fear that they waste time and that they do not cover the content. It is therefore important that facilitation be included in the training of nurse educators.

  5. Sosiaalinen asiakassuhdejohtaminen ja big data

    OpenAIRE

    Toivonen, Topi-Antti

    2015-01-01

    Tässä tutkielmassa käsitellään sosiaalista asiakassuhdejohtamista sekä hyötyjä, joita siihen voidaan saada big datan avulla. Sosiaalinen asiakassuhdejohtaminen on terminä uusi ja monille tuntematon. Tutkimusta motivoi aiheen vähäinen tutkimus, suomenkielisen tutkimuksen puuttuminen kokonaan sekä sosiaalisen asiakassuhdejohtamisen mahdollinen olennainen rooli yritysten toiminnassa tulevaisuudessa. Big dataa käsittelevissä tutkimuksissa keskitytään monesti sen tekniseen puoleen, eikä sovellutuk...

  6. [Big Data- challenges and risks].

    Science.gov (United States)

    Krauß, Manuela; Tóth, Tamás; Hanika, Heinrich; Kozlovszky, Miklós; Dinya, Elek

    2015-12-01

    The term "Big Data" is commonly used to describe the growing mass of information being created recently. New conclusions can be drawn and new services can be developed by the connection, processing and analysis of these information. This affects all aspects of life, including health and medicine. The authors review the application areas of Big Data, and present examples from health and other areas. However, there are several preconditions of the effective use of the opportunities: proper infrastructure, well defined regulatory environment with particular emphasis on data protection and privacy. These issues and the current actions for solution are also presented. PMID:26614539

  7. Towards a big crunch dual

    Energy Technology Data Exchange (ETDEWEB)

    Hertog, Thomas E-mail: hertog@vulcan2.physics.ucsb.edu; Horowitz, Gary T

    2004-07-01

    We show there exist smooth asymptotically anti-de Sitter initial data which evolve to a big crunch singularity in a low energy supergravity limit of string theory. This opens up the possibility of using the dual conformal field theory to obtain a fully quantum description of the cosmological singularity. A preliminary study of this dual theory suggests that the big crunch is an endpoint of evolution even in the full string theory. We also show that any theory with scalar solitons must have negative energy solutions. The results presented here clarify our earlier work on cosmic censorship violation in N=8 supergravity. (author)

  8. Release plan for Big Pete

    International Nuclear Information System (INIS)

    This release plan is to provide instructions for the Radiological Control Technician (RCT) to conduct surveys for the unconditional release of ''Big Pete,'' which was used in the removal of ''Spacers'' from the N-Reactor. Prior to performing surveys on the rear end portion of ''Big Pete,'' it shall be cleaned (i.e., free of oil, grease, caked soil, heavy dust). If no contamination is found, the vehicle may be released with the permission of the area RCT Supervisor. If contamination is found by any of the surveys, contact the cognizant Radiological Engineer for decontamination instructions

  9. The BigBOSS Experiment

    OpenAIRE

    Schlegel, D.; Abdalla, F.; Abraham, T.; Ahn, C.; Prieto, C. Allende; Annis, J.; Aubourg, E.; Azzaro, M.; Baltay, S. Bailey. C.; Baugh, C.; Bebek, C.; Becerril, S.; Blanton, M.; Bolton, A.; Bromley, B.

    2011-01-01

    BigBOSS is a Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with a wide-area galaxy and quasar redshift survey over 14,000 square degrees. It has been conditionally accepted by NOAO in response to a call for major new instrumentation and a high-impact science program for the 4-m Mayall telescope at Kitt Peak. The BigBOSS instrument is a robotically-actuated, fiber-fed spectrograph capable of taking 5000 simultaneous spectra...

  10. [Big Data- challenges and risks].

    Science.gov (United States)

    Krauß, Manuela; Tóth, Tamás; Hanika, Heinrich; Kozlovszky, Miklós; Dinya, Elek

    2015-12-01

    The term "Big Data" is commonly used to describe the growing mass of information being created recently. New conclusions can be drawn and new services can be developed by the connection, processing and analysis of these information. This affects all aspects of life, including health and medicine. The authors review the application areas of Big Data, and present examples from health and other areas. However, there are several preconditions of the effective use of the opportunities: proper infrastructure, well defined regulatory environment with particular emphasis on data protection and privacy. These issues and the current actions for solution are also presented.

  11. Big society, big data. The radicalisation of the network society

    NARCIS (Netherlands)

    Frissen, V.

    2011-01-01

    During the British election campaign of 2010, David Cameron produced the idea of the ‘Big Society’ as a cornerstone of his political agenda. At the core of the idea is a stronger civil society and local community coupled with a more withdrawn government. Although many commentators have dismissed thi

  12. Essence: Facilitating Software Innovation

    DEFF Research Database (Denmark)

    Aaen, Ivan

    2008-01-01

      This paper suggests ways to facilitate creativity and innovation in software development. The paper applies four perspectives – Product, Project, Process, and People –to identify an outlook for software innovation. The paper then describes a new facility–Software Innovation Research Lab (SIRL......) – and a new method concept for software innovation – Essence – based on views, modes, and team roles. Finally, the paper reports from an early experiment using SIRL and Essence and identifies further research....

  13. Development of Self-Compressing BLSOM for Comprehensive Analysis of Big Sequence Data

    Directory of Open Access Journals (Sweden)

    Akihito Kikuchi

    2015-01-01

    Full Text Available With the remarkable increase in genomic sequence data from various organisms, novel tools are needed for comprehensive analyses of available big sequence data. We previously developed a Batch-Learning Self-Organizing Map (BLSOM, which can cluster genomic fragment sequences according to phylotype solely dependent on oligonucleotide composition and applied to genome and metagenomic studies. BLSOM is suitable for high-performance parallel-computing and can analyze big data simultaneously, but a large-scale BLSOM needs a large computational resource. We have developed Self-Compressing BLSOM (SC-BLSOM for reduction of computation time, which allows us to carry out comprehensive analysis of big sequence data without the use of high-performance supercomputers. The strategy of SC-BLSOM is to hierarchically construct BLSOMs according to data class, such as phylotype. The first-layer BLSOM was constructed with each of the divided input data pieces that represents the data subclass, such as phylotype division, resulting in compression of the number of data pieces. The second BLSOM was constructed with a total of weight vectors obtained in the first-layer BLSOMs. We compared SC-BLSOM with the conventional BLSOM by analyzing bacterial genome sequences. SC-BLSOM could be constructed faster than BLSOM and cluster the sequences according to phylotype with high accuracy, showing the method’s suitability for efficient knowledge discovery from big sequence data.

  14. Pillow seal system at the BigRIPS separator

    Science.gov (United States)

    Tanaka, K.; Inabe, N.; Yoshida, K.; Kusaka, K.; Kubo, T.

    2013-12-01

    We have designed and installed a pillow seal system for the BigRIPS fragment separator at the RIKEN Radioactive Isotope Beam Factory (RIBF) to facilitate remote maintenance in a radioactive environment. The pillow seal system is a device to connect a vacuum chamber and a beam tube. It allows quick attachment and detachment of vacuum connections in the BigRIPS separator and consists of a double diaphragm with a differential pumping system. The leakage rate achieved with this system is as low as 10-9 Pa m3/s. We have also designed and installed a local radiation-shielding system, integrated with the pillow seal system, to protect the superconducting magnets and to reduce the heat load on the cryogenic system. We present an overview of the pillow seal and the local shielding systems.

  15. Parkinson’s Brain Disease Prediction Using Big Data Analytics

    Directory of Open Access Journals (Sweden)

    N. Shamli

    2016-06-01

    Full Text Available In healthcare industries, the demand for maintaining large amount of patients’ data is steadily growing due to rising population which has resulted in the increase of details about clinical and laboratory tests, imaging, prescription and medication. These data can be called “Big Data”, because of their size, complexity and diversity. Big data analytics aims at improving patient care and identifying preventive measures proactively. To save lives and recommend life style changes for a peaceful and healthier life at low costs. The proposed predictive analytics framework is a combination of Decision Tree, Support Vector Machine and Artificial Neural Network which is used to gain insights from patients. Parkinson’s disease voice dataset from UCI Machine learning repository is used as input. The experimental results show that early detection of disease will facilitate clinical monitoring of elderly people and increase the chances of their life span and improved lifestyle to lead peaceful life.

  16. A short story about a big magic bug.

    Science.gov (United States)

    Bunk, Boyke; Schulz, Arne; Stammen, Simon; Münch, Richard; Warren, Martin J; Rohde, Manfred; Jahn, Dieter; Biedendieck, Rebekka

    2010-01-01

    Bacillus megaterium, the "big beast," is a Gram-positive bacterium with a size of 4 × 1.5 µm. During the last years, it became more and more popular in the field of biotechnology for its recombinant protein production capacity. For the purpose of intra- as well as extracellular protein synthesis several vectors were constructed and commercialized (MoBiTec GmbH, Germany). On the basis of two compatible vectors, a T7 RNA polymerase driven protein production system was established. Vectors for chromosomal integration enable the direct manipulation of the genome. The vitamin B(12) biosynthesis of B. megaterium served as a model for the systematic development of a production strain using these tools. For this purpose, the overexpression of chromosomal and plasmid encoded genes and operons, the synthesis of anti-sense RNA for gene silencing, the removal of inhibitory regulatory elements in combination with the utilization of strong promoters, directed protein design, and the recombinant production of B(12) binding proteins to overcome feedback inhibition were successfully employed. For further system biotechnology based optimization strategies the genome sequence will provide a closer look into genomic capacities of B. megaterium. DNA arrays are available. Proteome, fluxome and metabolome analyses are possible. All data can be integrated by using a novel bioinformatics platform. Finally, the size of the "big beast" B. megaterium invites for cell biology research projects. All these features provide a solid basis for challenging biotechnological approaches.

  17. The Uses of Big Data in Cities.

    Science.gov (United States)

    Bettencourt, Luís M A

    2014-03-01

    There is much enthusiasm currently about the possibilities created by new and more extensive sources of data to better understand and manage cities. Here, I explore how big data can be useful in urban planning by formalizing the planning process as a general computational problem. I show that, under general conditions, new sources of data coordinated with urban policy can be applied following fundamental principles of engineering to achieve new solutions to important age-old urban problems. I also show that comprehensive urban planning is computationally intractable (i.e., practically impossible) in large cities, regardless of the amounts of data available. This dilemma between the need for planning and coordination and its impossibility in detail is resolved by the recognition that cities are first and foremost self-organizing social networks embedded in space and enabled by urban infrastructure and services. As such, the primary role of big data in cities is to facilitate information flows and mechanisms of learning and coordination by heterogeneous individuals. However, processes of self-organization in cities, as well as of service improvement and expansion, must rely on general principles that enforce necessary conditions for cities to operate and evolve. Such ideas are the core of a developing scientific theory of cities, which is itself enabled by the growing availability of quantitative data on thousands of cities worldwide, across different geographies and levels of development. These three uses of data and information technologies in cities constitute then the necessary pillars for more successful urban policy and management that encourages, and does not stifle, the fundamental role of cities as engines of development and innovation in human societies.

  18. The Natural Science Underlying Big History

    Directory of Open Access Journals (Sweden)

    Eric J. Chaisson

    2014-01-01

    Full Text Available Nature’s many varied complex systems—including galaxies, stars, planets, life, and society—are islands of order within the increasingly disordered Universe. All organized systems are subject to physical, biological, or cultural evolution, which together comprise the grander interdisciplinary subject of cosmic evolution. A wealth of observational data supports the hypothesis that increasingly complex systems evolve unceasingly, uncaringly, and unpredictably from big bang to humankind. These are global history greatly extended, big history with a scientific basis, and natural history broadly portrayed across ∼14 billion years of time. Human beings and our cultural inventions are not special, unique, or apart from Nature; rather, we are an integral part of a universal evolutionary process connecting all such complex systems throughout space and time. Such evolution writ large has significant potential to unify the natural sciences into a holistic understanding of who we are and whence we came. No new science (beyond frontier, nonequilibrium thermodynamics is needed to describe cosmic evolution’s major milestones at a deep and empirical level. Quantitative models and experimental tests imply that a remarkable simplicity underlies the emergence and growth of complexity for a wide spectrum of known and diverse systems. Energy is a principal facilitator of the rising complexity of ordered systems within the expanding Universe; energy flows are as central to life and society as they are to stars and galaxies. In particular, energy rate density—contrasting with information content or entropy production—is an objective metric suitable to gauge relative degrees of complexity among a hierarchy of widely assorted systems observed throughout the material Universe. Operationally, those systems capable of utilizing optimum amounts of energy tend to survive, and those that cannot are nonrandomly eliminated.

  19. Characterizing and Subsetting Big Data Workloads

    OpenAIRE

    Jia, Zhen; Zhan, Jianfeng; Wang, Lei; Han, Rui; Mckee, Sally A.; Yang, Qiang; Luo, Chunjie; Li, Jingwei

    2014-01-01

    Big data benchmark suites must include a diversity of data and workloads to be useful in fairly evaluating big data systems and architectures. However, using truly comprehensive benchmarks poses great challenges for the architecture community. First, we need to thoroughly understand the behaviors of a variety of workloads. Second, our usual simulation-based research methods become prohibitively expensive for big data. As big data is an emerging field, more and more software stacks are being p...

  20. BIG DATA IN BUSINESS ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Logica BANICA

    2015-06-01

    Full Text Available In recent years, dealing with a lot of data originating from social media sites and mobile communications among data from business environments and institutions, lead to the definition of a new concept, known as Big Data. The economic impact of the sheer amount of data produced in a last two years has increased rapidly. It is necessary to aggregate all types of data (structured and unstructured in order to improve current transactions, to develop new business models, to provide a real image of the supply and demand and thereby, generate market advantages. So, the companies that turn to Big Data have a competitive advantage over other firms. Looking from the perspective of IT organizations, they must accommodate the storage and processing Big Data, and provide analysis tools that are easily integrated into business processes. This paper aims to discuss aspects regarding the Big Data concept, the principles to build, organize and analyse huge datasets in the business environment, offering a three-layer architecture, based on actual software solutions. Also, the article refers to the graphical tools for exploring and representing unstructured data, Gephi and NodeXL.

  1. Big data and urban governance

    NARCIS (Netherlands)

    L. Taylor; C. Richter

    2015-01-01

    This chapter examines the ways in which big data is involved in the rise of smart cities. Mobile phones, sensors and online applications produce streams of data which are used to regulate and plan the city, often in real time, but which presents challenges as to how the city’s functions are seen and

  2. Do big gods cause anything?

    DEFF Research Database (Denmark)

    Geertz, Armin W.

    2014-01-01

    Dette er et bidrag til et review symposium vedrørende Ara Norenzayans bog Big Gods: How Religion Transformed Cooperation and Conflict (Princeton University Press 2013). Bogen er spændende men problematisk i forhold til kausalitet, ateisme og stereotyper om jægere-samlere....

  3. China: Big Changes Coming Soon

    Science.gov (United States)

    Rowen, Henry S.

    2011-01-01

    Big changes are ahead for China, probably abrupt ones. The economy has grown so rapidly for many years, over 30 years at an average of nine percent a year, that its size makes it a major player in trade and finance and increasingly in political and military matters. This growth is not only of great importance internationally, it is already having…

  4. YOUNG CITY,BIG PARTY

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Shenzhen Universiade unites the world’s young people through sports with none of the usual hoop-la, no fireworks, no grand performances by celebrities and superstars, the Shenzhen Summer Universiade lowered the curtain on a big party for youth and college students on August 23.

  5. 1976 Big Thompson flood, Colorado

    Science.gov (United States)

    Jarrett, R. D.; Vandas, S.J.

    2006-01-01

    In the early evening of July 31, 1976, a large stationary thunderstorm released as much as 7.5 inches of rainfall in about an hour (about 12 inches in a few hours) in the upper reaches of the Big Thompson River drainage. This large amount of rainfall in such a short period of time produced a flash flood that caught residents and tourists by surprise. The immense volume of water that churned down the narrow Big Thompson Canyon scoured the river channel and destroyed everything in its path, including 418 homes, 52 businesses, numerous bridges, paved and unpaved roads, power and telephone lines, and many other structures. The tragedy claimed the lives of 144 people. Scores of other people narrowly escaped with their lives. The Big Thompson flood ranks among the deadliest of Colorado's recorded floods. It is one of several destructive floods in the United States that has shown the necessity of conducting research to determine the causes and effects of floods. The U.S. Geological Survey (USGS) conducts research and operates a Nationwide streamgage network to help understand and predict the magnitude and likelihood of large streamflow events such as the Big Thompson Flood. Such research and streamgage information are part of an ongoing USGS effort to reduce flood hazards and to increase public awareness.

  6. The Big European Bubble Chamber

    CERN Document Server

    1977-01-01

    The 3.70 metre Big European Bubble Chamber (BEBC), dismantled on 9 August 1984. During operation it was one of the biggest detectors in the world, producing direct visual recordings of particle tracks. 6.3 million photos of interactions were taken with the chamber in the course of its existence.

  7. Big data e data science

    OpenAIRE

    Cavique, Luís

    2014-01-01

    Neste artigo foram apresentados os conceitos básicos de Big Data e a nova área a que deu origem, a Data Science. Em Data Science foi discutida e exemplificada a noção de redução da dimensionalidade dos dados.

  8. The BigBoss Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Schelgel, D.; Abdalla, F.; Abraham, T.; Ahn, C.; Allende Prieto, C.; Annis, J.; Aubourg, E.; Azzaro, M.; Bailey, S.; Baltay, C.; Baugh, C.; Bebek, C.; Becerril, S.; Blanton, M.; Bolton, A.; Bromley, B.; Cahn, R.; Carton, P.-H.; Cervanted-Cota, J.L.; Chu, Y.; Cortes, M.; /APC, Paris /Brookhaven /IRFU, Saclay /Marseille, CPPM /Marseille, CPT /Durham U. / /IEU, Seoul /Fermilab /IAA, Granada /IAC, La Laguna / /IAC, Mexico / / /Madrid, IFT /Marseille, Lab. Astrophys. / / /New York U. /Valencia U.

    2012-06-07

    BigBOSS is a Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with a wide-area galaxy and quasar redshift survey over 14,000 square degrees. It has been conditionally accepted by NOAO in response to a call for major new instrumentation and a high-impact science program for the 4-m Mayall telescope at Kitt Peak. The BigBOSS instrument is a robotically-actuated, fiber-fed spectrograph capable of taking 5000 simultaneous spectra over a wavelength range from 340 nm to 1060 nm, with a resolution R = {lambda}/{Delta}{lambda} = 3000-4800. Using data from imaging surveys that are already underway, spectroscopic targets are selected that trace the underlying dark matter distribution. In particular, targets include luminous red galaxies (LRGs) up to z = 1.0, extending the BOSS LRG survey in both redshift and survey area. To probe the universe out to even higher redshift, BigBOSS will target bright [OII] emission line galaxies (ELGs) up to z = 1.7. In total, 20 million galaxy redshifts are obtained to measure the BAO feature, trace the matter power spectrum at smaller scales, and detect redshift space distortions. BigBOSS will provide additional constraints on early dark energy and on the curvature of the universe by measuring the Ly-alpha forest in the spectra of over 600,000 2.2 < z < 3.5 quasars. BigBOSS galaxy BAO measurements combined with an analysis of the broadband power, including the Ly-alpha forest in BigBOSS quasar spectra, achieves a FOM of 395 with Planck plus Stage III priors. This FOM is based on conservative assumptions for the analysis of broad band power (k{sub max} = 0.15), and could grow to over 600 if current work allows us to push the analysis to higher wave numbers (k{sub max} = 0.3). BigBOSS will also place constraints on theories of modified gravity and inflation, and will measure the sum of neutrino masses to 0.024 eV accuracy.

  9. Data, Data, Data : Big, Linked & Open

    NARCIS (Netherlands)

    Folmer, E.J.A.; Krukkert, D.; Eckartz, S.M.

    2013-01-01

    De gehele business en IT-wereld praat op dit moment over Big Data, een trend die medio 2013 Cloud Computing is gepasseerd (op basis van Google Trends). Ook beleidsmakers houden zich actief bezig met Big Data. Neelie Kroes, vice-president van de Europese Commissie, spreekt over de ‘Big Data Revolutio

  10. A SWOT Analysis of Big Data

    Science.gov (United States)

    Ahmadi, Mohammad; Dileepan, Parthasarati; Wheatley, Kathleen K.

    2016-01-01

    This is the decade of data analytics and big data, but not everyone agrees with the definition of big data. Some researchers see it as the future of data analysis, while others consider it as hype and foresee its demise in the near future. No matter how it is defined, big data for the time being is having its glory moment. The most important…

  11. Big Data: Implications for Health System Pharmacy.

    Science.gov (United States)

    Stokes, Laura B; Rogers, Joseph W; Hertig, John B; Weber, Robert J

    2016-07-01

    Big Data refers to datasets that are so large and complex that traditional methods and hardware for collecting, sharing, and analyzing them are not possible. Big Data that is accurate leads to more confident decision making, improved operational efficiency, and reduced costs. The rapid growth of health care information results in Big Data around health services, treatments, and outcomes, and Big Data can be used to analyze the benefit of health system pharmacy services. The goal of this article is to provide a perspective on how Big Data can be applied to health system pharmacy. It will define Big Data, describe the impact of Big Data on population health, review specific implications of Big Data in health system pharmacy, and describe an approach for pharmacy leaders to effectively use Big Data. A few strategies involved in managing Big Data in health system pharmacy include identifying potential opportunities for Big Data, prioritizing those opportunities, protecting privacy concerns, promoting data transparency, and communicating outcomes. As health care information expands in its content and becomes more integrated, Big Data can enhance the development of patient-centered pharmacy services.

  12. "Big Data" - Grosse Daten, viel Wissen?

    OpenAIRE

    Hothorn, Torsten

    2015-01-01

    Since a couple of years, the term Big Data describes technologies to extract knowledge from data. Applications of Big Data and their consequences are also increasingly discussed in the mass media. Because medicine is an empirical science, we discuss the meaning of Big Data and its potential for future medical research.

  13. Big Data: Implications for Health System Pharmacy.

    Science.gov (United States)

    Stokes, Laura B; Rogers, Joseph W; Hertig, John B; Weber, Robert J

    2016-07-01

    Big Data refers to datasets that are so large and complex that traditional methods and hardware for collecting, sharing, and analyzing them are not possible. Big Data that is accurate leads to more confident decision making, improved operational efficiency, and reduced costs. The rapid growth of health care information results in Big Data around health services, treatments, and outcomes, and Big Data can be used to analyze the benefit of health system pharmacy services. The goal of this article is to provide a perspective on how Big Data can be applied to health system pharmacy. It will define Big Data, describe the impact of Big Data on population health, review specific implications of Big Data in health system pharmacy, and describe an approach for pharmacy leaders to effectively use Big Data. A few strategies involved in managing Big Data in health system pharmacy include identifying potential opportunities for Big Data, prioritizing those opportunities, protecting privacy concerns, promoting data transparency, and communicating outcomes. As health care information expands in its content and becomes more integrated, Big Data can enhance the development of patient-centered pharmacy services. PMID:27559194

  14. The BigBoss Experiment

    International Nuclear Information System (INIS)

    BigBOSS is a Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with a wide-area galaxy and quasar redshift survey over 14,000 square degrees. It has been conditionally accepted by NOAO in response to a call for major new instrumentation and a high-impact science program for the 4-m Mayall telescope at Kitt Peak. The BigBOSS instrument is a robotically-actuated, fiber-fed spectrograph capable of taking 5000 simultaneous spectra over a wavelength range from 340 nm to 1060 nm, with a resolution R = λ/Δλ = 3000-4800. Using data from imaging surveys that are already underway, spectroscopic targets are selected that trace the underlying dark matter distribution. In particular, targets include luminous red galaxies (LRGs) up to z = 1.0, extending the BOSS LRG survey in both redshift and survey area. To probe the universe out to even higher redshift, BigBOSS will target bright [OII] emission line galaxies (ELGs) up to z = 1.7. In total, 20 million galaxy redshifts are obtained to measure the BAO feature, trace the matter power spectrum at smaller scales, and detect redshift space distortions. BigBOSS will provide additional constraints on early dark energy and on the curvature of the universe by measuring the Ly-alpha forest in the spectra of over 600,000 2.2 max = 0.15), and could grow to over 600 if current work allows us to push the analysis to higher wave numbers (kmax = 0.3). BigBOSS will also place constraints on theories of modified gravity and inflation, and will measure the sum of neutrino masses to 0.024 eV accuracy.

  15. Facilitating Knowledge Sharing

    DEFF Research Database (Denmark)

    Holdt Christensen, Peter

    knowledge sharing is to ensure that the exchange is seen as equitable for the parties involved, and by viewing the problems of knowledge sharing as motivational problems situated in different organizational settings, the paper explores how knowledge exchange can be conceptualized as going on in four...... distinct situations of exchange denominated organizational exchange yielding extrinsic rewards, organizational exchange yielding intrinsic rewards, financial exchange, and social exchange. The paper argues that each situation of exchange has distinct assumptions about individual behaviour...... and the intermediaries regulating the exchange, and facilitating knowledge sharing should therefore be viewed as a continuum of practices under the influence of opportunistic behaviour, obedience or organizational citizenship behaviour. Keywords: Knowledge sharing, motivation, organizational settings, situations...

  16. Global Fluctuation Spectra in Big Crunch/Big Bang String Vacua

    OpenAIRE

    Craps, Ben; Ovrut, Burt A.

    2003-01-01

    We study Big Crunch/Big Bang cosmologies that correspond to exact world-sheet superconformal field theories of type II strings. The string theory spacetime contains a Big Crunch and a Big Bang cosmology, as well as additional ``whisker'' asymptotic and intermediate regions. Within the context of free string theory, we compute, unambiguously, the scalar fluctuation spectrum in all regions of spacetime. Generically, the Big Crunch fluctuation spectrum is altered while passing through the bounce...

  17. Big Bang Day : The Great Big Particle Adventure - 3. Origins

    CERN Multimedia

    2008-01-01

    In this series, comedian and physicist Ben Miller asks the CERN scientists what they hope to find. If the LHC is successful, it will explain the nature of the Universe around us in terms of a few simple ingredients and a few simple rules. But the Universe now was forged in a Big Bang where conditions were very different, and the rules were very different, and those early moments were crucial to determining how things turned out later. At the LHC they can recreate conditions as they were billionths of a second after the Big Bang, before atoms and nuclei existed. They can find out why matter and antimatter didn't mutually annihilate each other to leave behind a Universe of pure, brilliant light. And they can look into the very structure of space and time - the fabric of the Universe

  18. Antigravity and the big crunch/big bang transition

    Energy Technology Data Exchange (ETDEWEB)

    Bars, Itzhak [Department of Physics and Astronomy, University of Southern California, Los Angeles, CA 90089-2535 (United States); Chen, Shih-Hung [Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 (Canada); Department of Physics and School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287-1404 (United States); Steinhardt, Paul J., E-mail: steinh@princeton.edu [Department of Physics and Princeton Center for Theoretical Physics, Princeton University, Princeton, NJ 08544 (United States); Turok, Neil [Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 (Canada)

    2012-08-29

    We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

  19. Antigravity and the big crunch/big bang transition

    Science.gov (United States)

    Bars, Itzhak; Chen, Shih-Hung; Steinhardt, Paul J.; Turok, Neil

    2012-08-01

    We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

  20. Antigravity and the big crunch/big bang transition

    CERN Document Server

    Bars, Itzhak; Steinhardt, Paul J; Turok, Neil

    2011-01-01

    We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

  1. Perspectives on Big Data and Big Data Analytics

    Directory of Open Access Journals (Sweden)

    Elena Geanina ULARU

    2012-12-01

    Full Text Available Nowadays companies are starting to realize the importance of using more data in order to support decision for their strategies. It was said and proved through study cases that “More data usually beats better algorithms”. With this statement companies started to realize that they can chose to invest more in processing larger sets of data rather than investing in expensive algorithms. The large quantity of data is better used as a whole because of the possible correlations on a larger amount, correlations that can never be found if the data is analyzed on separate sets or on a smaller set. A larger amount of data gives a better output but also working with it can become a challenge due to processing limitations. This article intends to define the concept of Big Data and stress the importance of Big Data Analytics.

  2. Web Science Big Wins: Information Big Bang & Fundamental Constants

    OpenAIRE

    Carr, Les

    2010-01-01

    We take for granted a Web that provides free and unrestricted information exchange, but the Web is under pressure to change in order to respond to issues of security, commerce, criminality, privacy. Web Science needs to explain how the Web impacts society and predict the outcomes of proposed changes to Web infrastructure on business and society. Using the analogy of the Big Bang, this presentation describes how the Web spread the conditions of its initial creation throughout the whole of soci...

  3. Nástroje pro Big Data Analytics

    OpenAIRE

    Miloš, Marek

    2013-01-01

    The thesis covers the term for specific data analysis called Big Data. The thesis firstly defines the term Big Data and the need for its creation because of the rising need for deeper data processing and analysis tools and methods. The thesis also covers some of the technical aspects of Big Data tools, focusing on Apache Hadoop in detail. The later chapters contain Big Data market analysis and describe the biggest Big Data competitors and tools. The practical part of the thesis presents a way...

  4. ISSUES, CHALLENGES, AND SOLUTIONS: BIG DATA MINING

    Directory of Open Access Journals (Sweden)

    Jaseena K.U.

    2014-12-01

    Full Text Available Data has become an indispensable part of every economy, industry, organization, business function and individual. Big Data is a term used to identify the datasets that whose size is beyond the ability of typical database software tools to store, manage and analyze. The Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This paper presents the literature review about the Big data Mining and the issues and challenges with emphasis on the distinguished features of Big Data. It also discusses some methods to deal with big data.

  5. AN AI PLANNING APPROACH FOR GENERATING BIG DATA WORKFLOWS

    Directory of Open Access Journals (Sweden)

    Wesley Deneke

    2015-09-01

    Full Text Available The scale of big data causes the compositions of extract-transform-load (ETL workflows to grow increasingly complex. With the turnaround time for delivering solutions becoming a greater emphasis, stakeholders cannot continue to afford to wait the hundreds of hours it takes for domain experts to manually compose a workflow solution. This paper describes a novel AI planning approach that facilitates rapid composition and maintenance of ETL workflows. The workflow engine is evaluated on real-world scenarios from an industrial partner and results gathered from a prototype are reported to demonstrate the validity of the approach.

  6. Big data is not a monolith

    CERN Document Server

    Sugimoto, Cassidy R; Mattioli, Michael

    2016-01-01

    Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies. The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control throu...

  7. Personal Spaces in Public Repositories as a Facilitator for Open Educational Resource Usage

    Science.gov (United States)

    Cohen, Anat; Reisman, Sorel; Sperling, Barbra Bied

    2015-01-01

    Learning object repositories are a shared, open and public space; however, the possibility and ability of personal expression in an open, global, public space is crucial. The aim of this study is to explore personal spaces in a big learning object repository as a facilitator for adoption of Open Educational Resources (OER) into teaching practices…

  8. Facilitating post traumatic growth

    Science.gov (United States)

    Turner, de Sales; Cox, Helen

    2004-01-01

    Background Whilst negative responses to traumatic injury have been well documented in the literature, there is a small but growing body of work that identifies posttraumatic growth as a salient feature of this experience. We contribute to this discourse by reporting on the experiences of 13 individuals who were traumatically injured, had undergone extensive rehabilitation and were discharged from formal care. All participants were injured through involvement in a motor vehicle accident, with the exception of one, who was injured through falling off the roof of a house. Methods In this qualitative study, we used an audio-taped in-depth interview with each participant as the means of data collection. Interviews were transcribed verbatim and analysed thematically to determine the participants' unique perspectives on the experience of recovery from traumatic injury. In reporting the findings, all participants' were given a pseudonym to assure their anonymity. Results Most participants indicated that their involvement in a traumatic occurrence was a springboard for growth that enabled them to develop new perspectives on life and living. Conclusion There are a number of contributions that health providers may make to the recovery of individuals who have been traumatically injured to assist them to develop new views of vulnerability and strength, make changes in relationships, and facilitate philosophical, physical and spiritual growth. PMID:15248894

  9. Facilitating post traumatic growth

    Directory of Open Access Journals (Sweden)

    Cox Helen

    2004-07-01

    Full Text Available Abstract Background Whilst negative responses to traumatic injury have been well documented in the literature, there is a small but growing body of work that identifies posttraumatic growth as a salient feature of this experience. We contribute to this discourse by reporting on the experiences of 13 individuals who were traumatically injured, had undergone extensive rehabilitation and were discharged from formal care. All participants were injured through involvement in a motor vehicle accident, with the exception of one, who was injured through falling off the roof of a house. Methods In this qualitative study, we used an audio-taped in-depth interview with each participant as the means of data collection. Interviews were transcribed verbatim and analysed thematically to determine the participants' unique perspectives on the experience of recovery from traumatic injury. In reporting the findings, all participants' were given a pseudonym to assure their anonymity. Results Most participants indicated that their involvement in a traumatic occurrence was a springboard for growth that enabled them to develop new perspectives on life and living. Conclusion There are a number of contributions that health providers may make to the recovery of individuals who have been traumatically injured to assist them to develop new views of vulnerability and strength, make changes in relationships, and facilitate philosophical, physical and spiritual growth.

  10. Big biomedical data as the key resource for discovery science.

    Science.gov (United States)

    Toga, Arthur W; Foster, Ian; Kesselman, Carl; Madduri, Ravi; Chard, Kyle; Deutsch, Eric W; Price, Nathan D; Glusman, Gustavo; Heavner, Benjamin D; Dinov, Ivo D; Ames, Joseph; Van Horn, John; Kramer, Roger; Hood, Leroy

    2015-11-01

    Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an "-ome to home" approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center's computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson's and Alzheimer's.

  11. George and the big bang

    CERN Document Server

    Hawking, Lucy; Parsons, Gary

    2012-01-01

    George has problems. He has twin baby sisters at home who demand his parents’ attention. His beloved pig Freddy has been exiled to a farm, where he’s miserable. And worst of all, his best friend, Annie, has made a new friend whom she seems to like more than George. So George jumps at the chance to help Eric with his plans to run a big experiment in Switzerland that seeks to explore the earliest moment of the universe. But there is a conspiracy afoot, and a group of evildoers is planning to sabotage the experiment. Can George repair his friendship with Annie and piece together the clues before Eric’s experiment is destroyed forever? This engaging adventure features essays by Professor Stephen Hawking and other eminent physicists about the origins of the universe and ends with a twenty-page graphic novel that explains how the Big Bang happened—in reverse!

  12. Big Numbers in String Theory

    CERN Document Server

    Schellekens, A N

    2016-01-01

    This paper contains some personal reflections on several computational contributions to what is now known as the "String Theory Landscape". It consists of two parts. The first part concerns the origin of big numbers, and especially the number $10^{1500}$ that appeared in work on the covariant lattice construction (with W. Lerche and D. Luest). This part contains some new results. I correct a huge but inconsequential error, discuss some more accurate estimates, and compare with the counting for free fermion constructions. In particular I prove that the latter only provide an exponentially small fraction of all even self-dual lattices for large lattice dimensions. The second part of the paper concerns dealing with big numbers, and contains some lessons learned from various vacuum scanning projects.

  13. The big wheels of ATLAS

    CERN Multimedia

    2006-01-01

    The ATLAS cavern is filling up at an impressive rate. The installation of the first of the big wheels of the muon spectrometer, a thin gap chamber (TGC) wheel, was completed in September. The muon spectrometer will include four big moving wheels at each end, each measuring 25 metres in diameter. Of the eight wheels in total, six will be composed of thin gap chambers for the muon trigger system and the other two will consist of monitored drift tubes (MDTs) to measure the position of the muons (see Bulletin No. 13/2006). The installation of the 688 muon chambers in the barrel is progressing well, with three-quarters of them already installed between the coils of the toroid magnet.

  14. Big data and ophthalmic research.

    Science.gov (United States)

    Clark, Antony; Ng, Jonathon Q; Morlet, Nigel; Semmens, James B

    2016-01-01

    Large population-based health administrative databases, clinical registries, and data linkage systems are a rapidly expanding resource for health research. Ophthalmic research has benefited from the use of these databases in expanding the breadth of knowledge in areas such as disease surveillance, disease etiology, health services utilization, and health outcomes. Furthermore, the quantity of data available for research has increased exponentially in recent times, particularly as e-health initiatives come online in health systems across the globe. We review some big data concepts, the databases and data linkage systems used in eye research-including their advantages and limitations, the types of studies previously undertaken, and the future direction for big data in eye research. PMID:26844660

  15. Big data and ophthalmic research.

    Science.gov (United States)

    Clark, Antony; Ng, Jonathon Q; Morlet, Nigel; Semmens, James B

    2016-01-01

    Large population-based health administrative databases, clinical registries, and data linkage systems are a rapidly expanding resource for health research. Ophthalmic research has benefited from the use of these databases in expanding the breadth of knowledge in areas such as disease surveillance, disease etiology, health services utilization, and health outcomes. Furthermore, the quantity of data available for research has increased exponentially in recent times, particularly as e-health initiatives come online in health systems across the globe. We review some big data concepts, the databases and data linkage systems used in eye research-including their advantages and limitations, the types of studies previously undertaken, and the future direction for big data in eye research.

  16. Big Bang Nucleosynthesis: An Update

    OpenAIRE

    Olive, Keith A.; Scully, Sean T.

    1995-01-01

    WThe current status of big bang nucleosynthesis is reviewed with an emphasis on the comparison between the observational determination of the light element abundances of \\D, \\he3, \\he4 and \\li7 and the predictions from theory. In particular, we present new analyses for \\he4 and \\li7. Implications for physics beyond the standard model are also discussed. Limits on the effective number of neutrino flavors are also updated.

  17. Big data processing with Hadoop

    OpenAIRE

    Wu, Shiqi

    2015-01-01

    Computing technology has changed the way we work, study, and live. The distributed data processing technology is one of the popular topics in the IT field. It provides a simple and centralized computing platform by reducing the cost of the hardware. The characteristics of distributed data processing technology have changed the whole industry. Hadoop, as the open source project of Apache foundation, is the most representative platform of distributed big data processing. The Hadoop distribu...

  18. BIG DATA IN BUSINESS ENVIRONMENT

    OpenAIRE

    Logica BANICA; Alina HAGIU

    2015-01-01

    In recent years, dealing with a lot of data originating from social media sites and mobile communications among data from business environments and institutions, lead to the definition of a new concept, known as Big Data. The economic impact of the sheer amount of data produced in a last two years has increased rapidly. It is necessary to aggregate all types of data (structured and unstructured) in order to improve current transactions, to develop new business models, to provide a real image ...

  19. BIG Data – A Review.

    OpenAIRE

    Anuradha Bhatia; Gaurav Vaswani

    2013-01-01

    As more data becomes available from an abundance of sources both within and outside, organizations are seeking to use those abundant resources to increase innovation, retain customers, and increase operational efficiency. At the same time, organizations are challenged by their end users, who are demanding greater capability and integration to mine and analyze burgeoning new sources of information. Big Data provides opportunities for business users to ask questions they never were able to ask ...

  20. Pragmatic Interaction between Big Powers

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Lu. It is very difficult to summarize the relationship among big powers in 2004. Looking east, there existed a """"small cold war"""" named by some media between Europe and Russia and between the United States and Russia; with regard to the """"orange revolution"""" in Ukraine at the end of the year, a rival show rope and Russia. Looking east, awas displayed between America, Eufresh scent seems to fill the air.

  1. Big data: the management revolution.

    Science.gov (United States)

    McAfee, Andrew; Brynjolfsson, Erik

    2012-10-01

    Big data, the authors write, is far more powerful than the analytics of the past. Executives can measure and therefore manage more precisely than ever before. They can make better predictions and smarter decisions. They can target more-effective interventions in areas that so far have been dominated by gut and intuition rather than by data and rigor. The differences between big data and analytics are a matter of volume, velocity, and variety: More data now cross the internet every second than were stored in the entire internet 20 years ago. Nearly real-time information makes it possible for a company to be much more agile than its competitors. And that information can come from social networks, images, sensors, the web, or other unstructured sources. The managerial challenges, however, are very real. Senior decision makers have to learn to ask the right questions and embrace evidence-based decision making. Organizations must hire scientists who can find patterns in very large data sets and translate them into useful business information. IT departments have to work hard to integrate all the relevant internal and external sources of data. The authors offer two success stories to illustrate how companies are using big data: PASSUR Aerospace enables airlines to match their actual and estimated arrival times. Sears Holdings directly analyzes its incoming store data to make promotions much more precise and faster. PMID:23074865

  2. Big Data Comes to School

    Directory of Open Access Journals (Sweden)

    Bill Cope

    2016-03-01

    Full Text Available The prospect of “big data” at once evokes optimistic views of an information-rich future and concerns about surveillance that adversely impacts our personal and private lives. This overview article explores the implications of big data in education, focusing by way of example on data generated by student writing. We have chosen writing because it presents particular complexities, highlighting the range of processes for collecting and interpreting evidence of learning in the era of computer-mediated instruction and assessment as well as the challenges. Writing is significant not only because it is central to the core subject area of literacy; it is also an ideal medium for the representation of deep disciplinary knowledge across a number of subject areas. After defining what big data entails in education, we map emerging sources of evidence of learning that separately and together have the potential to generate unprecedented amounts of data: machine assessments, structured data embedded in learning, and unstructured data collected incidental to learning activity. Our case is that these emerging sources of evidence of learning have significant implications for the traditional relationships between assessment and instruction. Moreover, for educational researchers, these data are in some senses quite different from traditional evidentiary sources, and this raises a number of methodological questions. The final part of the article discusses implications for practice in an emerging field of education data science, including publication of data, data standards, and research ethics.

  3. The BigBOSS Experiment

    CERN Document Server

    Schlegel, D; Abraham, T; Ahn, C; Prieto, C Allende; Annis, J; Aubourg, E; Azzaro, M; Baltay, S Bailey C; Baugh, C; Bebek, C; Becerril, S; Blanton, M; Bolton, A; Bromley, B; Cahn, R; Carton, P -H; Cervantes-Cota, J L; Chu, Y; Cortes, M; Dawson, K; Dey, A; Dickinson, M; Diehl, H T; Doel, P; Ealet, A; Edelstein, J; Eppelle, D; Escoffier, S; Evrard, A; Faccioli, L; Frenk, C; Geha, M; Gerdes, D; Gondolo, P; Gonzalez-Arroyo, A; Grossan, B; Heckman, T; Heetderks, H; Ho, S; Honscheid, K; Huterer, D; Ilbert, O; Ivans, I; Jelinsky, P; Jing, Y; Joyce, D; Kennedy, R; Kent, S; Kieda, D; Kim, A; Kim, C; Kneib, J -P; Kong, X; Kosowsky, A; Krishnan, K; Lahav, O; Lampton, M; LeBohec, S; Brun, V Le; Levi, M; Li, C; Liang, M; Lim, H; Lin, W; Linder, E; Lorenzon, W; de la Macorra, A; Magneville, Ch; Malina, R; Marinoni, C; Martinez, V; Majewski, S; Matheson, T; McCloskey, R; McDonald, P; McKay, T; McMahon, J; Menard, B; Miralda-Escude, J; Modjaz, M; Montero-Dorta, A; Morales, I; Mostek, N; Newman, J; Nichol, R; Nugent, P; Olsen, K; Padmanabhan, N; Palanque-Delabrouille, N; Park, I; Peacock, J; Percival, W; Perlmutter, S; Peroux, C; Petitjean, P; Prada, F; Prieto, E; Prochaska, J; Reil, K; Rockosi, C; Roe, N; Rollinde, E; Roodman, A; Ross, N; Rudnick, G; Ruhlmann-Kleider, V; Sanchez, J; Sawyer, D; Schimd, C; Schubnell, M; Scoccimaro, R; Seljak, U; Seo, H; Sheldon, E; Sholl, M; Shulte-Ladbeck, R; Slosar, A; Smith, D S; Smoot, G; Springer, W; Stril, A; Szalay, A S; Tao, C; Tarle, G; Taylor, E; Tilquin, A; Tinker, J; Valdes, F; Wang, J; Wang, T; Weaver, B A; Weinberg, D; White, M; Wood-Vasey, M; Yang, J; Yeche, X Yang Ch; Zakamska, N; Zentner, A; Zhai, C; Zhang, P

    2011-01-01

    BigBOSS is a Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with a wide-area galaxy and quasar redshift survey over 14,000 square degrees. It has been conditionally accepted by NOAO in response to a call for major new instrumentation and a high-impact science program for the 4-m Mayall telescope at Kitt Peak. The BigBOSS instrument is a robotically-actuated, fiber-fed spectrograph capable of taking 5000 simultaneous spectra over a wavelength range from 340 nm to 1060 nm, with a resolution R = 3000-4800. Using data from imaging surveys that are already underway, spectroscopic targets are selected that trace the underlying dark matter distribution. In particular, targets include luminous red galaxies (LRGs) up to z = 1.0, extending the BOSS LRG survey in both redshift and survey area. To probe the universe out to even higher redshift, BigBOSS will target bright [OII] emission line galaxies (ELGs) up to z = 1.7. In total, 20 million galaxy red...

  4. Big Pharma: a former insider's view.

    Science.gov (United States)

    Badcott, David

    2013-05-01

    There is no lack of criticisms frequently levelled against the international pharmaceutical industry (Big Pharma): excessive profits, dubious or even dishonest practices, exploiting the sick and selective use of research data. Neither is there a shortage of examples used to support such opinions. A recent book by Brody (Hooked: Ethics, the Medical Profession and the Pharmaceutical Industry, 2008) provides a précis of the main areas of criticism, adopting a twofold strategy: (1) An assumption that the special nature and human need for pharmaceutical medicines requires that such products should not be treated like other commodities and (2) A multilevel descriptive approach that facilitates an ethical analysis of relationships and practices. At the same time, Brody is fully aware of the nature of the fundamental dilemma: the apparent addiction to (and denial of) the widespread availability of gifts and financial support for conferences etc., but recognises that 'Remove the industry and its products, and a considerable portion of scientific medicine's power to help the patient vanishes' (Brody 2008, p. 5). The paper explores some of the relevant issues, and argues that despite the identified shortcomings and a need for rigorous and perhaps enhanced regulation, and realistic price control, the commercially competitive pharmaceutical industry remains the best option for developing safer and more effective medicinal treatments. At the same time, adoption of a broader ethical basis for the industry's activities, such as a triple bottom line policy, would register an important move in the right direction and go some way toward answering critics.

  5. [Big data, medical language and biomedical terminology systems].

    Science.gov (United States)

    Schulz, Stefan; López-García, Pablo

    2015-08-01

    A variety of rich terminology systems, such as thesauri, classifications, nomenclatures and ontologies support information and knowledge processing in health care and biomedical research. Nevertheless, human language, manifested as individually written texts, persists as the primary carrier of information, in the description of disease courses or treatment episodes in electronic medical records, and in the description of biomedical research in scientific publications. In the context of the discussion about big data in biomedicine, we hypothesize that the abstraction of the individuality of natural language utterances into structured and semantically normalized information facilitates the use of statistical data analytics to distil new knowledge out of textual data from biomedical research and clinical routine. Computerized human language technologies are constantly evolving and are increasingly ready to annotate narratives with codes from biomedical terminology. However, this depends heavily on linguistic and terminological resources. The creation and maintenance of such resources is labor-intensive. Nevertheless, it is sensible to assume that big data methods can be used to support this process. Examples include the learning of hierarchical relationships, the grouping of synonymous terms into concepts and the disambiguation of homonyms. Although clear evidence is still lacking, the combination of natural language technologies, semantic resources, and big data analytics is promising. PMID:26077872

  6. Perspective: Materials informatics and big data: Realization of the "fourth paradigm" of science in materials science

    Science.gov (United States)

    Agrawal, Ankit; Choudhary, Alok

    2016-05-01

    Our ability to collect "big data" has greatly surpassed our capability to analyze it, underscoring the emergence of the fourth paradigm of science, which is data-driven discovery. The need for data informatics is also emphasized by the Materials Genome Initiative (MGI), further boosting the emerging field of materials informatics. In this article, we look at how data-driven techniques are playing a big role in deciphering processing-structure-property-performance relationships in materials, with illustrative examples of both forward models (property prediction) and inverse models (materials discovery). Such analytics can significantly reduce time-to-insight and accelerate cost-effective materials discovery, which is the goal of MGI.

  7. Big Bang–Big Crunch Optimization Algorithm for Linear Phase Fir Digital Filter Design

    OpenAIRE

    Ms. Rashmi Singh Dr. H. K. Verma

    2012-01-01

    The Big Bang–Big Crunch (BB–BC) optimization algorithm is a new optimization method that relies on the Big Bang and Big Crunch theory, one of the theories of the evolution of the universe. In this paper, a Big Bang–Big Crunch algorithm has been used here for the design of linear phase finite impulse response (FIR) filters. Here the experimented fitness function based on the mean squared error between the actual and the ideal filter response. This paper presents the plot of magnitude response ...

  8. Re-evaluation of the immunological Big Bang.

    Science.gov (United States)

    Flajnik, Martin F

    2014-11-01

    Classically the immunological 'Big Bang' of adaptive immunity was believed to have resulted from the insertion of a transposon into an immunoglobulin superfamily gene member, initiating antigen receptor gene rearrangement via the RAG recombinase in an ancestor of jawed vertebrates. However, the discovery of a second, convergent adaptive immune system in jawless fish, focused on the so-called variable lymphocyte receptors (VLRs), was arguably the most exciting finding of the past decade in immunology and has drastically changed the view of immune origins. The recent report of a new lymphocyte lineage in lampreys, defined by the antigen receptor VLRC, suggests that there were three lymphocyte lineages in the common ancestor of jawless and jawed vertebrates that co-opted different antigen receptor supertypes. The transcriptional control of these lineages during development is predicted to be remarkably similar in both the jawless (agnathan) and jawed (gnathostome) vertebrates, suggesting that an early 'division of labor' among lymphocytes was a driving force in the emergence of adaptive immunity. The recent cartilaginous fish genome project suggests that most effector cytokines and chemokines were also present in these fish, and further studies of the lamprey and hagfish genomes will determine just how explosive the Big Bang actually was. PMID:25517375

  9. Domestication and plant genomes.

    Science.gov (United States)

    Tang, Haibao; Sezen, Uzay; Paterson, Andrew H

    2010-04-01

    The techniques of plant improvement have been evolving with the advancement of technology, progressing from crop domestication by Neolithic humans to scientific plant breeding, and now including DNA-based genotyping and genetic engineering. Archeological findings have shown that early human ancestors often unintentionally selected for and finally fixed a few major domestication traits over time. Recent advancement of molecular and genomic tools has enabled scientists to pinpoint changes to specific chromosomal regions and genetic loci that are responsible for dramatic morphological and other transitions that distinguish crops from their wild progenitors. Extensive studies in a multitude of additional crop species, facilitated by rapid progress in sequencing and resequencing(s) of crop genomes, will further our understanding of the genomic impact from both the unusual population history of cultivated plants and millennia of human selection.

  10. BIG GEO DATA MANAGEMENT: AN EXPLORATION WITH SOCIAL MEDIA AND TELECOMMUNICATIONS OPEN DATA

    Directory of Open Access Journals (Sweden)

    C. Arias Munoz

    2016-06-01

    Full Text Available The term Big Data has been recently used to define big, highly varied, complex data sets, which are created and updated at a high speed and require faster processing, namely, a reduced time to filter and analyse relevant data. These data is also increasingly becoming Open Data (data that can be freely distributed made public by the government, agencies, private enterprises and among others. There are at least two issues that can obstruct the availability and use of Open Big Datasets: Firstly, the gathering and geoprocessing of these datasets are very computationally intensive; hence, it is necessary to integrate high-performance solutions, preferably internet based, to achieve the goals. Secondly, the problems of heterogeneity and inconsistency in geospatial data are well known and affect the data integration process, but is particularly problematic for Big Geo Data. Therefore, Big Geo Data integration will be one of the most challenging issues to solve. With these applications, we demonstrate that is possible to provide processed Big Geo Data to common users, using open geospatial standards and technologies. NoSQL databases like MongoDB and frameworks like RASDAMAN could offer different functionalities that facilitate working with larger volumes and more heterogeneous geospatial data sources.

  11. Big Geo Data Management: AN Exploration with Social Media and Telecommunications Open Data

    Science.gov (United States)

    Arias Munoz, C.; Brovelli, M. A.; Corti, S.; Zamboni, G.

    2016-06-01

    The term Big Data has been recently used to define big, highly varied, complex data sets, which are created and updated at a high speed and require faster processing, namely, a reduced time to filter and analyse relevant data. These data is also increasingly becoming Open Data (data that can be freely distributed) made public by the government, agencies, private enterprises and among others. There are at least two issues that can obstruct the availability and use of Open Big Datasets: Firstly, the gathering and geoprocessing of these datasets are very computationally intensive; hence, it is necessary to integrate high-performance solutions, preferably internet based, to achieve the goals. Secondly, the problems of heterogeneity and inconsistency in geospatial data are well known and affect the data integration process, but is particularly problematic for Big Geo Data. Therefore, Big Geo Data integration will be one of the most challenging issues to solve. With these applications, we demonstrate that is possible to provide processed Big Geo Data to common users, using open geospatial standards and technologies. NoSQL databases like MongoDB and frameworks like RASDAMAN could offer different functionalities that facilitate working with larger volumes and more heterogeneous geospatial data sources.

  12. Earth Science Data Analysis in the Era of Big Data

    Science.gov (United States)

    Kuo, K.-S.; Clune, T. L.; Ramachandran, R.

    2014-01-01

    Anyone with even a cursory interest in information technology cannot help but recognize that "Big Data" is one of the most fashionable catchphrases of late. From accurate voice and facial recognition, language translation, and airfare prediction and comparison, to monitoring the real-time spread of flu, Big Data techniques have been applied to many seemingly intractable problems with spectacular successes. They appear to be a rewarding way to approach many currently unsolved problems. Few fields of research can claim a longer history with problems involving voluminous data than Earth science. The problems we are facing today with our Earth's future are more complex and carry potentially graver consequences than the examples given above. How has our climate changed? Beside natural variations, what is causing these changes? What are the processes involved and through what mechanisms are these connected? How will they impact life as we know it? In attempts to answer these questions, we have resorted to observations and numerical simulations with ever-finer resolutions, which continue to feed the "data deluge." Plausibly, many Earth scientists are wondering: How will Big Data technologies benefit Earth science research? As an example from the global water cycle, one subdomain among many in Earth science, how would these technologies accelerate the analysis of decades of global precipitation to ascertain the changes in its characteristics, to validate these changes in predictive climate models, and to infer the implications of these changes to ecosystems, economies, and public health? Earth science researchers need a viable way to harness the power of Big Data technologies to analyze large volumes and varieties of data with velocity and veracity. Beyond providing speedy data analysis capabilities, Big Data technologies can also play a crucial, albeit indirect, role in boosting scientific productivity by facilitating effective collaboration within an analysis environment

  13. Big defensins, a diverse family of antimicrobial peptides that follows different patterns of expression in hemocytes of the oyster Crassostrea gigas.

    Directory of Open Access Journals (Sweden)

    Rafael D Rosa

    Full Text Available BACKGROUND: Big defensin is an antimicrobial peptide composed of a highly hydrophobic N-terminal region and a cationic C-terminal region containing six cysteine residues involved in three internal disulfide bridges. While big defensin sequences have been reported in various mollusk species, few studies have been devoted to their sequence diversity, gene organization and their expression in response to microbial infections. FINDINGS: Using the high-throughput Digital Gene Expression approach, we have identified in Crassostrea gigas oysters several sequences coding for big defensins induced in response to a Vibrio infection. We showed that the oyster big defensin family is composed of three members (named Cg-BigDef1, Cg-BigDef2 and Cg-BigDef3 that are encoded by distinct genomic sequences. All Cg-BigDefs contain a hydrophobic N-terminal domain and a cationic C-terminal domain that resembles vertebrate β-defensins. Both domains are encoded by separate exons. We found that big defensins form a group predominantly present in mollusks and closer to vertebrate defensins than to invertebrate and fungi CSαβ-containing defensins. Moreover, we showed that Cg-BigDefs are expressed in oyster hemocytes only and follow different patterns of gene expression. While Cg-BigDef3 is non-regulated, both Cg-BigDef1 and Cg-BigDef2 transcripts are strongly induced in response to bacterial challenge. Induction was dependent on pathogen associated molecular patterns but not damage-dependent. The inducibility of Cg-BigDef1 was confirmed by HPLC and mass spectrometry, since ions with a molecular mass compatible with mature Cg-BigDef1 (10.7 kDa were present in immune-challenged oysters only. From our biochemical data, native Cg-BigDef1 would result from the elimination of a prepropeptide sequence and the cyclization of the resulting N-terminal glutamine residue into a pyroglutamic acid. CONCLUSIONS: We provide here the first report showing that big defensins form a family

  14. Development and validation of Big Four personality scales for the Schedule for Nonadaptive and Adaptive Personality--Second Edition (SNAP-2).

    Science.gov (United States)

    Calabrese, William R; Rudick, Monica M; Simms, Leonard J; Clark, Lee Anna

    2012-09-01

    Recently, integrative, hierarchical models of personality and personality disorder (PD)--such as the Big Three, Big Four, and Big Five trait models--have gained support as a unifying dimensional framework for describing PD. However, no measures to date can simultaneously represent each of these potentially interesting levels of the personality hierarchy. To unify these measurement models psychometrically, we sought to develop Big Five trait scales within the Schedule for Nonadaptive and Adaptive Personality--Second Edition (SNAP-2). Through structural and content analyses, we examined relations between the SNAP-2, the Big Five Inventory (BFI), and the NEO Five-Factor Inventory (NEO-FFI) ratings in a large data set (N = 8,690), including clinical, military, college, and community participants. Results yielded scales consistent with the Big Four model of personality (i.e., Neuroticism, Conscientiousness, Introversion, and Antagonism) and not the Big Five, as there were insufficient items related to Openness. Resulting scale scores demonstrated strong internal consistency and temporal stability. Structural validity and external validity were supported by strong convergent and discriminant validity patterns between Big Four scale scores and other personality trait scores and expectable patterns of self-peer agreement. Descriptive statistics and community-based norms are provided. The SNAP-2 Big Four Scales enable researchers and clinicians to assess personality at multiple levels of the trait hierarchy and facilitate comparisons among competing big-trait models.

  15. An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species

    Directory of Open Access Journals (Sweden)

    Deborah Galpert

    2015-01-01

    Full Text Available Orthology detection requires more effective scaling algorithms. In this paper, a set of gene pair features based on similarity measures (alignment scores, sequence length, gene membership to conserved regions, and physicochemical profiles are combined in a supervised pairwise ortholog detection approach to improve effectiveness considering low ortholog ratios in relation to the possible pairwise comparison between two genomes. In this scenario, big data supervised classifiers managing imbalance between ortholog and nonortholog pair classes allow for an effective scaling solution built from two genomes and extended to other genome pairs. The supervised approach was compared with RBH, RSD, and OMA algorithms by using the following yeast genome pairs: Saccharomyces cerevisiae-Kluyveromyces lactis, Saccharomyces cerevisiae-Candida glabrata, and Saccharomyces cerevisiae-Schizosaccharomyces pombe as benchmark datasets. Because of the large amount of imbalanced data, the building and testing of the supervised model were only possible by using big data supervised classifiers managing imbalance. Evaluation metrics taking low ortholog ratios into account were applied. From the effectiveness perspective, MapReduce Random Oversampling combined with Spark SVM outperformed RBH, RSD, and OMA, probably because of the consideration of gene pair features beyond alignment similarities combined with the advances in big data supervised classification.

  16. An Overview of Big Data Privacy Issues

    OpenAIRE

    Patrick Hung

    2013-01-01

    Big data is the term for a collection of large and complex datasets from different sources that is difficult to process using traditional data management and processing applications. In these datasets, some information must be kept secret from others. On the other hand, some information has to be released for acquainting information or big data analytical services. The research challenge is how to protect the private information in the context of big data. Privacy is described by the ability ...

  17. Social Big Data and Privacy Awareness

    OpenAIRE

    Sang, Lin

    2015-01-01

    Based on the rapid development of Big Data, the data from the online social network becomea major part of it. Big data make the social networks became data-oriented rather than social-oriented. Taking this into account, this dissertation presents a qualitative study to research howdoes the data-oriented social network affect its users’ privacy management for nowadays. Within this dissertation, an overview of Big Data and privacy issues on the social network waspresented as a background study. ...

  18. EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Unit, Texas, 2014

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — A first-surface topography digital elevation model (DEM) mosaic for the Big Sandy Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely...

  19. EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Corridor Unit, Texas, 2014

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — A first-surface topography Digital Elevation Model (DEM) mosaic for the Big Sandy Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from...

  20. EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Corridor Unit, Texas, 2014

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — A bare-earth topography Digital Elevation Model (DEM) mosaic for the Big Sandy Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from...

  1. EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Unit, Texas, 2014

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — A bare-earth topography digital elevation model (DEM) mosaic for the Big Sandy Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely...

  2. Traffic information computing platform for big data

    International Nuclear Information System (INIS)

    Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users

  3. Big data optimization recent developments and challenges

    CERN Document Server

    2016-01-01

    The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

  4. Big Data Analytics Using Cloud and Crowd

    OpenAIRE

    Allahbakhsh, Mohammad; Arbabi, Saeed; Motahari-Nezhad, Hamid-Reza; Benatallah, Boualem

    2016-01-01

    The increasing application of social and human-enabled systems in people's daily life from one side and from the other side the fast growth of mobile and smart phones technologies have resulted in generating tremendous amount of data, also referred to as big data, and a need for analyzing these data, i.e., big data analytics. Recently a trend has emerged to incorporate human computing power into big data analytics to solve some shortcomings of existing big data analytics such as dealing with ...

  5. The big de Rham–Witt complex

    DEFF Research Database (Denmark)

    Hesselholt, Lars

    2015-01-01

    This paper gives a new and direct construction of the multi-prime big de Rham–Witt complex, which is defined for every commutative and unital ring; the original construction by Madsen and myself relied on the adjoint functor theorem and accordingly was very indirect. The construction given here....... It is the existence of these divided Frobenius operators that makes the new construction of the big de Rham–Witt complex possible. It is further shown that the big de Rham–Witt complex behaves well with respect to étale maps, and finally, the big de Rham–Witt complex of the ring of integers is explicitly evaluated....

  6. Urgent Call for Nursing Big Data.

    Science.gov (United States)

    Delaney, Connie W

    2016-01-01

    The purpose of this panel is to expand internationally a National Action Plan for sharable and comparable nursing data for quality improvement and big data science. There is an urgent need to assure that nursing has sharable and comparable data for quality improvement and big data science. A national collaborative - Nursing Knowledge and Big Data Science includes multi-stakeholder groups focused on a National Action Plan toward implementing and using sharable and comparable nursing big data. Panelists will share accomplishments and future plans with an eye toward international collaboration. This presentation is suitable for any audience attending the NI2016 conference. PMID:27332330

  7. Traffic information computing platform for big data

    Energy Technology Data Exchange (ETDEWEB)

    Duan, Zongtao, E-mail: ztduan@chd.edu.cn; Li, Ying, E-mail: ztduan@chd.edu.cn; Zheng, Xibin, E-mail: ztduan@chd.edu.cn; Liu, Yan, E-mail: ztduan@chd.edu.cn; Dai, Jiting, E-mail: ztduan@chd.edu.cn; Kang, Jun, E-mail: ztduan@chd.edu.cn [Chang' an University School of Information Engineering, Xi' an, China and Shaanxi Engineering and Technical Research Center for Road and Traffic Detection, Xi' an (China)

    2014-10-06

    Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users.

  8. Big data analytics with R and Hadoop

    CERN Document Server

    Prajapati, Vignesh

    2013-01-01

    Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.

  9. Fitting ERGMs on big networks.

    Science.gov (United States)

    An, Weihua

    2016-09-01

    The exponential random graph model (ERGM) has become a valuable tool for modeling social networks. In particular, ERGM provides great flexibility to account for both covariates effects on tie formations and endogenous network formation processes. However, there are both conceptual and computational issues for fitting ERGMs on big networks. This paper describes a framework and a series of methods (based on existent algorithms) to address these issues. It also outlines the advantages and disadvantages of the methods and the conditions to which they are most applicable. Selected methods are illustrated through examples. PMID:27480375

  10. Big Brother Has Bigger Say

    Institute of Scientific and Technical Information of China (English)

    Yang Wei

    2009-01-01

    @@ 156 delegates from all walks of life in Guangdong province composed the Guangdong delegation for the NPC this year. The import and export value of Guangdong makes up one-third of national total value, and accounts for one-eighth of national economic growth. Guangdong province has maintained its top spot in import and export value among China's many provinces and cities for several years, commonly referred to as "Big Brother". At the same time, it is the region where the global financial crisis has hit China hardest.

  11. Big Five -persoonallisuuspiirteiden yhteydet unettomuuteen

    OpenAIRE

    Aronen, Aino

    2015-01-01

    Tutkimuksen tarkoituksena oli selvittÀÀ, ovatko Big Five -persoonallisuuspiirteet (neuroottisuus, ulospÀinsuuntautuneisuus, tunnollisuus, avoimuus kokemuksille ja sovinnollisuus) yhteydessÀ unettomuuden oireisiin, joita olivat nukahtamisvaikeudet, herÀilyt, vaikeudet pysyÀ unessa ja vÀsyneenÀ herÀÀmiset normaalipituisten unien jÀlkeen. Unettomuutta koskevien teorioiden mukaan korkea neuroottisuus, matala ulospÀinsuuntautuneisuus, matala tunnollisuus ja matala sovinnollisuus voivat...

  12. Cancer genomics

    DEFF Research Database (Denmark)

    Norrild, Bodil; Guldberg, Per; Ralfkiær, Elisabeth Methner

    2007-01-01

    Almost all cells in the human body contain a complete copy of the genome with an estimated number of 25,000 genes. The sequences of these genes make up about three percent of the genome and comprise the inherited set of genetic information. The genome also contains information that determines whe...

  13. BigDataBench: a Big Data Benchmark Suite from Internet Services

    OpenAIRE

    Wang, Lei; Zhan, Jianfeng; Luo, Chunjie; Zhu, Yuqing; Yang, Qiang; He, Yongqiang; Gao, Wanling; Jia, Zhen; Shi, Yingjie; Zhang, Shujie; Zheng, Chen; Lu, Gang; Zhan, Kent; Li, Xiaona; Qiu, Bizhu

    2014-01-01

    As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purpo...

  14. Big Data; A Management Revolution : The emerging role of big data in businesses

    OpenAIRE

    Blasiak, Kevin

    2014-01-01

    Big data is a term that was coined in 2012 and has since then emerged to one of the top trends in business and technology. Big data is an agglomeration of different technologies resulting in data processing capabilities that have been unreached before. Big data is generally characterized by 4 factors. Volume, velocity and variety. These three factors distinct it from the traditional data use. The possibilities to utilize this technology are vast. Big data technology has touch points in differ...

  15. Comparative validity of brief to medium-length Big Five and Big Six personality questionnaires

    NARCIS (Netherlands)

    A.G. Thalmayer; G. Saucier; A. Eigenhuis

    2011-01-01

    A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five

  16. Comparative Validity of Brief to Medium-Length Big Five and Big Six Personality Questionnaires

    Science.gov (United States)

    Thalmayer, Amber Gayle; Saucier, Gerard; Eigenhuis, Annemarie

    2011-01-01

    A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five inventories when conducting a study and are…

  17. Privacy-Preserving Computation of Disease Risk by Using Genomic, Clinical, and Environmental Data

    OpenAIRE

    Ayday, Erman; Raisaro, Jean Louis; Laren, Mc; Jack, Paul; Fellay, Jacques; Hubaux, Jean-Pierre

    2013-01-01

    According to many scientists and clinicians, genomics is the "next big thing" in the field of medicine. On one hand, decreasing costs in genome sequencing has been paving the way to better preventive and personalized medicine. On the other hand, genomic data also raises serious privacy concerns, as it is the ultimate identifier of an individual and it contains privacy-sensitive data (e.g., disease predispositions, ancestry information). Thus, it is necessary to find ways of using genomic data...

  18. Using Sex to Cure the Genome.

    Directory of Open Access Journals (Sweden)

    Eduardo P C Rocha

    2016-03-01

    Full Text Available The diversification of prokaryotes is accelerated by their ability to acquire DNA from other genomes. However, the underlying processes also facilitate genome infection by costly mobile genetic elements. The discovery that cells can uptake DNA by natural transformation was instrumental to the birth of molecular biology nearly a century ago. Surprisingly, a new study shows that this mechanism could efficiently cure the genome of mobile elements acquired through previous sexual exchanges.

  19. Georges et le big bang

    CERN Document Server

    Hawking, Lucy; Parsons, Gary

    2011-01-01

    Georges et Annie, sa meilleure amie, sont sur le point d'assister à l'une des plus importantes expériences scientifiques de tous les temps : explorer les premiers instants de l'Univers, le Big Bang ! Grâce à Cosmos, leur super ordinateur, et au Grand Collisionneur de hadrons créé par Éric, le père d'Annie, ils vont enfin pouvoir répondre à cette question essentielle : pourquoi existons nous ? Mais Georges et Annie découvrent qu'un complot diabolique se trame. Pire, c'est toute la recherche scientifique qui est en péril ! Entraîné dans d'incroyables aventures, Georges ira jusqu'aux confins de la galaxie pour sauver ses amis...Une plongée passionnante au coeur du Big Bang. Les toutes dernières théories de Stephen Hawking et des plus grands scientifiques actuels.

  20. Baryon symmetric big bang cosmology

    Science.gov (United States)

    Stecker, F. W.

    1978-01-01

    Both the quantum theory and Einsteins theory of special relativity lead to the supposition that matter and antimatter were produced in equal quantities during the big bang. It is noted that local matter/antimatter asymmetries may be reconciled with universal symmetry by assuming (1) a slight imbalance of matter over antimatter in the early universe, annihilation, and a subsequent remainder of matter; (2) localized regions of excess for one or the other type of matter as an initial condition; and (3) an extremely dense, high temperature state with zero net baryon number; i.e., matter/antimatter symmetry. Attention is given to the third assumption, which is the simplest and the most in keeping with current knowledge of the cosmos, especially as pertains the universality of 3 K background radiation. Mechanisms of galaxy formation are discussed, whereby matter and antimatter might have collided and annihilated each other, or have coexisted (and continue to coexist) at vast distances. It is pointed out that baryon symmetric big bang cosmology could probably be proved if an antinucleus could be detected in cosmic radiation.

  1. Astronomical surveys and big data

    Science.gov (United States)

    Mickaelian, Areg M.

    Recent all-sky and large-area astronomical surveys and their catalogued data over the whole range of electromagnetic spectrum, from γ -rays to radio waves, are reviewed, including such as Fermi-GLAST and INTEGRAL in γ -ray, ROSAT, XMM and Chandra in X-ray, GALEX in UV, SDSS and several POSS I and POSS II-based catalogues (APM, MAPS, USNO, GSC) in the optical range, 2MASS in NIR, WISE and AKARI IRC in MIR, IRAS and AKARI FIS in FIR, NVSS and FIRST in radio range, and many others, as well as the most important surveys giving optical images (DSS I and II, SDSS, etc.), proper motions (Tycho, USNO, Gaia), variability (GCVS, NSVS, ASAS, Catalina, Pan-STARRS), and spectroscopic data (FBS, SBS, Case, HQS, HES, SDSS, CALIFA, GAMA). An overall understanding of the coverage along the whole wavelength range and comparisons between various surveys are given: galaxy redshift surveys, QSO/AGN, radio, Galactic structure, and Dark Energy surveys. Astronomy has entered the Big Data era, with Astrophysical Virtual Observatories and Computational Astrophysics playing an important role in using and analyzing big data for new discoveries.

  2. An analysis of cross-sectional differences in big and non-big public accounting firms' audit programs

    NARCIS (Netherlands)

    Blokdijk, J.H. (Hans); Drieenhuizen, F.; Stein, M.T.; Simunic, D.A.

    2006-01-01

    A significant body of prior research has shown that audits by the Big 5 (now Big 4) public accounting firms are quality differentiated relative to non-Big 5 audits. This result can be derived analytically by assuming that Big 5 and non-Big 5 firms face different loss functions for "audit failures" a

  3. Competing Distractors Facilitate Visual Search in Heterogeneous Displays

    Science.gov (United States)

    Kong, Garry; Alais, David; Van der Burg, Erik

    2016-01-01

    In the present study, we examine how observers search among complex displays. Participants were asked to search for a big red horizontal line among 119 distractor lines of various sizes, orientations and colours, leading to 36 different feature combinations. To understand how people search in such a heterogeneous display, we evolved the search display by using a genetic algorithm (Experiment 1). The best displays (i.e., displays corresponding to the fastest reaction times) were selected and combined to create new, evolved displays. Search times declined over generations. Results show that items sharing the same colour and orientation as the target disappeared over generations, implying they interfered with search, but items sharing the same colour and were 12.5° different in orientation only interfered if they were also the same size. Furthermore, and inconsistent with most dominant visual search theories, we found that non-red horizontal distractors increased over generations, indicating that these distractors facilitated visual search while participants were searching for a big red horizontally oriented target. In Experiments 2 and 3, we replicated these results using conventional, factorial experiments. Interestingly, in Experiment 4, we found that this facilitation effect was only present when the displays were very heterogeneous. While current models of visual search are able to successfully describe search in homogeneous displays, our results challenge the ability of these models to describe visual search in heterogeneous environments. PMID:27508298

  4. Small molecules for big tasks

    Institute of Scientific and Technical Information of China (English)

    Jiarui Wu

    2011-01-01

    @@ One of the most important achievements in the post-genome era is discovery of microRNAs (miRNAs), which widely exist from simple-genome organisms such as viruses and bacteria to complexgenome organisms such as plants and animals.miRNAs are single-stranded non-coding RNAs of 18-25 nucleotides in length, which are generated from larger precursors that are transcribed from noncoding genes.As a new type of regulatory molecules, miRNAs present unique features in regulating gene and its products, including rapidly turning off protein production, reversibly, and compartmentalized regulating gene expression.

  5. Research Progress of the Application of Big Data in China’s Urban Planning

    Institute of Scientific and Technical Information of China (English)

    Dang; Anrong; Xu; Jian; Tong; Biao; Li; Juan; Qian; Fang

    2015-01-01

    The arrival of the big data era facilitates the reform on related research and its application in the fi eld of urban planning from the mode of thinking to the technical method, which provides a technical foundation and platform for supporting the demands of residents as micro subjects in the process of city development. Beginning with analyzing the changes in urban planning thoughts under the infl uence of big data, this paper then summarizes the major reforms in urban planning research methodology and a city’s plan formulation process caused by the application of big data, such as thinking mode, researching method, and planning process, based on which relevant issues like publicity and sharing of data, authenticity of data, and security of data that need to be further discussed and solved are analyzed, with the expectation of promoting the development of urban planning research and application in this new era.

  6. Unlocking the Power of Big Data at the National Institutes of Health.

    Science.gov (United States)

    Coakley, Meghan F; Leerkes, Maarten R; Barnett, Jason; Gabrielian, Andrei E; Noble, Karlynn; Weber, M Nick; Huyen, Yentram

    2013-09-01

    The era of "big data" presents immense opportunities for scientific discovery and technological progress, with the potential to have enormous impact on research and development in the public sector. In order to capitalize on these benefits, there are significant challenges to overcome in data analytics. The National Institute of Allergy and Infectious Diseases held a symposium entitled "Data Science: Unlocking the Power of Big Data" to create a forum for big data experts to present and share some of the creative and innovative methods to gleaning valuable knowledge from an overwhelming flood of biological data. A significant investment in infrastructure and tool development, along with more and better-trained data scientists, may facilitate methods for assimilation of data and machine learning, to overcome obstacles such as data security, data cleaning, and data integration.

  7. Unlocking the Power of Big Data at the National Institutes of Health.

    Science.gov (United States)

    Coakley, Meghan F; Leerkes, Maarten R; Barnett, Jason; Gabrielian, Andrei E; Noble, Karlynn; Weber, M Nick; Huyen, Yentram

    2013-09-01

    The era of "big data" presents immense opportunities for scientific discovery and technological progress, with the potential to have enormous impact on research and development in the public sector. In order to capitalize on these benefits, there are significant challenges to overcome in data analytics. The National Institute of Allergy and Infectious Diseases held a symposium entitled "Data Science: Unlocking the Power of Big Data" to create a forum for big data experts to present and share some of the creative and innovative methods to gleaning valuable knowledge from an overwhelming flood of biological data. A significant investment in infrastructure and tool development, along with more and better-trained data scientists, may facilitate methods for assimilation of data and machine learning, to overcome obstacles such as data security, data cleaning, and data integration. PMID:27442200

  8. Why Big Data Is a Big Deal (Ⅱ)

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    A new group of data mining technologies promises to change forever the way we sift through our vast stores of data,making it faster and cheaper.Some of the technologies are actively being used by people on the bleeding edge who need the technology now,like those involved in creating Web-based services that are driven by social media.They're also heavily contributing to these projects.In other vertical industries,businesses are realizing that much more of their value proposition is informationbased than they had previously thought,which will allow big data technologies to gain traction quickly,Olofson says.Couple that with affordable hardware and software,and enterprises find themselves in a perfect storm of business transformation opportunities.

  9. Big Data – Big Deal for Organization Design?

    Directory of Open Access Journals (Sweden)

    Janne J. Korhonen

    2014-04-01

    Full Text Available Analytics is an increasingly important source of competitive advantage. It has even been posited that big data will be the next strategic emphasis of organizations and that analytics capability will be manifested in organizational structure. In this article, I explore how analytics capability might be reflected in organizational structure using the notion of  “requisite organization” developed by Jaques (1998. Requisite organization argues that a new strategic emphasis requires the addition of a new stratum in the organization, resulting in greater organizational complexity. Requisite organization could serve as an objective, verifiable criterion for what qualifies as a genuine new strategic emphasis. Such a criterion is  necessary for research on the co-evolution of strategy and structure.

  10. 革命者BIG BANG

    Institute of Scientific and Technical Information of China (English)

    刘岩

    2015-01-01

    <正>在鄂尔多斯的繁荣时代,我遇见了那里的一位"意见领袖",因为他从美国回来,见过外面的世界,有着对奢侈品辽阔的见识和独到的品味。他引领着那座神秘财富城市中一个小圈子的购物风潮,他们一块接一块儿地购入Big Bang。那个时候,我并不太清楚他们迷恋这款腕表的原因,直到我一次次地去到巴塞尔表展,一次次地了解到Big Bang的想象力。是的,Big Bang的确充满了魅力。Big Bang进化史2005年Big Bang系列诞生2006年Big Bang全黑"全黑"理念使Big Bang更加纯粹和简洁。Big Bang全黑腕表从表壳到表盘浑然天成的亚光质感和多层次、不同材料融合起来的黑色,蕴含"不可见的可见"之禅意。

  11. Kansen voor Big data – WPA Vertrouwen

    NARCIS (Netherlands)

    Broek, T.A. van den; Roosendaal, A.P.C.; Veenstra, A.F.E. van; Nunen, A.M. van

    2014-01-01

    Big data is expected to become a driver for economic growth, but this can only be achieved when services based on (big) data are accepted by citizens and consumers. In a recent policy brief, the Cabinet Office mentions trust as one of the three pillars (the others being transparency and control) for

  12. The ethics of Big data: analytical survey

    OpenAIRE

    GIBER L.; KAZANTSEV N.

    2015-01-01

    The number of recent publications on the matter of ethical challenges of the implementation of Big Data has signified the growing interest to all the aspects of this issue. The proposed study specifically aims at analyzing ethical issues connected with Big Data.

  13. An embedding for the big bang

    Science.gov (United States)

    Wesson, Paul S.

    1994-01-01

    A cosmological model is given that has good physical properties for the early and late universe but is a hypersurface in a flat five-dimensional manifold. The big bang can therefore be regarded as an effect of a choice of coordinates in a truncated higher-dimensional geometry. Thus the big bang is in some sense a geometrical illusion.

  14. Big Red: A Development Environment for Bigraphs

    DEFF Research Database (Denmark)

    Faithfull, Alexander John; Perrone, Gian David; Hildebrandt, Thomas

    2013-01-01

    We present Big Red, a visual editor for bigraphs and bigraphical reactive systems, based upon Eclipse. The editor integrates with several existing bigraph tools to permit simulation and model-checking of bigraphical models. We give a brief introduction to the bigraphs formalism, and show how these...... concepts manifest within the tool using a small motivating example bigraphical model developed in Big Red....

  15. The Big Sleep in the Woods

    Institute of Scientific and Technical Information of China (English)

    王玉峰

    2002-01-01

    Now it's the time of the big sleep for the bees and the bears. Even the buds of the plants whose leaves fall off share in it. But the intensity of this winter sleep, or hibernation, depends on who's doing it.The big sleep of the bears ,for instance ,would probably be thought of as a

  16. A New Look at Big History

    Science.gov (United States)

    Hawkey, Kate

    2014-01-01

    The article sets out a "big history" which resonates with the priorities of our own time. A globalizing world calls for new spacial scales to underpin what the history curriculum addresses, "big history" calls for new temporal scales, while concern over climate change calls for a new look at subject boundaries. The article…

  17. Big Science and Long-tail Science

    CERN Multimedia

    2008-01-01

    Jim Downing and I were privileged to be the guests of Salavtore Mele at CERN yesterday and to see the Atlas detector of the Large Hadron Collider . This is a wow experience - although I knew it was big, I hadnt realised how big.

  18. The Death of the Big Men

    DEFF Research Database (Denmark)

    Martin, Keir

    2010-01-01

    Recently Tolai people og Papua New Guinea have adopted the term 'Big Shot' to decribe an emerging post-colonial political elite. The mergence of the term is a negative moral evaluation of new social possibilities that have arisen as a consequence of the Big Shots' privileged position within a glo...

  19. Big system: Interactive graphics for the engineer

    Science.gov (United States)

    Quenneville, C. E.

    1975-01-01

    The BCS Interactive Graphics System (BIG System) approach to graphics was presented, along with several significant engineering applications. The BIG System precompiler, the graphics support library, and the function requirements of graphics applications are discussed. It was concluded that graphics standardization and a device independent code can be developed to assure maximum graphic terminal transferability.

  20. What is beyond the big five?

    Science.gov (United States)

    Saucier, G; Goldberg, L R

    1998-08-01

    Previous investigators have proposed that various kinds of person-descriptive content--such as differences in attitudes or values, in sheer evaluation, in attractiveness, or in height and girth--are not adequately captured by the Big Five Model. We report on a rather exhaustive search for reliable sources of Big Five-independent variation in data from person-descriptive adjectives. Fifty-three candidate clusters were developed in a college sample using diverse approaches and sources. In a nonstudent adult sample, clusters were evaluated with respect to a minimax criterion: minimum multiple correlation with factors from Big Five markers and maximum reliability. The most clearly Big Five-independent clusters referred to Height, Girth, Religiousness, Employment Status, Youthfulness and Negative Valence (or low-base-rate attributes). Clusters referring to Fashionableness, Sensuality/Seductiveness, Beauty, Masculinity, Frugality, Humor, Wealth, Prejudice, Folksiness, Cunning, and Luck appeared to be potentially beyond the Big Five, although each of these clusters demonstrated Big Five multiple correlations of .30 to .45, and at least one correlation of .20 and over with a Big Five factor. Of all these content areas, Religiousness, Negative Valence, and the various aspects of Attractiveness were found to be represented by a substantial number of distinct, common adjectives. Results suggest directions for supplementing the Big Five when one wishes to extend variable selection outside the domain of personality traits as conventionally defined. PMID:9728415

  1. Big Food, Food Systems, and Global Health

    OpenAIRE

    Stuckler, David; Nestle, Marion

    2012-01-01

    In an article that forms part of the PLoS Medicine series on Big Food, guest editors David Stuckler and Marion Nestle lay out why more examination of the food industry is necessary, and offer three competing views on how public health professionals might engage with Big Food.

  2. In Search of the Big Bubble

    Science.gov (United States)

    Simoson, Andrew; Wentzky, Bethany

    2011-01-01

    Freely rising air bubbles in water sometimes assume the shape of a spherical cap, a shape also known as the "big bubble". Is it possible to find some objective function involving a combination of a bubble's attributes for which the big bubble is the optimal shape? Following the basic idea of the definite integral, we define a bubble's surface as…

  3. Lecture 10: The European Bioinformatics Institute - "Big data" for biomedical sciences

    CERN Document Server

    CERN. Geneva; Dana, Jose

    2013-01-01

    Part 1: Big data for biomedical sciences (Tom Hancocks) Ten years ago witnessed the completion of the first international 'Big Biology' project that sequenced the human genome. In the years since biological sciences, have seen a vast growth in data. In the coming years advances will come from integration of experimental approaches and the translation into applied technologies is the hospital, clinic and even at home. This talk will examine the development of infrastructure, physical and virtual, that will allow millions of life scientists across Europe better access to biological data Tom studied Human Genetics at the University of Leeds and McMaster University, before completing an MSc in Analytical Genomics at the University of Birmingham. He has worked for the UK National Health Service in diagnostic genetics and in training healthcare scientists and clinicians in bioinformatics. Tom joined the EBI in 2012 and is responsible for the scientific development and delivery of training for the BioMedBridges pr...

  4. Learning to Facilitate (Online) Meetings

    DEFF Research Database (Denmark)

    Reimann, Peter; Bull, Susan; Vatrapu, Ravi

    2013-01-01

    We describe an approach to teaching collaboration skills directly by building on competences for meeting facilitation. (Online) meetings provide a rich arena to practice collaboration since they can serve multiple purposes: learning, problem solving, decision making, idea generation and advancement......, etc.. We argue that facilitating meetings is a competence worth developing in students and describe the main knowledge and skill components that pertain to this competence. We then describe some implemented software tools that can be used in schools and colleges to provide opportunities for practicing...... and developing group facilitation skills....

  5. The evolution of the Anopheles 16 genomes project

    NARCIS (Netherlands)

    Neafsey, Daniel E.; Christophides, George K.; Collins, Frank H.; Emrich, Scott J.; Fontaine, Michael C.; Gelbart, William; Hahn, Matthew W.; Howell, Paul I.; Kafatos, Fotis C.; Lawson, Daniel; Muskavitch, Marc A. T.; Waterhouse, Robert M.; Williams, Louise J.; Besansky, Nora J.

    2013-01-01

    We report the imminent completion of a set of reference genome assemblies for 16 species of Anopheles mosquitoes. In addition to providing a generally useful resource for comparative genomic analyses, these genome sequences will greatly facilitate exploration of the capacity exhibited by some Anophe

  6. Recurrent DNA inversion rearrangements in the human genome

    DEFF Research Database (Denmark)

    Flores, Margarita; Morales, Lucía; Gonzaga-Jauregui, Claudia;

    2007-01-01

    Several lines of evidence suggest that reiterated sequences in the human genome are targets for nonallelic homologous recombination (NAHR), which facilitates genomic rearrangements. We have used a PCR-based approach to identify breakpoint regions of rearranged structures in the human genome...

  7. The ethics of biomedical big data

    CERN Document Server

    Mittelstadt, Brent Daniel

    2016-01-01

    This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understan...

  8. Cloud Based Big Data Infrastructure: Architectural Components and Automated Provisioning

    OpenAIRE

    Demchenko, Yuri; Turkmen, Fatih; Blanchet, Christophe; Loomis, Charles; Laat, Caees de

    2016-01-01

    This paper describes the general architecture and functional components of the cloud based Big Data Infrastructure (BDI). The proposed BDI architecture is based on the analysis of the emerging Big Data and data intensive technologies and supported by the definition of the Big Data Architecture Framework (BDAF) that defines the following components of the Big Data technologies: Big Data definition, Data Management including data lifecycle and data structures, Big Data Infrastructure (generical...

  9. Big Data Initiatives for Agroecosystems

    Science.gov (United States)

    NAL has developed a workspace for research groups associated with the i5k initiative, which aims to sequence the genomes of all insesct species known to be important to worldwide agriculture, food safety, medicine, and energy production; all those used as models in biology; the most abundant in worl...

  10. Application Research on Agricultural Big Data%农业领域大数据的应用研究

    Institute of Scientific and Technical Information of China (English)

    光峰; 姚程宽; 王维进

    2015-01-01

    本文将大数据技术在农业中的特点、应用领域进行了详细的阐述,并指出了发展中面临的问题。%With the development of Internet technology and communication technology , human community has entered the era of huge amounts of data .The term “big data” has been very popular in the fields of industry and commerce.Although China is a big agricultural country , the foundation of agriculture is weak and the agricultural productivity is low .Big data technology applied in agriculture can facilitate the improvement of agricultural produc-tion conditions and the increase of farming population ’ s income.In this paper, the characteristics, application fields, as well as the current difficulties of big data applied in agriculture are detailed .

  11. Using Globus GridFTP to Transfer and Share Big Data | Poster

    Science.gov (United States)

    By Ashley DeVine, Staff Writer, and Mark Wance, Guest Writer; photo by Richard Frederickson, Staff Photographer Transferring big data, such as the genomics data delivered to customers from the Center for Cancer Research Sequencing Facility (CCR SF), has been difficult in the past because the transfer systems have not kept pace with the size of the data. However, the situation is changing as a result of the Globus GridFTP project.

  12. Planning for the Future of Epidemiology in the Era of Big Data and Precision Medicine

    OpenAIRE

    Khoury, Muin J.

    2015-01-01

    We live in the era of genomics and big data. Evaluating the impact on health of large-scale biological, social, and environmental data is an emerging challenge in the field of epidemiology. In the past 3 years, major discussions and plans for the future of epidemiology, including with several recommendations for actions to transform the field, have been launched by 2 institutes within the National Institutes of Health. In the present commentary, I briefly explore the themes of these recommend...

  13. On novice facilitators doing research

    DEFF Research Database (Denmark)

    Tavella, Elena

    2016-01-01

    Opportunities for novices to facilitate Problem Structuring Methods (PSMs) workshops are limited, especially because of a lack of access to real-world interventions and confidence in their capabilities. Novices are usually young academics building their careers through publishing. Publishing...

  14. Den gode facilitator af refleksionsarbejde

    DEFF Research Database (Denmark)

    Jørgensen, Pia

    2009-01-01

    tværfaglig lektorgruppe fra social og sundhedssektoren.’Learning by doing’, selvevaluering og sparring følger herefter som bud på, hvordan man kan leve op til de tilsyneladende ret utopiske krav til en god facilitator. At kunne skabe det tillidsfulde refleksionsrum og at kunne stille gode...... præsenteres i det følgende afsnit, og forfatteren argumenterer for begrebet facilitator af refleksionsarbejde. Herefter udfoldes rollen som facilitator ifølge Ghay og Lillyman. De har fokus på positive praksisoplevelser og tillidsfulde relationer. Gillie Boltons teoretiske og praktiske referenceramme...... for facilitatorrollen beskrives herefter. Bolton beskriver refleksionsarbejde som en fysisk (ikke ren kognitiv), passioneret (ikke ren intellektuel) kontekstbunden kunstnerisk proces, som kræver flair, stil og intuition. I de følgende afsnit beskrives den gode facilitator af refleksionsarbejde detaljeret af en...

  15. Facilitative root interactions in intercrops

    DEFF Research Database (Denmark)

    Hauggaard-Nielsen, H.; Jensen, E.S.

    2005-01-01

    Facilitation takes place when plants ameliorate the environment of their neighbours, and increase their growth and survival. Facilitation occurs in natural ecosystems as well as in agroecosystems. We discuss examples of facilitative root interactions in intercropped agroecosystems; including...... of root architecture, exudation of growth stimulating substances, and biofumigation. Facilitative root interactions are most likely to be of importance in nutrient poor soils and in low-input agroecosystems due to critical interspecific competition for plant growth factors. However, studies from more...... nitrogen transfer between legumes and non-leguminous plants, exploitation of the soil via mycorrhizal fungi and soil-plant processes which alter the mobilisation of plant growth resources such as through exudation of amino acids, extra-cellular enzymes, acidification, competition-induced modification...

  16. Big Book of Apple Hacks

    CERN Document Server

    Seibold, Chris

    2008-01-01

    Bigger in size, longer in length, broader in scope, and even more useful than our original Mac OS X Hacks, the new Big Book of Apple Hacks offers a grab bag of tips, tricks and hacks to get the most out of Mac OS X Leopard, as well as the new line of iPods, iPhone, and Apple TV. With 125 entirely new hacks presented in step-by-step fashion, this practical book is for serious Apple computer and gadget users who really want to take control of these systems. Many of the hacks take you under the hood and show you how to tweak system preferences, alter or add keyboard shortcuts, mount drives and

  17. Was the Big Bang hot?

    Science.gov (United States)

    Wright, E. L.

    1983-01-01

    Techniques for verifying the spectrum defined by Woody and Richards (WR, 1981), which serves as a base for dust-distorted models of the 3 K background, are discussed. WR detected a sharp deviation from the Planck curve in the 3 K background. The absolute intensity of the background may be determined by the frequency dependence of the dipole anisotropy of the background or the frequency dependence effect in galactic clusters. Both methods involve the Doppler shift; analytical formulae are defined for characterization of the dipole anisotropy. The measurement of the 30-300 GHz spectra of cold galactic dust may reveal the presence of significant amounts of needle-shaped grains, which would in turn support a theory of a cold Big Bang.

  18. Advancements in Big Data Processing

    CERN Document Server

    Vaniachine, A; The ATLAS collaboration

    2012-01-01

    The ever-increasing volumes of scientific data present new challenges for Distributed Computing and Grid-technologies. The emerging Big Data revolution drives new discoveries in scientific fields including nanotechnology, astrophysics, high-energy physics, biology and medicine. New initiatives are transforming data-driven scientific fields by pushing Bid Data limits enabling massive data analysis in new ways. In petascale data processing scientists deal with datasets, not individual files. As a result, a task (comprised of many jobs) became a unit of petascale data processing on the Grid. Splitting of a large data processing task into jobs enabled fine-granularity checkpointing analogous to the splitting of a large file into smaller TCP/IP packets during data transfers. Transferring large data in small packets achieves reliability through automatic re-sending of the dropped TCP/IP packets. Similarly, transient job failures on the Grid can be recovered by automatic re-tries to achieve reliable Six Sigma produc...

  19. Exploring Relationships in Big Data

    Science.gov (United States)

    Mahabal, A.; Djorgovski, S. G.; Crichton, D. J.; Cinquini, L.; Kelly, S.; Colbert, M. A.; Kincaid, H.

    2015-12-01

    Big Data are characterized by several different 'V's. Volume, Veracity, Volatility, Value and so on. For many datasets inflated Volumes through redundant features often make the data more noisy and difficult to extract Value out of. This is especially true if one is comparing/combining different datasets, and the metadata are diverse. We have been exploring ways to exploit such datasets through a variety of statistical machinery, and visualization. We show how we have applied it to time-series from large astronomical sky-surveys. This was done in the Virtual Observatory framework. More recently we have been doing similar work for a completely different domain viz. biology/cancer. The methodology reuse involves application to diverse datasets gathered through the various centers associated with the Early Detection Research Network (EDRN) for cancer, an initiative of the National Cancer Institute (NCI). Application to Geo datasets is a natural extension.

  20. Island Universe or Big Galaxy?

    Science.gov (United States)

    Wolfschmidt, Gudrun

    In 1920, the "great debate" took place: Harlow Shapley defended his model of the "Big Galaxy", i.e. we live in a large galaxy and all nebulous objects belong to our galaxy. He got this result from the distribution of the globular nebulae. Heber D. Curtis on the other side analyzed novae and was then convinced that nebulae are far distant objects which are stellar systems themselves like our galaxy. The solution of the discussion was brought by Edwin P. Hubble who confirmed the interpretation of nebulae as extragalactic objects, i.e. galaxies, and introduced the red shift for getting the distance of galaxies. The resulting expansion of the universe led to a new cosmological world view.

  1. Facilitation Skills for Library Professionals

    OpenAIRE

    O'Shea, Anne; Matheson, Laura

    2010-01-01

    Session summary: Brainstorming, problem-solving, team-building and group communication – all of these things can be made easier through facilitation! Come to this fun, interactive workshop to learn techniques and exercises to boost your group meetings. Taught by two information professionals with formal facilitation training and experience, this workshop will give you theory, hands-on practice time and feedback. What participants will learn: Participants will learn techniques to he...

  2. [Bioinformatics of tumor molecular targets from big data].

    Science.gov (United States)

    Huang, Jinyan; Yu, Yingyan

    2015-01-01

    The big data from high throughput research disclosed 4V features: volume of data, variety of data, value for deep mining, and velocity of processing speed. Regarding the whole genome sequencing for human sample, at average 30x of coverage, a total of 100 GB of original data (compression FASTQ format) could be produced. Replying to the binary BAM format, a total of 150 GB data could be produced. In the analysis of high throughput data, we need to combine both clinical information and pathological features. In addition, the data sources of medical research involved in ethical and privacy of patients. At present, the costs are gradually cheaper. For example, a whole genome sequencing by Illumina X Ten with 30x coverage costs about 10,000 RMB, and RNA-seq costs 5000 RMB for a single sample. Therefore, cancer genome research provides opportunities for discovery of molecular targets, but also brings enormous challenges on the data integration and utilization. This article introduces methodologies for high throughput data analysis and processing, and explains possible application on molecular target discovery. PMID:25656022

  3. Microsystems - The next big thing

    Energy Technology Data Exchange (ETDEWEB)

    STINNETT,REGAN W.

    2000-05-11

    Micro-Electro-Mechanical Systems (MEMS) is a big name for tiny devices that will soon make big changes in everyday life and the workplace. These and other types of Microsystems range in size from a few millimeters to a few microns, much smaller than a human hair. These Microsystems have the capability to enable new ways to solve problems in commercial applications ranging from automotive, aerospace, telecommunications, manufacturing equipment, medical diagnostics to robotics, and in national security applications such as nuclear weapons safety and security, battlefield intelligence, and protection against chemical and biological weapons. This broad range of applications of Microsystems reflects the broad capabilities of future Microsystems to provide the ability to sense, think, act, and communicate, all in a single integrated package. Microsystems have been called the next silicon revolution, but like many revolutions, they incorporate more elements than their predecessors. Microsystems do include MEMS components fabricated from polycrystalline silicon processed using techniques similar to those used in the manufacture of integrated electrical circuits. They also include optoelectronic components made from gallium arsenide and other semiconducting compounds from the III-V groups of the periodic table. Microsystems components are also being made from pure metals and metal alloys using the LIGA process, which utilizes lithography, etching, and casting at the micron scale. Generically, Microsystems are micron scale, integrated systems that have the potential to combine the ability to sense light, heat, pressure, acceleration, vibration, and chemicals with the ability to process the collected data using CMOS circuitry, execute an electrical, mechanical, or photonic response, and communicate either optically or with microwaves.

  4. Design and development of a medical big data processing system based on Hadoop.

    Science.gov (United States)

    Yao, Qin; Tian, Yu; Li, Peng-Fei; Tian, Li-Li; Qian, Yang-Ming; Li, Jing-Song

    2015-03-01

    Secondary use of medical big data is increasingly popular in healthcare services and clinical research. Understanding the logic behind medical big data demonstrates tendencies in hospital information technology and shows great significance for hospital information systems that are designing and expanding services. Big data has four characteristics--Volume, Variety, Velocity and Value (the 4 Vs)--that make traditional systems incapable of processing these data using standalones. Apache Hadoop MapReduce is a promising software framework for developing applications that process vast amounts of data in parallel with large clusters of commodity hardware in a reliable, fault-tolerant manner. With the Hadoop framework and MapReduce application program interface (API), we can more easily develop our own MapReduce applications to run on a Hadoop framework that can scale up from a single node to thousands of machines. This paper investigates a practical case of a Hadoop-based medical big data processing system. We developed this system to intelligently process medical big data and uncover some features of hospital information system user behaviors. This paper studies user behaviors regarding various data produced by different hospital information systems for daily work. In this paper, we also built a five-node Hadoop cluster to execute distributed MapReduce algorithms. Our distributed algorithms show promise in facilitating efficient data processing with medical big data in healthcare services and clinical research compared with single nodes. Additionally, with medical big data analytics, we can design our hospital information systems to be much more intelligent and easier to use by making personalized recommendations. PMID:25666927

  5. Big Data, data integrity, and the fracturing of the control zone

    Directory of Open Access Journals (Sweden)

    Carl Lagoze

    2014-11-01

    Full Text Available Despite all the attention to Big Data and the claims that it represents a “paradigm shift” in science, we lack understanding about what are the qualities of Big Data that may contribute to this revolutionary impact. In this paper, we look beyond the quantitative aspects of Big Data (i.e. lots of data and examine it from a sociotechnical perspective. We argue that a key factor that distinguishes “Big Data” from “lots of data” lies in changes to the traditional, well-established “control zones” that facilitated clear provenance of scientific data, thereby ensuring data integrity and providing the foundation for credible science. The breakdown of these control zones is a consequence of the manner in which our network technology and culture enable and encourage open, anonymous sharing of information, participation regardless of expertise, and collaboration across geographic, disciplinary, and institutional barriers. We are left with the conundrum—how to reap the benefits of Big Data while re-creating a trust fabric and an accountable chain of responsibility that make credible science possible.

  6. Secure Genomic Computation through Site-Wise Encryption.

    Science.gov (United States)

    Zhao, Yongan; Wang, XiaoFeng; Tang, Haixu

    2015-01-01

    Commercial clouds provide on-demand IT services for big-data analysis, which have become an attractive option for users who have no access to comparable infrastructure. However, utilizing these services for human genome analysis is highly risky, as human genomic data contains identifiable information of human individuals and their disease susceptibility. Therefore, currently, no computation on personal human genomic data is conducted on public clouds. To address this issue, here we present a site-wise encryption approach to encrypt whole human genome sequences, which can be subject to secure searching of genomic signatures on public clouds. We implemented this method within the Hadoop framework, and tested it on the case of searching disease markers retrieved from the ClinVar database against patients' genomic sequences. The secure search runs only one order of magnitude slower than the simple search without encryption, indicating our method is ready to be used for secure genomic computation on public clouds. PMID:26306278

  7. Success factors in cluster initiative management: Mapping out the ‘big five’

    OpenAIRE

    Klofsten, Magnus; Bienkowska, Dzamila; Laur, Inessa; Sölvell, Ingela

    2015-01-01

    Cluster development is prioritized in policy programmes as a means to facilitate regional growth and job creation. Triple Helix actors are often involved in so-called cluster initiatives – intermediary organizations having the objective of the development of a local or regional cluster. This paper maps out the ‘big five’ qualitative success factors in cluster initiative management: the idea; driving forces and commitment; activities; critical mass; and organization. The proposed framework ena...

  8. What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets

    Directory of Open Access Journals (Sweden)

    Rob Kitchin

    2016-02-01

    Full Text Available Big Data has been variously defined in the literature. In the main, definitions suggest that Big Data possess a suite of key traits: volume, velocity and variety (the 3Vs, but also exhaustivity, resolution, indexicality, relationality, extensionality and scalability. However, these definitions lack ontological clarity, with the term acting as an amorphous, catch-all label for a wide selection of data. In this paper, we consider the question ‘what makes Big Data, Big Data?’, applying Kitchin’s taxonomy of seven Big Data traits to 26 datasets drawn from seven domains, each of which is considered in the literature to constitute Big Data. The results demonstrate that only a handful of datasets possess all seven traits, and some do not possess either volume and/or variety. Instead, there are multiple forms of Big Data. Our analysis reveals that the key definitional boundary markers are the traits of velocity and exhaustivity. We contend that Big Data as an analytical category needs to be unpacked, with the genus of Big Data further delineated and its various species identified. It is only through such ontological work that we will gain conceptual clarity about what constitutes Big Data, formulate how best to make sense of it, and identify how it might be best used to make sense of the world.

  9. [Big data in medicine and healthcare].

    Science.gov (United States)

    Rüping, Stefan

    2015-08-01

    Healthcare is one of the business fields with the highest Big Data potential. According to the prevailing definition, Big Data refers to the fact that data today is often too large and heterogeneous and changes too quickly to be stored, processed, and transformed into value by previous technologies. The technological trends drive Big Data: business processes are more and more executed electronically, consumers produce more and more data themselves - e.g. in social networks - and finally ever increasing digitalization. Currently, several new trends towards new data sources and innovative data analysis appear in medicine and healthcare. From the research perspective, omics-research is one clear Big Data topic. In practice, the electronic health records, free open data and the "quantified self" offer new perspectives for data analytics. Regarding analytics, significant advances have been made in the information extraction from text data, which unlocks a lot of data from clinical documentation for analytics purposes. At the same time, medicine and healthcare is lagging behind in the adoption of Big Data approaches. This can be traced to particular problems regarding data complexity and organizational, legal, and ethical challenges. The growing uptake of Big Data in general and first best-practice examples in medicine and healthcare in particular, indicate that innovative solutions will be coming. This paper gives an overview of the potentials of Big Data in medicine and healthcare.

  10. The life cycle of a genome project: perspectives and guidelines inspired by insect genome projects.

    Science.gov (United States)

    Papanicolaou, Alexie

    2016-01-01

    Many research programs on non-model species biology have been empowered by genomics. In turn, genomics is underpinned by a reference sequence and ancillary information created by so-called "genome projects". The most reliable genome projects are the ones created as part of an active research program and designed to address specific questions but their life extends past publication. In this opinion paper I outline four key insights that have facilitated maintaining genomic communities: the key role of computational capability, the iterative process of building genomic resources, the value of community participation and the importance of manual curation. Taken together, these ideas can and do ensure the longevity of genome projects and the growing non-model species community can use them to focus a discussion with regards to its future genomic infrastructure.

  11. The life cycle of a genome project: perspectives and guidelines inspired by insect genome projects.

    Science.gov (United States)

    Papanicolaou, Alexie

    2016-01-01

    Many research programs on non-model species biology have been empowered by genomics. In turn, genomics is underpinned by a reference sequence and ancillary information created by so-called "genome projects". The most reliable genome projects are the ones created as part of an active research program and designed to address specific questions but their life extends past publication. In this opinion paper I outline four key insights that have facilitated maintaining genomic communities: the key role of computational capability, the iterative process of building genomic resources, the value of community participation and the importance of manual curation. Taken together, these ideas can and do ensure the longevity of genome projects and the growing non-model species community can use them to focus a discussion with regards to its future genomic infrastructure. PMID:27006757

  12. Genomic dairy cattle breeding

    DEFF Research Database (Denmark)

    Mark, Thomas; Sandøe, Peter

    2010-01-01

    it less accountable to the concern of private farmers for the welfare of their animals. It is argued that there is a need to mobilise a wide range of stakeholders to monitor developments and maintain pressure on breeding companies so that they are aware of the need to take precautionary measures to avoid...... these new genomic tools are especially useful for traits relating to animal welfare that are difficult to improve using traditional breeding tools, they may also facilitate breeding schemes with reduced generation intervals carrying a higher risk of unwanted side-effects on animal welfare. In this paper...... negative effects on animal welfare and to invest in breeding for increased animal welfare. Researchers are encouraged to further investigate the long-term effects of various breeding schemes that rely on genomic breeding values....

  13. A Big Bang model of human colorectal tumor growth.

    Science.gov (United States)

    Sottoriva, Andrea; Kang, Haeyoun; Ma, Zhicheng; Graham, Trevor A; Salomon, Matthew P; Zhao, Junsong; Marjoram, Paul; Siegmund, Kimberly; Press, Michael F; Shibata, Darryl; Curtis, Christina

    2015-03-01

    What happens in early, still undetectable human malignancies is unknown because direct observations are impractical. Here we present and validate a 'Big Bang' model, whereby tumors grow predominantly as a single expansion producing numerous intermixed subclones that are not subject to stringent selection and where both public (clonal) and most detectable private (subclonal) alterations arise early during growth. Genomic profiling of 349 individual glands from 15 colorectal tumors showed an absence of selective sweeps, uniformly high intratumoral heterogeneity (ITH) and subclone mixing in distant regions, as postulated by our model. We also verified the prediction that most detectable ITH originates from early private alterations and not from later clonal expansions, thus exposing the profile of the primordial tumor. Moreover, some tumors appear 'born to be bad', with subclone mixing indicative of early malignant potential. This new model provides a quantitative framework to interpret tumor growth dynamics and the origins of ITH, with important clinical implications. PMID:25665006

  14. RIKEN mouse genome encyclopedia.

    Science.gov (United States)

    Hayashizaki, Yoshihide

    2003-01-01

    We have been working to establish the comprehensive mouse full-length cDNA collection and sequence database to cover as many genes as we can, named Riken mouse genome encyclopedia. Recently we are constructing higher-level annotation (Functional ANnoTation Of Mouse cDNA; FANTOM) not only with homology search based annotation but also with expression data profile, mapping information and protein-protein database. More than 1,000,000 clones prepared from 163 tissues were end-sequenced to classify into 159,789 clusters and 60,770 representative clones were fully sequenced. As a conclusion, the 60,770 sequences contained 33,409 unique. The next generation of life science is clearly based on all of the genome information and resources. Based on our cDNA clones we developed the additional system to explore gene function. We developed cDNA microarray system to print all of these cDNA clones, protein-protein interaction screening system, protein-DNA interaction screening system and so on. The integrated database of all the information is very useful not only for analysis of gene transcriptional network and for the connection of gene to phenotype to facilitate positional candidate approach. In this talk, the prospect of the application of these genome resourced should be discussed. More information is available at the web page: http://genome.gsc.riken.go.jp/.

  15. Big questions, big science: meeting the challenges of global ecology.

    Science.gov (United States)

    Schimel, David; Keller, Michael

    2015-04-01

    Ecologists are increasingly tackling questions that require significant infrastucture, large experiments, networks of observations, and complex data and computation. Key hypotheses in ecology increasingly require more investment, and larger data sets to be tested than can be collected by a single investigator's or s group of investigator's labs, sustained for longer than a typical grant. Large-scale projects are expensive, so their scientific return on the investment has to justify the opportunity cost-the science foregone because resources were expended on a large project rather than supporting a number of individual projects. In addition, their management must be accountable and efficient in the use of significant resources, requiring the use of formal systems engineering and project management to mitigate risk of failure. Mapping the scientific method into formal project management requires both scientists able to work in the context, and a project implementation team sensitive to the unique requirements of ecology. Sponsoring agencies, under pressure from external and internal forces, experience many pressures that push them towards counterproductive project management but a scientific community aware and experienced in large project science can mitigate these tendencies. For big ecology to result in great science, ecologists must become informed, aware and engaged in the advocacy and governance of large ecological projects. PMID:25680334

  16. Processing Solutions for Big Data in Astronomy

    Science.gov (United States)

    Fillatre, L.; Lepiller, D.

    2016-09-01

    This paper gives a simple introduction to processing solutions applied to massive amounts of data. It proposes a general presentation of the Big Data paradigm. The Hadoop framework, which is considered as the pioneering processing solution for Big Data, is described together with YARN, the integrated Hadoop tool for resource allocation. This paper also presents the main tools for the management of both the storage (NoSQL solutions) and computing capacities (MapReduce parallel processing schema) of a cluster of machines. Finally, more recent processing solutions like Spark are discussed. Big Data frameworks are now able to run complex applications while keeping the programming simple and greatly improving the computing speed.

  17. Big data governance an emerging imperative

    CERN Document Server

    Soares, Sunil

    2012-01-01

    Written by a leading expert in the field, this guide focuses on the convergence of two major trends in information management-big data and information governance-by taking a strategic approach oriented around business cases and industry imperatives. With the advent of new technologies, enterprises are expanding and handling very large volumes of data; this book, nontechnical in nature and geared toward business audiences, encourages the practice of establishing appropriate governance over big data initiatives and addresses how to manage and govern big data, highlighting the relevant processes,

  18. BLENDING IOT AND BIG DATA ANALYTICS

    OpenAIRE

    Tulasi.B*; Girish J Vemulkar

    2016-01-01

    Internet is continuously evolving and changing. Internet of Things (IoT) can be considered as the future of Internet applications which involves machine to machine learning (M2M). The actionable intelligence can be derived through fusion of Big Data and real time analytics with IoT. Big Data and IoT can be viewed as two sides of a coin. With the connection between Big Data and the objects on Internet benefits of IoT can be easily reaped. The applications of IoT spread across various domains l...

  19. Big data and the electronic health record.

    Science.gov (United States)

    Peters, Steve G; Buntrock, James D

    2014-01-01

    The electronic medical record has evolved from a digital representation of individual patient results and documents to information of large scale and complexity. Big Data refers to new technologies providing management and processing capabilities, targeting massive and disparate data sets. For an individual patient, techniques such as Natural Language Processing allow the integration and analysis of textual reports with structured results. For groups of patients, Big Data offers the promise of large-scale analysis of outcomes, patterns, temporal trends, and correlations. The evolution of Big Data analytics moves us from description and reporting to forecasting, predictive modeling, and decision optimization. PMID:24887521

  20. Big Data and historical social science

    Directory of Open Access Journals (Sweden)

    Peter Bearman

    2015-11-01

    Full Text Available “Big Data” can revolutionize historical social science if it arises from substantively important contexts and is oriented towards answering substantively important questions. Such data may be especially important for answering previously largely intractable questions about the timing and sequencing of events, and of event boundaries. That said, “Big Data” makes no difference for social scientists and historians whose accounts rest on narrative sentences. Since such accounts are the norm, the effects of Big Data on the practice of historical social science may be more limited than one might wish.

  1. Big data and the electronic health record.

    Science.gov (United States)

    Peters, Steve G; Buntrock, James D

    2014-01-01

    The electronic medical record has evolved from a digital representation of individual patient results and documents to information of large scale and complexity. Big Data refers to new technologies providing management and processing capabilities, targeting massive and disparate data sets. For an individual patient, techniques such as Natural Language Processing allow the integration and analysis of textual reports with structured results. For groups of patients, Big Data offers the promise of large-scale analysis of outcomes, patterns, temporal trends, and correlations. The evolution of Big Data analytics moves us from description and reporting to forecasting, predictive modeling, and decision optimization.

  2. Swine Genome Science Comes of Age

    Directory of Open Access Journals (Sweden)

    Zhihua Jiang, Max F. Rothschild

    2007-01-01

    Full Text Available Pigs were among the first animals to be domesticated and pork is one of the most widely eaten meats in the world today. The pig has also been an excellent biomedical model for understanding a variety of human health issues such as obesity, diabetes, cancer, female reproductive health, cardiovascular disease, and infectious diseases. Genome sequencing, mapping, expression and functional analyses have significantly advanced our ability to unravel the secrets of the pig. Therefore, this edition, with six reviews from leading scientists, offers the opportunity for all interested researchers and readers to see the big picture of porcine genomics.

  3. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    Energy Technology Data Exchange (ETDEWEB)

    Susan M. Capalbo

    2004-06-01

    The Big Sky Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts during the second performance period fall into four areas: evaluation of sources and carbon sequestration sinks; development of GIS-based reporting framework; designing an integrated suite of monitoring, measuring, and verification technologies; and initiating a comprehensive education and outreach program. At the first two Partnership meetings the groundwork was put in place to provide an assessment of capture and storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other western DOE partnerships. Efforts are also being made to find funding to include Wyoming in the coverage areas for both geological and terrestrial sinks and sources. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts begun in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best management practices for

  4. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    Energy Technology Data Exchange (ETDEWEB)

    Susan M. Capalbo

    2004-01-04

    The Big Sky Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts during the first performance period fall into four areas: evaluation of sources and carbon sequestration sinks; development of GIS-based reporting framework; designing an integrated suite of monitoring, measuring, and verification technologies; and initiating a comprehensive education and outreach program. At the first Partnership meeting the groundwork was put in place to provide an assessment of capture and storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Complementary to the efforts on evaluation of sources and sinks is the development of the Big Sky Partnership Carbon Cyberinfrastructure (BSP-CC) and a GIS Road Map for the Partnership. These efforts will put in place a map-based integrated information management system for our Partnership, with transferability to the national carbon sequestration effort. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but other policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts begun in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best

  5. Soil biogeochemistry in the age of big data

    Science.gov (United States)

    Cécillon, Lauric; Barré, Pierre; Coissac, Eric; Plante, Alain; Rasse, Daniel

    2015-04-01

    Data is becoming one of the key resource of the XXIst century. Soil biogeochemistry is not spared by this new movement. The conservation of soils and their services recently came into the political agenda. However, clear knowledge on the links between soil characteristics and the various processes ensuring the provision of soil services is rare at the molecular or the plot scale, and does not exist at the landscape scale. This split between society's expectations on its natural capital, and scientific knowledge on the most complex material on earth has lead to an increasing number of studies on soils, using an increasing number of techniques of increasing complexity, with an increasing spatial and temporal coverage. From data scarcity with a basic data management system, soil biogeochemistry is now facing a proliferation of data, with few quality controls from data collection to publication and few skills to deal with them. Based on this observation, here we (1) address how big data could help in making sense of all these soil biogeochemical data, (2) point out several shortcomings of big data that most biogeochemists will experience in their future career. Massive storage of data is now common and recent opportunities for cloud storage enables data sharing among researchers all over the world. The need for integrative and collaborative computational databases in soil biogeochemistry is emerging through pioneering initiatives in this direction (molTERdb; earthcube), following soil microbiologists (GenBank). We expect that a series of data storage and management systems will rapidly revolutionize the way of accessing raw biogeochemical data, published or not. Data mining techniques combined with cluster or cloud computing hold significant promises for facilitating the use of complex analytical methods, and for revealing new insights previously hidden in complex data on soil mineralogy, organic matter and biodiversity. Indeed, important scientific advances have

  6. «Sochi Goes International» – Required Actions to be Taken to Facilitate the Stay for International Tourists

    Directory of Open Access Journals (Sweden)

    Eduard Besel

    2012-09-01

    Full Text Available As host city of many big international sport events, Sochi's publicity is increasing and people from all over the world will discover it as a new travel destination. To guarantee and enlarge the attractiveness and popularity of the city, some essential improvements, which would facilitate the stay for international tourists, are recommended.

  7. BIG DATA, BIG CONSEQUENCES? EEN VERKENNING NAAR PRIVACY EN BIG DATA GEBRUIK BINNEN DE OPSPORING, VERVOLGING EN RECHTSPRAAK

    OpenAIRE

    Lodder, A.R.; Meulen, van der, N.; Wisman, T.H.A.; Meij, Lisette; Zwinkels, C.M.M.

    2014-01-01

    In deze verkenning is ingegaan op de privacy aspecten van Big Data analysis binnen het domein Veiligheid en Justitie. Besproken zijn toepassingen binnen de rechtspraak zoals voorspellen van uitspraken en gebruik in rechtszaken. Met betrekking tot opsporing is onder andere ingegaan op predictive policing en internetopsporing. Na een uiteenzetting van de privacynormen en toepassingsmogelijkheden, zijn de volgende zes uitgangspunten voor Big Data toepassingen voorgesteld: 7 A.R. Lodder e.a. ‐ Bi...

  8. NOAA Big Data Partnership RFI

    Science.gov (United States)

    de la Beaujardiere, J.

    2014-12-01

    In February 2014, the US National Oceanic and Atmospheric Administration (NOAA) issued a Big Data Request for Information (RFI) from industry and other organizations (e.g., non-profits, research laboratories, and universities) to assess capability and interest in establishing partnerships to position a copy of NOAA's vast data holdings in the Cloud, co-located with easy and affordable access to analytical capabilities. This RFI was motivated by a number of concerns. First, NOAA's data facilities do not necessarily have sufficient network infrastructure to transmit all available observations and numerical model outputs to all potential users, or sufficient infrastructure to support simultaneous computation by many users. Second, the available data are distributed across multiple services and data facilities, making it difficult to find and integrate data for cross-domain analysis and decision-making. Third, large datasets require users to have substantial network, storage, and computing capabilities of their own in order to fully interact with and exploit the latent value of the data. Finally, there may be commercial opportunities for value-added products and services derived from our data. Putting a working copy of data in the Cloud outside of NOAA's internal networks and infrastructures should reduce demands and risks on our systems, and should enable users to interact with multiple datasets and create new lines of business (much like the industries built on government-furnished weather or GPS data). The NOAA Big Data RFI therefore solicited information on technical and business approaches regarding possible partnership(s) that -- at no net cost to the government and minimum impact on existing data facilities -- would unleash the commercial potential of its environmental observations and model outputs. NOAA would retain the master archival copy of its data. Commercial partners would not be permitted to charge fees for access to the NOAA data they receive, but

  9. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    Energy Technology Data Exchange (ETDEWEB)

    Susan M. Capalbo

    2005-01-31

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership in Phase I fall into four areas: evaluation of sources and carbon sequestration sinks that will be used to determine the location of pilot demonstrations in Phase II; development of GIS-based reporting framework that links with national networks; designing an integrated suite of monitoring, measuring, and verification technologies and assessment frameworks; and initiating a comprehensive education and outreach program. The groundwork is in place to provide an assessment of storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. Efforts are underway to showcase the architecture of the GIS framework and initial results for sources and sinks. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other western DOE partnerships. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is

  10. Distributed and Big Data Storage Management in Grid Computing

    Directory of Open Access Journals (Sweden)

    Ajay Kumar

    2012-07-01

    Full Text Available Big data storage management is one of the most challenging issues for Grid computing environments, since large amount of data intensive applications frequently involve a high degree of data access locality. Grid applications typically deal with large amounts of data. In traditional approaches high-performance computing consists dedicated servers that are used to data storage and data replication. In this paper we present a new mechanism for distributed and big data storage and resource discovery services. Here we proposed an architecture named Dynamic and Scalable Storage Management (DSSM architecture in grid environments. This allows in grid computing not only sharing the computational cycles, but also share the storage space. The storage can be transparently accessed from any grid machine, allowing easy data sharing among grid users and applications. The concept of virtual ids that, allows the creation of virtual spaces has been introduced and used. The DSSM divides all Grid Oriented Storage devices (nodes into multiple geographically distributed domains and to facilitate the locality and simplify the intra-domain storage management. Grid service based storage resources are adopted to stack simple modular service piece by piece as demand grows. To this end, we propose four axes that define: DSSM architecture and algorithms description, Storage resources and resource discovery into Grid service, Evaluate purpose prototype system, dynamically, scalability, and bandwidth, and Discuss results. Algorithms at bottom and upper level for standardization dynamic and scalable storage management, along with higher bandwidths have been designed.

  11. Intelligent Decisional Assistant that Facilitate the Choice of a Proper Computer System Applied in Busines

    Directory of Open Access Journals (Sweden)

    Nicolae MARGINEAN

    2009-01-01

    Full Text Available The choice of a proper computer system is not an easy task for a decider. One reason could be the present market development of computer systems applied in business. The big number of the Romanian market players determines a big number of computerized products, with a multitude of various properties. Our proposal tries to optimize and facilitate this decisional process within an e-shop where are sold IT packets applied in business, building an online decisional assistant, a special component conceived to facilitate the decision making needed for the selection of the pertinent IT package that fits the requirements of one certain business, described by the decider. The user interacts with the system as an online buyer that visit an e-shop where are sold IT package applied in economy.

  12. Big Bang–Big Crunch Optimization Algorithm for Linear Phase Fir Digital Filter Design

    Directory of Open Access Journals (Sweden)

    Ms. Rashmi Singh Dr. H. K. Verma

    2012-02-01

    Full Text Available The Big Bang–Big Crunch (BB–BC optimization algorithm is a new optimization method that relies on the Big Bang and Big Crunch theory, one of the theories of the evolution of the universe. In this paper, a Big Bang–Big Crunch algorithm has been used here for the design of linear phase finite impulse response (FIR filters. Here the experimented fitness function based on the mean squared error between the actual and the ideal filter response. This paper presents the plot of magnitude response of FIR filters and error graph. The BB-BC seems to be promising tool for FIR filter design especially in a dynamic environment where filter coefficients have to be adapted and fast convergence is of importance.

  13. 6 Top Tools for Taming Big Data%6Top Tools for Taming Big Data

    Institute of Scientific and Technical Information of China (English)

    JakoB BJ orklund

    2012-01-01

    The industry now has a buzzword,"big data," for how we're going to do something with the huge amount of information piling up."Big data" is replacing "business intelligence,"which subsumed "reporting," which put a nicer gloss on "spreadsheets," which beat out the old-fashioned "printouts."Managers who long ago studied printouts are now hiring mathematicians who claim to be big data specialists to help them solve the same old problem:What's selling and why?

  14. "Big Data" : big gaps of knowledge in the field of internet science

    OpenAIRE

    Snijders, CCP Chris; Matzat, U Uwe; Reips, UD

    2012-01-01

    Research on so-called 'Big Data' has received a considerable momentum and is expected to grow in the future. One very interesting stream of research on Big Data analyzes online networks. Many online networks are known to have some typical macro-characteristics, such as 'small world' properties. Much less is known about underlying micro-processes leading to these properties. The models used by Big Data researchers usually are inspired by mathematical ease of exposition. We propose to follow in...

  15. BDGS: A Scalable Big Data Generator Suite in Big Data Benchmarking

    OpenAIRE

    Ming, Zijian; Luo, Chunjie; Gao, Wanling; Han, Rui; Yang, Qiang; Wang, Lei; Zhan, Jianfeng

    2014-01-01

    Data generation is a key issue in big data benchmarking that aims to generate application-specific data sets to meet the 4V requirements of big data. Specifically, big data generators need to generate scalable data (Volume) of different types (Variety) under controllable generation rates (Velocity) while keeping the important characteristics of raw data (Veracity). This gives rise to various new challenges about how we design generators efficiently and successfully. To date, most existing tec...

  16. Figure 1 from Integrative Genomics Viewer: Visualizing Big Data | Office of Cancer Genomics

    Science.gov (United States)

    A screenshot of the IGV user interface at the chromosome view. IGV user interface showing five data types (copy number, methylation, gene expression, and loss of heterozygosity; mutations are overlaid with black boxes) from approximately 80 glioblastoma multiforme samples. Adapted from Figure S1; Robinson et al. 2011

  17. Conjecture on Avoidance of Big Crunch

    Institute of Scientific and Technical Information of China (English)

    SUN Cheng-Yi; ZHANG De-Hai

    2006-01-01

    By conjecturing the physics at the Planck scale, we modify the definition of the Hawking temperature and modify the Friedmann equation. It is found that we can avoid the singularity of the big crunch and obtain a bouncing cosmological model.

  18. Big Data for Business Ecosystem Players

    Directory of Open Access Journals (Sweden)

    Perko Igor

    2016-06-01

    Full Text Available In the provided research, some of the Big Data most prospective usage domains connect with distinguished player groups found in the business ecosystem. Literature analysis is used to identify the state of the art of Big Data related research in the major domains of its use-namely, individual marketing, health treatment, work opportunities, financial services, and security enforcement. System theory was used to identify business ecosystem major player types disrupted by Big Data: individuals, small and mid-sized enterprises, large organizations, information providers, and regulators. Relationships between the domains and players were explained through new Big Data opportunities and threats and by players’ responsive strategies. System dynamics was used to visualize relationships in the provided model.

  19. Fisicos argentinos reproduciran el Big Bang

    CERN Multimedia

    De Ambrosio, Martin

    2008-01-01

    Two groups of argentine physicists from La Plata and Buenos Aires Universities work in a sery of experiments who while recreate the conditions of the big explosion that was at the origin of the universe. (1 page)

  20. Big Data Components for Business Process Optimization

    Directory of Open Access Journals (Sweden)

    Mircea Raducu TRIFU

    2016-01-01

    Full Text Available In these days, more and more people talk about Big Data, Hadoop, noSQL and so on, but very few technical people have the necessary expertise and knowledge to work with those concepts and technologies. The present issue explains one of the concept that stand behind two of those keywords, and this is the map reduce concept. MapReduce model is the one that makes the Big Data and Hadoop so powerful, fast, and diverse for business process optimization. MapReduce is a programming model with an implementation built to process and generate large data sets. In addition, it is presented the benefits of integrating Hadoop in the context of Business Intelligence and Data Warehousing applications. The concepts and technologies behind big data let organizations to reach a variety of objectives. Like other new information technologies, the main important objective of big data technology is to bring dramatic cost reduction.

  1. Cosmic relics from the big bang

    International Nuclear Information System (INIS)

    A brief introduction to the big bang picture of the early universe is given. Dark matter is discussed; particularly its implications for elementary particle physics. A classification scheme for dark matter relics is given. 21 refs., 11 figs., 1 tab

  2. Soft computing in big data processing

    CERN Document Server

    Park, Seung-Jong; Lee, Jee-Hyong

    2014-01-01

    Big data is an essential key to build a smart world as a meaning of the streaming, continuous integration of large volume and high velocity data covering from all sources to final destinations. The big data range from data mining, data analysis and decision making, by drawing statistical rules and mathematical patterns through systematical or automatically reasoning. The big data helps serve our life better, clarify our future and deliver greater value. We can discover how to capture and analyze data. Readers will be guided to processing system integrity and implementing intelligent systems. With intelligent systems, we deal with the fundamental data management and visualization challenges in effective management of dynamic and large-scale data, and efficient processing of real-time and spatio-temporal data. Advanced intelligent systems have led to managing the data monitoring, data processing and decision-making in realistic and effective way. Considering a big size of data, variety of data and frequent chan...

  3. Big Data and Analytics in Healthcare.

    Science.gov (United States)

    Tan, S S-L; Gao, G; Koch, S

    2015-01-01

    This editorial is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". The amount of data being generated in the healthcare industry is growing at a rapid rate. This has generated immense interest in leveraging the availability of healthcare data (and "big data") to improve health outcomes and reduce costs. However, the nature of healthcare data, and especially big data, presents unique challenges in processing and analyzing big data in healthcare. This Focus Theme aims to disseminate some novel approaches to address these challenges. More specifically, approaches ranging from efficient methods of processing large clinical data to predictive models that could generate better predictions from healthcare data are presented.

  4. Heat Waves Pose Big Health Threats

    Science.gov (United States)

    ... https://medlineplus.gov/news/fullstory_159744.html Heat Waves Pose Big Health Threats Kids, elderly among those ... can be inherently dangerous, but the initial heat waves every summer can be particularly perilous to those ...

  5. Big Fish and Prized Trees Gain Protection

    Institute of Scientific and Technical Information of China (English)

    Fred Pearce; 吴敏

    2004-01-01

    @@ Decisions made at a key conservation① meeting are good news for big and quirky② fish and commercially prized trees. Several species will enjoy extra protection against trade following rulings made at the Convention on International Trade in Endangered Species (CITES).

  6. Cosmic relics from the big bang

    Energy Technology Data Exchange (ETDEWEB)

    Hall, L.J.

    1988-12-01

    A brief introduction to the big bang picture of the early universe is given. Dark matter is discussed; particularly its implications for elementary particle physics. A classification scheme for dark matter relics is given. 21 refs., 11 figs., 1 tab.

  7. Tick-Borne Diseases: The Big Two

    Science.gov (United States)

    ... Ticks and Diseases Tick-borne Diseases: The Big Two Past Issues / Spring - Summer 2010 Table of Contents ... muscle pain. The red-spotted rash usually happens 2 to 5 days after the fever begins. Antibiotics ...

  8. Big Data in food and agriculture

    Directory of Open Access Journals (Sweden)

    Kelly Bronson

    2016-06-01

    Full Text Available Farming is undergoing a digital revolution. Our existing review of current Big Data applications in the agri-food sector has revealed several collection and analytics tools that may have implications for relationships of power between players in the food system (e.g. between farmers and large corporations. For example, Who retains ownership of the data generated by applications like Monsanto Corproation's Weed I.D. “app”? Are there privacy implications with the data gathered by John Deere's precision agricultural equipment? Systematically tracing the digital revolution in agriculture, and charting the affordances as well as the limitations of Big Data applied to food and agriculture, should be a broad research goal for Big Data scholarship. Such a goal brings data scholarship into conversation with food studies and it allows for a focus on the material consequences of big data in society.

  9. Scaling big data with Hadoop and Solr

    CERN Document Server

    Karambelkar, Hrishikesh Vijay

    2015-01-01

    This book is aimed at developers, designers, and architects who would like to build big data enterprise search solutions for their customers or organizations. No prior knowledge of Apache Hadoop and Apache Solr/Lucene technologies is required.

  10. ARC Code TI: BigView

    Data.gov (United States)

    National Aeronautics and Space Administration — BigView allows for interactive panning and zooming of images of arbitrary size on desktop PCs running linux. Additionally, it can work in a multi-screen environment...

  11. Hunting Plan : Big Stone National Wildlife Refuge

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The Big Stone National Wildlife Refuge Hunting Plan provides guidance for the management of hunting on the refuge. Hunting program objectives include providing a...

  12. Astronomical Surveys and Big Data

    CERN Document Server

    Mickaelian, A M

    2015-01-01

    Recent all-sky and large-area astronomical surveys and their catalogued data over the whole range of electromagnetic spectrum are reviewed, from Gamma-ray to radio, such as Fermi-GLAST and INTEGRAL in Gamma-ray, ROSAT, XMM and Chandra in X-ray, GALEX in UV, SDSS and several POSS I and II based catalogues (APM, MAPS, USNO, GSC) in optical range, 2MASS in NIR, WISE and AKARI IRC in MIR, IRAS and AKARI FIS in FIR, NVSS and FIRST in radio and many others, as well as most important surveys giving optical images (DSS I and II, SDSS, etc.), proper motions (Tycho, USNO, Gaia), variability (GCVS, NSVS, ASAS, Catalina, Pan-STARRS) and spectroscopic data (FBS, SBS, Case, HQS, HES, SDSS, CALIFA, GAMA). An overall understanding of the coverage along the whole wavelength range and comparisons between various surveys are given: galaxy redshift surveys, QSO/AGN, radio, Galactic structure, and Dark Energy surveys. Astronomy has entered the Big Data era. Astrophysical Virtual Observatories and Computational Astrophysics play a...

  13. Neutrinos and Big Bang Nucleosynthesis

    Directory of Open Access Journals (Sweden)

    Gary Steigman

    2012-01-01

    Full Text Available According to the standard models of particle physics and cosmology, there should be a background of cosmic neutrinos in the present Universe, similar to the cosmic microwave photon background. The weakness of the weak interactions renders this neutrino background undetectable with current technology. The cosmic neutrino background can, however, be probed indirectly through its cosmological effects on big bang nucleosynthesis (BBN and the cosmic microwave background (CMB radiation. In this BBN review, focused on neutrinos and more generally on dark radiation, the BBN constraints on the number of “equivalent neutrinos” (dark radiation, on the baryon asymmetry (baryon density, and on a possible lepton asymmetry (neutrino degeneracy are reviewed and updated. The BBN constraints on dark radiation and on the baryon density following from considerations of the primordial abundances of deuterium and helium-4 are in excellent agreement with the complementary results from the CMB, providing a suggestive, but currently inconclusive, hint of the presence of dark radiation, and they constrain any lepton asymmetry. For all the cases considered here there is a “lithium problem”: the BBN-predicted lithium abundance exceeds the observationally inferred primordial value by a factor of ~3.

  14. Big Sky Carbon Sequestration Partnership

    Energy Technology Data Exchange (ETDEWEB)

    Susan Capalbo

    2005-12-31

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership in Phase I are organized into four areas: (1) Evaluation of sources and carbon sequestration sinks that will be used to determine the location of pilot demonstrations in Phase II; (2) Development of GIS-based reporting framework that links with national networks; (3) Design of an integrated suite of monitoring, measuring, and verification technologies, market-based opportunities for carbon management, and an economic/risk assessment framework; (referred to below as the Advanced Concepts component of the Phase I efforts) and (4) Initiation of a comprehensive education and outreach program. As a result of the Phase I activities, the groundwork is in place to provide an assessment of storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that complements the ongoing DOE research agenda in Carbon Sequestration. The geology of the Big Sky Carbon Sequestration Partnership Region is favorable for the potential sequestration of enormous volume of CO{sub 2}. The United States Geological Survey (USGS 1995) identified 10 geologic provinces and 111 plays in the region. These provinces and plays include both sedimentary rock types characteristic of oil, gas, and coal productions as well as large areas of mafic volcanic rocks. Of the 10 provinces and 111 plays, 1 province and 4 plays are located within Idaho. The remaining 9 provinces and 107 plays are dominated by sedimentary rocks and located in the states of Montana and Wyoming. The potential sequestration capacity of the 9 sedimentary provinces within the region ranges from 25,000 to almost 900,000 million metric tons of CO{sub 2}. Overall every sedimentary formation investigated

  15. "Big Science" exhibition at Balexert

    CERN Multimedia

    2008-01-01

    CERN is going out to meet those members of the general public who were unable to attend the recent Open Day. The Laboratory will be taking its "Big Science" exhibition from the Globe of Science and Innovation to the Balexert shopping centre from 19 to 31 May 2008. The exhibition, which shows the LHC and its experiments through the eyes of a photographer, features around thirty spectacular photographs measuring 4.5 metres high and 2.5 metres wide. Welcomed and guided around the exhibition by CERN volunteers, shoppers at Balexert will also have the opportunity to discover LHC components on display and watch films. "Fun with Physics" workshops will be held at certain times of the day. Main hall of the Balexert shopping centre, ground floor, from 9.00 a.m. to 7.00 p.m. Monday to Friday and from 10 a.m. to 6 p.m. on the two Saturdays. Call for volunteers All members of the CERN personnel are invited to enrol as volunteers to help welcom...

  16. Big-bang nucleosynthesis revisited

    Science.gov (United States)

    Olive, Keith A.; Schramm, David N.; Steigman, Gary; Walker, Terry P.

    1989-01-01

    The homogeneous big-bang nucleosynthesis yields of D, He-3, He-4, and Li-7 are computed taking into account recent measurements of the neutron mean-life as well as updates of several nuclear reaction rates which primarily affect the production of Li-7. The extraction of primordial abundances from observation and the likelihood that the primordial mass fraction of He-4, Y(sub p) is less than or equal to 0.24 are discussed. Using the primordial abundances of D + He-3 and Li-7 we limit the baryon-to-photon ratio (eta in units of 10 exp -10) 2.6 less than or equal to eta(sub 10) less than or equal to 4.3; which we use to argue that baryons contribute between 0.02 and 0.11 to the critical energy density of the universe. An upper limit to Y(sub p) of 0.24 constrains the number of light neutrinos to N(sub nu) less than or equal to 3.4, in excellent agreement with the LEP and SLC collider results. We turn this argument around to show that the collider limit of 3 neutrino species can be used to bound the primordial abundance of He-4: 0.235 less than or equal to Y(sub p) less than or equal to 0.245.

  17. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    Energy Technology Data Exchange (ETDEWEB)

    Susan M. Capalbo

    2004-06-01

    The Big Sky Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts during the second performance period fall into four areas: evaluation of sources and carbon sequestration sinks; development of GIS-based reporting framework; designing an integrated suite of monitoring, measuring, and verification technologies; and initiating a comprehensive education and outreach program. At the first two Partnership meetings the groundwork was put in place to provide an assessment of capture and storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other western DOE partnerships. Efforts are also being made to find funding to include Wyoming in the coverage areas for both geological and terrestrial sinks and sources. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts begun in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best management practices for

  18. Big-Learn: Towards a Tool Based on Big Data to Improve Research in an E-Learning Environment

    Directory of Open Access Journals (Sweden)

    Karim Aoulad Abdelouarit

    2015-10-01

    Full Text Available In the area of data management for information system and especially at the level of e-learning platforms, the Big Data phenomenon makes the data difficult to deal with standard database or information management tools. Indeed, for educational purposes and especially in a distance training or online research, the learner that uses the e-learning platform is left with a heterogeneous set of data such as files of all kinds, curves, course materials, quizzes, etc. This requires a specialized fusion system to combine the variety of data and improve the performance, robustness, flexibility, consistency and scalability, so that they can provide the best result to the learner The user of the e-learning platform. In this context, it is proposed to develop a tool called "Big-Learn" based on a technique to integrate the mixing of structured and unstructured data in one data layer, and, in order to facilitate access more optimal search relevance with adequate and consistent results according to the expectations of the learner. The methodology adopted will consist initially in a quantitative and qualitative study of the variety of data and their typology, followed by a detailed analysis of the structure and harmonization of the data to finally find a fictional model for their treatment. This conceptual work will be crowned with a working prototype as a tool achieved with UML and Java technology.

  19. Cincinnati Big Area Additive Manufacturing (BAAM)

    Energy Technology Data Exchange (ETDEWEB)

    Duty, Chad E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Love, Lonnie J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-03-04

    Oak Ridge National Laboratory (ORNL) worked with Cincinnati Incorporated (CI) to demonstrate Big Area Additive Manufacturing which increases the speed of the additive manufacturing (AM) process by over 1000X, increases the size of parts by over 10X and shows a cost reduction of over 100X. ORNL worked with CI to transition the Big Area Additive Manufacturing (BAAM) technology from a proof-of-principle (TRL 2-3) demonstration to a prototype product stage (TRL 7-8).

  20. Effective Dynamics of the Matrix Big Bang

    OpenAIRE

    Craps, Ben; Rajaraman, Arvind; Sethi, Savdeep

    2006-01-01

    We study the leading quantum effects in the recently introduced Matrix Big Bang model. This amounts to a study of supersymmetric Yang-Mills theory compactified on the Milne orbifold. We find a one-loop potential that is attractive near the Big Bang. Surprisingly, the potential decays very rapidly at late times, where it appears to be generated by D-brane effects. Usually, general covariance constrains the form of any effective action generated by renormalization group flow. However, the form ...

  1. Dark energy, wormholes, and the Big Rip

    OpenAIRE

    Faraoni, Valerio; Israel, Werner

    2005-01-01

    The time evolution of a wormhole in a Friedmann universe approaching the Big Rip is studied. The wormhole is modeled by a thin spherical shell accreting the superquintessence fluid - two different models are presented. Contrary to recent claims that the wormhole overtakes the expansion of the universe and engulfs it before the Big Rip is reached, it is found that the wormhole becomes asymptotically comoving with the cosmic fluid and the future evolution of the universe is fully causal.

  2. Mining Big Data to Predicting Future

    OpenAIRE

    Tyagi, Amit K.; Priya, R.

    2015-01-01

    Due to technological advances, vast data sets (e.g. big data) are increasing now days. Big Data a new term; is used to identify the collected datasets. But due to their large size and complexity, we cannot manage with our current methodologies or data mining software tools to extract those datasets. Such datasets provide us with unparalleled opportunities for modelling and predicting of future with new challenges. So as an awareness of this and weaknesses as well as the possibilit...

  3. BigBangの叛乱时代

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    1月底的首尔,BigBang将连开三场引GSHOW演唱会集体回归舞台。2010年,他们早已计划满满——大成,TOP都将在上半年发表SOLO专辑,今年夏天.BigBang也将发行新专辑,带着新歌和久违的Fans见面。

  4. COBE looks back to the Big Bang

    Science.gov (United States)

    Mather, John C.

    1993-01-01

    An overview is presented of NASA-Goddard's Cosmic Background Explorer (COBE), the first NASA satellite designed to observe the primeval explosion of the universe. The spacecraft carries three extremely sensitive IR and microwave instruments designed to measure the faint residual radiation from the Big Bang and to search for the formation of the first galaxies. COBE's far IR absolute spectrophotometer has shown that the Big Bang radiation has a blackbody spectrum, proving that there was no large energy release after the explosion.

  5. Data Confidentiality Challenges in Big Data Applications

    Energy Technology Data Exchange (ETDEWEB)

    Yin, Jian; Zhao, Dongfang

    2015-12-15

    In this paper, we address the problem of data confidentiality in big data analytics. In many fields, much useful patterns can be extracted by applying machine learning techniques to big data. However, data confidentiality must be protected. In many scenarios, data confidentiality could well be a prerequisite for data to be shared. We present a scheme to provide provable secure data confidentiality and discuss various techniques to optimize performance of such a system.

  6. From data quality to big data quality

    OpenAIRE

    Batini, C; Rula, A; Scannapieco, M; Viscusi, G

    2015-01-01

    This article investigates the evolution of data quality issues from traditional structured data managed in relational databases to Big Data. In particular, the paper examines the nature of the relationship between Data Quality and several research coordinates that are relevant in Big Data, such as the variety of data types, data sources and application domains, focusing on maps, semi-structured texts, linked open data, sensor &sensor networks and official statistics. Consequently a set of str...

  7. Adapting bioinformatics curricula for big data

    OpenAIRE

    Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S; Jason H Moore

    2015-01-01

    Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these...

  8. Complete Genome Sequence of Haemophilus parasuis SH0165▿

    OpenAIRE

    Yue, Min; Yang, Fan; Yang, Jian; Bei, Weicheng; Cai, Xuwang; Chen, Lihong; Dong, Jie; Zhou, Rui; Jin, Meilin; Jin, Qi; Chen, Huanchun

    2008-01-01

    Haemophilus parasuis is the causative agent of Glässer's disease, which produces big losses in swine populations worldwide. H. parasuis SH0165, belonging to the dominant serovar 5 in China, is a clinically isolated strain with high-level virulence. Here, we report the first completed genome sequence of this species.

  9. Taming the genome: towards better genetic test interpretation

    OpenAIRE

    Caleshu, Colleen; Ashley, Euan A.

    2016-01-01

    Editorial summary Advances in sequencing technology have taught us much about the human genome, including how difficult it is to interpret rare variation. Improvements in genetic test interpretation are likely to come through data sharing, international collaborative efforts to develop disease–gene specific guidelines, and computational analyses using big data.

  10. Producing gestures facilitates route learning.

    Directory of Open Access Journals (Sweden)

    Wing Chee So

    Full Text Available The present study investigates whether producing gestures would facilitate route learning in a navigation task and whether its facilitation effect is comparable to that of hand movements that leave physical visible traces. In two experiments, we focused on gestures produced without accompanying speech, i.e., co-thought gestures (e.g., an index finger traces the spatial sequence of a route in the air. Adult participants were asked to study routes shown in four diagrams, one at a time. Participants reproduced the routes (verbally in Experiment 1 and non-verbally in Experiment 2 without rehearsal or after rehearsal by mentally simulating the route, by drawing it, or by gesturing (either in the air or on paper. Participants who moved their hands (either in the form of gestures or drawing recalled better than those who mentally simulated the routes and those who did not rehearse, suggesting that hand movements produced during rehearsal facilitate route learning. Interestingly, participants who gestured the routes in the air or on paper recalled better than those who drew them on paper in both experiments, suggesting that the facilitation effect of co-thought gesture holds for both verbal and nonverbal recall modalities. It is possibly because, co-thought gesture, as a kind of representational action, consolidates spatial sequence better than drawing and thus exerting more powerful influence on spatial representation.

  11. Producing gestures facilitates route learning.

    Science.gov (United States)

    So, Wing Chee; Ching, Terence Han-Wei; Lim, Phoebe Elizabeth; Cheng, Xiaoqin; Ip, Kit Yee

    2014-01-01

    The present study investigates whether producing gestures would facilitate route learning in a navigation task and whether its facilitation effect is comparable to that of hand movements that leave physical visible traces. In two experiments, we focused on gestures produced without accompanying speech, i.e., co-thought gestures (e.g., an index finger traces the spatial sequence of a route in the air). Adult participants were asked to study routes shown in four diagrams, one at a time. Participants reproduced the routes (verbally in Experiment 1 and non-verbally in Experiment 2) without rehearsal or after rehearsal by mentally simulating the route, by drawing it, or by gesturing (either in the air or on paper). Participants who moved their hands (either in the form of gestures or drawing) recalled better than those who mentally simulated the routes and those who did not rehearse, suggesting that hand movements produced during rehearsal facilitate route learning. Interestingly, participants who gestured the routes in the air or on paper recalled better than those who drew them on paper in both experiments, suggesting that the facilitation effect of co-thought gesture holds for both verbal and nonverbal recall modalities. It is possibly because, co-thought gesture, as a kind of representational action, consolidates spatial sequence better than drawing and thus exerting more powerful influence on spatial representation. PMID:25426624

  12. Brug af mindfulness til facilitering

    DEFF Research Database (Denmark)

    Adriansen, Hanne Kirstine; Krohn, Simon

    2011-01-01

    Gennem de senere år er mindfulness gået fra udelukkende at være en eksistentiel praksis til også at være en behandlingsform og senest til også at blive brugt som et praktisk redskab i erhvervslivet. Denne artikel viser, at mindfulness også kan anvendes i forbindelse med facilitering. Facilitering...... er et værktøj, som bruges i arbejdslivet fx til møder og konferencer, hvor en gruppe mennesker er samlet for at lære eller udrette noget sammen. Det nye ved at kombinere mindfulness med facilitering er, at fokus hermed ændres fra individet, som er centrum for den eksistentielle fordybelse eller det...... terapeutiske forløb, til gruppen, som er udgangspunktet i facilitering. Artiklen viser, hvordan mindfulness konkret kan bruges på gruppeniveau og diskuterer samtidig hvilke problemer, der kan være forbundet hermed. Baseret på vores egne erfaringer, diskuterer vi, hvordan mindfulness kan påvirke en gruppes...

  13. Sign Facilitation in Word Recognition.

    Science.gov (United States)

    Wauters, Loes N.; Knoors, Harry E. T.; Vervloed, Mathijs P. J.; Aarnoutse, Cor A. J.

    2001-01-01

    This study examined whether use of sign language would facilitate reading word recognition by 16 deaf children (6- to 1 years-old) in the Netherlands. Results indicated that if words were learned through speech, accompanied by the relevant sign, accuracy of word recognition was greater than if words were learned solely through speech. (Contains…

  14. Corpus Linguistics Facilitates English Teaching

    Institute of Scientific and Technical Information of China (English)

    朱思亲

    2014-01-01

    Corpus linguistics has been widely applied in English teaching. Corpus linguistics has changed the way to teach English. The essay discusses two approaches in English teaching based on corpus, corpus-driven approach and corpus-based approach. It finds out that both corpus-driven approach and corpus-based approach facilitate English teaching in their own ways.

  15. Main Issues in Big Data Security

    Directory of Open Access Journals (Sweden)

    Julio Moreno

    2016-09-01

    Full Text Available Data is currently one of the most important assets for companies in every field. The continuous growth in the importance and volume of data has created a new problem: it cannot be handled by traditional analysis techniques. This problem was, therefore, solved through the creation of a new paradigm: Big Data. However, Big Data originated new issues related not only to the volume or the variety of the data, but also to data security and privacy. In order to obtain a full perspective of the problem, we decided to carry out an investigation with the objective of highlighting the main issues regarding Big Data security, and also the solutions proposed by the scientific community to solve them. In this paper, we explain the results obtained after applying a systematic mapping study to security in the Big Data ecosystem. It is almost impossible to carry out detailed research into the entire topic of security, and the outcome of this research is, therefore, a big picture of the main problems related to security in a Big Data system, along with the principal solutions to them proposed by the research community.

  16. Molecular evolution of colorectal cancer: from multistep carcinogenesis to the big bang.

    Science.gov (United States)

    Amaro, Adriana; Chiara, Silvana; Pfeffer, Ulrich

    2016-03-01

    Colorectal cancer is characterized by exquisite genomic instability either in the form of microsatellite instability or chromosomal instability. Microsatellite instability is the result of mutation of mismatch repair genes or their silencing through promoter methylation as a consequence of the CpG island methylator phenotype. The molecular causes of chromosomal instability are less well characterized. Genomic instability and field cancerization lead to a high degree of intratumoral heterogeneity and determine the formation of cancer stem cells and epithelial-mesenchymal transition mediated by the TGF-β and APC pathways. Recent analyses using integrated genomics reveal different phases of colorectal cancer evolution. An initial phase of genomic instability that yields many clones with different mutations (big bang) is followed by an important, previously not detected phase of cancer evolution that consists in the stabilization of several clones and a relatively flat outgrowth. The big bang model can best explain the coexistence of several stable clones and is compatible with the fact that the analysis of the bulk of the primary tumor yields prognostic information. PMID:26947218

  17. BIG SKY CARBON SEQUESTRATION PARTNERSHIP

    Energy Technology Data Exchange (ETDEWEB)

    Susan M. Capalbo

    2004-06-30

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership fall into four areas: evaluation of sources and carbon sequestration sinks; development of GIS-based reporting framework; designing an integrated suite of monitoring, measuring, and verification technologies; and initiating a comprehensive education and outreach program. At the first two Partnership meetings the groundwork was put in place to provide an assessment of capture and storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research. During the third quarter, planning efforts are underway for the next Partnership meeting which will showcase the architecture of the GIS framework and initial results for sources and sinks, discuss the methods and analysis underway for assessing geological and terrestrial sequestration potentials. The meeting will conclude with an ASME workshop (see attached agenda). The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other western DOE partnerships. Efforts are also being made to find funding to include Wyoming in the coverage areas for both geological and terrestrial sinks and sources. The Partnership recognizes the critical importance of measurement

  18. Small government or big government?

    Directory of Open Access Journals (Sweden)

    MATEO SPAHO

    2015-03-01

    Full Text Available Since the beginning of the twentieth century, economists and philosophers were polarizedon their positions beyond the role that the government should have in the economy. On one hand John Maynard Keynes represented, within the optics of market economy, a position where the state should intervene in the economy to maintain the aggregate demand and the employment in the country, without hesitation in creating budget deficits and public debt expansion. This approach happens especially in the moments when the domestic economy and global economic trends show a weak growth or a recession. This means a heavy interference inthe economy, with higher income but with high expenditure to GDP too. On the other side, Liberals and Neoliberalsled by Friedrich Hayek advocated a withdrawal of the government from economic activity not just in moments of economic growth but also during the crisis, believing that the market has self-regulating mechanisms within itself. The government, as a result will have a smaller dimension with lower income and also low expenditures compared to the GDP of the country. We took the South-Eastern Europe countries distinguishing those with a "Big Government" or countries with "Small Government". There are analyzed the economic performances during the global crisis (2007-2014. In which countries the public debt grew less? Which country managed to attract more investments and which were the countries that preserved the purchasing power of their consumers? We shall see if during the economic crisis in Eastern Europe the Great Government or the Liberal and "Small" one has been the most successful the model.

  19. Big Sky Carbon Sequestration Partnership

    Energy Technology Data Exchange (ETDEWEB)

    Susan Capalbo

    2005-12-31

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership in Phase I are organized into four areas: (1) Evaluation of sources and carbon sequestration sinks that will be used to determine the location of pilot demonstrations in Phase II; (2) Development of GIS-based reporting framework that links with national networks; (3) Design of an integrated suite of monitoring, measuring, and verification technologies, market-based opportunities for carbon management, and an economic/risk assessment framework; (referred to below as the Advanced Concepts component of the Phase I efforts) and (4) Initiation of a comprehensive education and outreach program. As a result of the Phase I activities, the groundwork is in place to provide an assessment of storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that complements the ongoing DOE research agenda in Carbon Sequestration. The geology of the Big Sky Carbon Sequestration Partnership Region is favorable for the potential sequestration of enormous volume of CO{sub 2}. The United States Geological Survey (USGS 1995) identified 10 geologic provinces and 111 plays in the region. These provinces and plays include both sedimentary rock types characteristic of oil, gas, and coal productions as well as large areas of mafic volcanic rocks. Of the 10 provinces and 111 plays, 1 province and 4 plays are located within Idaho. The remaining 9 provinces and 107 plays are dominated by sedimentary rocks and located in the states of Montana and Wyoming. The potential sequestration capacity of the 9 sedimentary provinces within the region ranges from 25,000 to almost 900,000 million metric tons of CO{sub 2}. Overall every sedimentary formation investigated

  20. Big Sky Carbon Sequestration Partnership

    Energy Technology Data Exchange (ETDEWEB)

    Susan M. Capalbo

    2005-11-01

    The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership in Phase I fall into four areas: evaluation of sources and carbon sequestration sinks that will be used to determine the location of pilot demonstrations in Phase II; development of GIS-based reporting framework that links with national networks; designing an integrated suite of monitoring, measuring, and verification technologies and assessment frameworks; and initiating a comprehensive education and outreach program. The groundwork is in place to provide an assessment of storage capabilities for CO2 utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that would complement the ongoing DOE research agenda in Carbon Sequestration. The region has a diverse array of geological formations that could provide storage options for carbon in one or more of its three states. Likewise, initial estimates of terrestrial sinks indicate a vast potential for increasing and maintaining soil C on forested, agricultural, and reclaimed lands. Both options include the potential for offsetting economic benefits to industry and society. Steps have been taken to assure that the GIS-based framework is consistent among types of sinks within the Big Sky Partnership area and with the efforts of other DOE regional partnerships. The Partnership recognizes the critical importance of measurement, monitoring, and verification technologies to support not only carbon trading but all policies and programs that DOE and other agencies may want to pursue in support of GHG mitigation. The efforts in developing and implementing MMV technologies for geological sequestration reflect this concern. Research is also underway to identify and validate best management practices for soil C in the

  1. Big Data Analytics for Disaster Preparedness and Response of Mobile Communication Infrastructure during Natural Hazards

    Science.gov (United States)

    Zhong, L.; Takano, K.; Ji, Y.; Yamada, S.

    2015-12-01

    The disruption of telecommunications is one of the most critical disasters during natural hazards. As the rapid expanding of mobile communications, the mobile communication infrastructure plays a very fundamental role in the disaster response and recovery activities. For this reason, its disruption will lead to loss of life and property, due to information delays and errors. Therefore, disaster preparedness and response of mobile communication infrastructure itself is quite important. In many cases of experienced disasters, the disruption of mobile communication networks is usually caused by the network congestion and afterward long-term power outage. In order to reduce this disruption, the knowledge of communication demands during disasters is necessary. And big data analytics will provide a very promising way to predict the communication demands by analyzing the big amount of operational data of mobile users in a large-scale mobile network. Under the US-Japan collaborative project on 'Big Data and Disaster Research (BDD)' supported by the Japan Science and Technology Agency (JST) and National Science Foundation (NSF), we are going to investigate the application of big data techniques in the disaster preparedness and response of mobile communication infrastructure. Specifically, in this research, we have considered to exploit the big amount of operational information of mobile users for predicting the communications needs in different time and locations. By incorporating with other data such as shake distribution of an estimated major earthquake and the power outage map, we are able to provide the prediction information of stranded people who are difficult to confirm safety or ask for help due to network disruption. In addition, this result could further facilitate the network operators to assess the vulnerability of their infrastructure and make suitable decision for the disaster preparedness and response. In this presentation, we are going to introduce the

  2. Patient advocacy: barriers and facilitators

    Directory of Open Access Journals (Sweden)

    Nikravesh Mansoure

    2006-03-01

    Full Text Available Abstract Background During the two recent decades, advocacy has been a topic of much debate in the nursing profession. Although advocacy has embraced a crucial role for nurses, its extent is often limited in practice. While a variety of studies have been generated all over the world, barriers and facilitators in the patient advocacy have not been completely identified. This article presents the findings of a study exploring the barriers and facilitators influencing the role of advocacy among Iranian nurses. Method This study was conducted by grounded theory method. Participants were 24 Iranian registered nurses working in a large university hospital in Tehran, Iran. Semi-structured interviews were used for data collection. All interviews were transcribed verbatim and simultaneously Constant comparative analysis was used according to the Strauss and Corbin method. Results Through data analysis, several main themes emerged to describe the factors that hindered or facilitated patient advocacy. Nurses in this study identified powerlessness, lack of support, law, code of ethics and motivation, limited communication, physicians leading, risk of advocacy, royalty to peers, and insufficient time to interact with patients and families as barriers to advocacy. As for factors that facilitated nurses to act as a patient advocate, it was found that the nature of nurse-patient relationship, recognizing patients' needs, nurses' responsibility, physician as a colleague, and nurses' knowledge and skills could be influential in adopting the advocacy role. Conclusion Participants believed that in this context taking an advocacy role is difficult for nurses due to the barriers mentioned. Therefore, they make decisions and act as a patient's advocate in any situation concerning patient needs and status of barriers and facilitators. In most cases, they can not act at an optimal level; instead they accept only what they can do, which we called 'limited advocacy' in

  3. Facilitating Facilitators to Facilitate, in Problem or Enquiry Based Learning Sessions

    Science.gov (United States)

    Coelho, Catherine

    2014-01-01

    Problem based learning (PBL) has been used in dental education over the past 20 years and uses a patient case scenario to stimulate learning in a small group setting, where a trained facilitator does not teach but guides the group to bring about deep contextualized learning, to be empathetic to each other and to encourage fair and equitable…

  4. Perspectives of integrative cancer genomics in next generation sequencing era.

    Science.gov (United States)

    Kwon, So Mee; Cho, Hyunwoo; Choi, Ji Hye; Jee, Byul A; Jo, Yuna; Woo, Hyun Goo

    2012-06-01

    The explosive development of genomics technologies including microarrays and next generation sequencing (NGS) has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establish the huge cancer genome compendium and integrative omics analyses, so-called "integromics", have extended our understanding on the cancer genome, showing its daunting complexity and heterogeneity. However, the challenges of the structured integration, sharing, and interpretation of the big omics data still remain to be resolved. Here, we review several issues raised in cancer omics data analysis, including NGS, focusing particularly on the study design and analysis strategies. This might be helpful to understand the current trends and strategies of the rapidly evolving cancer genomics research. PMID:23105932

  5. Benchmarking Big Data Systems and the BigData Top100 List.

    Science.gov (United States)

    Baru, Chaitanya; Bhandarkar, Milind; Nambiar, Raghunath; Poess, Meikel; Rabl, Tilmann

    2013-03-01

    "Big data" has become a major force of innovation across enterprises of all sizes. New platforms with increasingly more features for managing big datasets are being announced almost on a weekly basis. Yet, there is currently a lack of any means of comparability among such platforms. While the performance of traditional database systems is well understood and measured by long-established institutions such as the Transaction Processing Performance Council (TCP), there is neither a clear definition of the performance of big data systems nor a generally agreed upon metric for comparing these systems. In this article, we describe a community-based effort for defining a big data benchmark. Over the past year, a Big Data Benchmarking Community has become established in order to fill this void. The effort focuses on defining an end-to-end application-layer benchmark for measuring the performance of big data applications, with the ability to easily adapt the benchmark specification to evolving challenges in the big data space. This article describes the efforts that have been undertaken thus far toward the definition of a BigData Top100 List. While highlighting the major technical as well as organizational challenges, through this article, we also solicit community input into this process.

  6. Big Data Big Changes%大数据,大变革

    Institute of Scientific and Technical Information of China (English)

    梁爽

    2014-01-01

    大数据正时刻发生在人们的身边,大数据时代已经到来。本文通过对大数据特点的描述,分析了大数据在国内外的研究现状以及未来的应用方向,只有重新认识大数据,从思维上变革对大数据的认识,从商业模式上适应大数据的变化,创新大数据管理模式,加强制度建设,增强法律意识,保证个人和国家的安全,才能不断推动大数据的健康发展。%Big data are always happen in people’s side, big data era has arrived. This paper has described the characteristics of big data, analyzed big data research status and future application direction. Only to understand big data again, change the thinking of big data, adapt to changes in business model, innovative big data management, strengthen institution construction, enhance law awareness, ensure the personal and national security, it can continuously promote the healthy development of big data.

  7. Five Big, Big Five Issues : Rationale, Content, Structure, Status, and Crosscultural Assessment

    NARCIS (Netherlands)

    De Raad, Boele

    1998-01-01

    This article discusses the rationale, content, structure, status, and crosscultural assessment of the Big Five trait factors, focusing on topics of dispute and misunderstanding. Taxonomic restrictions of the original Big Five forerunner, the "Norman Five," are discussed, and criticisms regarding the

  8. 大数据,大变革%Big Data Big Changes

    Institute of Scientific and Technical Information of China (English)

    梁爽

    2014-01-01

    Big data are always happen in people’s side, big data era has arrived. This paper has described the characteristics of big data, analyzed big data research status and future application direction. Only to understand big data again, change the thinking of big data, adapt to changes in business model, innovative big data management, strengthen institution construction, enhance law awareness, ensure the personal and national security, it can continuously promote the healthy development of big data.%大数据正时刻发生在人们的身边,大数据时代已经到来。本文通过对大数据特点的描述,分析了大数据在国内外的研究现状以及未来的应用方向,只有重新认识大数据,从思维上变革对大数据的认识,从商业模式上适应大数据的变化,创新大数据管理模式,加强制度建设,增强法律意识,保证个人和国家的安全,才能不断推动大数据的健康发展。

  9. GIS-facilitated spatial narratives

    DEFF Research Database (Denmark)

    Møller-Jensen, Lasse; Jeppesen, Henrik; Kofie, Richard Y.

    2008-01-01

    -based' exploration of sites related to the narrative and as a tool that facilitates the design of spatial narratives before implementation within portable GIS devices. The Google Earth-based visualization of the spatial narrative is created by a Python script that outputs a web-accessible KML format file. The KML......-file defines extended functionality for navigating within the narrative as well as additional data layers....

  10. Facilitating Conversations about Managerial Identities

    DEFF Research Database (Denmark)

    Madsen, Mona Toft

    -based organization in the engineering consulting sector b) a reflection meeting, where the same three managers were gathered, and conversations were facilitated based on identity work in the context of earlier interviews. More specifically, three themes were discussed; flat organizational structure, tensions between...... project work and professional development, and the role of Department Heads. Theoretically, the study contributes to discussions on the need for legitimizing different mixtures of bureaucratic and post bureaucratic ideals. Methodological reflections are made in the discussion as well....

  11. From darwin to the census of marine life: marine biology as big science.

    Directory of Open Access Journals (Sweden)

    Niki Vermeulen

    Full Text Available With the development of the Human Genome Project, a heated debate emerged on biology becoming 'big science'. However, biology already has a long tradition of collaboration, as natural historians were part of the first collective scientific efforts: exploring the variety of life on earth. Such mappings of life still continue today, and if field biology is gradually becoming an important subject of studies into big science, research into life in the world's oceans is not taken into account yet. This paper therefore explores marine biology as big science, presenting the historical development of marine research towards the international 'Census of Marine Life' (CoML making an inventory of life in the world's oceans. Discussing various aspects of collaboration--including size, internationalisation, research practice, technological developments, application, and public communication--I will ask if CoML still resembles traditional collaborations to collect life. While showing both continuity and change, I will argue that marine biology is a form of natural history: a specific way of working together in biology that has transformed substantially in interaction with recent developments in the life sciences and society. As a result, the paper does not only give an overview of transformations towards large scale research in marine biology, but also shines a new light on big biology, suggesting new ways to deepen the understanding of collaboration in the life sciences by distinguishing between different 'collective ways of knowing'.

  12. From darwin to the census of marine life: marine biology as big science.

    Science.gov (United States)

    Vermeulen, Niki

    2013-01-01

    With the development of the Human Genome Project, a heated debate emerged on biology becoming 'big science'. However, biology already has a long tradition of collaboration, as natural historians were part of the first collective scientific efforts: exploring the variety of life on earth. Such mappings of life still continue today, and if field biology is gradually becoming an important subject of studies into big science, research into life in the world's oceans is not taken into account yet. This paper therefore explores marine biology as big science, presenting the historical development of marine research towards the international 'Census of Marine Life' (CoML) making an inventory of life in the world's oceans. Discussing various aspects of collaboration--including size, internationalisation, research practice, technological developments, application, and public communication--I will ask if CoML still resembles traditional collaborations to collect life. While showing both continuity and change, I will argue that marine biology is a form of natural history: a specific way of working together in biology that has transformed substantially in interaction with recent developments in the life sciences and society. As a result, the paper does not only give an overview of transformations towards large scale research in marine biology, but also shines a new light on big biology, suggesting new ways to deepen the understanding of collaboration in the life sciences by distinguishing between different 'collective ways of knowing'.

  13. Heritability estimates of the Big Five personality traits based on common genetic variants.

    Science.gov (United States)

    Power, R A; Pluess, M

    2015-07-14

    According to twin studies, the Big Five personality traits have substantial heritable components explaining 40-60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527,469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e. = 0.08, P = 0.04) and openness (21%, s.e. = 0.08, P Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences.

  14. GeNemo: a search engine for web-based functional genomic data.

    Science.gov (United States)

    Zhang, Yongqing; Cao, Xiaoyi; Zhong, Sheng

    2016-07-01

    A set of new data types emerged from functional genomic assays, including ChIP-seq, DNase-seq, FAIRE-seq and others. The results are typically stored as genome-wide intensities (WIG/bigWig files) or functional genomic regions (peak/BED files). These data types present new challenges to big data science. Here, we present GeNemo, a web-based search engine for functional genomic data. GeNemo searches user-input data against online functional genomic datasets, including the entire collection of ENCODE and mouse ENCODE datasets. Unlike text-based search engines, GeNemo's searches are based on pattern matching of functional genomic regions. This distinguishes GeNemo from text or DNA sequence searches. The user can input any complete or partial functional genomic dataset, for example, a binding intensity file (bigWig) or a peak file. GeNemo reports any genomic regions, ranging from hundred bases to hundred thousand bases, from any of the online ENCODE datasets that share similar functional (binding, modification, accessibility) patterns. This is enabled by a Markov Chain Monte Carlo-based maximization process, executed on up to 24 parallel computing threads. By clicking on a search result, the user can visually compare her/his data with the found datasets and navigate the identified genomic regions. GeNemo is available at www.genemo.org.

  15. GeNemo: a search engine for web-based functional genomic data.

    Science.gov (United States)

    Zhang, Yongqing; Cao, Xiaoyi; Zhong, Sheng

    2016-07-01

    A set of new data types emerged from functional genomic assays, including ChIP-seq, DNase-seq, FAIRE-seq and others. The results are typically stored as genome-wide intensities (WIG/bigWig files) or functional genomic regions (peak/BED files). These data types present new challenges to big data science. Here, we present GeNemo, a web-based search engine for functional genomic data. GeNemo searches user-input data against online functional genomic datasets, including the entire collection of ENCODE and mouse ENCODE datasets. Unlike text-based search engines, GeNemo's searches are based on pattern matching of functional genomic regions. This distinguishes GeNemo from text or DNA sequence searches. The user can input any complete or partial functional genomic dataset, for example, a binding intensity file (bigWig) or a peak file. GeNemo reports any genomic regions, ranging from hundred bases to hundred thousand bases, from any of the online ENCODE datasets that share similar functional (binding, modification, accessibility) patterns. This is enabled by a Markov Chain Monte Carlo-based maximization process, executed on up to 24 parallel computing threads. By clicking on a search result, the user can visually compare her/his data with the found datasets and navigate the identified genomic regions. GeNemo is available at www.genemo.org. PMID:27098038

  16. Transcriptome marker diagnostics using big data.

    Science.gov (United States)

    Han, Henry; Liu, Ying

    2016-02-01

    The big omics data are challenging translational bioinformatics in an unprecedented way for its complexities and volumes. How to employ big omics data to achieve a rivalling-clinical, reproducible disease diagnosis from a systems approach is an urgent problem to be solved in translational bioinformatics and machine learning. In this study, the authors propose a novel transcriptome marker diagnosis to tackle this problem using big RNA-seq data by viewing whole transcriptome as a profile marker systematically. The systems diagnosis not only avoids the reproducibility issue of the existing gene-/network-marker-based diagnostic methods, but also achieves rivalling-clinical diagnostic results by extracting true signals from big RNA-seq data. Their method demonstrates a better fit for personalised diagnostics by attaining exceptional diagnostic performance via using systems information than its competitive methods and prepares itself as a good candidate for clinical usage. To the best of their knowledge, it is the first study on this topic and will inspire the more investigations in big omics data diagnostics.

  17. Volume and Value of Big Healthcare Data

    Science.gov (United States)

    Dinov, Ivo D.

    2016-01-01

    Modern scientific inquiries require significant data-driven evidence and trans-disciplinary expertise to extract valuable information and gain actionable knowledge about natural processes. Effective evidence-based decisions require collection, processing and interpretation of vast amounts of complex data. The Moore's and Kryder's laws of exponential increase of computational power and information storage, respectively, dictate the need rapid trans-disciplinary advances, technological innovation and effective mechanisms for managing and interrogating Big Healthcare Data. In this article, we review important aspects of Big Data analytics and discuss important questions like: What are the challenges and opportunities associated with this biomedical, social, and healthcare data avalanche? Are there innovative statistical computing strategies to represent, model, analyze and interpret Big heterogeneous data? We present the foundation of a new compressive big data analytics (CBDA) framework for representation, modeling and inference of large, complex and heterogeneous datasets. Finally, we consider specific directions likely to impact the process of extracting information from Big healthcare data, translating that information to knowledge, and deriving appropriate actions. PMID:26998309

  18. Big data analytics a management perspective

    CERN Document Server

    Corea, Francesco

    2016-01-01

    This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership – while others concern more specific business situations (e.g., initial public offering, growth st...

  19. Big Data Analytics in Immunology: A Knowledge-Based Approach

    Directory of Open Access Journals (Sweden)

    Guang Lan Zhang

    2014-01-01

    Full Text Available With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

  20. Big data analytics in immunology: a knowledge-based approach.

    Science.gov (United States)

    Zhang, Guang Lan; Sun, Jing; Chitkushev, Lou; Brusic, Vladimir

    2014-01-01

    With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.