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Sample records for genome education model

  1. Human genome education model project. Ethical, legal, and social implications of the human genome project: Education of interdisciplinary professionals

    Energy Technology Data Exchange (ETDEWEB)

    Weiss, J.O. [Alliance of Genetic Support Groups, Chevy Chase, MD (United States); Lapham, E.V. [Georgetown Univ., Washington, DC (United States). Child Development Center

    1996-12-31

    This meeting was held June 10, 1996 at Georgetown University. The purpose of this meeting was to provide a multidisciplinary forum for exchange of state-of-the-art information on the human genome education model. Topics of discussion include the following: psychosocial issues; ethical issues for professionals; legislative issues and update; and education issues.

  2. Human Genome Education Program

    Energy Technology Data Exchange (ETDEWEB)

    Richard Myers; Lane Conn

    2000-05-01

    The funds from the DOE Human Genome Program, for the project period 2/1/96 through 1/31/98, have provided major support for the curriculum development and field testing efforts for two high school level instructional units: Unit 1, ''Exploring Genetic Conditions: Genes, Culture and Choices''; and Unit 2, ''DNA Snapshots: Peaking at Your DNA''. In the original proposal, they requested DOE support for the partial salary and benefits of a Field Test Coordinator position to: (1) complete the field testing and revision of two high school curriculum units, and (2) initiate the education of teachers using these units. During the project period of this two-year DOE grant, a part-time Field-Test Coordinator was hired (Ms. Geraldine Horsma) and significant progress has been made in both of the original proposal objectives. Field testing for Unit 1 has occurred in over 12 schools (local and non-local sites with diverse student populations). Field testing for Unit 2 has occurred in over 15 schools (local and non-local sites) and will continue in 12-15 schools during the 96-97 school year. For both curricula, field-test sites and site teachers were selected for their interest in genetics education and in hands-on science education. Many of the site teachers had no previous experience with HGEP or the unit under development. Both of these first-year biology curriculum units, which contain genetics, biotechnology, societal, ethical and cultural issues related to HGP, are being implemented in many local and non-local schools (SF Bay Area, Southern California, Nebraska, Hawaii, and Texas) and in programs for teachers. These units will reach over 10,000 students in the SF Bay Area and continues to receive support from local corporate and private philanthropic organizations. Although HGEP unit development is nearing completion for both units, data is still being gathered and analyzed on unit effectiveness and student learning. The final field

  3. Musa sebagai Model Genom

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    RITA MEGIA

    2005-12-01

    Full Text Available During the meeting in Arlington, USA in 2001, the scientists grouped in PROMUSA agreed with the launching of the Global Musa Genomics Consortium. The Consortium aims to apply genomics technologies to the improvement of this important crop. These genome projects put banana as the third model species after Arabidopsis and rice that will be analyzed and sequenced. Comparing to Arabidopsis and rice, banana genome provides a unique and powerful insight into structural and in functional genomics that could not be found in those two species. This paper discussed these subjects-including the importance of banana as the fourth main food in the world, the evolution and biodiversity of this genetic resource and its parasite.

  4. Genomic Feature Models

    DEFF Research Database (Denmark)

    Sørensen, Peter; Edwards, Stefan McKinnon; Rohde, Palle Duun

    -additive genetic mechanisms. These modeling approaches have proven to be highly useful to determine population genetic parameters as well as prediction of genetic risk or value. We present a series of statistical modelling approaches that use prior biological information for evaluating the collective action......Whole-genome sequences and multiple trait phenotypes from large numbers of individuals will soon be available in many populations. Well established statistical modeling approaches enable the genetic analyses of complex trait phenotypes while accounting for a variety of additive and non...... regions and gene ontologies) that provide better model fit and increase predictive ability of the statistical model for this trait....

  5. Democratizing Human Genome Project Information: A Model Program for Education, Information and Debate in Public Libraries.

    Science.gov (United States)

    Pollack, Miriam

    The "Mapping the Human Genome" project demonstrated that librarians can help whomever they serve in accessing information resources in the areas of biological and health information, whether it is the scientists who are developing the information or a member of the public who is using the information. Public libraries can guide library…

  6. Education models

    NARCIS (Netherlands)

    Poortman, Sybilla; Sloep, Peter

    2006-01-01

    Educational models describes a case study on a complex learning object. Possibilities are investigated for using this learning object, which is based on a particular educational model, outside of its original context. Furthermore, this study provides advice that might lead to an increase in

  7. The Human Genome Project and Biology Education.

    Science.gov (United States)

    McInerney, Joseph D.

    1996-01-01

    Highlights the importance of the Human Genome Project in educating the public about genetics. Discusses four challenges that science educators must address: teaching for conceptual understanding, the nature of science, the personal and social impact of science and technology, and the principles of technology. Contains 45 references. (JRH)

  8. Integrating genomics into undergraduate nursing education.

    Science.gov (United States)

    Daack-Hirsch, Sandra; Dieter, Carla; Quinn Griffin, Mary T

    2011-09-01

    To prepare the next generation of nurses, faculty are now faced with the challenge of incorporating genomics into curricula. Here we discuss how to meet this challenge. Steps to initiate curricular changes to include genomics are presented along with a discussion on creating a genomic curriculum thread versus a standalone course. Ideas for use of print material and technology on genomic topics are also presented. Information is based on review of the literature and curriculum change efforts by the authors. In recognition of advances in genomics, the nursing profession is increasing an emphasis on the integration of genomics into professional practice and educational standards. Incorporating genomics into nurses' practices begins with changes in our undergraduate curricula. Information given in didactic courses should be reinforced in clinical practica, and Internet-based tools such as WebQuest, Second Life, and wikis offer attractive, up-to-date platforms to deliver this now crucial content. To provide information that may assist faculty to prepare the next generation of nurses to practice using genomics. © 2011 Sigma Theta Tau International.

  9. Plantagora: modeling whole genome sequencing and assembly of plant genomes.

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    Roger Barthelson

    Full Text Available BACKGROUND: Genomics studies are being revolutionized by the next generation sequencing technologies, which have made whole genome sequencing much more accessible to the average researcher. Whole genome sequencing with the new technologies is a developing art that, despite the large volumes of data that can be produced, may still fail to provide a clear and thorough map of a genome. The Plantagora project was conceived to address specifically the gap between having the technical tools for genome sequencing and knowing precisely the best way to use them. METHODOLOGY/PRINCIPAL FINDINGS: For Plantagora, a platform was created for generating simulated reads from several different plant genomes of different sizes. The resulting read files mimicked either 454 or Illumina reads, with varying paired end spacing. Thousands of datasets of reads were created, most derived from our primary model genome, rice chromosome one. All reads were assembled with different software assemblers, including Newbler, Abyss, and SOAPdenovo, and the resulting assemblies were evaluated by an extensive battery of metrics chosen for these studies. The metrics included both statistics of the assembly sequences and fidelity-related measures derived by alignment of the assemblies to the original genome source for the reads. The results were presented in a website, which includes a data graphing tool, all created to help the user compare rapidly the feasibility and effectiveness of different sequencing and assembly strategies prior to testing an approach in the lab. Some of our own conclusions regarding the different strategies were also recorded on the website. CONCLUSIONS/SIGNIFICANCE: Plantagora provides a substantial body of information for comparing different approaches to sequencing a plant genome, and some conclusions regarding some of the specific approaches. Plantagora also provides a platform of metrics and tools for studying the process of sequencing and assembly

  10. Genome Modeling System: A Knowledge Management Platform for Genomics.

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    Malachi Griffith

    2015-07-01

    Full Text Available In this work, we present the Genome Modeling System (GMS, an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395 and matched lymphoblastoid line (HCC1395BL. These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

  11. Genomics education for medical professionals - the current UK landscape.

    Science.gov (United States)

    Slade, Ingrid; Subramanian, Deepak N; Burton, Hilary

    2016-08-01

    Genomics education in the UK is at an early stage of development, and its pace of evolution has lagged behind that of the genomics research upon which it is based. As a result, knowledge of genomics and its applications remains limited among non-specialist clinicians. In this review article, we describe the complex landscape for genomics education within the UK, and highlight the large number and variety of organisations that can influence, direct and provide genomics training to medical professionals. Postgraduate genomics education is being shaped by the work of the Health Education England (HEE) Genomics Education Programme, working in conjunction with the Joint Committee on Genomics in Medicine. The success of their work will be greatly enhanced by the full cooperation and engagement of the many groups, societies and organisations involved with medical education and training (such as the royal colleges). Without this cooperation, there is a risk of poor coordination and unnecessary duplication of work. Leadership from an organisation such as the HEE Genomics Education Programme will have a key role in guiding the formulation and delivery of genomics education policy by various stakeholders among the different disciplines in medicine. © 2016 Royal College of Physicians.

  12. The infinite sites model of genome evolution.

    Science.gov (United States)

    Ma, Jian; Ratan, Aakrosh; Raney, Brian J; Suh, Bernard B; Miller, Webb; Haussler, David

    2008-09-23

    We formalize the problem of recovering the evolutionary history of a set of genomes that are related to an unseen common ancestor genome by operations of speciation, deletion, insertion, duplication, and rearrangement of segments of bases. The problem is examined in the limit as the number of bases in each genome goes to infinity. In this limit, the chromosomes are represented by continuous circles or line segments. For such an infinite-sites model, we present a polynomial-time algorithm to find the most parsimonious evolutionary history of any set of related present-day genomes.

  13. Multiscale modeling of three-dimensional genome

    Science.gov (United States)

    Zhang, Bin; Wolynes, Peter

    The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

  14. Inferences from Genomic Models in Stratified Populations

    DEFF Research Database (Denmark)

    Janss, Luc; de los Campos, Gustavo; Sheehan, Nuala

    2012-01-01

    Unaccounted population stratification can lead to spurious associations in genome-wide association studies (GWAS) and in this context several methods have been proposed to deal with this problem. An alternative line of research uses whole-genome random regression (WGRR) models that fit all marker...

  15. Multiple models for Rosaceae genomics.

    Science.gov (United States)

    Shulaev, Vladimir; Korban, Schuyler S; Sosinski, Bryon; Abbott, Albert G; Aldwinckle, Herb S; Folta, Kevin M; Iezzoni, Amy; Main, Dorrie; Arús, Pere; Dandekar, Abhaya M; Lewers, Kim; Brown, Susan K; Davis, Thomas M; Gardiner, Susan E; Potter, Daniel; Veilleux, Richard E

    2008-07-01

    The plant family Rosaceae consists of over 100 genera and 3,000 species that include many important fruit, nut, ornamental, and wood crops. Members of this family provide high-value nutritional foods and contribute desirable aesthetic and industrial products. Most rosaceous crops have been enhanced by human intervention through sexual hybridization, asexual propagation, and genetic improvement since ancient times, 4,000 to 5,000 B.C. Modern breeding programs have contributed to the selection and release of numerous cultivars having significant economic impact on the U.S. and world markets. In recent years, the Rosaceae community, both in the United States and internationally, has benefited from newfound organization and collaboration that have hastened progress in developing genetic and genomic resources for representative crops such as apple (Malus spp.), peach (Prunus spp.), and strawberry (Fragaria spp.). These resources, including expressed sequence tags, bacterial artificial chromosome libraries, physical and genetic maps, and molecular markers, combined with genetic transformation protocols and bioinformatics tools, have rendered various rosaceous crops highly amenable to comparative and functional genomics studies. This report serves as a synopsis of the resources and initiatives of the Rosaceae community, recent developments in Rosaceae genomics, and plans to apply newly accumulated knowledge and resources toward breeding and crop improvement.

  16. Modern Media Education Models

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    Fedorov, Alexander

    2011-01-01

    The author supposed that media education models can be divided into the following groups: (1) educational-information models (the study of the theory, history, language of media culture, etc.), based on the cultural, aesthetic, semiotic, socio-cultural theories of media education; (2) educational-ethical models (the study of moral, religions,…

  17. Genome scale metabolic modeling of cancer

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens

    2017-01-01

    of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...

  18. Passage relevance models for genomics search

    Directory of Open Access Journals (Sweden)

    Frieder Ophir

    2009-03-01

    Full Text Available Abstract We present a passage relevance model for integrating syntactic and semantic evidence of biomedical concepts and topics using a probabilistic graphical model. Component models of topics, concepts, terms, and document are represented as potential functions within a Markov Random Field. The probability of a passage being relevant to a biologist's information need is represented as the joint distribution across all potential functions. Relevance model feedback of top ranked passages is used to improve distributional estimates of query concepts and topics in context, and a dimensional indexing strategy is used for efficient aggregation of concept and term statistics. By integrating multiple sources of evidence including dependencies between topics, concepts, and terms, we seek to improve genomics literature passage retrieval precision. Using this model, we are able to demonstrate statistically significant improvements in retrieval precision using a large genomics literature corpus.

  19. MODERN MEDIA EDUCATION MODELS

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    Alexander Fedorov

    2011-03-01

    Full Text Available The author supposed that media education models can be divided into the following groups:- educational-information models (the study of the theory, history, language of media culture, etc., based on the cultural, aesthetic, semiotic, socio-cultural theories of media education;- educational-ethical models (the study of moral, religions, philosophical problems relying on the ethic, religious, ideological, ecological, protectionist theories of media education;- pragmatic models (practical media technology training, based on the uses and gratifications and ‘practical’ theories of media education;- aesthetical models (aimed above all at the development of the artistic taste and enriching the skills of analysis of the best media culture examples. Relies on the aesthetical (art and cultural studies theory; - socio-cultural models (socio-cultural development of a creative personality as to the perception, imagination, visual memory, interpretation analysis, autonomic critical thinking, relying on the cultural studies, semiotic, ethic models of media education.

  20. Merging Marine Ecosystem Models and Genomics

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    Coles, V.; Hood, R. R.; Stukel, M. R.; Moran, M. A.; Paul, J. H.; Satinsky, B.; Zielinski, B.; Yager, P. L.

    2015-12-01

    oceanography. One of the grand challenges of oceanography is to develop model techniques to more effectively incorporate genomic information. As one approach, we developed an ecosystem model whose community is determined by randomly assigning functional genes to build each organism's "DNA". Microbes are assigned a size that sets their baseline environmental responses using allometric response cuves. These responses are modified by the costs and benefits conferred by each gene in an organism's genome. The microbes are embedded in a general circulation model where environmental conditions shape the emergent population. This model is used to explore whether organisms constructed from randomized combinations of metabolic capability alone can self-organize to create realistic oceanic biogeochemical gradients. Realistic community size spectra and chlorophyll-a concentrations emerge in the model. The model is run repeatedly with randomly-generated microbial communities and each time realistic gradients in community size spectra, chlorophyll-a, and forms of nitrogen develop. This supports the hypothesis that the metabolic potential of a community rather than the realized species composition is the primary factor setting vertical and horizontal environmental gradients. Vertical distributions of nitrogen and transcripts for genes involved in nitrification are broadly consistent with observations. Modeled gene and transcript abundance for nitrogen cycling and processing of land-derived organic material match observations along the extreme gradients in the Amazon River plume, and they help to explain the factors controlling observed variability.

  1. Correction for Measurement Error from Genotyping-by-Sequencing in Genomic Variance and Genomic Prediction Models

    DEFF Research Database (Denmark)

    Ashraf, Bilal; Janss, Luc; Jensen, Just

    sample). The GBSeq data can be used directly in genomic models in the form of individual SNP allele-frequency estimates (e.g., reference reads/total reads per polymorphic site per individual), but is subject to measurement error due to the low sequencing depth per individual. Due to technical reasons....... In the current work we show how the correction for measurement error in GBSeq can also be applied in whole genome genomic variance and genomic prediction models. Bayesian whole-genome random regression models are proposed to allow implementation of large-scale SNP-based models with a per-SNP correction...... for measurement error. We show correct retrieval of genomic explained variance, and improved genomic prediction when accounting for the measurement error in GBSeq data...

  2. Exploring the mycobacteriophage metaproteome: phage genomics as an educational platform.

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    Graham F Hatfull

    2006-06-01

    Full Text Available Bacteriophages are the most abundant forms of life in the biosphere and carry genomes characterized by high genetic diversity and mosaic architectures. The complete sequences of 30 mycobacteriophage genomes show them collectively to encode 101 tRNAs, three tmRNAs, and 3,357 proteins belonging to 1,536 "phamilies" of related sequences, and a statistical analysis predicts that these represent approximately 50% of the total number of phamilies in the mycobacteriophage population. These phamilies contain 2.19 proteins on average; more than half (774 of them contain just a single protein sequence. Only six phamilies have representatives in more than half of the 30 genomes, and only three-encoding tape-measure proteins, lysins, and minor tail proteins-are present in all 30 phages, although these phamilies are themselves highly modular, such that no single amino acid sequence element is present in all 30 mycobacteriophage genomes. Of the 1,536 phamilies, only 230 (15% have amino acid sequence similarity to previously reported proteins, reflecting the enormous genetic diversity of the entire phage population. The abundance and diversity of phages, the simplicity of phage isolation, and the relatively small size of phage genomes support bacteriophage isolation and comparative genomic analysis as a highly suitable platform for discovery-based education.

  3. A trade secret model for genomic biobanking.

    Science.gov (United States)

    Conley, John M; Mitchell, Robert; Cadigan, R Jean; Davis, Arlene M; Dobson, Allison W; Gladden, Ryan Q

    2012-01-01

    Genomic biobanks present ethical challenges that are qualitatively unique and quantitatively unprecedented. Many critics have questioned whether the current system of informed consent can be meaningfully applied to genomic biobanking. Proposals for reform have come from many directions, but have tended to involve incremental change in current informed consent practice. This paper reports on our efforts to seek new ideas and approaches from those whom informed consent is designed to protect: research subjects. Our model emerged from semi-structured interviews with healthy volunteers who had been recruited to join either of two biobanks (some joined, some did not), and whom we encouraged to explain their concerns and how they understood the relationship between specimen contributors and biobanks. These subjects spoke about their DNA and the information it contains in ways that were strikingly evocative of the legal concept of the trade secret. They then described the terms and conditions under which they might let others study their DNA, and there was a compelling analogy to the commonplace practice of trade secret licensing. We propose a novel biobanking model based on this trade secret concept, and argue that it would be a practical, legal, and ethical improvement on the status quo. © 2012 American Society of Law, Medicine & Ethics, Inc.

  4. A Probabilistic Genome-Wide Gene Reading Frame Sequence Model

    DEFF Research Database (Denmark)

    Have, Christian Theil; Mørk, Søren

    We introduce a new type of probabilistic sequence model, that model the sequential composition of reading frames of genes in a genome. Our approach extends gene finders with a model of the sequential composition of genes at the genome-level -- effectively producing a sequential genome annotation...... as output. The model can be used to obtain the most probable genome annotation based on a combination of i: a gene finder score of each gene candidate and ii: the sequence of the reading frames of gene candidates through a genome. The model --- as well as a higher order variant --- is developed and tested...... and are evaluated by the effect on prediction performance. Since bacterial gene finding to a large extent is a solved problem it forms an ideal proving ground for evaluating the explicit modeling of larger scale gene sequence composition of genomes. We conclude that the sequential composition of gene reading frames...

  5. Technical note: Equivalent genomic models with a residual polygenic effect.

    Science.gov (United States)

    Liu, Z; Goddard, M E; Hayes, B J; Reinhardt, F; Reents, R

    2016-03-01

    Routine genomic evaluations in animal breeding are usually based on either a BLUP with genomic relationship matrix (GBLUP) or single nucleotide polymorphism (SNP) BLUP model. For a multi-step genomic evaluation, these 2 alternative genomic models were proven to give equivalent predictions for genomic reference animals. The model equivalence was verified also for young genotyped animals without phenotypes. Due to incomplete linkage disequilibrium of SNP markers to genes or causal mutations responsible for genetic inheritance of quantitative traits, SNP markers cannot explain all the genetic variance. A residual polygenic effect is normally fitted in the genomic model to account for the incomplete linkage disequilibrium. In this study, we start by showing the proof that the multi-step GBLUP and SNP BLUP models are equivalent for the reference animals, when they have a residual polygenic effect included. Second, the equivalence of both multi-step genomic models with a residual polygenic effect was also verified for young genotyped animals without phenotypes. Additionally, we derived formulas to convert genomic estimated breeding values of the GBLUP model to its components, direct genomic values and residual polygenic effect. Third, we made a proof that the equivalence of these 2 genomic models with a residual polygenic effect holds also for single-step genomic evaluation. Both the single-step GBLUP and SNP BLUP models lead to equal prediction for genotyped animals with phenotypes (e.g., reference animals), as well as for (young) genotyped animals without phenotypes. Finally, these 2 single-step genomic models with a residual polygenic effect were proven to be equivalent for estimation of SNP effects, too. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  6. Learning about the Human Genome. Part 2: Resources for Science Educators. ERIC Digest.

    Science.gov (United States)

    Haury, David L.

    This ERIC Digest identifies how the human genome project fits into the "National Science Education Standards" and lists Human Genome Project Web sites found on the World Wide Web. It is a resource companion to "Learning about the Human Genome. Part 1: Challenge to Science Educators" (Haury 2001). The Web resources and…

  7. Genomics education for decision making : proceedings of the second invitational workshop on genomics education, 2–3 December 2010, Utrecht, The Netherlands

    NARCIS (Netherlands)

    Boerwinkel, D.J.; Waarlo, A.J.

    2011-01-01

    Advances in genomics research and technology generate new personal and societal choices. As science education has the task of preparing students for decision-making on socio-scientific issues, research is needed to develop genomics education aimed at empowering students in the decision-making

  8. Connectionist Modelling and Education.

    Science.gov (United States)

    Evers, Colin W.

    2000-01-01

    Provides a detailed, technical introduction to the state of cognitive science research, in particular the rise of the "new cognitive science," especially artificial neural net (ANN) models. Explains one influential ANN model and describes diverse applications and their implications for education. (EV)

  9. Genomic ancestry and education level independently influence abdominal fat distributions in a Brazilian admixed population.

    Science.gov (United States)

    França, Giovanny Vinícius Araújo de; De Lucia Rolfe, Emanuella; Horta, Bernardo Lessa; Gigante, Denise Petrucci; Yudkin, John S; Ong, Ken K; Victora, Cesar Gomes

    2017-01-01

    We aimed to identify the independent associations of genomic ancestry and education level with abdominal fat distributions in the 1982 Pelotas birth cohort study, Brazil. In 2,890 participants (1,409 men and 1,481 women), genomic ancestry was assessed using genotype data on 370,539 genome-wide variants to quantify ancestral proportions in each individual. Years of completed education was used to indicate socio-economic position. Visceral fat depth and subcutaneous abdominal fat thickness were measured by ultrasound at age 29-31y; these measures were adjusted for BMI to indicate abdominal fat distributions. Linear regression models were performed, separately by sex. Admixture was observed between European (median proportion 85.3), African (6.6), and Native American (6.3) ancestries, with a strong inverse correlation between the African and European ancestry scores (ρ = -0.93; pabdominal fat distributions in men (both P = 0.001), and inversely associated with subcutaneous abdominal fat distribution in women (p = 0.009). Independent of genomic ancestry, higher education level was associated with lower visceral fat, but higher subcutaneous fat, in both men and women (all pabdominal fat distribution in adults. African ancestry appeared to lower abdominal fat distributions, particularly in men.

  10. Sequence modelling and an extensible data model for genomic database

    Energy Technology Data Exchange (ETDEWEB)

    Li, Peter Wei-Der [California Univ., San Francisco, CA (United States); Univ. of California, Berkeley, CA (United States)

    1992-01-01

    The Human Genome Project (HGP) plans to sequence the human genome by the beginning of the next century. It will generate DNA sequences of more than 10 billion bases and complex marker sequences (maps) of more than 100 million markers. All of these information will be stored in database management systems (DBMSs). However, existing data models do not have the abstraction mechanism for modelling sequences and existing DBMS`s do not have operations for complex sequences. This work addresses the problem of sequence modelling in the context of the HGP and the more general problem of an extensible object data model that can incorporate the sequence model as well as existing and future data constructs and operators. First, we proposed a general sequence model that is application and implementation independent. This model is used to capture the sequence information found in the HGP at the conceptual level. In addition, abstract and biological sequence operators are defined for manipulating the modelled sequences. Second, we combined many features of semantic and object oriented data models into an extensible framework, which we called the ``Extensible Object Model``, to address the need of a modelling framework for incorporating the sequence data model with other types of data constructs and operators. This framework is based on the conceptual separation between constructors and constraints. We then used this modelling framework to integrate the constructs for the conceptual sequence model. The Extensible Object Model is also defined with a graphical representation, which is useful as a tool for database designers. Finally, we defined a query language to support this model and implement the query processor to demonstrate the feasibility of the extensible framework and the usefulness of the conceptual sequence model.

  11. Sequence modelling and an extensible data model for genomic database

    Energy Technology Data Exchange (ETDEWEB)

    Li, Peter Wei-Der (California Univ., San Francisco, CA (United States) Lawrence Berkeley Lab., CA (United States))

    1992-01-01

    The Human Genome Project (HGP) plans to sequence the human genome by the beginning of the next century. It will generate DNA sequences of more than 10 billion bases and complex marker sequences (maps) of more than 100 million markers. All of these information will be stored in database management systems (DBMSs). However, existing data models do not have the abstraction mechanism for modelling sequences and existing DBMS's do not have operations for complex sequences. This work addresses the problem of sequence modelling in the context of the HGP and the more general problem of an extensible object data model that can incorporate the sequence model as well as existing and future data constructs and operators. First, we proposed a general sequence model that is application and implementation independent. This model is used to capture the sequence information found in the HGP at the conceptual level. In addition, abstract and biological sequence operators are defined for manipulating the modelled sequences. Second, we combined many features of semantic and object oriented data models into an extensible framework, which we called the Extensible Object Model'', to address the need of a modelling framework for incorporating the sequence data model with other types of data constructs and operators. This framework is based on the conceptual separation between constructors and constraints. We then used this modelling framework to integrate the constructs for the conceptual sequence model. The Extensible Object Model is also defined with a graphical representation, which is useful as a tool for database designers. Finally, we defined a query language to support this model and implement the query processor to demonstrate the feasibility of the extensible framework and the usefulness of the conceptual sequence model.

  12. The IGNITE network: a model for genomic medicine implementation and research.

    Science.gov (United States)

    Weitzel, Kristin Wiisanen; Alexander, Madeline; Bernhardt, Barbara A; Calman, Neil; Carey, David J; Cavallari, Larisa H; Field, Julie R; Hauser, Diane; Junkins, Heather A; Levin, Phillip A; Levy, Kenneth; Madden, Ebony B; Manolio, Teri A; Odgis, Jacqueline; Orlando, Lori A; Pyeritz, Reed; Wu, R Ryanne; Shuldiner, Alan R; Bottinger, Erwin P; Denny, Joshua C; Dexter, Paul R; Flockhart, David A; Horowitz, Carol R; Johnson, Julie A; Kimmel, Stephen E; Levy, Mia A; Pollin, Toni I; Ginsburg, Geoffrey S

    2016-01-05

    Patients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility. To address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.ignite-genomics.org ) Network, comprised of six projects and a coordinating center, was established in 2013 to support the development, investigation and dissemination of genomic medicine practice models that seamlessly integrate genomic data into the electronic health record and that deploy tools for point of care decision making. IGNITE site projects are aligned in their purpose of testing these models, but individual projects vary in scope and design, including exploring genetic markers for disease risk prediction and prevention, developing tools for using family history data, incorporating pharmacogenomic data into clinical care, refining disease diagnosis using sequence-based mutation discovery, and creating novel educational approaches. This paper describes the IGNITE Network and member projects, including network structure, collaborative initiatives, clinical decision support strategies, methods for return of genomic test results, and educational initiatives for patients and providers. Clinical and outcomes data from individual sites and network-wide projects are anticipated to begin being published over the next few years. The IGNITE Network is an innovative series of projects and pilot demonstrations aiming to enhance translation of validated actionable genomic information into clinical settings and develop and use measures of outcome in response to genome-based clinical interventions using a pragmatic framework to provide early data and proofs of concept on the utility of these

  13. Genome sequence analysis of the model grass Brachypodium distachyon: insights into grass genome evolution

    Energy Technology Data Exchange (ETDEWEB)

    Schulman, Al

    2009-08-09

    Three subfamilies of grasses, the Erhardtoideae (rice), the Panicoideae (maize, sorghum, sugar cane and millet), and the Pooideae (wheat, barley and cool season forage grasses) provide the basis of human nutrition and are poised to become major sources of renewable energy. Here we describe the complete genome sequence of the wild grass Brachypodium distachyon (Brachypodium), the first member of the Pooideae subfamily to be completely sequenced. Comparison of the Brachypodium, rice and sorghum genomes reveals a precise sequence- based history of genome evolution across a broad diversity of the grass family and identifies nested insertions of whole chromosomes into centromeric regions as a predominant mechanism driving chromosome evolution in the grasses. The relatively compact genome of Brachypodium is maintained by a balance of retroelement replication and loss. The complete genome sequence of Brachypodium, coupled to its exceptional promise as a model system for grass research, will support the development of new energy and food crops

  14. Developmental Education Evaluation Model.

    Science.gov (United States)

    Perry-Miller, Mitzi; And Others

    A developmental education evaluation model designed to be used at a multi-unit urban community college is described. The purpose of the design was to determine the cost effectiveness/worth of programs in order to initiate self-improvement. A needs assessment was conducted by interviewing and taping the responses of students, faculty, staff, and…

  15. Academic Education Chain Operation Model

    OpenAIRE

    Ruskov, Petko; Ruskov, Andrey

    2007-01-01

    This paper presents an approach for modelling the educational processes as a value added chain. It is an attempt to use a business approach to interpret and compile existing business and educational processes towards reference models and suggest an Academic Education Chain Operation Model. The model can be used to develop an Academic Chain Operation Reference Model.

  16. Building a model: developing genomic resources for common milkweed (Asclepias syriaca with low coverage genome sequencing

    Directory of Open Access Journals (Sweden)

    Weitemier Kevin

    2011-05-01

    Full Text Available Abstract Background Milkweeds (Asclepias L. have been extensively investigated in diverse areas of evolutionary biology and ecology; however, there are few genetic resources available to facilitate and compliment these studies. This study explored how low coverage genome sequencing of the common milkweed (Asclepias syriaca L. could be useful in characterizing the genome of a plant without prior genomic information and for development of genomic resources as a step toward further developing A. syriaca as a model in ecology and evolution. Results A 0.5× genome of A. syriaca was produced using Illumina sequencing. A virtually complete chloroplast genome of 158,598 bp was assembled, revealing few repeats and loss of three genes: accD, clpP, and ycf1. A nearly complete rDNA cistron (18S-5.8S-26S; 7,541 bp and 5S rDNA (120 bp sequence were obtained. Assessment of polymorphism revealed that the rDNA cistron and 5S rDNA had 0.3% and 26.7% polymorphic sites, respectively. A partial mitochondrial genome sequence (130,764 bp, with identical gene content to tobacco, was also assembled. An initial characterization of repeat content indicated that Ty1/copia-like retroelements are the most common repeat type in the milkweed genome. At least one A. syriaca microread hit 88% of Catharanthus roseus (Apocynaceae unigenes (median coverage of 0.29× and 66% of single copy orthologs (COSII in asterids (median coverage of 0.14×. From this partial characterization of the A. syriaca genome, markers for population genetics (microsatellites and phylogenetics (low-copy nuclear genes studies were developed. Conclusions The results highlight the promise of next generation sequencing for development of genomic resources for any organism. Low coverage genome sequencing allows characterization of the high copy fraction of the genome and exploration of the low copy fraction of the genome, which facilitate the development of molecular tools for further study of a target species

  17. Building a model: developing genomic resources for common milkweed (Asclepias syriaca) with low coverage genome sequencing.

    Science.gov (United States)

    Straub, Shannon C K; Fishbein, Mark; Livshultz, Tatyana; Foster, Zachary; Parks, Matthew; Weitemier, Kevin; Cronn, Richard C; Liston, Aaron

    2011-05-04

    Milkweeds (Asclepias L.) have been extensively investigated in diverse areas of evolutionary biology and ecology; however, there are few genetic resources available to facilitate and compliment these studies. This study explored how low coverage genome sequencing of the common milkweed (Asclepias syriaca L.) could be useful in characterizing the genome of a plant without prior genomic information and for development of genomic resources as a step toward further developing A. syriaca as a model in ecology and evolution. A 0.5× genome of A. syriaca was produced using Illumina sequencing. A virtually complete chloroplast genome of 158,598 bp was assembled, revealing few repeats and loss of three genes: accD, clpP, and ycf1. A nearly complete rDNA cistron (18S-5.8S-26S; 7,541 bp) and 5S rDNA (120 bp) sequence were obtained. Assessment of polymorphism revealed that the rDNA cistron and 5S rDNA had 0.3% and 26.7% polymorphic sites, respectively. A partial mitochondrial genome sequence (130,764 bp), with identical gene content to tobacco, was also assembled. An initial characterization of repeat content indicated that Ty1/copia-like retroelements are the most common repeat type in the milkweed genome. At least one A. syriaca microread hit 88% of Catharanthus roseus (Apocynaceae) unigenes (median coverage of 0.29×) and 66% of single copy orthologs (COSII) in asterids (median coverage of 0.14×). From this partial characterization of the A. syriaca genome, markers for population genetics (microsatellites) and phylogenetics (low-copy nuclear genes) studies were developed. The results highlight the promise of next generation sequencing for development of genomic resources for any organism. Low coverage genome sequencing allows characterization of the high copy fraction of the genome and exploration of the low copy fraction of the genome, which facilitate the development of molecular tools for further study of a target species and its relatives. This study represents a first

  18. Modeling Lactococcus lactis using a genome-scale flux model

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2005-06-01

    Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

  19. Promoting synergistic research and education in genomics and bioinformatics.

    Science.gov (United States)

    Yang, Jack Y; Yang, Mary Qu; Zhu, Mengxia Michelle; Arabnia, Hamid R; Deng, Youping

    2008-01-01

    Bioinformatics and Genomics are closely related disciplines that hold great promises for the advancement of research and development in complex biomedical systems, as well as public health, drug design, comparative genomics, personalized medicine and so on. Research and development in these two important areas are impacting the science and technology.High throughput sequencing and molecular imaging technologies marked the beginning of a new era for modern translational medicine and personalized healthcare. The impact of having the human sequence and personalized digital images in hand has also created tremendous demands of developing powerful supercomputing, statistical learning and artificial intelligence approaches to handle the massive bioinformatics and personalized healthcare data, which will obviously have a profound effect on how biomedical research will be conducted toward the improvement of human health and prolonging of human life in the future. The International Society of Intelligent Biological Medicine (http://www.isibm.org) and its official journals, the International Journal of Functional Informatics and Personalized Medicine (http://www.inderscience.com/ijfipm) and the International Journal of Computational Biology and Drug Design (http://www.inderscience.com/ijcbdd) in collaboration with International Conference on Bioinformatics and Computational Biology (Biocomp), touch tomorrow's bioinformatics and personalized medicine throughout today's efforts in promoting the research, education and awareness of the upcoming integrated inter/multidisciplinary field. The 2007 international conference on Bioinformatics and Computational Biology (BIOCOMP07) was held in Las Vegas, the United States of American on June 25-28, 2007. The conference attracted over 400 papers, covering broad research areas in the genomics, biomedicine and bioinformatics. The Biocomp 2007 provides a common platform for the cross fertilization of ideas, and to help shape knowledge and

  20. Academic Education Chain Operation Model

    NARCIS (Netherlands)

    Ruskov, Petko; Ruskov, Andrey

    2007-01-01

    This paper presents an approach for modelling the educational processes as a value added chain. It is an attempt to use a business approach to interpret and compile existing business and educational processes towards reference models and suggest an Academic Education Chain Operation Model. The model

  1. Genome-scale biological models for industrial microbial systems.

    Science.gov (United States)

    Xu, Nan; Ye, Chao; Liu, Liming

    2018-04-01

    The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

  2. Use of genome-scale microbial models for metabolic engineering

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

    2004-01-01

    Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metaboli...... network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction....

  3. Azolla--a model organism for plant genomic studies.

    Science.gov (United States)

    Qiu, Yin-Long; Yu, Jun

    2003-02-01

    The aquatic ferns of the genus Azolla are nitrogen-fixing plants that have great potentials in agricultural production and environmental conservation. Azolla in many aspects is qualified to serve as a model organism for genomic studies because of its importance in agriculture, its unique position in plant evolution, its symbiotic relationship with the N2-fixing cyanobacterium, Anabaena azollae, and its moderate-sized genome. The goals of this genome project are not only to understand the biology of the Azolla genome to promote its applications in biological research and agriculture practice but also to gain critical insights about evolution of plant genomes. Together with the strategic and technical improvement as well as cost reduction of DNA sequencing, the deciphering of their genetic code is imminent.

  4. Exploiting linkage disequilibrium in statistical modelling in quantitative genomics

    DEFF Research Database (Denmark)

    Wang, Lei

    Alleles at two loci are said to be in linkage disequilibrium (LD) when they are correlated or statistically dependent. Genomic prediction and gene mapping rely on the existence of LD between gentic markers and causul variants of complex traits. In the first part of the thesis, a novel method...... to quantify and visualize local variation in LD along chromosomes in describet, and applied to characterize LD patters at the local and genome-wide scale in three Danish pig breeds. In the second part, different ways of taking LD into account in genomic prediction models are studied. One approach is to use...... the recently proposed antedependence models, which treat neighbouring marker effects as correlated; another approach involves use of haplotype block information derived using the program Beagle. The overall conclusion is that taking LD information into account in genomic prediction models potentially improves...

  5. Genomic value prediction for quantitative traits under the epistatic model

    Directory of Open Access Journals (Sweden)

    Xu Shizhong

    2011-01-01

    Full Text Available Abstract Background Most quantitative traits are controlled by multiple quantitative trait loci (QTL. The contribution of each locus may be negligible but the collective contribution of all loci is usually significant. Genome selection that uses markers of the entire genome to predict the genomic values of individual plants or animals can be more efficient than selection on phenotypic values and pedigree information alone for genetic improvement. When a quantitative trait is contributed by epistatic effects, using all markers (main effects and marker pairs (epistatic effects to predict the genomic values of plants can achieve the maximum efficiency for genetic improvement. Results In this study, we created 126 recombinant inbred lines of soybean and genotyped 80 makers across the genome. We applied the genome selection technique to predict the genomic value of somatic embryo number (a quantitative trait for each line. Cross validation analysis showed that the squared correlation coefficient between the observed and predicted embryo numbers was 0.33 when only main (additive effects were used for prediction. When the interaction (epistatic effects were also included in the model, the squared correlation coefficient reached 0.78. Conclusions This study provided an excellent example for the application of genome selection to plant breeding.

  6. The Genomics Education Partnership: Successful Integration of Research into Laboratory Classes at a Diverse Group of Undergraduate Institutions

    Science.gov (United States)

    Shaffer, Christopher D.; Alvarez, Consuelo; Bailey, Cheryl; Barnard, Daron; Bhalla, Satish; Chandrasekaran, Chitra; Chandrasekaran, Vidya; Chung, Hui-Min; Dorer, Douglas R.; Du, Chunguang; Eckdahl, Todd T.; Poet, Jeff L.; Frohlich, Donald; Goodman, Anya L.; Gosser, Yuying; Hauser, Charles; Hoopes, Laura L.M.; Johnson, Diana; Jones, Christopher J.; Kaehler, Marian; Kokan, Nighat; Kopp, Olga R.; Kuleck, Gary A.; McNeil, Gerard; Moss, Robert; Myka, Jennifer L.; Nagengast, Alexis; Morris, Robert; Overvoorde, Paul J.; Shoop, Elizabeth; Parrish, Susan; Reed, Kelynne; Regisford, E. Gloria; Revie, Dennis; Rosenwald, Anne G.; Saville, Ken; Schroeder, Stephanie; Shaw, Mary; Skuse, Gary; Smith, Christopher; Smith, Mary; Spana, Eric P.; Spratt, Mary; Stamm, Joyce; Thompson, Jeff S.; Wawersik, Matthew; Wilson, Barbara A.; Youngblom, Jim; Leung, Wilson; Buhler, Jeremy; Mardis, Elaine R.; Lopatto, David

    2010-01-01

    Genomics is not only essential for students to understand biology but also provides unprecedented opportunities for undergraduate research. The goal of the Genomics Education Partnership (GEP), a collaboration between a growing number of colleges and universities around the country and the Department of Biology and Genome Center of Washington University in St. Louis, is to provide such research opportunities. Using a versatile curriculum that has been adapted to many different class settings, GEP undergraduates undertake projects to bring draft-quality genomic sequence up to high quality and/or participate in the annotation of these sequences. GEP undergraduates have improved more than 2 million bases of draft genomic sequence from several species of Drosophila and have produced hundreds of gene models using evidence-based manual annotation. Students appreciate their ability to make a contribution to ongoing research, and report increased independence and a more active learning approach after participation in GEP projects. They show knowledge gains on pre- and postcourse quizzes about genes and genomes and in bioinformatic analysis. Participating faculty also report professional gains, increased access to genomics-related technology, and an overall positive experience. We have found that using a genomics research project as the core of a laboratory course is rewarding for both faculty and students. PMID:20194808

  7. Ocean biogeochemistry modeled with emergent trait-based genomics

    Science.gov (United States)

    Coles, V. J.; Stukel, M. R.; Brooks, M. T.; Burd, A.; Crump, B. C.; Moran, M. A.; Paul, J. H.; Satinsky, B. M.; Yager, P. L.; Zielinski, B. L.; Hood, R. R.

    2017-12-01

    Marine ecosystem models have advanced to incorporate metabolic pathways discovered with genomic sequencing, but direct comparisons between models and “omics” data are lacking. We developed a model that directly simulates metagenomes and metatranscriptomes for comparison with observations. Model microbes were randomly assigned genes for specialized functions, and communities of 68 species were simulated in the Atlantic Ocean. Unfit organisms were replaced, and the model self-organized to develop community genomes and transcriptomes. Emergent communities from simulations that were initialized with different cohorts of randomly generated microbes all produced realistic vertical and horizontal ocean nutrient, genome, and transcriptome gradients. Thus, the library of gene functions available to the community, rather than the distribution of functions among specific organisms, drove community assembly and biogeochemical gradients in the model ocean.

  8. Multiple Models for Rosaceae Genomics[OA

    Science.gov (United States)

    Shulaev, Vladimir; Korban, Schuyler S.; Sosinski, Bryon; Abbott, Albert G.; Aldwinckle, Herb S.; Folta, Kevin M.; Iezzoni, Amy; Main, Dorrie; Arús, Pere; Dandekar, Abhaya M.; Lewers, Kim; Brown, Susan K.; Davis, Thomas M.; Gardiner, Susan E.; Potter, Daniel; Veilleux, Richard E.

    2008-01-01

    The plant family Rosaceae consists of over 100 genera and 3,000 species that include many important fruit, nut, ornamental, and wood crops. Members of this family provide high-value nutritional foods and contribute desirable aesthetic and industrial products. Most rosaceous crops have been enhanced by human intervention through sexual hybridization, asexual propagation, and genetic improvement since ancient times, 4,000 to 5,000 B.C. Modern breeding programs have contributed to the selection and release of numerous cultivars having significant economic impact on the U.S. and world markets. In recent years, the Rosaceae community, both in the United States and internationally, has benefited from newfound organization and collaboration that have hastened progress in developing genetic and genomic resources for representative crops such as apple (Malus spp.), peach (Prunus spp.), and strawberry (Fragaria spp.). These resources, including expressed sequence tags, bacterial artificial chromosome libraries, physical and genetic maps, and molecular markers, combined with genetic transformation protocols and bioinformatics tools, have rendered various rosaceous crops highly amenable to comparative and functional genomics studies. This report serves as a synopsis of the resources and initiatives of the Rosaceae community, recent developments in Rosaceae genomics, and plans to apply newly accumulated knowledge and resources toward breeding and crop improvement. PMID:18487361

  9. Hospital nursing leadership-led interventions increased genomic awareness and educational intent in Magnet settings.

    Science.gov (United States)

    Calzone, Kathleen A; Jenkins, Jean; Culp, Stacey; Badzek, Laurie

    2017-11-13

    The Precision Medicine Initiative will accelerate genomic discoveries that improve health care, necessitating a genomic competent workforce. This study assessed leadership team (administrator/educator) year-long interventions to improve registered nurses' (RNs) capacity to integrate genomics into practice. We examined genomic competency outcomes in 8,150 RNs. Awareness and intention to learn more increased compared with controls. Findings suggest achieving genomic competency requires a longer intervention and support strategies such as infrastructure and policies. Leadership played a role in mobilizing staff, resources, and supporting infrastructure to sustain a large-scale competency effort on an institutional basis. Results demonstrate genomic workforce competency can be attained with leadership support and sufficient time. Our study provides evidence of the critical role health-care leaders play in facilitating genomic integration into health care to improve patient outcomes. Genomics' impact on quality, safety, and cost indicate a leader-initiated national competency effort is achievable and warranted. Published by Elsevier Inc.

  10. Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

    Science.gov (United States)

    Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

    2016-01-01

    The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

  11. Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

    Directory of Open Access Journals (Sweden)

    Jaime Cuevas

    2017-01-01

    Full Text Available The phenomenon of genotype × environment (G × E interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects ( u that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP and Gaussian (Gaussian kernel, GK. The other model has the same genetic component as the first model ( u plus an extra component, f, that captures random effects between environments that were not captured by the random effects u . We used five CIMMYT data sets (one maize and four wheat that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u   and   f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u .

  12. Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

    Science.gov (United States)

    Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

    2017-01-05

    The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

  13. Functional Coverage of the Human Genome by Existing Structures, Structural Genomics Targets, and Homology Models.

    Directory of Open Access Journals (Sweden)

    2005-08-01

    Full Text Available The bias in protein structure and function space resulting from experimental limitations and targeting of particular functional classes of proteins by structural biologists has long been recognized, but never continuously quantified. Using the Enzyme Commission and the Gene Ontology classifications as a reference frame, and integrating structure data from the Protein Data Bank (PDB, target sequences from the structural genomics projects, structure homology derived from the SUPERFAMILY database, and genome annotations from Ensembl and NCBI, we provide a quantified view, both at the domain and whole-protein levels, of the current and projected coverage of protein structure and function space relative to the human genome. Protein structures currently provide at least one domain that covers 37% of the functional classes identified in the genome; whole structure coverage exists for 25% of the genome. If all the structural genomics targets were solved (twice the current number of structures in the PDB, it is estimated that structures of one domain would cover 69% of the functional classes identified and complete structure coverage would be 44%. Homology models from existing experimental structures extend the 37% coverage to 56% of the genome as single domains and 25% to 31% for complete structures. Coverage from homology models is not evenly distributed by protein family, reflecting differing degrees of sequence and structure divergence within families. While these data provide coverage, conversely, they also systematically highlight functional classes of proteins for which structures should be determined. Current key functional families without structure representation are highlighted here; updated information on the "most wanted list" that should be solved is available on a weekly basis from http://function.rcsb.org:8080/pdb/function_distribution/index.html.

  14. Genome typing of nonhuman primate models: implications for biomedical research.

    Science.gov (United States)

    Haus, Tanja; Ferguson, Betsy; Rogers, Jeffrey; Doxiadis, Gaby; Certa, Ulrich; Rose, Nicola J; Teepe, Robert; Weinbauer, Gerhard F; Roos, Christian

    2014-11-01

    The success of personalized medicine rests on understanding the genetic variation between individuals. Thus, as medical practice evolves and variation among individuals becomes a fundamental aspect of clinical medicine, a thorough consideration of the genetic and genomic information concerning the animals used as models in biomedical research also becomes critical. In particular, nonhuman primates (NHPs) offer great promise as models for many aspects of human health and disease. These are outbred species exhibiting substantial levels of genetic variation; however, understanding of the contribution of this variation to phenotypes is lagging behind in NHP species. Thus, there is a pivotal need to address this gap and define strategies for characterizing both genomic content and variability within primate models of human disease. Here, we discuss the current state of genomics of NHP models and offer guidelines for future work to ensure continued improvement and utility of this line of biomedical research. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Microbial comparative pan-genomics using binomial mixture models

    DEFF Research Database (Denmark)

    Ussery, David; Snipen, L; Almøy, T

    2009-01-01

    The size of the core- and pan-genome of bacterial species is a topic of increasing interest due to the growing number of sequenced prokaryote genomes, many from the same species. Attempts to estimate these quantities have been made, using regression methods or mixture models. We extend the latter...... approach by using statistical ideas developed for capture-recapture problems in ecology and epidemiology. RESULTS: We estimate core- and pan-genome sizes for 16 different bacterial species. The results reveal a complex dependency structure for most species, manifested as heterogeneous detection...... probabilities. Estimated pan-genome sizes range from small (around 2600 gene families) in Buchnera aphidicola to large (around 43000 gene families) in Escherichia coli. Results for Echerichia coli show that as more data become available, a larger diversity is estimated, indicating an extensive pool of rarely...

  16. Microbial comparative pan-genomics using binomial mixture models

    Directory of Open Access Journals (Sweden)

    Ussery David W

    2009-08-01

    Full Text Available Abstract Background The size of the core- and pan-genome of bacterial species is a topic of increasing interest due to the growing number of sequenced prokaryote genomes, many from the same species. Attempts to estimate these quantities have been made, using regression methods or mixture models. We extend the latter approach by using statistical ideas developed for capture-recapture problems in ecology and epidemiology. Results We estimate core- and pan-genome sizes for 16 different bacterial species. The results reveal a complex dependency structure for most species, manifested as heterogeneous detection probabilities. Estimated pan-genome sizes range from small (around 2600 gene families in Buchnera aphidicola to large (around 43000 gene families in Escherichia coli. Results for Echerichia coli show that as more data become available, a larger diversity is estimated, indicating an extensive pool of rarely occurring genes in the population. Conclusion Analyzing pan-genomics data with binomial mixture models is a way to handle dependencies between genomes, which we find is always present. A bottleneck in the estimation procedure is the annotation of rarely occurring genes.

  17. Visualization of RNA structure models within the Integrative Genomics Viewer.

    Science.gov (United States)

    Busan, Steven; Weeks, Kevin M

    2017-07-01

    Analyses of the interrelationships between RNA structure and function are increasingly important components of genomic studies. The SHAPE-MaP strategy enables accurate RNA structure probing and realistic structure modeling of kilobase-length noncoding RNAs and mRNAs. Existing tools for visualizing RNA structure models are not suitable for efficient analysis of long, structurally heterogeneous RNAs. In addition, structure models are often advantageously interpreted in the context of other experimental data and gene annotation information, for which few tools currently exist. We have developed a module within the widely used and well supported open-source Integrative Genomics Viewer (IGV) that allows visualization of SHAPE and other chemical probing data, including raw reactivities, data-driven structural entropies, and data-constrained base-pair secondary structure models, in context with linear genomic data tracks. We illustrate the usefulness of visualizing RNA structure in the IGV by exploring structure models for a large viral RNA genome, comparing bacterial mRNA structure in cells with its structure under cell- and protein-free conditions, and comparing a noncoding RNA structure modeled using SHAPE data with a base-pairing model inferred through sequence covariation analysis. © 2017 Busan and Weeks; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  18. Education through fiction: acquiring opinion-forming skills in the context of genomics

    NARCIS (Netherlands)

    Knippels, M.C.P.J.; Severiens, S.E.; Klop, T.

    2009-01-01

    The present study examined the outcomes of a newly designed four-lesson science module on opinion-forming in the context of genomics in upper secondary education. The lesson plan aims to foster 16-year-old students’ opinion-forming skills in the context of genomics and to test the effect of the use

  19. Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models

    Directory of Open Access Journals (Sweden)

    Surovcik Katharina

    2006-03-01

    Full Text Available Abstract Background Horizontal gene transfer (HGT is considered a strong evolutionary force shaping the content of microbial genomes in a substantial manner. It is the difference in speed enabling the rapid adaptation to changing environmental demands that distinguishes HGT from gene genesis, duplications or mutations. For a precise characterization, algorithms are needed that identify transfer events with high reliability. Frequently, the transferred pieces of DNA have a considerable length, comprise several genes and are called genomic islands (GIs or more specifically pathogenicity or symbiotic islands. Results We have implemented the program SIGI-HMM that predicts GIs and the putative donor of each individual alien gene. It is based on the analysis of codon usage (CU of each individual gene of a genome under study. CU of each gene is compared against a carefully selected set of CU tables representing microbial donors or highly expressed genes. Multiple tests are used to identify putatively alien genes, to predict putative donors and to mask putatively highly expressed genes. Thus, we determine the states and emission probabilities of an inhomogeneous hidden Markov model working on gene level. For the transition probabilities, we draw upon classical test theory with the intention of integrating a sensitivity controller in a consistent manner. SIGI-HMM was written in JAVA and is publicly available. It accepts as input any file created according to the EMBL-format. It generates output in the common GFF format readable for genome browsers. Benchmark tests showed that the output of SIGI-HMM is in agreement with known findings. Its predictions were both consistent with annotated GIs and with predictions generated by different methods. Conclusion SIGI-HMM is a sensitive tool for the identification of GIs in microbial genomes. It allows to interactively analyze genomes in detail and to generate or to test hypotheses about the origin of acquired

  20. Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

    Science.gov (United States)

    Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

    2017-11-01

    Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Human Cancer Models Initiative | Office of Cancer Genomics

    Science.gov (United States)

    The Human Cancer Models Initiative (HCMI) is an international consortium that is generating novel human tumor-derived culture models, which are annotated with genomic and clinical data. In an effort to advance cancer research and more fully understand how in vitro findings are related to clinical biology, HCMI-developed models and related data will be available as a community resource for cancer research.

  2. Genetics/genomics education for nongenetic health professionals: a systematic literature review.

    Science.gov (United States)

    Talwar, Divya; Tseng, Tung-Sung; Foster, Margaret; Xu, Lei; Chen, Lei-Shih

    2017-07-01

    The completion of the Human Genome Project has enhanced avenues for disease prevention, diagnosis, and management. Owing to the shortage of genetic professionals, genetics/genomics training has been provided to nongenetic health professionals for years to establish their genomic competencies. We conducted a systematic literature review to summarize and evaluate the existing genetics/genomics education programs for nongenetic health professionals. Five electronic databases were searched from January 1990 to June 2016. Forty-four studies met our inclusion criteria. There was a growing publication trend. Program participants were mainly physicians and nurses. The curricula, which were most commonly provided face to face, included basic genetics; applied genetics/genomics; ethical, legal, and social implications of genetics/genomics; and/or genomic competencies/recommendations in particular professional fields. Only one-third of the curricula were theory-based. The majority of studies adopted a pre-/post-test design and lacked follow-up data collection. Nearly all studies reported participants' improvements in one or more of the following areas: knowledge, attitudes, skills, intention, self-efficacy, comfort level, and practice. However, most studies did not report participants' age, ethnicity, years of clinical practice, data validity, and data reliability. Many genetics/genomics education programs for nongenetic health professionals exist. Nevertheless, enhancement in methodological quality is needed to strengthen education initiatives.Genet Med advance online publication 20 October 2016.

  3. The genome sequence of the model ascomycete fungus Podospora anserina

    NARCIS (Netherlands)

    Espagne, Eric; Lespinet, Olivier; Malagnac, Fabienne; Da Silva, Corinne; Jaillon, Olivier; Porcel, Betina M; Couloux, Arnaud; Aury, Jean-Marc; Ségurens, Béatrice; Poulain, Julie; Anthouard, Véronique; Grossetete, Sandrine; Khalili, Hamid; Coppin, Evelyne; Déquard-Chablat, Michelle; Picard, Marguerite; Contamine, Véronique; Arnaise, Sylvie; Bourdais, Anne; Berteaux-Lecellier, Véronique; Gautheret, Daniel; de Vries, Ronald P; Battaglia, Evy; Coutinho, Pedro M; Danchin, Etienne Gj; Henrissat, Bernard; Khoury, Riyad El; Sainsard-Chanet, Annie; Boivin, Antoine; Pinan-Lucarré, Bérangère; Sellem, Carole H; Debuchy, Robert; Wincker, Patrick; Weissenbach, Jean; Silar, Philippe

    2008-01-01

    BACKGROUND: The dung-inhabiting ascomycete fungus Podospora anserina is a model used to study various aspects of eukaryotic and fungal biology, such as ageing, prions and sexual development. RESULTS: We present a 10X draft sequence of P. anserina genome, linked to the sequences of a large expressed

  4. Modeling Ebola Virus Genome Replication and Transcription with Minigenome Systems.

    Science.gov (United States)

    Cressey, Tessa; Brauburger, Kristina; Mühlberger, Elke

    2017-01-01

    In this chapter, we describe the minigenome system for Ebola virus (EBOV), which reconstitutes EBOV polymerase activity in cells and can be used to model viral genome replication and transcription. This protocol comprises all steps including cell culture, plasmid preparation, transfection, and luciferase reporter assay readout.

  5. Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.

    Science.gov (United States)

    Meuwissen, Theo H E; Indahl, Ulf G; Ødegård, Jørgen

    2017-12-27

    Non-linear Bayesian genomic prediction models such as BayesA/B/C/R involve iteration and mostly Markov chain Monte Carlo (MCMC) algorithms, which are computationally expensive, especially when whole-genome sequence (WGS) data are analyzed. Singular value decomposition (SVD) of the genotype matrix can facilitate genomic prediction in large datasets, and can be used to estimate marker effects and their prediction error variances (PEV) in a computationally efficient manner. Here, we developed, implemented, and evaluated a direct, non-iterative method for the estimation of marker effects for the BayesC genomic prediction model. The BayesC model assumes a priori that markers have normally distributed effects with probability [Formula: see text] and no effect with probability (1 - [Formula: see text]). Marker effects and their PEV are estimated by using SVD and the posterior probability of the marker having a non-zero effect is calculated. These posterior probabilities are used to obtain marker-specific effect variances, which are subsequently used to approximate BayesC estimates of marker effects in a linear model. A computer simulation study was conducted to compare alternative genomic prediction methods, where a single reference generation was used to estimate marker effects, which were subsequently used for 10 generations of forward prediction, for which accuracies were evaluated. SVD-based posterior probabilities of markers having non-zero effects were generally lower than MCMC-based posterior probabilities, but for some regions the opposite occurred, resulting in clear signals for QTL-rich regions. The accuracies of breeding values estimated using SVD- and MCMC-based BayesC analyses were similar across the 10 generations of forward prediction. For an intermediate number of generations (2 to 5) of forward prediction, accuracies obtained with the BayesC model tended to be slightly higher than accuracies obtained using the best linear unbiased prediction of SNP

  6. Lampreys as Diverse Model Organisms in the Genomics Era.

    Science.gov (United States)

    McCauley, David W; Docker, Margaret F; Whyard, Steve; Li, Weiming

    2015-11-01

    Lampreys, one of the two surviving groups of ancient vertebrates, have become important models for study in diverse fields of biology. Lampreys (of which there are approximately 40 species) are being studied, for example, (a) to control pest sea lamprey in the North American Great Lakes and to restore declining populations of native species elsewhere; (b) in biomedical research, focusing particularly on the regenerative capability of lampreys; and (c) by developmental biologists studying the evolution of key vertebrate characters. Although a lack of genetic resources has hindered research on the mechanisms regulating many aspects of lamprey life history and development, formerly intractable questions are now amenable to investigation following the recent publication of the sea lamprey genome. Here, we provide an overview of the ways in which genomic tools are currently being deployed to tackle diverse research questions and suggest several areas that may benefit from the availability of the sea lamprey genome.

  7. Functional validation of candidate genes detected by genomic feature models

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Østergaard, Solveig; Kristensen, Torsten Nygaard

    2018-01-01

    to investigate locomotor activity, and applied genomic feature prediction models to identify gene ontology (GO) cate- gories predictive of this phenotype. Next, we applied the covariance association test to partition the genomic variance of the predictive GO terms to the genes within these terms. We...... then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated......Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait...

  8. A unifying model of genome evolution under parsimony.

    Science.gov (United States)

    Paten, Benedict; Zerbino, Daniel R; Hickey, Glenn; Haussler, David

    2014-06-19

    Parsimony and maximum likelihood methods of phylogenetic tree estimation and parsimony methods for genome rearrangements are central to the study of genome evolution yet to date they have largely been pursued in isolation. We present a data structure called a history graph that offers a practical basis for the analysis of genome evolution. It conceptually simplifies the study of parsimonious evolutionary histories by representing both substitutions and double cut and join (DCJ) rearrangements in the presence of duplications. The problem of constructing parsimonious history graphs thus subsumes related maximum parsimony problems in the fields of phylogenetic reconstruction and genome rearrangement. We show that tractable functions can be used to define upper and lower bounds on the minimum number of substitutions and DCJ rearrangements needed to explain any history graph. These bounds become tight for a special type of unambiguous history graph called an ancestral variation graph (AVG), which constrains in its combinatorial structure the number of operations required. We finally demonstrate that for a given history graph G, a finite set of AVGs describe all parsimonious interpretations of G, and this set can be explored with a few sampling moves. This theoretical study describes a model in which the inference of genome rearrangements and phylogeny can be unified under parsimony.

  9. A Three-Dimensional Model of the Yeast Genome

    Science.gov (United States)

    Noble, William; Duan, Zhi-Jun; Andronescu, Mirela; Schutz, Kevin; McIlwain, Sean; Kim, Yoo Jung; Lee, Choli; Shendure, Jay; Fields, Stanley; Blau, C. Anthony

    Layered on top of information conveyed by DNA sequence and chromatin are higher order structures that encompass portions of chromosomes, entire chromosomes, and even whole genomes. Interphase chromosomes are not positioned randomly within the nucleus, but instead adopt preferred conformations. Disparate DNA elements co-localize into functionally defined aggregates or factories for transcription and DNA replication. In budding yeast, Drosophila and many other eukaryotes, chromosomes adopt a Rabl configuration, with arms extending from centromeres adjacent to the spindle pole body to telomeres that abut the nuclear envelope. Nonetheless, the topologies and spatial relationships of chromosomes remain poorly understood. Here we developed a method to globally capture intra- and inter-chromosomal interactions, and applied it to generate a map at kilobase resolution of the haploid genome of Saccharomyces cerevisiae. The map recapitulates known features of genome organization, thereby validating the method, and identifies new features. Extensive regional and higher order folding of individual chromosomes is observed. Chromosome XII exhibits a striking conformation that implicates the nucleolus as a formidable barrier to interaction between DNA sequences at either end. Inter-chromosomal contacts are anchored by centromeres and include interactions among transfer RNA genes, among origins of early DNA replication and among sites where chromosomal breakpoints occur. Finally, we constructed a three-dimensional model of the yeast genome. Our findings provide a glimpse of the interface between the form and function of a eukaryotic genome.

  10. Genetic link between family socioeconomic status and children's educational achievement estimated from genome-wide SNPs.

    Science.gov (United States)

    Krapohl, E; Plomin, R

    2016-03-01

    One of the best predictors of children's educational achievement is their family's socioeconomic status (SES), but the degree to which this association is genetically mediated remains unclear. For 3000 UK-representative unrelated children we found that genome-wide single-nucleotide polymorphisms could explain a third of the variance of scores on an age-16 UK national examination of educational achievement and half of the correlation between their scores and family SES. Moreover, genome-wide polygenic scores based on a previously published genome-wide association meta-analysis of total number of years in education accounted for ~3.0% variance in educational achievement and ~2.5% in family SES. This study provides the first molecular evidence for substantial genetic influence on differences in children's educational achievement and its association with family SES.

  11. A system-level model for the microbial regulatory genome.

    Science.gov (United States)

    Brooks, Aaron N; Reiss, David J; Allard, Antoine; Wu, Wei-Ju; Salvanha, Diego M; Plaisier, Christopher L; Chandrasekaran, Sriram; Pan, Min; Kaur, Amardeep; Baliga, Nitin S

    2014-07-15

    Microbes can tailor transcriptional responses to diverse environmental challenges despite having streamlined genomes and a limited number of regulators. Here, we present data-driven models that capture the dynamic interplay of the environment and genome-encoded regulatory programs of two types of prokaryotes: Escherichia coli (a bacterium) and Halobacterium salinarum (an archaeon). The models reveal how the genome-wide distributions of cis-acting gene regulatory elements and the conditional influences of transcription factors at each of those elements encode programs for eliciting a wide array of environment-specific responses. We demonstrate how these programs partition transcriptional regulation of genes within regulons and operons to re-organize gene-gene functional associations in each environment. The models capture fitness-relevant co-regulation by different transcriptional control mechanisms acting across the entire genome, to define a generalized, system-level organizing principle for prokaryotic gene regulatory networks that goes well beyond existing paradigms of gene regulation. An online resource (http://egrin2.systemsbiology.net) has been developed to facilitate multiscale exploration of conditional gene regulation in the two prokaryotes. © 2014 The Authors. Published under the terms of the CC BY 4.0 license.

  12. Genomes

    National Research Council Canada - National Science Library

    Brown, T. A. (Terence A.)

    2002-01-01

    ... of genome expression and replication processes, and transcriptomics and proteomics. This text is richly illustrated with clear, easy-to-follow, full color diagrams, which are downloadable from the book's website...

  13. Genomic breeding value estimation using nonparametric additive regression models

    Directory of Open Access Journals (Sweden)

    Solberg Trygve

    2009-01-01

    Full Text Available Abstract Genomic selection refers to the use of genomewide dense markers for breeding value estimation and subsequently for selection. The main challenge of genomic breeding value estimation is the estimation of many effects from a limited number of observations. Bayesian methods have been proposed to successfully cope with these challenges. As an alternative class of models, non- and semiparametric models were recently introduced. The present study investigated the ability of nonparametric additive regression models to predict genomic breeding values. The genotypes were modelled for each marker or pair of flanking markers (i.e. the predictors separately. The nonparametric functions for the predictors were estimated simultaneously using additive model theory, applying a binomial kernel. The optimal degree of smoothing was determined by bootstrapping. A mutation-drift-balance simulation was carried out. The breeding values of the last generation (genotyped was predicted using data from the next last generation (genotyped and phenotyped. The results show moderate to high accuracies of the predicted breeding values. A determination of predictor specific degree of smoothing increased the accuracy.

  14. Genome-wide association study identifies 74 loci associated with educational attainment

    NARCIS (Netherlands)

    A. Okbay (Aysu); J.P. Beauchamp (Jonathan); Fontana, M.A. (Mark Alan); J.J. Lee (James J.); T.H. Pers (Tune); Rietveld, C.A. (Cornelius A.); P. Turley (Patrick); Chen, G.-B. (Guo-Bo); V. Emilsson (Valur); Meddens, S.F.W. (S. Fleur W.); Oskarsson, S. (Sven); Pickrell, J.K. (Joseph K.); Thom, K. (Kevin); Timshel, P. (Pascal); R. de Vlaming (Ronald); A. Abdellaoui (Abdel); T.S. Ahluwalia (Tarunveer Singh); J. Bacelis (Jonas); C. Baumbach (Clemens); Bjornsdottir, G. (Gyda); J.H. Brandsma (Johan); Pina Concas, M. (Maria); J. Derringer; Furlotte, N.A. (Nicholas A.); T.E. Galesloot (Tessel); S. Girotto; Gupta, R. (Richa); L.M. Hall (Leanne M.); S.E. Harris (Sarah); E. Hofer; Horikoshi, M. (Momoko); J.E. Huffman (Jennifer E.); Kaasik, K. (Kadri); I.-P. Kalafati (Ioanna-Panagiota); R. Karlsson (Robert); A. Kong (Augustine); J. Lahti (Jari); S.J. van der Lee (Sven); Deleeuw, C. (Christiaan); P.A. Lind (Penelope); Lindgren, K.-O. (Karl-Oskar); Liu, T. (Tian); M. Mangino (Massimo); J. Marten (Jonathan); E. Mihailov (Evelin); M. Miller (Mike); P.J. van der Most (Peter); C. Oldmeadow (Christopher); A. Payton (Antony); N. Pervjakova (Natalia); W.J. Peyrot (Wouter ); Qian, Y. (Yong); O. Raitakari (Olli); Rueedi, R. (Rico); Salvi, E. (Erika); Schmidt, B. (Börge); Schraut, K.E. (Katharina E.); Shi, J. (Jianxin); A.V. Smith (Albert Vernon); R.A. Poot (Raymond); B. St Pourcain (Beate); A. Teumer (Alexander); G. Thorleifsson (Gudmar); N. Verweij (Niek); D. Vuckovic (Dragana); Wellmann, J. (Juergen); H.J. Westra (Harm-Jan); Yang, J. (Jingyun); Zhao, W. (Wei); Zhu, Z. (Zhihong); B.Z. Alizadeh (Behrooz); N. Amin (Najaf); Bakshi, A. (Andrew); S.E. Baumeister (Sebastian); G. Biino (Ginevra); K. Bønnelykke (Klaus); P.A. Boyle (Patricia); H. Campbell (Harry); Cappuccio, F.P. (Francesco P.); G. Davies (Gail); J.E. de Neve (Jan-Emmanuel); P. Deloukas (Panagiotis); I. Demuth (Ilja); Ding, J. (Jun); Eibich, P. (Peter); Eisele, L. (Lewin); N. Eklund (Niina); D.M. Evans (David); J.D. Faul (Jessica D.); M.F. Feitosa (Mary Furlan); A.J. Forstner (Andreas); I. Gandin (Ilaria); Gunnarsson, B. (Bjarni); B.V. Halldorsson (Bjarni); T.B. Harris (Tamara); E.G. Holliday (Elizabeth); A.C. Heath (Andrew C.); L.J. Hocking; G. Homuth (Georg); M. Horan (Mike); J.J. Hottenga (Jouke Jan); P.L. de Jager (Philip); P.K. Joshi (Peter); A. Juqessur (Astanand); M. Kaakinen (Marika); M. Kähönen (Mika); S. Kanoni (Stavroula); Keltigangas-Järvinen, L. (Liisa); L.A.L.M. Kiemeney (Bart); I. Kolcic (Ivana); Koskinen, S. (Seppo); A. Kraja (Aldi); Kroh, M. (Martin); Z. Kutalik (Zoltán); A. Latvala (Antti); L.J. Launer (Lenore); Lebreton, M.P. (Maël P.); D.F. Levinson (Douglas F.); P. Lichtenstein (Paul); P. Lichtner (Peter); D.C. Liewald (David C.); A. Loukola (Anu); P.A. Madden (Pamela); R. Mägi (Reedik); Mäki-Opas, T. (Tomi); R.E. Marioni (Riccardo); P. Marques-Vidal; Meddens, G.A. (Gerardus A.); G. Mcmahon (George); C. Meisinger (Christa); T. Meitinger (Thomas); Milaneschi, Y. (Yusplitri); L. Milani (Lili); G.W. Montgomery (Grant); R. Myhre (Ronny); C.P. Nelson (Christopher P.); D.R. Nyholt (Dale); W.E.R. Ollier (William); A. Palotie (Aarno); L. Paternoster (Lavinia); N.L. Pedersen (Nancy); K. Petrovic (Katja); D.J. Porteous (David J.); K. Räikkönen (Katri); Ring, S.M. (Susan M.); A. Robino (Antonietta); O. Rostapshova (Olga); I. Rudan (Igor); A. Rustichini (Aldo); V. Salomaa (Veikko); Sanders, A.R. (Alan R.); A.-P. Sarin; R. Schmidt (Reinhold); R.J. Scott (Rodney); B.H. Smith (Blair); J.A. Smith (Jennifer A); J.A. Staessen (Jan); E. Steinhagen-Thiessen (Elisabeth); K. Strauch (Konstantin); A. Terracciano; M.D. Tobin (Martin); S. Ulivi (Shelia); S. Vaccargiu (Simona); L. Quaye (Lydia); F.J.A. van Rooij (Frank); C. Venturini (Cristina); A.A.E. Vinkhuyzen (Anna A.); U. Völker (Uwe); Völzke, H. (Henry); J.M. Vonk (Judith); D. Vozzi (Diego); J. Waage (Johannes); E.B. Ware (Erin B.); G.A.H.M. Willemsen (Gonneke); J. Attia (John); D.A. Bennett (David A.); Berger, K. (Klaus); L. Bertram (Lars); H. Bisgaard (Hans); D.I. Boomsma (Dorret); I.B. Borecki (Ingrid); U. Bültmann (Ute); C.F. Chabris (Christopher F.); F. Cucca (Francesco); D. Cusi (Daniele); I.J. Deary (Ian J.); G.V. Dedoussis (George); C.M. van Duijn (Cornelia); K. Hagen (Knut); B. Franke (Barbara); L. Franke (Lude); P. Gasparini (Paolo); P.V. Gejman (Pablo); C. Gieger (Christian); H.J. Grabe (Hans Jörgen); J. Gratten (Jacob); P.J.F. Groenen (Patrick); V. Gudnason (Vilmundur); P. van der Harst (Pim); C. Hayward (Caroline); D.A. Hinds (David A.); W. Hoffmann (Wolfgang); E. Hypponen (Elina); W.G. Iacono (William); B. Jacobsson (Bo); M.-R. Jarvelin (Marjo-Riitta); K.-H. JöCkel (Karl-Heinz); J. Kaprio (Jaakko); S.L.R. Kardia (Sharon); T. Lehtimäki (Terho); Lehrer, S.F. (Steven F.); P.K. Magnusson (Patrik); N.G. Martin (Nicholas); M. McGue (Matt); A. Metspalu (Andres); N. Pendleton (Neil); B.W.J.H. Penninx (Brenda); M. Perola (Markus); N. Pirastu (Nicola); M. Pirastu (Mario); O. Polasek (Ozren); D. Posthuma (Danielle); C. Power (Christopher); M.A. Province (Mike); N.J. Samani (Nilesh); Schlessinger, D. (David); R. Schmidt (Reinhold); T.I.A. Sørensen (Thorkild); T.D. Spector (Timothy); J-A. Zwart (John-Anker); U. Thorsteinsdottir (Unnur); A.R. Thurik (Roy); Timpson, N.J. (Nicholas J.); H.W. Tiemeier (Henning); J.Y. Tung (Joyce Y.); A.G. Uitterlinden (André); Vitart, V. (Veronique); P. Vollenweider (Peter); D.R. Weir (David); J.F. Wilson (James F.); A.F. Wright (Alan); Conley, D.C. (Dalton C.); R.F. Krueger; G.D. Smith; Hofman, A. (Albert); D. Laibson (David); S.E. Medland (Sarah Elizabeth); M.N. Meyer (Michelle N.); J. Yang (Joanna); M. Johannesson (Magnus); P.M. Visscher (Peter); T. Esko (Tõnu); Ph.D. Koellinger (Philipp); D. Cesarini (David); D.J. Benjamin (Daniel J.)

    2016-01-01

    textabstractEducational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that

  15. Genome-wide association study identifies 74 loci associated with educational attainment

    NARCIS (Netherlands)

    Okbay, A.; Beauchamp, J.; Fontana, M.A.; Lee, J.J.; Pers, T.H.; Rietveld, C.A.; Turley, P.; Chen, G.B.; Emilsson, V.; Meddens, S.F.W.; de Vlaming, R.; Abdellaoui, A.; Peyrot, W.; Vinkhuyzen, A.A.E.; Hottenga, J.J.; Willemsen, G.; Boomsma, D.I.; Penninx, B.W.J.H.; Laibson, D.; Medland, S.E.; Meyer, M.N.; Yang, J.; Johannesson, M.; Visscher, P.M.; Esko, T.; Koellinger, P.D.; Cesarini, D.; Benjamin, D.J.

    2016-01-01

    Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our

  16. Genome-wide association study identifies 74 loci associated with educational attainment

    NARCIS (Netherlands)

    Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark Alan; Lee, James J.; Pers, Tune H.; Rietveld, Cornelius A.; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S. Fleur W.; Oskarsson, Sven; Pickrell, Joseph K.; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S.; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H.; Concas, Maria Pina; Derringer, Jaime; Furlotte, Nicholas A.; Galesloot, Tessel E.; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M.; Harris, Sarah E.; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E.; Kaasik, Kadri; Kalafati, Ioanna P.; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J.; de Leeuw, Christiaan; Lind, Penelope A.; Lindgren, Karl-Oskar; Liu, Tian; van der Most, Peter J.; Verweij, Niek; Alizadeh, Behrooz Z.; Vonk, Judith M.; Bultmann, Ute; Franke, Lude; van der Harst, Pim; Penninx, Brenda W. J. H.

    2016-01-01

    Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals(1). Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends

  17. Role Modeling for Clinical Educators.

    Science.gov (United States)

    Ettinger, Ellen Richter

    1991-01-01

    To become better role models, higher educators in institutions of clinical education should be conscious of the behaviors they demonstrate and the broad range of activities and attitudes that students observe and emulate, including clinical competence, professional demeanor, doctor-patient interactions, ethical values, and social consciousness.…

  18. Genome-scale modeling for metabolic engineering.

    Science.gov (United States)

    Simeonidis, Evangelos; Price, Nathan D

    2015-03-01

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  19. Educational Technology Funding Models

    Science.gov (United States)

    Mark, Amy E.

    2008-01-01

    Library and cross-disciplinary literature all stress the increasing importance of instructional technology in higher education. However, there is a dearth of articles detailing funding for library instructional technology. The bulk of library literature on funding for these projects focuses on one-time grant opportunities and on the architecture…

  20. Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling.

    Science.gov (United States)

    Niida, Atsushi; Nagayama, Satoshi; Miyano, Satoru; Mimori, Koshi

    2018-04-01

    Cancer is composed of multiple cell populations with different genomes. This phenomenon called intratumor heterogeneity (ITH) is supposed to be a fundamental cause of therapeutic failure. Therefore, its principle-level understanding is a clinically important issue. To achieve this goal, an interdisciplinary approach combining genome analysis and mathematical modeling is essential. For example, we have recently performed multiregion sequencing to unveil extensive ITH in colorectal cancer. Moreover, by employing mathematical modeling of cancer evolution, we demonstrated that it is possible that this ITH is generated by neutral evolution. In this review, we introduce recent advances in a research field related to ITH and also discuss strategies for exploiting novel findings on ITH in a clinical setting. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

  1. Next-generation genome-scale models for metabolic engineering

    DEFF Research Database (Denmark)

    King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....

  2. Online Genome Analysis Resources for Educators, a Comparative Review

    OpenAIRE

    Sarah Grace Prescott

    2012-01-01

    A comparative review of several companies that offer similar kits or services that allow students to isolate DNA (human and others), amplify it by PCR, and in some cases sequence the resulting sample.  The companies include:  Carolina® Biological Supply Company, Bio-Rad®, Edvotek® Inc., Hiram Genomics Store, and 23andMe.

  3. Virtual Genome Walking across the 32 Gb Ambystoma mexicanum genome; assembling gene models and intronic sequence.

    Science.gov (United States)

    Evans, Teri; Johnson, Andrew D; Loose, Matthew

    2018-01-12

    Large repeat rich genomes present challenges for assembly using short read technologies. The 32 Gb axolotl genome is estimated to contain ~19 Gb of repetitive DNA making an assembly from short reads alone effectively impossible. Indeed, this model species has been sequenced to 20× coverage but the reads could not be conventionally assembled. Using an alternative strategy, we have assembled subsets of these reads into scaffolds describing over 19,000 gene models. We call this method Virtual Genome Walking as it locally assembles whole genome reads based on a reference transcriptome, identifying exons and iteratively extending them into surrounding genomic sequence. These assemblies are then linked and refined to generate gene models including upstream and downstream genomic, and intronic, sequence. Our assemblies are validated by comparison with previously published axolotl bacterial artificial chromosome (BAC) sequences. Our analyses of axolotl intron length, intron-exon structure, repeat content and synteny provide novel insights into the genic structure of this model species. This resource will enable new experimental approaches in axolotl, such as ChIP-Seq and CRISPR and aid in future whole genome sequencing efforts. The assembled sequences and annotations presented here are freely available for download from https://tinyurl.com/y8gydc6n . The software pipeline is available from https://github.com/LooseLab/iterassemble .

  4. Towards an educational diabetes model

    NARCIS (Netherlands)

    Maas, A.H.

    2012-01-01

    We are developing a mathematical model to serve as the heart of an educational diabetes simulator. The model is based on physiological principles and consists of three compartments: the gut, the plasma and the interstitial fluid. Glucose and insulin in- and outflow is described for all three

  5. An object model for genome information at all levels of resolution

    Energy Technology Data Exchange (ETDEWEB)

    Honda, S.; Parrott, N.W.; Smith, R.; Lawrence, C.

    1993-12-31

    An object model for genome data at all levels of resolution is described. The model was derived by considering the requirements for representing genome related objects in three application domains: genome maps, large-scale DNA sequencing, and exploring functional information in gene and protein sequences. The methodology used for the object-oriented analysis is also described.

  6. Online Genome Analysis Resources for Educators, a Comparative Review

    Directory of Open Access Journals (Sweden)

    Sarah Grace Prescott

    2012-08-01

    Full Text Available A comparative review of several companies that offer similar kits or services that allow students to isolate DNA (human and others, amplify it by PCR, and in some cases sequence the resulting sample.  The companies include:  Carolina® Biological Supply Company, Bio-Rad®, Edvotek® Inc., Hiram Genomics Store, and 23andMe.

  7. Framework for development of physician competencies in genomic medicine: report of the Competencies Working Group of the Inter-Society Coordinating Committee for Physician Education in Genomics.

    Science.gov (United States)

    Korf, Bruce R; Berry, Anna B; Limson, Melvin; Marian, Ali J; Murray, Michael F; O'Rourke, P Pearl; Passamani, Eugene R; Relling, Mary V; Tooker, John; Tsongalis, Gregory J; Rodriguez, Laura L

    2014-11-01

    Completion of the Human Genome Project, in conjunction with dramatic reductions in the cost of DNA sequencing and advances in translational research, is gradually ushering genomic discoveries and technologies into the practice of medicine. The rapid pace of these advances is opening up a gap between the knowledge available about the clinical relevance of genomic information and the ability of clinicians to include such information in their medical practices. This educational gap threatens to be rate limiting to the clinical adoption of genomics in medicine. Solutions will require not only a better understanding of the clinical implications of genetic discoveries but also training in genomics at all levels of professional development, including for individuals in formal training and others who long ago completed such training. The National Human Genome Research Institute has convened the Inter-Society Coordinating Committee for Physician Education in Genomics (ISCC) to develop and share best practices in the use of genomics in medicine. The ISCC has developed a framework for development of genomics practice competencies that may serve as a starting point for formulation of competencies for physicians in various medical disciplines.

  8. Education of a model student.

    Science.gov (United States)

    Novikoff, Timothy P; Kleinberg, Jon M; Strogatz, Steven H

    2012-02-07

    A dilemma faced by teachers, and increasingly by designers of educational software, is the trade-off between teaching new material and reviewing what has already been taught. Complicating matters, review is useful only if it is neither too soon nor too late. Moreover, different students need to review at different rates. We present a mathematical model that captures these issues in idealized form. The student's needs are modeled as constraints on the schedule according to which educational material and review are spaced over time. Our results include algorithms to construct schedules that adhere to various spacing constraints, and bounds on the rate at which new material can be introduced under these schedules.

  9. Genome-wide association study identifies 74 loci associated with educational attainment

    DEFF Research Database (Denmark)

    Okbay, Aysu; P. Beauchamp, Jonathan; Alan Fontana, Mark

    2016-01-01

    -nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural......Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends...... development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals...

  10. A Bayesian antedependence model for whole genome prediction.

    Science.gov (United States)

    Yang, Wenzhao; Tempelman, Robert J

    2012-04-01

    Hierarchical mixed effects models have been demonstrated to be powerful for predicting genomic merit of livestock and plants, on the basis of high-density single-nucleotide polymorphism (SNP) marker panels, and their use is being increasingly advocated for genomic predictions in human health. Two particularly popular approaches, labeled BayesA and BayesB, are based on specifying all SNP-associated effects to be independent of each other. BayesB extends BayesA by allowing a large proportion of SNP markers to be associated with null effects. We further extend these two models to specify SNP effects as being spatially correlated due to the chromosomally proximal effects of causal variants. These two models, that we respectively dub as ante-BayesA and ante-BayesB, are based on a first-order nonstationary antedependence specification between SNP effects. In a simulation study involving 20 replicate data sets, each analyzed at six different SNP marker densities with average LD levels ranging from r(2) = 0.15 to 0.31, the antedependence methods had significantly (P 0. 24) with differences exceeding 3%. A cross-validation study was also conducted on the heterogeneous stock mice data resource (http://mus.well.ox.ac.uk/mouse/HS/) using 6-week body weights as the phenotype. The antedependence methods increased cross-validation prediction accuracies by up to 3.6% compared to their classical counterparts (P benchmark data sets and demonstrated that the antedependence methods were more accurate than their classical counterparts for genomic predictions, even for individuals several generations beyond the training data.

  11. The genome of the model beetle and pest Tribolium castaneum

    DEFF Research Database (Denmark)

    Richards, Stephen; Gibbs, Richard A; Weinstock, George M

    2008-01-01

    Tribolium castaneum is a member of the most species-rich eukaryotic order, a powerful model organism for the study of generalized insect development, and an important pest of stored agricultural products. We describe its genome sequence here. This omnivorous beetle has evolved the ability...... to interact with a diverse chemical environment, as shown by large expansions in odorant and gustatory receptors, as well as P450 and other detoxification enzymes. Development in Tribolium is more representative of other insects than is Drosophila, a fact reflected in gene content and function. For example...

  12. Genome-wide association study identifies 74 loci associated with educational attainment

    OpenAIRE

    Okbay, Aysu; Beauchamp, Jonathan; Fontana, M.A. (Mark Alan); Lee, James J.; Pers, Tune; Rietveld, C.A. (Cornelius A.); Turley, Patrick; Chen, G.-B. (Guo-Bo); Emilsson, Valur; Meddens, S.F.W. (S. Fleur W.); Oskarsson, S. (Sven); Pickrell, J.K. (Joseph K.); Thom, K. (Kevin); Timshel, P. (Pascal); Vlaming, Ronald

    2016-01-01

    textabstractEducational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 geno...

  13. A Critical Analysis of Assessment Quality in Genomics and Bioinformatics Education Research

    Science.gov (United States)

    Campbell, Chad E.; Nehm, Ross H.

    2013-01-01

    The growing importance of genomics and bioinformatics methods and paradigms in biology has been accompanied by an explosion of new curricula and pedagogies. An important question to ask about these educational innovations is whether they are having a meaningful impact on students' knowledge, attitudes, or skills. Although assessments are…

  14. Learning about the Human Genome. Part 1: Challenge to Science Educators. ERIC Digest.

    Science.gov (United States)

    Haury, David L.

    This digest explains how to inform high school students and their parents about the human genome project (HGP) and how the information from this milestone finding will affect future biological and medical research and challenge science educators. The sections include: (1) "The Emerging Legacy of the HGP"; (2) "Transforming How…

  15. New Models for American Education.

    Science.gov (United States)

    Guthrie, James W.; Wynne, Edward

    Contents of this book include: (1) "New Models: The Need for School Reform," James W. Guthrie--a survey of some of the past successes of our educational system, an attempt to assess present public opinion about it, and an analysis of some possible explanations for its apparent inability to perform satisfactory; (2) "National Assessment: A History…

  16. Genome engineering of stem cell organoids for disease modeling.

    Science.gov (United States)

    Sun, Yingmin; Ding, Qiurong

    2017-05-01

    Precision medicine emerges as a new approach that takes into account individual variability. Successful realization of precision medicine requires disease models that are able to incorporate personalized disease information and recapitulate disease development processes at the molecular, cellular and organ levels. With recent development in stem cell field, a variety of tissue organoids can be derived from patient specific pluripotent stem cells and adult stem cells. In combination with the state-of-the-art genome editing tools, organoids can be further engineered to mimic disease-relevant genetic and epigenetic status of a patient. This has therefore enabled a rapid expansion of sophisticated in vitro disease models, offering a unique system for fundamental and biomedical research as well as the development of personalized medicine. Here we summarize some of the latest advances and future perspectives in engineering stem cell organoids for human disease modeling.

  17. GENOME-BASED MODELING AND DESIGN OF METABOLIC INTERACTIONS IN MICROBIAL COMMUNITIES

    Directory of Open Access Journals (Sweden)

    Radhakrishnan Mahadevan

    2012-10-01

    With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

  18. New transgenic models of Parkinson's disease using genome editing technology.

    Science.gov (United States)

    Cota-Coronado, J A; Sandoval-Ávila, S; Gaytan-Dávila, Y P; Diaz, N F; Vega-Ruiz, B; Padilla-Camberos, E; Díaz-Martínez, N E

    2017-11-28

    Parkinson's disease (PD) is the second most common neurodegenerative disorder. It is characterised by selective loss of dopaminergic neurons in the substantia nigra pars compacta, which results in dopamine depletion, leading to a number of motor and non-motor symptoms. In recent years, the development of new animal models using nuclease-based genome-editing technology (ZFN, TALEN, and CRISPR/Cas9 nucleases) has enabled the introduction of custom-made modifications into the genome to replicate key features of PD, leading to significant advances in our understanding of the pathophysiology of the disease. We review the most recent studies on this new generation of in vitro and in vivo PD models, which replicate the most relevant symptoms of the disease and enable better understanding of the aetiology and mechanisms of PD. This may be helpful in the future development of effective treatments to halt or slow disease progression. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

  19. Genomic predictions across Nordic Holstein and Nordic Red using the genomic best linear unbiased prediction model with different genomic relationship matrices.

    Science.gov (United States)

    Zhou, L; Lund, M S; Wang, Y; Su, G

    2014-08-01

    This study investigated genomic predictions across Nordic Holstein and Nordic Red using various genomic relationship matrices. Different sources of information, such as consistencies of linkage disequilibrium (LD) phase and marker effects, were used to construct the genomic relationship matrices (G-matrices) across these two breeds. Single-trait genomic best linear unbiased prediction (GBLUP) model and two-trait GBLUP model were used for single-breed and two-breed genomic predictions. The data included 5215 Nordic Holstein bulls and 4361 Nordic Red bulls, which was composed of three populations: Danish Red, Swedish Red and Finnish Ayrshire. The bulls were genotyped with 50 000 SNP chip. Using the two-breed predictions with a joint Nordic Holstein and Nordic Red reference population, accuracies increased slightly for all traits in Nordic Red, but only for some traits in Nordic Holstein. Among the three subpopulations of Nordic Red, accuracies increased more for Danish Red than for Swedish Red and Finnish Ayrshire. This is because closer genetic relationships exist between Danish Red and Nordic Holstein. Among Danish Red, individuals with higher genomic relationship coefficients with Nordic Holstein showed more increased accuracies in the two-breed predictions. Weighting the two-breed G-matrices by LD phase consistencies, marker effects or both did not further improve accuracies of the two-breed predictions. © 2014 Blackwell Verlag GmbH.

  20. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

    DEFF Research Database (Denmark)

    King, Zachary A.; Lu, Justin; Dräger, Andreas

    2016-01-01

    Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repo...

  1. Educational attainment: A genome wide association study in 9538 Australians

    NARCIS (Netherlands)

    Martin, N.W.; Medland, S.E.; Verweij, K.J.H.; Lee, S.H.; Nyholt, D.R.; Madden, P.A.F.; Heath, A.C.; Montgomery, G.W.; Wright, M.J.; Martin, N.G.

    2011-01-01

    Background: Correlations between Educational Attainment (EA) and measures of cognitive performance are as high as 0.8. This makes EA an attractive alternative phenotype for studies wishing to map genes affecting cognition due to the ease of collecting EA data compared to other cognitive phenotypes

  2. Genomic Model with Correlation Between Additive and Dominance Effects.

    Science.gov (United States)

    Xiang, Tao; Christensen, Ole Fredslund; Vitezica, Zulma Gladis; Legarra, Andres

    2018-05-09

    Dominance genetic effects are rarely included in pedigree-based genetic evaluation. With the availability of single nucleotide polymorphism markers and the development of genomic evaluation, estimates of dominance genetic effects have become feasible using genomic best linear unbiased prediction (GBLUP). Usually, studies involving additive and dominance genetic effects ignore possible relationships between them. It has been often suggested that the magnitude of functional additive and dominance effects at the quantitative trait loci are related, but there is no existing GBLUP-like approach accounting for such correlation. Wellmann and Bennewitz showed two ways of considering directional relationships between additive and dominance effects, which they estimated in a Bayesian framework. However, these relationships cannot be fitted at the level of individuals instead of loci in a mixed model and are not compatible with standard animal or plant breeding software. This comes from a fundamental ambiguity in assigning the reference allele at a given locus. We show that, if there has been selection, assigning the most frequent as the reference allele orients the correlation between functional additive and dominance effects. As a consequence, the most frequent reference allele is expected to have a positive value. We also demonstrate that selection creates negative covariance between genotypic additive and dominance genetic values. For parameter estimation, it is possible to use a combined additive and dominance relationship matrix computed from marker genotypes, and to use standard restricted maximum likelihood (REML) algorithms based on an equivalent model. Through a simulation study, we show that such correlations can easily be estimated by mixed model software and accuracy of prediction for genetic values is slightly improved if such correlations are used in GBLUP. However, a model assuming uncorrelated effects and fitting orthogonal breeding values and dominant

  3. Awareness, Solidarity, and Action: An Educational Model

    Science.gov (United States)

    Reichenbach, Michael R.

    2016-01-01

    How Extension fosters social change and innovation can be improved through the use of theory-based educational models. Educational models can serve as foundations for the conceptual designs of educational interventions. I describe, using examples from my own work, one such model: the awareness, solidarity, and action model. This three-part model…

  4. Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model

    DEFF Research Database (Denmark)

    Olivares Hernandez, Roberto

    Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been construc......Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been...

  5. Applying the Sport Education Model to Tennis

    Science.gov (United States)

    Ayvazo, Shiri

    2009-01-01

    The physical education field abounds with theoretically sound curricular approaches such as fitness education, skill theme approach, tactical approach, and sport education. In an era that emphasizes authentic sport experiences, the Sport Education Model includes unique features that sets it apart from other curricular models and can be a valuable…

  6. Educational game models: conceptualization and evaluation ...

    African Journals Online (AJOL)

    Educational game models: conceptualization and evaluation. ... The Game Object Model (GOM), that marries educational theory and game design, forms the basis for the development of the Persona Outlining ... AJOL African Journals Online.

  7. Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger.

    Science.gov (United States)

    Wright, James C; Sugden, Deana; Francis-McIntyre, Sue; Riba-Garcia, Isabel; Gaskell, Simon J; Grigoriev, Igor V; Baker, Scott E; Beynon, Robert J; Hubbard, Simon J

    2009-02-04

    Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI) and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS) were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS) and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR). 405 identified peptide sequences were mapped to 214 different A.niger genomic loci to which 4093 predicted gene models clustered, 2872 of which contained the mapped peptides. Interestingly, 13 (6%) of these loci either had no preferred predicted gene model or the genome annotators' chosen "best" model for that genomic locus was not found to be the most parsimonious match to the identified peptides. The peptides identified also boosted confidence in predicted gene structures spanning 54 introns from different gene models. This work highlights the potential of integrating experimental proteomics data into genomic annotation pipelines much as expressed sequence tag (EST) data has been. A comparison of the published genome from another strain of A.niger sequenced by DSM showed that a number of the gene models or proteins with proteomics evidence did not occur in both genomes, further highlighting the utility of the method.

  8. Zebrafish models for the functional genomics of neurogenetic disorders.

    Science.gov (United States)

    Kabashi, Edor; Brustein, Edna; Champagne, Nathalie; Drapeau, Pierre

    2011-03-01

    In this review, we consider recent work using zebrafish to validate and study the functional consequences of mutations of human genes implicated in a broad range of degenerative and developmental disorders of the brain and spinal cord. Also we present technical considerations for those wishing to study their own genes of interest by taking advantage of this easily manipulated and clinically relevant model organism. Zebrafish permit mutational analyses of genetic function (gain or loss of function) and the rapid validation of human variants as pathological mutations. In particular, neural degeneration can be characterized at genetic, cellular, functional, and behavioral levels. Zebrafish have been used to knock down or express mutations in zebrafish homologs of human genes and to directly express human genes bearing mutations related to neurodegenerative disorders such as spinal muscular atrophy, ataxia, hereditary spastic paraplegia, amyotrophic lateral sclerosis (ALS), epilepsy, Huntington's disease, Parkinson's disease, fronto-temporal dementia, and Alzheimer's disease. More recently, we have been using zebrafish to validate mutations of synaptic genes discovered by large-scale genomic approaches in developmental disorders such as autism, schizophrenia, and non-syndromic mental retardation. Advances in zebrafish genetics such as multigenic analyses and chemical genetics now offer a unique potential for disease research. Thus, zebrafish hold much promise for advancing the functional genomics of human diseases, the understanding of the genetics and cell biology of degenerative and developmental disorders, and the discovery of therapeutics. This article is part of a Special Issue entitled Zebrafish Models of Neurological Diseases. Copyright © 2010 Elsevier B.V. All rights reserved.

  9. Genomic comparison of closely related Giant Viruses supports an accordion-like model of evolution.

    Directory of Open Access Journals (Sweden)

    Jonathan eFilée

    2015-06-01

    Full Text Available Genome gigantism occurs so far in Phycodnaviridae and Mimiviridae (order Megavirales. Origin and evolution of these Giant Viruses (GVs remain open questions. Interestingly, availability of a collection of closely related GV genomes enabling genomic comparisons offer the opportunity to better understand the different evolutionary forces acting on these genomes. Whole genome alignment for 5 groups of viruses belonging to the Mimiviridae and Phycodnaviridae families show that there is no trend of genome expansion or general tendency of genome contraction. Instead, GV genomes accumulated genomic mutations over the time with gene gains compensating the different losses. In addition, each lineage displays specific patterns of genome evolution. Mimiviridae (megaviruses and mimiviruses and Chlorella Phycodnaviruses evolved mainly by duplications and losses of genes belonging to large paralogous families (including movements of diverse mobiles genetic elements, whereas Micromonas and Ostreococcus Phycodnaviruses derive most of their genetic novelties thought lateral gene transfers. Taken together, these data support an accordion-like model of evolution in which GV genomes have undergone successive steps of gene gain and gene loss, accrediting the hypothesis that genome gigantism appears early, before the diversification of the different GV lineages.

  10. Genomic comparison of closely related Giant Viruses supports an accordion-like model of evolution.

    Science.gov (United States)

    Filée, Jonathan

    2015-01-01

    Genome gigantism occurs so far in Phycodnaviridae and Mimiviridae (order Megavirales). Origin and evolution of these Giant Viruses (GVs) remain open questions. Interestingly, availability of a collection of closely related GV genomes enabling genomic comparisons offer the opportunity to better understand the different evolutionary forces acting on these genomes. Whole genome alignment for five groups of viruses belonging to the Mimiviridae and Phycodnaviridae families show that there is no trend of genome expansion or general tendency of genome contraction. Instead, GV genomes accumulated genomic mutations over the time with gene gains compensating the different losses. In addition, each lineage displays specific patterns of genome evolution. Mimiviridae (megaviruses and mimiviruses) and Chlorella Phycodnaviruses evolved mainly by duplications and losses of genes belonging to large paralogous families (including movements of diverse mobiles genetic elements), whereas Micromonas and Ostreococcus Phycodnaviruses derive most of their genetic novelties thought lateral gene transfers. Taken together, these data support an accordion-like model of evolution in which GV genomes have undergone successive steps of gene gain and gene loss, accrediting the hypothesis that genome gigantism appears early, before the diversification of the different GV lineages.

  11. Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing.

    Science.gov (United States)

    Schmidlen, Tara; Sturm, Amy C; Hovick, Shelly; Scheinfeldt, Laura; Scott Roberts, J; Morr, Lindsey; McElroy, Joseph; Toland, Amanda E; Christman, Michael; O'Daniel, Julianne M; Gordon, Erynn S; Bernhardt, Barbara A; Ormond, Kelly E; Sweet, Kevin

    2018-02-19

    With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large-scale genomic testing effort. We preserve the provision of pre-test education and informed consent as established in Mendelian/single-gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post-counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow-up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.

  12. Mathematical Modeling: A Bridge to STEM Education

    Science.gov (United States)

    Kertil, Mahmut; Gurel, Cem

    2016-01-01

    The purpose of this study is making a theoretical discussion on the relationship between mathematical modeling and integrated STEM education. First of all, STEM education perspective and the construct of mathematical modeling in mathematics education is introduced. A review of literature is provided on how mathematical modeling literature may…

  13. GGRaSP: A R-package for selecting representative genomes using Gaussian mixture models.

    Science.gov (United States)

    Clarke, Thomas H; Brinkac, Lauren M; Sutton, Granger; Fouts, Derrick E

    2018-04-14

    The vast number of available sequenced bacterial genomes occasionally exceeds the facilities of comparative genomic methods or is dominated by a single outbreak strain, and thus a diverse and representative subset is required. Generation of the reduced subset currently requires a priori supervised clustering and sequence-only selection of medoid genomic sequences, independent of any additional genome metrics or strain attributes. The GGRaSP R-package described below generates a reduced subset of genomes that prioritizes maintaining genomes of interest to the user as well as minimizing the loss of genetic variation. The package also allows for unsupervised clustering by modeling the genomic relationships using a Gaussian Mixture Model to select an appropriate cluster threshold. We demonstrate the capabilities of GGRaSP by generating a reduced list of 315 genomes from a genomic dataset of 4600 Escherichia coli genomes, prioritizing selection by type strain and by genome completeness. GGRaSP is available at https://github.com/JCVenterInstitute/ggrasp/. tclarke@jcvi.org. Supplementary data are available at the GitHub site.

  14. Rapid genome reshaping by multiple-gene loss after whole-genome duplication in teleost fish suggested by mathematical modeling

    Science.gov (United States)

    Sato, Yukuto; Tsukamoto, Katsumi; Nishida, Mutsumi

    2015-01-01

    Whole-genome duplication (WGD) is believed to be a significant source of major evolutionary innovation. Redundant genes resulting from WGD are thought to be lost or acquire new functions. However, the rates of gene loss and thus temporal process of genome reshaping after WGD remain unclear. The WGD shared by all teleost fish, one-half of all jawed vertebrates, was more recent than the two ancient WGDs that occurred before the origin of jawed vertebrates, and thus lends itself to analysis of gene loss and genome reshaping. Using a newly developed orthology identification pipeline, we inferred the post–teleost-specific WGD evolutionary histories of 6,892 protein-coding genes from nine phylogenetically representative teleost genomes on a time-calibrated tree. We found that rapid gene loss did occur in the first 60 My, with a loss of more than 70–80% of duplicated genes, and produced similar genomic gene arrangements within teleosts in that relatively short time. Mathematical modeling suggests that rapid gene loss occurred mainly by events involving simultaneous loss of multiple genes. We found that the subsequent 250 My were characterized by slow and steady loss of individual genes. Our pipeline also identified about 1,100 shared single-copy genes that are inferred to have become singletons before the divergence of clupeocephalan teleosts. Therefore, our comparative genome analysis suggests that rapid gene loss just after the WGD reshaped teleost genomes before the major divergence, and provides a useful set of marker genes for future phylogenetic analysis. PMID:26578810

  15. Addressing the dynamics of science in curricular reform for scientific literacy: Towards authentic science education in the case of genomics.

    NARCIS (Netherlands)

    Eijck, van M.W.

    2010-01-01

    Science education reform must anticipate the scientific literacy required by the next generation of citizens. Particularly, this counts for rapidly emerging and evolving scientific disciplines such as genomics. Taking this discipline as a case, such anticipation is becoming increasingly problematic

  16. New Markov Model Approaches to Deciphering Microbial Genome Function and Evolution: Comparative Genomics of Laterally Transferred Genes

    Energy Technology Data Exchange (ETDEWEB)

    Borodovsky, M.

    2013-04-11

    Algorithmic methods for gene prediction have been developed and successfully applied to many different prokaryotic genome sequences. As the set of genes in a particular genome is not homogeneous with respect to DNA sequence composition features, the GeneMark.hmm program utilizes two Markov models representing distinct classes of protein coding genes denoted "typical" and "atypical". Atypical genes are those whose DNA features deviate significantly from those classified as typical and they represent approximately 10% of any given genome. In addition to the inherent interest of more accurately predicting genes, the atypical status of these genes may also reflect their separate evolutionary ancestry from other genes in that genome. We hypothesize that atypical genes are largely comprised of those genes that have been relatively recently acquired through lateral gene transfer (LGT). If so, what fraction of atypical genes are such bona fide LGTs? We have made atypical gene predictions for all fully completed prokaryotic genomes; we have been able to compare these results to other "surrogate" methods of LGT prediction.

  17. [Overview of patents on targeted genome editing technologies and their implications for innovation and entrepreneurship education in universities].

    Science.gov (United States)

    Fan, Xiang-yu; Lin, Yan-ping; Liao, Guo-jian; Xie, Jian-ping

    2015-12-01

    Zinc finger nuclease, transcription activator-like effector nuclease, and clustered regularly interspaced short palindromic repeats/Cas9 nuclease are important targeted genome editing technologies. They have great significance in scientific research and applications on aspects of functional genomics research, species improvement, disease prevention and gene therapy. There are past or ongoing disputes over ownership of the intellectual property behind every technology. In this review, we summarize the patents on these three targeted genome editing technologies in order to provide some reference for developing genome editing technologies with self-owned intellectual property rights and some implications for current innovation and entrepreneurship education in universities.

  18. Using Genome-scale Models to Predict Biological Capabilities

    DEFF Research Database (Denmark)

    O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellul...

  19. Reference genome sequence of the model plant Setaria.

    Science.gov (United States)

    Bennetzen, Jeffrey L; Schmutz, Jeremy; Wang, Hao; Percifield, Ryan; Hawkins, Jennifer; Pontaroli, Ana C; Estep, Matt; Feng, Liang; Vaughn, Justin N; Grimwood, Jane; Jenkins, Jerry; Barry, Kerrie; Lindquist, Erika; Hellsten, Uffe; Deshpande, Shweta; Wang, Xuewen; Wu, Xiaomei; Mitros, Therese; Triplett, Jimmy; Yang, Xiaohan; Ye, Chu-Yu; Mauro-Herrera, Margarita; Wang, Lin; Li, Pinghua; Sharma, Manoj; Sharma, Rita; Ronald, Pamela C; Panaud, Olivier; Kellogg, Elizabeth A; Brutnell, Thomas P; Doust, Andrew N; Tuskan, Gerald A; Rokhsar, Daniel; Devos, Katrien M

    2012-05-13

    We generated a high-quality reference genome sequence for foxtail millet (Setaria italica). The ∼400-Mb assembly covers ∼80% of the genome and >95% of the gene space. The assembly was anchored to a 992-locus genetic map and was annotated by comparison with >1.3 million expressed sequence tag reads. We produced more than 580 million RNA-Seq reads to facilitate expression analyses. We also sequenced Setaria viridis, the ancestral wild relative of S. italica, and identified regions of differential single-nucleotide polymorphism density, distribution of transposable elements, small RNA content, chromosomal rearrangement and segregation distortion. The genus Setaria includes natural and cultivated species that demonstrate a wide capacity for adaptation. The genetic basis of this adaptation was investigated by comparing five sequenced grass genomes. We also used the diploid Setaria genome to evaluate the ongoing genome assembly of a related polyploid, switchgrass (Panicum virgatum).

  20. Reference genome sequence of the model plant Setaria

    Energy Technology Data Exchange (ETDEWEB)

    Bennetzen, Jeffrey L [ORNL; Schmutz, Jeremy [Hudson Alpha Institute of Biotechnology; Wang, Hao [University of Georgia, Athens, GA; Percifield, Ryan [University of Georgia, Athens, GA; Hawkins, Jennifer [University of Georgia, Athens, GA; Pontaroli, Ana C. [University of Georgia, Athens, GA; Estep, Matt [University of Georgia, Athens, GA; Feng, Liang [University of Georgia, Athens, GA; Vaughn, Justin N [ORNL; Grimwood, Jane [Hudson Alpha Institute of Biotechnology; Jenkins, Jerry [Hudson Alpha Institute of Biotechnology; Barry, Kerrie [U.S. Department of Energy, Joint Genome Institute; Lindquist, Erika [U.S. Department of Energy, Joint Genome Institute; Hellsten, Uffe [U.S. Department of Energy, Joint Genome Institute; Deshpande, Shweta [U.S. Department of Energy, Joint Genome Institute; Wang, Xuewen [University of Georgia, Athens, GA; Wu, Xiaomei [University of Georgia, Athens, GA; Mitros, Therese [University of California, Berkeley; Triplett, Jimmy [University of Missouri, St. Louis; Yang, Xiaohan [ORNL; Ye, Chuyu [ORNL; Mauro-Herrera, Margarita [Oklahoma State University; Wang, Lin [Cornell University; Li, Pinghua [Cornell University; Sharma, Manoj [University of California, Davis; Sharma, Rita [University of California, Davis; Ronald, Pamela [University of California, Davis; Panaud, Olivier [Universite de Perpignan, Perpignan, France; Kellogg, Elizabeth A. [University of Missouri, St. Louis; Brutnell, Thomas P. [Cornell University; Doust, Andrew N. [Oklahoma State University; Tuskan, Gerald A [ORNL; Rokhsar, Daniel [U.S. Department of Energy, Joint Genome Institute; Devos, Katrien M [ORNL

    2012-01-01

    We generated a high-quality reference genome sequence for foxtail millet (Setaria italica). The ~400-Mb assembly covers ~80% of the genome and >95% of the gene space. The assembly was anchored to a 992-locus genetic map and was annotated by comparison with >1.3 million expressed sequence tag reads. We produced more than 580 million RNA-Seq reads to facilitate expression analyses. We also sequenced Setaria viridis, the ancestral wild relative of S. italica, and identified regions of differential single-nucleotide polymorphism density, distribution of transposable elements, small RNA content, chromosomal rearrangement and segregation distortion. The genus Setaria includes natural and cultivated species that demonstrate a wide capacity for adaptation. The genetic basis of this adaptation was investigated by comparing five sequenced grass genomes. We also used the diploid Setaria genome to evaluate the ongoing genome assembly of a related polyploid, switchgrass (Panicum virgatum).

  1. Reference genome sequence of the model plant Setaria

    Energy Technology Data Exchange (ETDEWEB)

    Bennetzen, Jeffrey L [ORNL; Yang, Xiaohan [ORNL; Ye, Chuyu [ORNL; Tuskan, Gerald A [ORNL

    2012-01-01

    We generated a high-quality reference genome sequence for foxtail millet (Setaria italica). The {approx}400-Mb assembly covers {approx}80% of the genome and >95% of the gene space. The assembly was anchored to a 992-locus genetic map and was annotated by comparison with >1.3 million expressed sequence tag reads. We produced more than 580 million RNA-Seq reads to facilitate expression analyses. We also sequenced Setaria viridis, the ancestral wild relative of S. italica, and identified regions of differential single-nucleotide polymorphism density, distribution of transposable elements, small RNA content, chromosomal rearrangement and segregation distortion. The genus Setaria includes natural and cultivated species that demonstrate a wide capacity for adaptation. The genetic basis of this adaptation was investigated by comparing five sequenced grass genomes. We also used the diploid Setaria genome to evaluate the ongoing genome assembly of a related polyploid, switchgrass (Panicum virgatum).

  2. A Forecast Model for Unemployment by Education

    DEFF Research Database (Denmark)

    Tranæs, Torben; Larsen, Anders Holm; Groes, Niels

    1994-01-01

    We present a dynamic forecast model for the labour market: demand for labour by education and the distribution of labour by education among industries are determined endogenously with overall demand by industry given exogenously. The model is derived from a simple behavioural equation based on a ...... for educational groups, where the initial forecast year is a change point for unemployment....

  3. Marketing Education on a Shoestring: A Model.

    Science.gov (United States)

    Shreeve, William; And Others

    Few educators envision themselves as marketing or public relations experts, yet economic reality is forcing many academicians into these roles. Over the past four years, the Eastern Washington University Department of Education has developed a successful marketing model for educators. The model begins with a successful reform of department…

  4. Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger

    OpenAIRE

    Wright, James C.; Sugden, Deana; Francis-McIntyre, Sue; Riba Garcia, Isabel; Gaskell, Simon J.; Grigoriev, Igor V.; Baker, Scott E.; Beynon, Robert J.; Hubbard, Simon J.

    2009-01-01

    Abstract Background Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI) and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS) were ac...

  5. GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes

    Directory of Open Access Journals (Sweden)

    Nakayama Yoichi

    2006-03-01

    Full Text Available Abstract Background Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. Results We developed the Genome-based Modeling (GEM System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. Conclusion The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

  6. Training future physicians in the era of genomic medicine: trends in undergraduate medical genetics education.

    Science.gov (United States)

    Plunkett-Rondeau, Jevon; Hyland, Katherine; Dasgupta, Shoumita

    2015-11-01

    Advances in genomic technologies are transforming medical practice, necessitating the expertise of genomically-literate physicians. This study examined 2013-2014 trends in genetics curricula in US and Canadian medical schools to ascertain whether and how curricula are keeping pace with this rapid evolution. Medical genetics course directors received a 60-item electronic questionnaire covering curriculum design, assessment, remediation of failing grades, and inclusion of specific topics. The response rate was 74%. Most schools teach the majority of genetics during the first 2 years, with an increase in the number of integrated curricula. Only 26% reported formal genetics teaching during years 3 and 4, and most respondents felt the amount of time spent on genetics was insufficient preparation for clinical practice. Most participants are using the Association of Professors of Human and Medical Genetics Core Curriculum(1) as a guide. Topics recently added include personalized medicine (21%) and direct-to-consumer testing (18%), whereas eugenics (17%), linkage analysis (16%), and evolutionary genetics (15%) have been recently eliminated. Remediation strategies were heterogeneous across institutions. These findings provide an important update on how genetics and genomics is taught at US and Canadian medical schools. Continuous improvement of educational initiatives will aid in producing genomically-literate physicians.

  7. Higher Education Quality Assessment Model: Towards Achieving Educational Quality Standard

    Science.gov (United States)

    Noaman, Amin Y.; Ragab, Abdul Hamid M.; Madbouly, Ayman I.; Khedra, Ahmed M.; Fayoumi, Ayman G.

    2017-01-01

    This paper presents a developed higher education quality assessment model (HEQAM) that can be applied for enhancement of university services. This is because there is no universal unified quality standard model that can be used to assess the quality criteria of higher education institutes. The analytical hierarchy process is used to identify the…

  8. Models for mergers in higher education

    African Journals Online (AJOL)

    Investing in creativity: Many happy returns. Education Leadership, ... A possible model for higher education mergers, based on such extrapolation, is ..... working styles should be carefully managed from the very beginning of the process.

  9. Genome-wide association study identifies 74 loci associated with educational attainment

    Science.gov (United States)

    Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark A.; Lee, James J.; Pers, Tune H.; Rietveld, Cornelius A.; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S. Fleur W.; Oskarsson, Sven; Pickrell, Joseph K.; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S.; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H.; Concas, Maria Pina; Derringer, Jaime; Furlotte, Nicholas A.; Galesloot, Tessel E.; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M.; Harris, Sarah E.; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E.; Kaasik, Kadri; Kalafati, Ioanna P.; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J.; de Leeuw, Christiaan; Lind, Penelope A.; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B.; van der Most, Peter J.; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J.; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Börge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z.; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E.; Biino, Ginevra; Bønnelykke, Klaus; Boyle, Patricia A.; Campbell, Harry; Cappuccio, Francesco P.; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans68, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, Bjarni V.; Harris, Tamara B.; Heath, Andrew C.; Hocking, Lynne J.; Holliday, Elizabeth G.; Homuth, Georg; Horan, Michael A.; Hottenga, Jouke-Jan; de Jager, Philip L.; Joshi, Peter K.; Jugessur, Astanand; Kaakinen, Marika A.; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A.L.M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Maël P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C.M.; Loukola, Anu; Madden, Pamela A.; Mägi, Reedik; Mäki-Opas, Tomi; Marioni, Riccardo E.; Marques-Vidal, Pedro; Meddens, Gerardus A.; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W.; Myhre, Ronny; Nelson, Christopher P.; Nyholt, Dale R.; Ollier, William E.R.; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L.; Petrovic, Katja E.; Porteous, David J.; Räikkönen, Katri; Ring, Susan M.; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R.; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J.; Smith, Blair H.; Smith, Jennifer A.; Staessen, Jan A.; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D.; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J.A.; Venturini, Cristina; Vinkhuyzen, Anna A.E.; Völker, Uwe; Völzke, Henry; Vonk, Judith M.; Vozzi, Diego; Waage, Johannes; Ware, Erin B.; Willemsen, Gonneke; Attia, John R.; Bennett, David A.; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I.; Borecki, Ingrid B.; Bultmann, Ute; Chabris, Christopher F.; Cucca, Francesco; Cusi, Daniele; Deary, Ian J.; Dedoussis, George V.; van Duijn, Cornelia M.; Eriksson, Johan G.; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V.; Gieger, Christian; Grabe, Hans-Jörgen; Gratten, Jacob; Groenen, Patrick J.F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G.; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L.R.; Lehtimäki, Terho; Lehrer, Steven F.; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W.J.H.; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A.; Samani, Nilesh J.; Schlessinger, David; Schmidt, Reinhold; Sørensen, Thorkild I.A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, André G.; Vitart, Veronique; Vollenweider, Peter; Weir, David R.; Wilson, James F.; Wright, Alan F.; Conley, Dalton C.; Krueger, Robert F.; Smith, George Davey; Hofman, Albert; Laibson, David I.; Medland, Sarah E.; Meyer, Michelle N.; Yang, Jian; Johannesson, Magnus; Visscher, Peter M.; Esko, Tõnu; Koellinger, Philipp D.; Cesarini, David; Benjamin, Daniel J.

    2016-01-01

    Summary Educational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease. PMID:27225129

  10. Meta-analysis of genome-wide association from genomic prediction models

    Science.gov (United States)

    A limitation of many genome-wide association studies (GWA) in animal breeding is that there are many loci with small effect sizes; thus, larger sample sizes (N) are required to guarantee suitable power of detection. To increase sample size, results from different GWA can be combined in a meta-analys...

  11. The General Education Collaboration Model: A Model for Successful Mainstreaming.

    Science.gov (United States)

    Simpson, Richard L.; Myles, Brenda Smith

    1990-01-01

    The General Education Collaboration Model is designed to support general educators teaching mainstreamed disabled students, through collaboration with special educators. The model is based on flexible departmentalization, program ownership, identification and development of supportive attitudes, student assessment as a measure of program…

  12. Towards a New Educational Model

    DEFF Research Database (Denmark)

    Moesby, Egon

    2003-01-01

    A presentation of the complexity in making organizational change in educational organizations when changing the educational paradighm towards POPBL (Project Organized and Problem Based Learning organized in teams). Involves three levels of decisionmaking and organization: Institutional Level......, System Level and Individual Level. The presentation is aimed at Rectors and Directors at Univeristies concidering posibilities for educational organizational change towards POPBL....

  13. Using Biology Education Research and Qualitative Inquiry to Inform Genomic Nursing Education.

    Science.gov (United States)

    Ward, Linda D

    Decades of research in biology education show that learning genetics is difficult and reveals specific sources of learning difficulty. Little is known about how nursing students learn in this domain, although they likely encounter similar difficulties as nonnursing students. Using qualitative approaches, this study investigated challenges to learning genetics among nursing students. Findings indicate that nursing students face learning difficulties already identified among biology students, suggesting that nurse educators might benefit from biology education research.

  14. A Spinozistic Model of Moral Education

    Science.gov (United States)

    Dahlbeck, Johan

    2017-01-01

    Spinoza's claim that self-preservation is the foundation of virtue makes for the point of departure of this philosophical investigation into what a Spinozistic model of moral education might look like. It is argued that Spinoza's metaphysics places constraints on moral education insofar as an educational account would be affected by Spinoza's…

  15. Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger

    Directory of Open Access Journals (Sweden)

    Grigoriev Igor V

    2009-02-01

    Full Text Available Abstract Background Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR. Results 405 identified peptide sequences were mapped to 214 different A.niger genomic loci to which 4093 predicted gene models clustered, 2872 of which contained the mapped peptides. Interestingly, 13 (6% of these loci either had no preferred predicted gene model or the genome annotators' chosen "best" model for that genomic locus was not found to be the most parsimonious match to the identified peptides. The peptides identified also boosted confidence in predicted gene structures spanning 54 introns from different gene models. Conclusion This work highlights the potential of integrating experimental proteomics data into genomic annotation pipelines much as expressed sequence tag (EST data has been. A comparison of the published genome from another strain of A.niger sequenced by DSM showed that a number of the gene models or proteins with proteomics evidence did not occur in both genomes, further highlighting the utility of the method.

  16. The Human Genome Project and Mental Retardation: An Educational Program. Final Progress Report

    Energy Technology Data Exchange (ETDEWEB)

    Davis, Sharon

    1999-05-03

    The Arc, a national organization on mental retardation, conducted an educational program for members, many of whom have a family member with a genetic condition causing mental retardation. The project informed members about the Human Genome scientific efforts, conducted training regarding ethical, legal and social implications and involved members in issue discussions. Short reports and fact sheets on genetic and ELSI topics were disseminated to 2,200 of the Arc's leaders across the country and to other interested individuals. Materials produced by the project can e found on the Arc's web site, TheArc.org.

  17. Establishing gene models from the Pinus pinaster genome using gene capture and BAC sequencing.

    Science.gov (United States)

    Seoane-Zonjic, Pedro; Cañas, Rafael A; Bautista, Rocío; Gómez-Maldonado, Josefa; Arrillaga, Isabel; Fernández-Pozo, Noé; Claros, M Gonzalo; Cánovas, Francisco M; Ávila, Concepción

    2016-02-27

    In the era of DNA throughput sequencing, assembling and understanding gymnosperm mega-genomes remains a challenge. Although drafts of three conifer genomes have recently been published, this number is too low to understand the full complexity of conifer genomes. Using techniques focused on specific genes, gene models can be established that can aid in the assembly of gene-rich regions, and this information can be used to compare genomes and understand functional evolution. In this study, gene capture technology combined with BAC isolation and sequencing was used as an experimental approach to establish de novo gene structures without a reference genome. Probes were designed for 866 maritime pine transcripts to sequence genes captured from genomic DNA. The gene models were constructed using GeneAssembler, a new bioinformatic pipeline, which reconstructed over 82% of the gene structures, and a high proportion (85%) of the captured gene models contained sequences from the promoter regulatory region. In a parallel experiment, the P. pinaster BAC library was screened to isolate clones containing genes whose cDNA sequence were already available. BAC clones containing the asparagine synthetase, sucrose synthase and xyloglucan endotransglycosylase gene sequences were isolated and used in this study. The gene models derived from the gene capture approach were compared with the genomic sequences derived from the BAC clones. This combined approach is a particularly efficient way to capture the genomic structures of gene families with a small number of members. The experimental approach used in this study is a valuable combined technique to study genomic gene structures in species for which a reference genome is unavailable. It can be used to establish exon/intron boundaries in unknown gene structures, to reconstruct incomplete genes and to obtain promoter sequences that can be used for transcriptional studies. A bioinformatics algorithm (GeneAssembler) is also provided as a

  18. Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim

    2008-01-01

    Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted...... model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion: A much enhanced annotation of the A. oryzae genome was performed and a genomescale metabolic model of A. oryzae was reconstructed. The model accurately predicted...

  19. A Model Technology Educator: Thomas A. Edison

    Science.gov (United States)

    Pretzer, William S.; Rogers, George E.; Bush, Jeffery

    2007-01-01

    Reflecting back over a century ago to the small village of Menlo Park, New Jersey provides insight into a remarkable visionary and an exceptional role model for today's problem-solving and design-focused technology educator: Thomas A. Edison, inventor, innovator, and model technology educator. Since Edison could not simply apply existing knowledge…

  20. A Critical Analysis of Assessment Quality in Genomics and Bioinformatics Education Research

    Science.gov (United States)

    Campbell, Chad E.; Nehm, Ross H.

    2013-01-01

    The growing importance of genomics and bioinformatics methods and paradigms in biology has been accompanied by an explosion of new curricula and pedagogies. An important question to ask about these educational innovations is whether they are having a meaningful impact on students’ knowledge, attitudes, or skills. Although assessments are necessary tools for answering this question, their outputs are dependent on their quality. Our study 1) reviews the central importance of reliability and construct validity evidence in the development and evaluation of science assessments and 2) examines the extent to which published assessments in genomics and bioinformatics education (GBE) have been developed using such evidence. We identified 95 GBE articles (out of 226) that contained claims of knowledge increases, affective changes, or skill acquisition. We found that 1) the purpose of most of these studies was to assess summative learning gains associated with curricular change at the undergraduate level, and 2) a minority (<10%) of studies provided any reliability or validity evidence, and only one study out of the 95 sampled mentioned both validity and reliability. Our findings raise concerns about the quality of evidence derived from these instruments. We end with recommendations for improving assessment quality in GBE. PMID:24006400

  1. biomvRhsmm: Genomic Segmentation with Hidden Semi-Markov Model

    Directory of Open Access Journals (Sweden)

    Yang Du

    2014-01-01

    Full Text Available High-throughput technologies like tiling array and next-generation sequencing (NGS generate continuous homogeneous segments or signal peaks in the genome that represent transcripts and transcript variants (transcript mapping and quantification, regions of deletion and amplification (copy number variation, or regions characterized by particular common features like chromatin state or DNA methylation ratio (epigenetic modifications. However, the volume and output of data produced by these technologies present challenges in analysis. Here, a hidden semi-Markov model (HSMM is implemented and tailored to handle multiple genomic profile, to better facilitate genome annotation by assisting in the detection of transcripts, regulatory regions, and copy number variation by holistic microarray or NGS. With support for various data distributions, instead of limiting itself to one specific application, the proposed hidden semi-Markov model is designed to allow modeling options to accommodate different types of genomic data and to serve as a general segmentation engine. By incorporating genomic positions into the sojourn distribution of HSMM, with optional prior learning using annotation or previous studies, the modeling output is more biologically sensible. The proposed model has been compared with several other state-of-the-art segmentation models through simulation benchmarking, which shows that our efficient implementation achieves comparable or better sensitivity and specificity in genomic segmentation.

  2. The genome of the model beetle and pest Tribolium castaneum

    Czech Academy of Sciences Publication Activity Database

    Richards, S.; Jindra, Marek

    2008-01-01

    Roč. 452, č. 7190 (2008), s. 949-955 ISSN 0028-0836 Institutional research plan: CEZ:AV0Z50070508 Keywords : Tribolium castaneum * genome * sequencing Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 31.434, year: 2008

  3. A probabilistic model to recover individual genomes from metagenomes

    NARCIS (Netherlands)

    J. Dröge (Johannes); A. Schönhuth (Alexander); A.C. McHardy (Alice)

    2017-01-01

    textabstractShotgun metagenomics of microbial communities reveal information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial but very challenging step due to the complexity of the underlying biological system and technical

  4. Evaluation of genome-enabled selection for bacterial cold water disease resistance using progeny performance data in Rainbow Trout: Insights on genotyping methods and genomic prediction models

    Science.gov (United States)

    Bacterial cold water disease (BCWD) causes significant economic losses in salmonid aquaculture, and traditional family-based breeding programs aimed at improving BCWD resistance have been limited to exploiting only between-family variation. We used genomic selection (GS) models to predict genomic br...

  5. Mathematical Modelling Approach in Mathematics Education

    Science.gov (United States)

    Arseven, Ayla

    2015-01-01

    The topic of models and modeling has come to be important for science and mathematics education in recent years. The topic of "Modeling" topic is especially important for examinations such as PISA which is conducted at an international level and measures a student's success in mathematics. Mathematical modeling can be defined as using…

  6. Higher Education: New Models, New Rules

    Science.gov (United States)

    Soares, Louis; Eaton, Judith S.; Smith, Burck

    2013-01-01

    The Internet enables new models. In the commercial world, for example, we have eBay, Amazon.com, and Netflix. These new models operate with a different set of rules than do traditional models. New models are emerging in higher education as well--for example, competency-based programs. In addition, courses that are being provided from outside the…

  7. How Much? Cost Models for Online Education.

    Science.gov (United States)

    Lorenzo, George

    2001-01-01

    Reviews some of the research being done in the area of cost models for online education. Describes a cost analysis handbook; an activity-based costing model that was based on an economic model for traditional instruction at the Indiana University Purdue University Indianapolis; and blending other costing models. (LRW)

  8. Invited review: Genetic and genomic mouse models for livestock research

    Directory of Open Access Journals (Sweden)

    D. Arends

    2018-02-01

    Full Text Available Knowledge about the function and functioning of single or multiple interacting genes is of the utmost significance for understanding the organism as a whole and for accurate livestock improvement through genomic selection. This includes, but is not limited to, understanding the ontogenetic and environmentally driven regulation of gene action contributing to simple and complex traits. Genetically modified mice, in which the functions of single genes are annotated; mice with reduced genetic complexity; and simplified structured populations are tools to gain fundamental knowledge of inheritance patterns and whole system genetics and genomics. In this review, we briefly describe existing mouse resources and discuss their value for fundamental and applied research in livestock.

  9. Rabbit models for biomedical research revisited via genome editing approaches

    Science.gov (United States)

    HONDA, Arata; OGURA, Atsuo

    2017-01-01

    Although the laboratory rabbit has long contributed to many paradigmatic studies in biology and medicine, it is often considered to be a “classical animal model” because in the last 30 years, the laboratory mouse has been more often used, thanks to the availability of embryonic stem cells that have allowed the generation of gene knockout (KO) animals. However, recent genome-editing strategies have changed this unrivaled condition; so far, more than 10 mammalian species have been added to the list of KO animals. Among them, the rabbit has distinct advantages for application of genome-editing systems, such as easy application of superovulation, consistency with fertile natural mating, well-optimized embryo manipulation techniques, and the short gestation period. The rabbit has now returned to the stage of advanced biomedical research. PMID:28579598

  10. A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types

    Science.gov (United States)

    Lin, Chen-Ching; Zhao, Junfei; Jia, Peilin; Li, Wen-Hsiung; Zhao, Zhongming

    2015-01-01

    Cancer development and progression result from somatic evolution by an accumulation of genomic alterations. The effects of those alterations on the fitness of somatic cells lead to evolutionary adaptations such as increased cell proliferation, angiogenesis, and altered anticancer drug responses. However, there are few general mathematical models to quantitatively examine how perturbations of a single gene shape subsequent evolution of the cancer genome. In this study, we proposed the gene gravity model to study the evolution of cancer genomes by incorporating the genome-wide transcription and somatic mutation profiles of ~3,000 tumors across 9 cancer types from The Cancer Genome Atlas into a broad gene network. We found that somatic mutations of a cancer driver gene may drive cancer genome evolution by inducing mutations in other genes. This functional consequence is often generated by the combined effect of genetic and epigenetic (e.g., chromatin regulation) alterations. By quantifying cancer genome evolution using the gene gravity model, we identified six putative cancer genes (AHNAK, COL11A1, DDX3X, FAT4, STAG2, and SYNE1). The tumor genomes harboring the nonsynonymous somatic mutations in these genes had a higher mutation density at the genome level compared to the wild-type groups. Furthermore, we provided statistical evidence that hypermutation of cancer driver genes on inactive X chromosomes is a general feature in female cancer genomes. In summary, this study sheds light on the functional consequences and evolutionary characteristics of somatic mutations during tumorigenesis by propelling adaptive cancer genome evolution, which would provide new perspectives for cancer research and therapeutics. PMID:26352260

  11. Rabbit models for biomedical research revisited via genome editing approaches

    OpenAIRE

    HONDA, Arata; OGURA, Atsuo

    2017-01-01

    Although the laboratory rabbit has long contributed to many paradigmatic studies in biology and medicine, it is often considered to be a “classical animal model” because in the last 30 years, the laboratory mouse has been more often used, thanks to the availability of embryonic stem cells that have allowed the generation of gene knockout (KO) animals. However, recent genome-editing strategies have changed this unrivaled condition; so far, more than 10 mammalian species have been added to the ...

  12. Methods for open innovation on a genome-design platform associating scientific, commercial, and educational communities in synthetic biology.

    Science.gov (United States)

    Toyoda, Tetsuro

    2011-01-01

    Synthetic biology requires both engineering efficiency and compliance with safety guidelines and ethics. Focusing on the rational construction of biological systems based on engineering principles, synthetic biology depends on a genome-design platform to explore the combinations of multiple biological components or BIO bricks for quickly producing innovative devices. This chapter explains the differences among various platform models and details a methodology for promoting open innovation within the scope of the statutory exemption of patent laws. The detailed platform adopts a centralized evaluation model (CEM), computer-aided design (CAD) bricks, and a freemium model. It is also important for the platform to support the legal aspects of copyrights as well as patent and safety guidelines because intellectual work including DNA sequences designed rationally by human intelligence is basically copyrightable. An informational platform with high traceability, transparency, auditability, and security is required for copyright proof, safety compliance, and incentive management for open innovation in synthetic biology. GenoCon, which we have organized and explained here, is a competition-styled, open-innovation method involving worldwide participants from scientific, commercial, and educational communities that aims to improve the designs of genomic sequences that confer a desired function on an organism. Using only a Web browser, a participating contributor proposes a design expressed with CAD bricks that generate a relevant DNA sequence, which is then experimentally and intensively evaluated by the GenoCon organizers. The CAD bricks that comprise programs and databases as a Semantic Web are developed, executed, shared, reused, and well stocked on the secure Semantic Web platform called the Scientists' Networking System or SciNetS/SciNeS, based on which a CEM research center for synthetic biology and open innovation should be established. Copyright © 2011 Elsevier Inc

  13. Gene finding with a hidden Markov model of genome structure and evolution

    DEFF Research Database (Denmark)

    Pedersen, Jakob Skou; Hein, Jotun

    2003-01-01

    the model are linear in alignment length and genome number. The model is applied to the problem of gene finding. The benefit of modelling sequence evolution is demonstrated both in a range of simulations and on a set of orthologous human/mouse gene pairs. AVAILABILITY: Free availability over the Internet...

  14. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Jensen Paul A

    2011-09-01

    Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

  15. Restricted DCJ-indel model: sorting linear genomes with DCJ and indels

    Science.gov (United States)

    2012-01-01

    Background The double-cut-and-join (DCJ) is a model that is able to efficiently sort a genome into another, generalizing the typical mutations (inversions, fusions, fissions, translocations) to which genomes are subject, but allowing the existence of circular chromosomes at the intermediate steps. In the general model many circular chromosomes can coexist in some intermediate step. However, when the compared genomes are linear, it is more plausible to use the so-called restricted DCJ model, in which we proceed the reincorporation of a circular chromosome immediately after its creation. These two consecutive DCJ operations, which create and reincorporate a circular chromosome, mimic a transposition or a block-interchange. When the compared genomes have the same content, it is known that the genomic distance for the restricted DCJ model is the same as the distance for the general model. If the genomes have unequal contents, in addition to DCJ it is necessary to consider indels, which are insertions and deletions of DNA segments. Linear time algorithms were proposed to compute the distance and to find a sorting scenario in a general, unrestricted DCJ-indel model that considers DCJ and indels. Results In the present work we consider the restricted DCJ-indel model for sorting linear genomes with unequal contents. We allow DCJ operations and indels with the following constraint: if a circular chromosome is created by a DCJ, it has to be reincorporated in the next step (no other DCJ or indel can be applied between the creation and the reincorporation of a circular chromosome). We then develop a sorting algorithm and give a tight upper bound for the restricted DCJ-indel distance. Conclusions We have given a tight upper bound for the restricted DCJ-indel distance. The question whether this bound can be reduced so that both the general and the restricted DCJ-indel distances are equal remains open. PMID:23281630

  16. Lukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

    CERN Document Server

    Baianu, I C

    2004-01-01

    A categorical and Lukasiewicz-Topos framework for Lukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes is proposed. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Lukasiewicz Topos with an n-valued Lukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.

  17. Exact Solution of Mutator Model with Linear Fitness and Finite Genome Length

    Science.gov (United States)

    Saakian, David B.

    2017-08-01

    We considered the infinite population version of the mutator phenomenon in evolutionary dynamics, looking at the uni-directional mutations in the mutator-specific genes and linear selection. We solved exactly the model for the finite genome length case, looking at the quasispecies version of the phenomenon. We calculated the mutator probability both in the statics and dynamics. The exact solution is important for us because the mutator probability depends on the genome length in a highly non-trivial way.

  18. Are Physical Education Majors Models for Fitness?

    Science.gov (United States)

    Kamla, James; Snyder, Ben; Tanner, Lori; Wash, Pamela

    2012-01-01

    The National Association of Sport and Physical Education (NASPE) (2002) has taken a firm stance on the importance of adequate fitness levels of physical education teachers stating that they have the responsibility to model an active lifestyle and to promote fitness behaviors. Since the NASPE declaration, national initiatives like Let's Move…

  19. Economic Modeling and Analysis of Educational Vouchers

    Science.gov (United States)

    Epple, Dennis; Romano, Richard

    2012-01-01

    The analysis of educational vouchers has evolved from market-based analogies to models that incorporate distinctive features of the educational environment. These distinctive features include peer effects, scope for private school pricing and admissions based on student characteristics, the linkage of household residential and school choices in…

  20. Eclectic Model in the Malaysian Education System

    Science.gov (United States)

    Othman, Nooraini; Mohamad, Khairul Azmi; Ilmuwan, Yayasan

    2011-01-01

    The present work aims at analysing the adoption of eclectic model in the Malaysian education system. The analysis is specifically looked from the angle of Islam and the Muslims. Malaysia has a long history of education system developments, from pre to post independence of the country. From what was initially traditional, modernity later came to…

  1. From genomes to vaccines: Leishmania as a model.

    Science.gov (United States)

    Almeida, Renata; Norrish, Alan; Levick, Mark; Vetrie, David; Freeman, Tom; Vilo, Jaak; Ivens, Alasdair; Lange, Uta; Stober, Carmel; McCann, Sharon; Blackwell, Jenefer M

    2002-01-01

    The 35 Mb genome of Leishmania should be sequenced by late 2002. It contains approximately 8500 genes that will probably translate into more than 10 000 proteins. In the laboratory we have been piloting strategies to try to harness the power of the genome-proteome for rapid screening of new vaccine candidate. To this end, microarray analysis of 1094 unique genes identified using an EST analysis of 2091 cDNA clones from spliced leader libraries prepared from different developmental stages of Leishmania has been employed. The plan was to identify amastigote-expressed genes that could be used in high-throughput DNA-vaccine screens to identify potential new vaccine candidates. Despite the lack of transcriptional regulation that polycistronic transcription in Leishmania dictates, the data provide evidence for a high level of post-transcriptional regulation of RNA abundance during the developmental cycle of promastigotes in culture and in lesion-derived amastigotes of Leishmania major. This has provided 147 candidates from the 1094 unique genes that are specifically upregulated in amastigotes and are being used in vaccine studies. Using DNA vaccination, it was demonstrated that pooling strategies can work to identify protective vaccines, but it was found that some potentially protective antigens are masked by other disease-exacerbatory antigens in the pool. A total of 100 new vaccine candidates are currently being tested separately and in pools to extend this analysis, and to facilitate retrospective bioinformatic analysis to develop predictive algorithms for sequences that constitute potentially protective antigens. We are also working with other members of the Leishmania Genome Network to determine whether RNA expression determined by microarray analyses parallels expression at the protein level. We believe we are making good progress in developing strategies that will allow rapid translation of the sequence of Leishmania into potential interventions for disease

  2. Postgraduate Education for Nurses: The Middlesex Model.

    Science.gov (United States)

    Caldwell, Kay

    2001-01-01

    A British university's curriculum model for master's and postgraduate diploma nursing education is characterized by structured collaboration among students, clinical mentors, and academic supervisors. A professional development portfolio individualizes the program and facilitates autonomous learning. (Contains 21 references.) (SK)

  3. QTL Analysis and Functional Genomics of Animal Model

    DEFF Research Database (Denmark)

    Farajzadeh, Leila

    , for example, has enabled scientists to examine more complex interactions in connection with studies of properties and diseases. In her PhD project, Leila Farajzadeh integrated different organisational levels in biology, including genotype, phenotype, association studies, transcription profiles and genetic......In recent years, the use of functional genomics and next-generation sequencing technologies has increased the probability of success in studies of complex properties. The integration of large data sets from association studies, DNA resequencing, gene expression profiles and phenotypic data...

  4. Functional validation of candidate genes detected by genomic feature models

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Østergaard, Solveig; Kristensen, Torsten Nygaard

    2018-01-01

    Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait...... then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated...

  5. Use of genome editing tools in human stem cell-based disease modeling and precision medicine.

    Science.gov (United States)

    Wei, Yu-da; Li, Shuang; Liu, Gai-gai; Zhang, Yong-xian; Ding, Qiu-rong

    2015-10-01

    Precision medicine emerges as a new approach that takes into account individual variability. The successful conduct of precision medicine requires the use of precise disease models. Human pluripotent stem cells (hPSCs), as well as adult stem cells, can be differentiated into a variety of human somatic cell types that can be used for research and drug screening. The development of genome editing technology over the past few years, especially the CRISPR/Cas system, has made it feasible to precisely and efficiently edit the genetic background. Therefore, disease modeling by using a combination of human stem cells and genome editing technology has offered a new platform to generate " personalized " disease models, which allow the study of the contribution of individual genetic variabilities to disease progression and the development of precise treatments. In this review, recent advances in the use of genome editing in human stem cells and the generation of stem cell models for rare diseases and cancers are discussed.

  6. Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

    2015-01-01

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....

  7. The Educational Situation Quality Model: Recent Advances.

    Science.gov (United States)

    Doménech-Betoret, Fernando

    2018-01-01

    The purpose of this work was to present an educational model developed in recent years entitled the "The Educational Situation Quality Model" (MOCSE, acronym in Spanish). MOCSE can be defined as an instructional model that simultaneously considers the teaching-learning process, where motivation plays a central role. It explains the functioning of an educational setting by organizing and relating the most important variables which, according to the literature, contribute to student learning. Besides being a conceptual framework, this model also provides a methodological procedure to guide research and to promote reflection in the classroom. It allows teachers to implement effective research-action programs to improve teacher-students satisfaction and learning outcomes in the classroom context. This work explains the model's characteristics and functioning, recent advances, and how teachers can use it in an educational setting with a specific subject. This proposal integrates approaches from several relevant psycho-educational theories and introduces a new perspective into the existing literature that will allow researchers to make progress in studying educational setting functioning. The initial MOCSE configuration has been refined over time in accordance with the empirical results obtained from previous research, carried out within the MOCSE framework and with the subsequent reflections that derived from these results. Finally, the contribution of the model to improve learning outcomes and satisfaction, and its applicability in the classroom, are also discussed.

  8. The complete genome sequence of Haloferax volcanii DS2, a model archaeon.

    Directory of Open Access Journals (Sweden)

    Amber L Hartman

    2010-03-01

    Full Text Available Haloferax volcanii is an easily culturable moderate halophile that grows on simple defined media, is readily transformable, and has a relatively stable genome. This, in combination with its biochemical and genetic tractability, has made Hfx. volcanii a key model organism, not only for the study of halophilicity, but also for archaeal biology in general.We report here the sequencing and analysis of the genome of Hfx. volcanii DS2, the type strain of this species. The genome contains a main 2.848 Mb chromosome, three smaller chromosomes pHV1, 3, 4 (85, 438, 636 kb, respectively and the pHV2 plasmid (6.4 kb.The completed genome sequence, presented here, provides an invaluable tool for further in vivo and in vitro studies of Hfx. volcanii.

  9. BioQ: tracing experimental origins in public genomic databases using a novel data provenance model.

    Science.gov (United States)

    Saccone, Scott F; Quan, Jiaxi; Jones, Peter L

    2012-04-15

    Public genomic databases, which are often used to guide genetic studies of human disease, are now being applied to genomic medicine through in silico integrative genomics. These databases, however, often lack tools for systematically determining the experimental origins of the data. We introduce a new data provenance model that we have implemented in a public web application, BioQ, for assessing the reliability of the data by systematically tracing its experimental origins to the original subjects and biologics. BioQ allows investigators to both visualize data provenance as well as explore individual elements of experimental process flow using precise tools for detailed data exploration and documentation. It includes a number of human genetic variation databases such as the HapMap and 1000 Genomes projects. BioQ is freely available to the public at http://bioq.saclab.net.

  10. Genomic prediction based on data from three layer lines using non-linear regression models

    NARCIS (Netherlands)

    Huang, H.; Windig, J.J.; Vereijken, A.; Calus, M.P.L.

    2014-01-01

    Background - Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. Methods - In an attempt to alleviate

  11. Gene finding with a hidden Markov model of genome structure and evolution

    DEFF Research Database (Denmark)

    Pedersen, Jakob Skou; Hein, Jotun

    2003-01-01

    -specific evolutionary models based on a phylogenetic tree. All parameters can be estimated by maximum likelihood, including the phylogenetic tree. It can handle any number of aligned genomes, using their phylogenetic tree to model the evolutionary correlations. The time complexity of all algorithms used for handling...

  12. A biological-based model that links genomic instability, bystander effects, and adaptive response

    International Nuclear Information System (INIS)

    Scott, B.R.

    2004-01-01

    This paper links genomic instability, bystander effects, and adaptive response in mammalian cell communities via a novel biological-based, dose-response model called NEOTRANS 3 . The model is an extension of the NEOTRANS 2 model that addressed stochastic effects (genomic instability, mutations, and neoplastic transformation) associated with brief exposure to low radiation doses. With both models, ionizing radiation produces DNA damage in cells that can be associated with varying degrees of genomic instability. Cells with persistent problematic instability (PPI) are mutants that arise via misrepair of DNA damage. Progeny of PPI cells also have PPI and can undergo spontaneous neoplastic transformation. Unlike NEOTRANS 2 , with NEOTRANS 3 newly induced mutant PPI cells and their neoplastically transformed progeny can be suppressed via our previously introduced protective apoptosis-mediated (PAM) process, which can be activated by low linear energy transfer (LET) radiation. However, with NEOTRANS 3 (which like NEOTRANS 2 involves cross-talk between nongenomically compromised [e.g., nontransformed, nonmutants] and genomically compromised [e.g., mutants, transformants, etc.] cells), it is assumed that PAM is only activated over a relatively narrow, dose-rate-dependent interval (D PAM ,D off ); where D PAM is a small stochastic activation threshold, and D off is the stochastic dose above which PAM does not occur. PAM cooperates with activated normal DNA repair and with activated normal apoptosis in guarding against genomic instability. Normal repair involves both error-free repair and misrepair components. Normal apoptosis and the error-free component of normal repair protect mammals by preventing the occurrence of mutant cells. PAM selectively removes mutant cells arising via the misrepair component of normal repair, selectively removes existing neoplastically transformed cells, and probably selectively removes other genomically compromised cells when it is activated

  13. Genome-based Modeling and Design of Metabolic Interactions in Microbial Communities.

    Science.gov (United States)

    Mahadevan, Radhakrishnan; Henson, Michael A

    2012-01-01

    Biotechnology research is traditionally focused on individual microbial strains that are perceived to have the necessary metabolic functions, or the capability to have these functions introduced, to achieve a particular task. For many important applications, the development of such omnipotent microbes is an extremely challenging if not impossible task. By contrast, nature employs a radically different strategy based on synergistic combinations of different microbial species that collectively achieve the desired task. These natural communities have evolved to exploit the native metabolic capabilities of each species and are highly adaptive to changes in their environments. However, microbial communities have proven difficult to study due to a lack of suitable experimental and computational tools. With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

  14. Genome-scale metabolic models as platforms for strain design and biological discovery.

    Science.gov (United States)

    Mienda, Bashir Sajo

    2017-07-01

    Genome-scale metabolic models (GEMs) have been developed and used in guiding systems' metabolic engineering strategies for strain design and development. This strategy has been used in fermentative production of bio-based industrial chemicals and fuels from alternative carbon sources. However, computer-aided hypotheses building using established algorithms and software platforms for biological discovery can be integrated into the pipeline for strain design strategy to create superior strains of microorganisms for targeted biosynthetic goals. Here, I described an integrated workflow strategy using GEMs for strain design and biological discovery. Specific case studies of strain design and biological discovery using Escherichia coli genome-scale model are presented and discussed. The integrated workflow presented herein, when applied carefully would help guide future design strategies for high-performance microbial strains that have existing and forthcoming genome-scale metabolic models.

  15. Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model

    NARCIS (Netherlands)

    Teusink, B.; Wiersma, A.; Molenaar, D.; Francke, C.; Vos, de W.M.; Siezen, R.J.; Smid, E.J.

    2006-01-01

    A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for

  16. The Educational Situation Quality Model: Recent Advances

    Science.gov (United States)

    Doménech-Betoret, Fernando

    2018-01-01

    The purpose of this work was to present an educational model developed in recent years entitled the “The Educational Situation Quality Model” (MOCSE, acronym in Spanish). MOCSE can be defined as an instructional model that simultaneously considers the teaching-learning process, where motivation plays a central role. It explains the functioning of an educational setting by organizing and relating the most important variables which, according to the literature, contribute to student learning. Besides being a conceptual framework, this model also provides a methodological procedure to guide research and to promote reflection in the classroom. It allows teachers to implement effective research-action programs to improve teacher–students satisfaction and learning outcomes in the classroom context. This work explains the model’s characteristics and functioning, recent advances, and how teachers can use it in an educational setting with a specific subject. This proposal integrates approaches from several relevant psycho-educational theories and introduces a new perspective into the existing literature that will allow researchers to make progress in studying educational setting functioning. The initial MOCSE configuration has been refined over time in accordance with the empirical results obtained from previous research, carried out within the MOCSE framework and with the subsequent reflections that derived from these results. Finally, the contribution of the model to improve learning outcomes and satisfaction, and its applicability in the classroom, are also discussed. PMID:29593623

  17. The Educational Situation Quality Model: Recent Advances

    Directory of Open Access Journals (Sweden)

    Fernando Doménech-Betoret

    2018-03-01

    Full Text Available The purpose of this work was to present an educational model developed in recent years entitled the “The Educational Situation Quality Model” (MOCSE, acronym in Spanish. MOCSE can be defined as an instructional model that simultaneously considers the teaching-learning process, where motivation plays a central role. It explains the functioning of an educational setting by organizing and relating the most important variables which, according to the literature, contribute to student learning. Besides being a conceptual framework, this model also provides a methodological procedure to guide research and to promote reflection in the classroom. It allows teachers to implement effective research-action programs to improve teacher–students satisfaction and learning outcomes in the classroom context. This work explains the model’s characteristics and functioning, recent advances, and how teachers can use it in an educational setting with a specific subject. This proposal integrates approaches from several relevant psycho-educational theories and introduces a new perspective into the existing literature that will allow researchers to make progress in studying educational setting functioning. The initial MOCSE configuration has been refined over time in accordance with the empirical results obtained from previous research, carried out within the MOCSE framework and with the subsequent reflections that derived from these results. Finally, the contribution of the model to improve learning outcomes and satisfaction, and its applicability in the classroom, are also discussed.

  18. Description of Hymenolepis microstoma (Nottingham strain: a classical tapeworm model for research in the genomic era

    Directory of Open Access Journals (Sweden)

    Olson Peter D

    2010-12-01

    Full Text Available Abstract Background Hymenolepis microstoma (Dujardin, 1845 Blanchard, 1891, the mouse bile duct tapeworm, is a rodent/beetle-hosted laboratory model that has been used in research and teaching since its domestication in the 1950s. Recent characterization of its genome has prompted us to describe the specific strain that underpins these data, anchoring its identity and bringing the 150+ year-old original description up-to-date. Results Morphometric and ultrastructural analyses were carried out on laboratory-reared specimens of the 'Nottingham' strain of Hymenolepis microstoma used for genome characterization. A contemporary description of the species is provided including detailed illustration of adult anatomy and elucidation of its taxonomy and the history of the specific laboratory isolate. Conclusions Our work acts to anchor the specific strain from which the H. microstoma genome has been characterized and provides an anatomical reference for researchers needing to employ a model tapeworm system that enables easy access to all stages of the life cycle. We review its classification, life history and development, and briefly discuss the genome and other model systems being employed at the beginning of a genomic era in cestodology.

  19. The Strategies of Modeling in Biology Education

    Science.gov (United States)

    Svoboda, Julia; Passmore, Cynthia

    2013-01-01

    Modeling, like inquiry more generally, is not a single method, but rather a complex suite of strategies. Philosophers of biology, citing the diverse aims, interests, and disciplinary cultures of biologists, argue that modeling is best understood in the context of its epistemic aims and cognitive payoffs. In the science education literature,…

  20. Exploring Causal Models of Educational Achievement.

    Science.gov (United States)

    Parkerson, Jo Ann; And Others

    1984-01-01

    This article evaluates five causal model of educational productivity applied to learning science in a sample of 882 fifth through eighth graders. Each model explores the relationship between achievement and a combination of eight constructs: home environment, peer group, media, ability, social environment, time on task, motivation, and…

  1. Enterprise Modelling for an Educational Information Infrastructure

    NARCIS (Netherlands)

    Widya, I.A.; Michiels, E.F.; Volman, C.J.A.M.; Pokraev, S.; de Diana, I.P.F.; Filipe, J.; Sharp, B.; Miranda, P.

    2001-01-01

    This paper reports the modelling exercise of an educational information infrastructure that aims to support the organisation of teaching and learning activities suitable for a wide range of didactic policies. The modelling trajectory focuses on capturing invariant structures of relations between

  2. Genomic prediction based on data from three layer lines using non-linear regression models.

    Science.gov (United States)

    Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L

    2014-11-06

    Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional

  3. Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

    Science.gov (United States)

    Sadhukhan, Priyanka P; Raghunathan, Anu

    2014-01-01

    Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

  4. Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

    Science.gov (United States)

    Spiliopoulou, Athina; Nagy, Reka; Bermingham, Mairead L.; Huffman, Jennifer E.; Hayward, Caroline; Vitart, Veronique; Rudan, Igor; Campbell, Harry; Wright, Alan F.; Wilson, James F.; Pong-Wong, Ricardo; Agakov, Felix; Navarro, Pau; Haley, Chris S.

    2015-01-01

    We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge. PMID:25918167

  5. Genomics approaches to unlock the high yield potential of cassava, a tropical model plant

    Directory of Open Access Journals (Sweden)

    Shengkui ZHANG,Ping'an MA,Haiyan WANG,Cheng LU,Xin CHEN,Zhiqiang XIA,Meiling ZOU,Xinchen ZHOU,Wenquan WANG

    2014-12-01

    Full Text Available Cassava, a tropical food, feed and biofuel crop, has great capacity for biomass accumulation and an extraordinary efficiency in water use and mineral nutrition, which makes it highly suitable as a model plant for tropical crops. However, the understanding of the metabolism and genomics of this important crop is limited. The recent breakthroughs in the genomics of cassava, including whole-genome sequencing and transcriptome analysis, as well as advances in the biology of photosynthesis, starch biosynthesis, adaptation to drought and high temperature, and resistance to virus and bacterial diseases, are reviewed here. Many of the new developments have come from comparative analyses between a wild ancestor and existing cultivars. Finally, the current challenges and future potential of cassava as a model plant are discussed.

  6. An Educational Model for Hands-On Hydrology Education

    Science.gov (United States)

    AghaKouchak, A.; Nakhjiri, N.; Habib, E. H.

    2014-12-01

    This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of hydrology.

  7. The Mouse Genome Database (MGD): facilitating mouse as a model for human biology and disease.

    Science.gov (United States)

    Eppig, Janan T; Blake, Judith A; Bult, Carol J; Kadin, James A; Richardson, Joel E

    2015-01-01

    The Mouse Genome Database (MGD, http://www.informatics.jax.org) serves the international biomedical research community as the central resource for integrated genomic, genetic and biological data on the laboratory mouse. To facilitate use of mouse as a model in translational studies, MGD maintains a core of high-quality curated data and integrates experimentally and computationally generated data sets. MGD maintains a unified catalog of genes and genome features, including functional RNAs, QTL and phenotypic loci. MGD curates and provides functional and phenotype annotations for mouse genes using the Gene Ontology and Mammalian Phenotype Ontology. MGD integrates phenotype data and associates mouse genotypes to human diseases, providing critical mouse-human relationships and access to repositories holding mouse models. MGD is the authoritative source of nomenclature for genes, genome features, alleles and strains following guidelines of the International Committee on Standardized Genetic Nomenclature for Mice. A new addition to MGD, the Human-Mouse: Disease Connection, allows users to explore gene-phenotype-disease relationships between human and mouse. MGD has also updated search paradigms for phenotypic allele attributes, incorporated incidental mutation data, added a module for display and exploration of genes and microRNA interactions and adopted the JBrowse genome browser. MGD resources are freely available to the scientific community. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. An integrated educational model for continuing nurse education.

    Science.gov (United States)

    Duff, Beverley; Gardner, Glenn; Osborne, Sonya

    2014-01-01

    This paper reports on the development and evaluation of an integrated clinical learning model to inform ongoing education for surgical nurses. The research aim was to evaluate the effectiveness of implementing a Respiratory Skills Update (ReSKU) education program, in the context of organisational utility, on improving surgical nurses' practice in the area of respiratory assessment. Continuous development and integration of technological innovations and research in the healthcare environment mandate the need for continuing education for nurses. Despite an increased worldwide emphasis on this, there is scant empirical evidence of program effectiveness. A quasi experimental pre test, post test non-equivalent control group design evaluated the impact of the ReSKU program on surgical nurses' clinical practice. The 2008 study was conducted in a 400 bed regional referral public hospital and was consistent with contemporary educational approaches using multi-modal, interactive teaching strategies. The study demonstrated statistically significant differences between groups regarding reported use of respiratory skills, three months after ReSKU program attendance. Between group data analysis indicated that the intervention group's reported beliefs and attitudes pertaining to subscale descriptors showed statistically significant differences in three of the six subscales. The construct of critical thinking in the clinical context, combined with clinical reasoning and purposeful reflection, was a powerful educational strategy to enhance competency and capability in clinicians. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

  9. Organoids as Models for Neoplastic Transformation | Office of Cancer Genomics

    Science.gov (United States)

    Cancer models strive to recapitulate the incredible diversity inherent in human tumors. A key challenge in accurate tumor modeling lies in capturing the panoply of homo- and heterotypic cellular interactions within the context of a three-dimensional tissue microenvironment. To address this challenge, researchers have developed organotypic cancer models (organoids) that combine the 3D architecture of in vivo tissues with the experimental facility of 2D cell lines.

  10. Optimality models in the age of experimental evolution and genomics

    OpenAIRE

    Bull, J. J.; Wang, I.-N.

    2010-01-01

    Optimality models have been used to predict evolution of many properties of organisms. They typically neglect genetic details, whether by necessity or design. This omission is a common source of criticism, and although this limitation of optimality is widely acknowledged, it has mostly been defended rather than evaluated for its impact. Experimental adaptation of model organisms provides a new arena for testing optimality models and for simultaneously integrating genetics. First, an experimen...

  11. Use of genomic models to study genetic control of environmental variance

    DEFF Research Database (Denmark)

    Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

    2011-01-01

    . The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable...... of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted...... to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm...

  12. Novel mouse model recapitulates genome and transcriptome alterations in human colorectal carcinomas.

    Science.gov (United States)

    McNeil, Nicole E; Padilla-Nash, Hesed M; Buishand, Floryne O; Hue, Yue; Ried, Thomas

    2017-03-01

    Human colorectal carcinomas are defined by a nonrandom distribution of genomic imbalances that are characteristic for this disease. Often, these imbalances affect entire chromosomes. Understanding the role of these aneuploidies for carcinogenesis is of utmost importance. Currently, established transgenic mice do not recapitulate the pathognonomic genome aberration profile of human colorectal carcinomas. We have developed a novel model based on the spontaneous transformation of murine colon epithelial cells. During this process, cells progress through stages of pre-immortalization, immortalization and, finally, transformation, and result in tumors when injected into immunocompromised mice. We analyzed our model for genome and transcriptome alterations using ArrayCGH, spectral karyotyping (SKY), and array based gene expression profiling. ArrayCGH revealed a recurrent pattern of genomic imbalances. These results were confirmed by SKY. Comparing these imbalances with orthologous maps of human chromosomes revealed a remarkable overlap. We observed focal deletions of the tumor suppressor genes Trp53 and Cdkn2a/p16. High-level focal genomic amplification included the locus harboring the oncogene Mdm2, which was confirmed by FISH in the form of double minute chromosomes. Array-based global gene expression revealed distinct differences between the sequential steps of spontaneous transformation. Gene expression changes showed significant similarities with human colorectal carcinomas. Pathways most prominently affected included genes involved in chromosomal instability and in epithelial to mesenchymal transition. Our novel mouse model therefore recapitulates the most prominent genome and transcriptome alterations in human colorectal cancer, and might serve as a valuable tool for understanding the dynamic process of tumorigenesis, and for preclinical drug testing. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  13. Modeling and interoperability of heterogeneous genomic big data for integrative processing and querying.

    Science.gov (United States)

    Masseroli, Marco; Kaitoua, Abdulrahman; Pinoli, Pietro; Ceri, Stefano

    2016-12-01

    While a huge amount of (epi)genomic data of multiple types is becoming available by using Next Generation Sequencing (NGS) technologies, the most important emerging problem is the so-called tertiary analysis, concerned with sense making, e.g., discovering how different (epi)genomic regions and their products interact and cooperate with each other. We propose a paradigm shift in tertiary analysis, based on the use of the Genomic Data Model (GDM), a simple data model which links genomic feature data to their associated experimental, biological and clinical metadata. GDM encompasses all the data formats which have been produced for feature extraction from (epi)genomic datasets. We specifically describe the mapping to GDM of SAM (Sequence Alignment/Map), VCF (Variant Call Format), NARROWPEAK (for called peaks produced by NGS ChIP-seq or DNase-seq methods), and BED (Browser Extensible Data) formats, but GDM supports as well all the formats describing experimental datasets (e.g., including copy number variations, DNA somatic mutations, or gene expressions) and annotations (e.g., regarding transcription start sites, genes, enhancers or CpG islands). We downloaded and integrated samples of all the above-mentioned data types and formats from multiple sources. The GDM is able to homogeneously describe semantically heterogeneous data and makes the ground for providing data interoperability, e.g., achieved through the GenoMetric Query Language (GMQL), a high-level, declarative query language for genomic big data. The combined use of the data model and the query language allows comprehensive processing of multiple heterogeneous data, and supports the development of domain-specific data-driven computations and bio-molecular knowledge discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Draft Genome Sequence of the Model Naphthalene-Utilizing Organism Pseudomonas putida OUS82

    DEFF Research Database (Denmark)

    Tay, Martin; Roizman, Dan; Cohen, Yehuda

    2014-01-01

    Pseudomonas putida OUS82 was isolated from petrol- and oil-contaminated soil in 1992, and ever since, it has been used as a model organism to study the microbial assimilation of naphthalene and phenanthrene. Here, we report the 6.7-Mb draft genome sequence of P. putida OUS82 and analyze its...

  15. Genome sequencing and comparison of two nonhuman primate animal models, the cynomolgus and Chinese rhesus macaques

    DEFF Research Database (Denmark)

    Yan, Guangmei; Zhang, Guojie; Fang, Xiaodong

    2011-01-01

    The nonhuman primates most commonly used in medical research are from the genus Macaca. To better understand the genetic differences between these animal models, we present high-quality draft genome sequences from two macaque species, the cynomolgus/crab-eating macaque and the Chinese rhesus...

  16. Translational genomics from model species Medicago truncatula to crop legume Trifolium pratense

    NARCIS (Netherlands)

    Lang Chunting, Chunting

    2012-01-01

    The legume Trifolium pratense (red clover) is an important fodder crop and produces important secondary metabolites. This makes red clover an interesting species. In this thesis, the red clover genome is compared to the legume model species Medicago truncatula, of which the

  17. Software engineering the mixed model for genome-wide association studies on large samples

    Science.gov (United States)

    Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample siz...

  18. Optimality models in the age of experimental evolution and genomics.

    Science.gov (United States)

    Bull, J J; Wang, I-N

    2010-09-01

    Optimality models have been used to predict evolution of many properties of organisms. They typically neglect genetic details, whether by necessity or design. This omission is a common source of criticism, and although this limitation of optimality is widely acknowledged, it has mostly been defended rather than evaluated for its impact. Experimental adaptation of model organisms provides a new arena for testing optimality models and for simultaneously integrating genetics. First, an experimental context with a well-researched organism allows dissection of the evolutionary process to identify causes of model failure--whether the model is wrong about genetics or selection. Second, optimality models provide a meaningful context for the process and mechanics of evolution, and thus may be used to elicit realistic genetic bases of adaptation--an especially useful augmentation to well-researched genetic systems. A few studies of microbes have begun to pioneer this new direction. Incompatibility between the assumed and actual genetics has been demonstrated to be the cause of model failure in some cases. More interestingly, evolution at the phenotypic level has sometimes matched prediction even though the adaptive mutations defy mechanisms established by decades of classic genetic studies. Integration of experimental evolutionary tests with genetics heralds a new wave for optimality models and their extensions that does not merely emphasize the forces driving evolution.

  19. Systematic review of knowledge, confidence and education in nutritional genomics for students and professionals in nutrition and dietetics.

    Science.gov (United States)

    Wright, O R L

    2014-06-01

    This review examines knowledge and confidence of nutrition and dietetics professionals in nutritional genomics and evaluates the teaching strategies in this field within nutrition and dietetics university programmes and professional development courses internationally. A systematic search of 10 literature databases was conducted from January 2000 to December 2012 to identify original research. Any studies of either nutrition and/or dietetics students or dietitians/nutritionists investigating current levels of knowledge or confidence in nutritional genomics, or strategies to improve learning and/or confidence in this area, were eligible. Eighteen articles (15 separate studies) met the inclusion criteria. Three articles were assessed as negative, eight as neutral and seven as positive according to the American Dietetics Association Quality Criteria Checklist. The overall ranking of evidence was low. Dietitians have low involvement, knowledge and confidence in nutritional genomics, and evidence for educational strategies is limited and methodologically weak. There is a need to develop training pathways and material to up-skill nutrition and/or dietetics students and nutrition and/or dietetics professionals in nutritional genomics through multidisciplinary collaboration with content area experts. There is a paucity of high quality evidence on optimum teaching strategies; however, methods promoting repetitive exposure to nutritional genomics material, problem-solving, collaborative and case-based learning are most promising for university and professional development programmes. © 2013 The British Dietetic Association Ltd.

  20. Approaches and models of intercultural education

    Directory of Open Access Journals (Sweden)

    Iván Manuel Sánchez Fontalvo

    2013-10-01

    Full Text Available Needed to be aware of the need to build an intercultural society, awareness must be assumed in all social spheres, where stands the role play education. A role of transcendental, since it must promote educational spaces to form people with virtues and powers that allow them to live together / as in multicultural contexts and social diversities (sometimes uneven in an increasingly globalized and interconnected world, and foster the development of feelings of civic belonging shared before the neighborhood, city, region and country, allowing them concern and critical judgement to marginalization, poverty, misery and inequitable distribution of wealth, causes of structural violence, but at the same time, wanting to work for the welfare and transformation of these scenarios. Since these budgets, it is important to know the approaches and models of intercultural education that have been developed so far, analysing their impact on the contexts educational where apply.   

  1. High intraspecific genome diversity in the model arbuscular mycorrhizal symbiont Rhizophagus irregularis.

    Science.gov (United States)

    Chen, Eric C H; Morin, Emmanuelle; Beaudet, Denis; Noel, Jessica; Yildirir, Gokalp; Ndikumana, Steve; Charron, Philippe; St-Onge, Camille; Giorgi, John; Krüger, Manuela; Marton, Timea; Ropars, Jeanne; Grigoriev, Igor V; Hainaut, Matthieu; Henrissat, Bernard; Roux, Christophe; Martin, Francis; Corradi, Nicolas

    2018-01-22

    Arbuscular mycorrhizal fungi (AMF) are known to improve plant fitness through the establishment of mycorrhizal symbioses. Genetic and phenotypic variations among closely related AMF isolates can significantly affect plant growth, but the genomic changes underlying this variability are unclear. To address this issue, we improved the genome assembly and gene annotation of the model strain Rhizophagus irregularis DAOM197198, and compared its gene content with five isolates of R. irregularis sampled in the same field. All isolates harbor striking genome variations, with large numbers of isolate-specific genes, gene family expansions, and evidence of interisolate genetic exchange. The observed variability affects all gene ontology terms and PFAM protein domains, as well as putative mycorrhiza-induced small secreted effector-like proteins and other symbiosis differentially expressed genes. High variability is also found in active transposable elements. Overall, these findings indicate a substantial divergence in the functioning capacity of isolates harvested from the same field, and thus their genetic potential for adaptation to biotic and abiotic changes. Our data also provide a first glimpse into the genome diversity that resides within natural populations of these symbionts, and open avenues for future analyses of plant-AMF interactions that link AMF genome variation with plant phenotype and fitness. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

  2. Genome-wide single nucleotide polymorphisms (SNPs) for a model invasive ascidian Botryllus schlosseri.

    Science.gov (United States)

    Gao, Yangchun; Li, Shiguo; Zhan, Aibin

    2018-04-01

    Invasive species cause huge damages to ecology, environment and economy globally. The comprehensive understanding of invasion mechanisms, particularly genetic bases of micro-evolutionary processes responsible for invasion success, is essential for reducing potential damages caused by invasive species. The golden star tunicate, Botryllus schlosseri, has become a model species in invasion biology, mainly owing to its high invasiveness nature and small well-sequenced genome. However, the genome-wide genetic markers have not been well developed in this highly invasive species, thus limiting the comprehensive understanding of genetic mechanisms of invasion success. Using restriction site-associated DNA (RAD) tag sequencing, here we developed a high-quality resource of 14,119 out of 158,821 SNPs for B. schlosseri. These SNPs were relatively evenly distributed at each chromosome. SNP annotations showed that the majority of SNPs (63.20%) were located at intergenic regions, and 21.51% and 14.58% were located at introns and exons, respectively. In addition, the potential use of the developed SNPs for population genomics studies was primarily assessed, such as the estimate of observed heterozygosity (H O ), expected heterozygosity (H E ), nucleotide diversity (π), Wright's inbreeding coefficient (F IS ) and effective population size (Ne). Our developed SNP resource would provide future studies the genome-wide genetic markers for genetic and genomic investigations, such as genetic bases of micro-evolutionary processes responsible for invasion success.

  3. Genomic prediction in a nuclear population of layers using single-step models.

    Science.gov (United States)

    Yan, Yiyuan; Wu, Guiqin; Liu, Aiqiao; Sun, Congjiao; Han, Wenpeng; Li, Guangqi; Yang, Ning

    2018-02-01

    Single-step genomic prediction method has been proposed to improve the accuracy of genomic prediction by incorporating information of both genotyped and ungenotyped animals. The objective of this study is to compare the prediction performance of single-step model with a 2-step models and the pedigree-based models in a nuclear population of layers. A total of 1,344 chickens across 4 generations were genotyped by a 600 K SNP chip. Four traits were analyzed, i.e., body weight at 28 wk (BW28), egg weight at 28 wk (EW28), laying rate at 38 wk (LR38), and Haugh unit at 36 wk (HU36). In predicting offsprings, individuals from generation 1 to 3 were used as training data and females from generation 4 were used as validation set. The accuracies of predicted breeding values by pedigree BLUP (PBLUP), genomic BLUP (GBLUP), SSGBLUP and single-step blending (SSBlending) were compared for both genotyped and ungenotyped individuals. For genotyped females, GBLUP performed no better than PBLUP because of the small size of training data, while the 2 single-step models predicted more accurately than the PBLUP model. The average predictive ability of SSGBLUP and SSBlending were 16.0% and 10.8% higher than the PBLUP model across traits, respectively. Furthermore, the predictive abilities for ungenotyped individuals were also enhanced. The average improvements of prediction abilities were 5.9% and 1.5% for SSGBLUP and SSBlending model, respectively. It was concluded that single-step models, especially the SSGBLUP model, can yield more accurate prediction of genetic merits and are preferable for practical implementation of genomic selection in layers. © 2017 Poultry Science Association Inc.

  4. Changes in chemistry and biochemistry education: creative responses to medical college admissions test revisions in the age of the genome.

    Science.gov (United States)

    Brenner, Charles

    2013-01-01

    Approximately two million students matriculate into American colleges and universities per year. Almost 20% of these students begin taking a series of courses specified by advisers of health preprofessionals. The single most important influence on health profession advisers and on course selection for this huge population of learners is the Medical College Admissions Test (MCAT), which was last revised in 1991, 10 years before publication of the first draft human genome sequence. In preparation for the 2015 MCAT, there is a broad discussion among stakeholders of how best to revise undergraduate and medical education in the molecular sciences to prepare researchers and doctors to acquire, analyze and use individual genomic and metabolomic data in the coming decades. Getting these changes right is among the most important educational problems of our era. Copyright © 2012 International Union of Biochemistry and Molecular Biology, Inc.

  5. Genome-scale modeling of yeast: chronology, applications and critical perspectives.

    Science.gov (United States)

    Lopes, Helder; Rocha, Isabel

    2017-08-01

    Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed. © FEMS 2017.

  6. Metingear: a development environment for annotating genome-scale metabolic models.

    Science.gov (United States)

    May, John W; James, A Gordon; Steinbeck, Christoph

    2013-09-01

    Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

  7. Macronuclear genome sequence of the ciliate Tetrahymena thermophila, a model eukaryote.

    Directory of Open Access Journals (Sweden)

    Jonathan A Eisen

    2006-09-01

    Full Text Available The ciliate Tetrahymena thermophila is a model organism for molecular and cellular biology. Like other ciliates, this species has separate germline and soma functions that are embodied by distinct nuclei within a single cell. The germline-like micronucleus (MIC has its genome held in reserve for sexual reproduction. The soma-like macronucleus (MAC, which possesses a genome processed from that of the MIC, is the center of gene expression and does not directly contribute DNA to sexual progeny. We report here the shotgun sequencing, assembly, and analysis of the MAC genome of T. thermophila, which is approximately 104 Mb in length and composed of approximately 225 chromosomes. Overall, the gene set is robust, with more than 27,000 predicted protein-coding genes, 15,000 of which have strong matches to genes in other organisms. The functional diversity encoded by these genes is substantial and reflects the complexity of processes required for a free-living, predatory, single-celled organism. This is highlighted by the abundance of lineage-specific duplications of genes with predicted roles in sensing and responding to environmental conditions (e.g., kinases, using diverse resources (e.g., proteases and transporters, and generating structural complexity (e.g., kinesins and dyneins. In contrast to the other lineages of alveolates (apicomplexans and dinoflagellates, no compelling evidence could be found for plastid-derived genes in the genome. UGA, the only T. thermophila stop codon, is used in some genes to encode selenocysteine, thus making this organism the first known with the potential to translate all 64 codons in nuclear genes into amino acids. We present genomic evidence supporting the hypothesis that the excision of DNA from the MIC to generate the MAC specifically targets foreign DNA as a form of genome self-defense. The combination of the genome sequence, the functional diversity encoded therein, and the presence of some pathways missing from

  8. Genome Scale Modeling in Systems Biology: Algorithms and Resources

    Science.gov (United States)

    Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

    2014-01-01

    In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

  9. Technology and Online Education: Models for Change

    Science.gov (United States)

    Cook, Catherine W.; Sonnenberg, Christian

    2014-01-01

    This paper contends that technology changes advance online education. A number of mobile computing and transformative technologies will be examined and incorporated into a descriptive study. The object of the study will be to design innovative mobile awareness models seeking to understand technology changes for mobile devices and how they can be…

  10. Teaching Mathematical Modeling in Mathematics Education

    Science.gov (United States)

    Saxena, Ritu; Shrivastava, Keerty; Bhardwaj, Ramakant

    2016-01-01

    Mathematics is not only a subject but it is also a language consisting of many different symbols and relations. Taught as a compulsory subject up the 10th class, students are then able to choose whether or not to study mathematics as a main subject. The present paper discusses mathematical modeling in mathematics education. The article provides…

  11. Behavioral and statistical models of educational inequality

    DEFF Research Database (Denmark)

    Holm, Anders; Breen, Richard

    2016-01-01

    This paper addresses the question of how students and their families make educational decisions. We describe three types of behavioral model that might underlie decision-making and we show that they have consequences for what decisions are made. Our study thus has policy implications if we wish...

  12. Humanistic Speech Education to Create Leadership Models.

    Science.gov (United States)

    Oka, Beverley Jeanne

    A theoretical framework based primarily on the humanistic psychology of Abraham Maslow is used in developing a humanistic approach to speech education. The holistic view of human learning and behavior, inherent in this approach, is seen to be compatible with a model of effective leadership. Specific applications of this approach to speech…

  13. A Technological Teacher Education Program Planning Model.

    Science.gov (United States)

    Hansen, Ronald E.

    1993-01-01

    A model for technology teacher education curriculum has three facets: (1) purpose (experiential learning, personal development, technological enlightenment, economic well-being); (2) content (professional knowledge, curriculum development competence, pedagogical knowledge and skill, technological foundations); and (3) process (planned reflection,…

  14. Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151)

    Science.gov (United States)

    Davies, G; Marioni, R E; Liewald, D C; Hill, W D; Hagenaars, S P; Harris, S E; Ritchie, S J; Luciano, M; Fawns-Ritchie, C; Lyall, D; Cullen, B; Cox, S R; Hayward, C; Porteous, D J; Evans, J; McIntosh, A M; Gallacher, J; Craddock, N; Pell, J P; Smith, D J; Gale, C R; Deary, I J

    2016-01-01

    People's differences in cognitive functions are partly heritable and are associated with important life outcomes. Previous genome-wide association (GWA) studies of cognitive functions have found evidence for polygenic effects yet, to date, there are few replicated genetic associations. Here we use data from the UK Biobank sample to investigate the genetic contributions to variation in tests of three cognitive functions and in educational attainment. GWA analyses were performed for verbal–numerical reasoning (N=36 035), memory (N=112 067), reaction time (N=111 483) and for the attainment of a college or a university degree (N=111 114). We report genome-wide significant single-nucleotide polymorphism (SNP)-based associations in 20 genomic regions, and significant gene-based findings in 46 regions. These include findings in the ATXN2, CYP2DG, APBA1 and CADM2 genes. We report replication of these hits in published GWA studies of cognitive function, educational attainment and childhood intelligence. There is also replication, in UK Biobank, of SNP hits reported previously in GWA studies of educational attainment and cognitive function. GCTA-GREML analyses, using common SNPs (minor allele frequency>0.01), indicated significant SNP-based heritabilities of 31% (s.e.m.=1.8%) for verbal–numerical reasoning, 5% (s.e.m.=0.6%) for memory, 11% (s.e.m.=0.6%) for reaction time and 21% (s.e.m.=0.6%) for educational attainment. Polygenic score analyses indicate that up to 5% of the variance in cognitive test scores can be predicted in an independent cohort. The genomic regions identified include several novel loci, some of which have been associated with intracranial volume, neurodegeneration, Alzheimer's disease and schizophrenia. PMID:27046643

  15. Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

    Science.gov (United States)

    Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

    2018-01-01

    In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

  16. In silico analysis of human metabolism: Reconstruction, contextualization and application of genome-scale models

    DEFF Research Database (Denmark)

    Geng, Jun; Nielsen, Jens

    2017-01-01

    The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising fram...... that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions....

  17. A probabilistic model to predict clinical phenotypic traits from genome sequencing.

    Science.gov (United States)

    Chen, Yun-Ching; Douville, Christopher; Wang, Cheng; Niknafs, Noushin; Yeo, Grace; Beleva-Guthrie, Violeta; Carter, Hannah; Stenson, Peter D; Cooper, David N; Li, Biao; Mooney, Sean; Karchin, Rachel

    2014-09-01

    Genetic screening is becoming possible on an unprecedented scale. However, its utility remains controversial. Although most variant genotypes cannot be easily interpreted, many individuals nevertheless attempt to interpret their genetic information. Initiatives such as the Personal Genome Project (PGP) and Illumina's Understand Your Genome are sequencing thousands of adults, collecting phenotypic information and developing computational pipelines to identify the most important variant genotypes harbored by each individual. These pipelines consider database and allele frequency annotations and bioinformatics classifications. We propose that the next step will be to integrate these different sources of information to estimate the probability that a given individual has specific phenotypes of clinical interest. To this end, we have designed a Bayesian probabilistic model to predict the probability of dichotomous phenotypes. When applied to a cohort from PGP, predictions of Gilbert syndrome, Graves' disease, non-Hodgkin lymphoma, and various blood groups were accurate, as individuals manifesting the phenotype in question exhibited the highest, or among the highest, predicted probabilities. Thirty-eight PGP phenotypes (26%) were predicted with area-under-the-ROC curve (AUC)>0.7, and 23 (15.8%) of these were statistically significant, based on permutation tests. Moreover, in a Critical Assessment of Genome Interpretation (CAGI) blinded prediction experiment, the models were used to match 77 PGP genomes to phenotypic profiles, generating the most accurate prediction of 16 submissions, according to an independent assessor. Although the models are currently insufficiently accurate for diagnostic utility, we expect their performance to improve with growth of publicly available genomics data and model refinement by domain experts.

  18. A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

    Science.gov (United States)

    Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

    2018-04-19

    Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model

  19. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    Energy Technology Data Exchange (ETDEWEB)

    Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  20. Genetic education and the challenge of genomic medicine: development of core competences to support preparation of health professionals in Europe

    DEFF Research Database (Denmark)

    Skirton, Heather; Lewis, Celine; Kent, Alastair

    2010-01-01

    in professional education and regulation between European countries, setting curricula may not be practical. Core competences are used as a basis for health professional education in many fields and settings. An Expert Group working under the auspices of the EuroGentest project and European Society of Human...... Genetics Education Committee agreed that a pragmatic solution to the need to establish common standards for education and practice in genetic health care was to agree to a set of core competences that could apply across Europe. These were agreed through an exhaustive process of consultation with relevant......The use of genetics and genomics within a wide range of health-care settings requires health professionals to develop expertise to practise appropriately. There is a need for a common minimum standard of competence in genetics for health professionals in Europe but because of differences...

  1. Transposons As Tools for Functional Genomics in Vertebrate Models.

    Science.gov (United States)

    Kawakami, Koichi; Largaespada, David A; Ivics, Zoltán

    2017-11-01

    Genetic tools and mutagenesis strategies based on transposable elements are currently under development with a vision to link primary DNA sequence information to gene functions in vertebrate models. By virtue of their inherent capacity to insert into DNA, transposons can be developed into powerful tools for chromosomal manipulations. Transposon-based forward mutagenesis screens have numerous advantages including high throughput, easy identification of mutated alleles, and providing insight into genetic networks and pathways based on phenotypes. For example, the Sleeping Beauty transposon has become highly instrumental to induce tumors in experimental animals in a tissue-specific manner with the aim of uncovering the genetic basis of diverse cancers. Here, we describe a battery of mutagenic cassettes that can be applied in conjunction with transposon vectors to mutagenize genes, and highlight versatile experimental strategies for the generation of engineered chromosomes for loss-of-function as well as gain-of-function mutagenesis for functional gene annotation in vertebrate models, including zebrafish, mice, and rats. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis

    Directory of Open Access Journals (Sweden)

    Balagurunathan Balaji

    2012-02-01

    Full Text Available Abstract Background Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. Results We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. Conclusion The genome

  3. Genome-wide investigation reveals high evolutionary rates in annual model plants.

    Science.gov (United States)

    Yue, Jia-Xing; Li, Jinpeng; Wang, Dan; Araki, Hitoshi; Tian, Dacheng; Yang, Sihai

    2010-11-09

    Rates of molecular evolution vary widely among species. While significant deviations from molecular clock have been found in many taxa, effects of life histories on molecular evolution are not fully understood. In plants, annual/perennial life history traits have long been suspected to influence the evolutionary rates at the molecular level. To date, however, the number of genes investigated on this subject is limited and the conclusions are mixed. To evaluate the possible heterogeneity in evolutionary rates between annual and perennial plants at the genomic level, we investigated 85 nuclear housekeeping genes, 10 non-housekeeping families, and 34 chloroplast genes using the genomic data from model plants including Arabidopsis thaliana and Medicago truncatula for annuals and grape (Vitis vinifera) and popular (Populus trichocarpa) for perennials. According to the cross-comparisons among the four species, 74-82% of the nuclear genes and 71-97% of the chloroplast genes suggested higher rates of molecular evolution in the two annuals than those in the two perennials. The significant heterogeneity in evolutionary rate between annuals and perennials was consistently found both in nonsynonymous sites and synonymous sites. While a linear correlation of evolutionary rates in orthologous genes between species was observed in nonsynonymous sites, the correlation was weak or invisible in synonymous sites. This tendency was clearer in nuclear genes than in chloroplast genes, in which the overall evolutionary rate was small. The slope of the regression line was consistently lower than unity, further confirming the higher evolutionary rate in annuals at the genomic level. The higher evolutionary rate in annuals than in perennials appears to be a universal phenomenon both in nuclear and chloroplast genomes in the four dicot model plants we investigated. Therefore, such heterogeneity in evolutionary rate should result from factors that have genome-wide influence, most likely those

  4. Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.

    Science.gov (United States)

    Onogi, Akio; Watanabe, Maya; Mochizuki, Toshihiro; Hayashi, Takeshi; Nakagawa, Hiroshi; Hasegawa, Toshihiro; Iwata, Hiroyoshi

    2016-04-01

    It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in

  5. Science communication in transition: genomics hype, public engagement, education and commercialization pressures.

    Science.gov (United States)

    Bubela, T

    2006-11-01

    This essay reports on the final session of a 2-day workshop entitled 'Genetic Diversity and Science Communication', hosted by the CIHR Institute of Genetics in Toronto, April 2006. The first speaker, Timothy Caulfield, introduced the intersecting communities that promulgate a 'cycle of hype' of the timelines and expected outcomes of the Human Genome Project (HGP): scientists, the media and the public. Other actors also contribute to the overall hype, the social science and humanities communities, industry and politicians. There currently appears to be an abatement of the overblown rhetoric of the HGP. As pointed out by the second speaker, Sharon Kardia, there is broad recognition that most phenotypic traits, including disease susceptibility are multi-factorial. That said, George Davey-Smith reminded us that some direct genotype-phenotype associations may be useful for public health issues. The Mendelian randomization approach hopes to revitalize the discipline of epidemiology by strengthening causal influences about environmentally modifiable risk factors. A more realistic informational environment paves the way for greater public engagement in science policy. Two such initiatives were presented by Kardia and Jason Robert, and Peter Finegold emphasized that science education and professional development for science teachers are important components of later public engagement in science issues. However, pressures on public research institutions to commercialize and seek industry funding may have negative impacts in both encouraging scientists to inappropriately hype research and on diminishing public trust in the scientific enterprise. The latter may have a significant effect on public engagement processes, such as those proposed by Robert and Kardia.

  6. Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model.

    Science.gov (United States)

    Lopez-Cruz, Marco; Crossa, Jose; Bonnett, David; Dreisigacker, Susanne; Poland, Jesse; Jannink, Jean-Luc; Singh, Ravi P; Autrique, Enrique; de los Campos, Gustavo

    2015-02-06

    Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates of selection. Originally, these models were developed without considering genotype × environment interaction(G×E). Several authors have proposed extensions of the single-environment GS model that accommodate G×E using either covariance functions or environmental covariates. In this study, we model G×E using a marker × environment interaction (M×E) GS model; the approach is conceptually simple and can be implemented with existing GS software. We discuss how the model can be implemented by using an explicit regression of phenotypes on markers or using co-variance structures (a genomic best linear unbiased prediction-type model). We used the M×E model to analyze three CIMMYT wheat data sets (W1, W2, and W3), where more than 1000 lines were genotyped using genotyping-by-sequencing and evaluated at CIMMYT's research station in Ciudad Obregon, Mexico, under simulated environmental conditions that covered different irrigation levels, sowing dates and planting systems. We compared the M×E model with a stratified (i.e., within-environment) analysis and with a standard (across-environment) GS model that assumes that effects are constant across environments (i.e., ignoring G×E). The prediction accuracy of the M×E model was substantially greater of that of an across-environment analysis that ignores G×E. Depending on the prediction problem, the M×E model had either similar or greater levels of prediction accuracy than the stratified analyses. The M×E model decomposes marker effects and genomic values into components that are stable across environments (main effects) and others that are environment-specific (interactions). Therefore, in principle, the interaction model could shed light over which variants have effects that are stable across environments and which ones are responsible for G×E. The data set and the scripts required to reproduce the analysis are

  7. A hidden Markov model approach for determining expression from genomic tiling micro arrays

    Directory of Open Access Journals (Sweden)

    Krogh Anders

    2006-05-01

    Full Text Available Abstract Background Genomic tiling micro arrays have great potential for identifying previously undiscovered coding as well as non-coding transcription. To-date, however, analyses of these data have been performed in an ad hoc fashion. Results We present a probabilistic procedure, ExpressHMM, that adaptively models tiling data prior to predicting expression on genomic sequence. A hidden Markov model (HMM is used to model the distributions of tiling array probe scores in expressed and non-expressed regions. The HMM is trained on sets of probes mapped to regions of annotated expression and non-expression. Subsequently, prediction of transcribed fragments is made on tiled genomic sequence. The prediction is accompanied by an expression probability curve for visual inspection of the supporting evidence. We test ExpressHMM on data from the Cheng et al. (2005 tiling array experiments on ten Human chromosomes 1. Results can be downloaded and viewed from our web site 2. Conclusion The value of adaptive modelling of fluorescence scores prior to categorisation into expressed and non-expressed probes is demonstrated. Our results indicate that our adaptive approach is superior to the previous analysis in terms of nucleotide sensitivity and transfrag specificity.

  8. Competency Modeling in Extension Education: Integrating an Academic Extension Education Model with an Extension Human Resource Management Model

    Science.gov (United States)

    Scheer, Scott D.; Cochran, Graham R.; Harder, Amy; Place, Nick T.

    2011-01-01

    The purpose of this study was to compare and contrast an academic extension education model with an Extension human resource management model. The academic model of 19 competencies was similar across the 22 competencies of the Extension human resource management model. There were seven unique competencies for the human resource management model.…

  9. Genetic and genomic analysis of RNases in model cyanobacteria.

    Science.gov (United States)

    Cameron, Jeffrey C; Gordon, Gina C; Pfleger, Brian F

    2015-10-01

    Cyanobacteria are diverse photosynthetic microbes with the ability to convert CO2 into useful products. However, metabolic engineering of cyanobacteria remains challenging because of the limited resources for modifying the expression of endogenous and exogenous biochemical pathways. Fine-tuned control of protein production will be critical to optimize the biological conversion of CO2 into desirable molecules. Messenger RNAs (mRNAs) are labile intermediates that play critical roles in determining the translation rate and steady-state protein concentrations in the cell. The majority of studies on mRNA turnover have focused on the model heterotrophic bacteria Escherichia coli and Bacillus subtilis. These studies have elucidated many RNA modifying and processing enzymes and have highlighted the differences between these Gram-negative and Gram-positive bacteria, respectively. In contrast, much less is known about mRNA turnover in cyanobacteria. We generated a compendium of the major ribonucleases (RNases) and provide an in-depth analysis of RNase III-like enzymes in commonly studied and diverse cyanobacteria. Furthermore, using targeted gene deletion, we genetically dissected the RNases in Synechococcus sp. PCC 7002, one of the fastest growing and industrially attractive cyanobacterial strains. We found that all three cyanobacterial homologs of RNase III and a member of the RNase II/R family are not essential under standard laboratory conditions, while homologs of RNase E/G, RNase J1/J2, PNPase, and a different member of the RNase II/R family appear to be essential for growth. This work will enhance our understanding of native control of gene expression and will facilitate the development of an RNA-based toolkit for metabolic engineering in cyanobacteria.

  10. Localized Retroprocessing as a Model of Intron Loss in the Plant Mitochondrial Genome.

    Science.gov (United States)

    Cuenca, Argelia; Ross, T Gregory; Graham, Sean W; Barrett, Craig F; Davis, Jerrold I; Seberg, Ole; Petersen, Gitte

    2016-08-03

    Loss of introns in plant mitochondrial genes is commonly explained by retroprocessing. Under this model, an mRNA is reverse transcribed and integrated back into the genome, simultaneously affecting the contents of introns and edited sites. To evaluate the extent to which retroprocessing explains intron loss, we analyzed patterns of intron content and predicted RNA editing for whole mitochondrial genomes of 30 species in the monocot order Alismatales. In this group, we found an unusually high degree of variation in the intron content, even expanding the hitherto known variation among angiosperms. Some species have lost some two-third of the cis-spliced introns. We found a strong correlation between intron content and editing frequency, and detected 27 events in which intron loss is consistent with the presence of nucleotides in an edited state, supporting retroprocessing. However, we also detected seven cases of intron loss not readily being explained by retroprocession. Our analyses are also not consistent with the entire length of a fully processed cDNA copy being integrated into the genome, but instead indicate that retroprocessing usually occurs for only part of the gene. In some cases, several rounds of retroprocessing may explain intron loss in genes completely devoid of introns. A number of taxa retroprocessing seem to be very common and a possibly ongoing process. It affects the entire mitochondrial genome. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  11. Building a complete image of genome regulation in the model organism Escherichia coli.

    Science.gov (United States)

    Ishihama, Akira

    2018-01-15

    The model organism, Escherichia coli, contains a total of more than 4,500 genes, but the total number of RNA polymerase (RNAP) core enzyme or the transcriptase is only about 2,000 molecules per genome. The regulatory targets of RNAP are, however, modulated by changing its promoter selectivity through two-steps of protein-protein interplay with 7 species of the sigma factor in the first step, and then 300 species of the transcription factor (TF) in the second step. Scientists working in the field of prokaryotic transcription in Japan have made considerable contributions to the elucidation of genetic frameworks and regulatory modes of the genome transcription in E. coli K-12. This review summarizes the findings by this group, first focusing on three sigma factors, the stationary-phase sigma RpoS, the heat-shock sigma RpoH, and the flagellar-chemotaxis sigma RpoF, as examples. It also presents an overview of the current state of the systematic research being carried out to identify the regulatory functions of all TFs from a single and the same bacterium E. coli K-12, using the genomic SELEX and PS-TF screening systems. All these studies have been undertaken with the aim of understanding the genome regulation in E. coli K-12 as a whole.

  12. Genome scale models of yeast: towards standardized evaluation and consistent omic integration

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Nielsen, Jens

    2015-01-01

    Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are curre......Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published...... in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted....

  13. Modeling the integration of bacterial rRNA fragments into the human cancer genome.

    Science.gov (United States)

    Sieber, Karsten B; Gajer, Pawel; Dunning Hotopp, Julie C

    2016-03-21

    Cancer is a disease driven by the accumulation of genomic alterations, including the integration of exogenous DNA into the human somatic genome. We previously identified in silico evidence of DNA fragments from a Pseudomonas-like bacteria integrating into the 5'-UTR of four proto-oncogenes in stomach cancer sequencing data. The functional and biological consequences of these bacterial DNA integrations remain unknown. Modeling of these integrations suggests that the previously identified sequences cover most of the sequence flanking the junction between the bacterial and human DNA. Further examination of these reads reveals that these integrations are rich in guanine nucleotides and the integrated bacterial DNA may have complex transcript secondary structures. The models presented here lay the foundation for future experiments to test if bacterial DNA integrations alter the transcription of the human genes.

  14. Genome editing of human pluripotent stem cells to generate human cellular disease models

    Directory of Open Access Journals (Sweden)

    Kiran Musunuru

    2013-07-01

    Full Text Available Disease modeling with human pluripotent stem cells has come into the public spotlight with the awarding of the Nobel Prize in Physiology or Medicine for 2012 to Drs John Gurdon and Shinya Yamanaka for the discovery that mature cells can be reprogrammed to become pluripotent. This discovery has opened the door for the generation of pluripotent stem cells from individuals with disease and the differentiation of these cells into somatic cell types for the study of disease pathophysiology. The emergence of genome-editing technology over the past few years has made it feasible to generate and investigate human cellular disease models with even greater speed and efficiency. Here, recent technological advances in genome editing, and its utility in human biology and disease studies, are reviewed.

  15. Making Validated Educational Models Central in Preschool Standards.

    Science.gov (United States)

    Schweinhart, Lawrence J.

    This paper presents some ideas to preschool educators and policy makers about how to make validated educational models central in standards for preschool education and care programs that are available to all 3- and 4-year-olds. Defining an educational model as a coherent body of program practices, curriculum content, program and child, and teacher…

  16. Humanistic Model in Adult Education and Science and Technology ...

    African Journals Online (AJOL)

    Humanistic Model in Adult Education and Science and Technology: Challenges of the 21 st Century Developing Nation. ... Annals of Modern Education ... is the result of the scientific and technological advancement, this paper considers humanistic model in adult education as liberal education appropriate for adult age.

  17. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

    Science.gov (United States)

    2016-03-15

    RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...jaques.reifman.civ@mail.mil Abstract A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm -based infections that are difficult to...eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic

  18. Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

    Science.gov (United States)

    Auinger, Hans-Jürgen; Schönleben, Manfred; Lehermeier, Christina; Schmidt, Malthe; Korzun, Viktor; Geiger, Hartwig H; Piepho, Hans-Peter; Gordillo, Andres; Wilde, Peer; Bauer, Eva; Schön, Chris-Carolin

    2016-11-01

    Genomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S 2 lines were genotyped with 16 k SNPs and each year testcrosses of 260 S 2 lines were phenotyped in seven or eight locations. The performance gap between GBLUP and PBLUP increased significantly for all traits when model calibration was performed on aggregated data from several cycles. Prediction accuracies obtained from cross-validation were in the order of 0.70 for all traits when data from all cycles (N CS  = 832) were used for model training and exceeded within-cycle accuracies in all cases. As long as selection cycles are connected by a sufficient number of common ancestors and prediction accuracy has not reached a plateau when increasing sample size, aggregating data from several preceding cycles is recommended for predicting genetic values in subsequent cycles despite decreasing relatedness over time.

  19. Competence development organizations in project management on the basis of genomic model methodologies

    OpenAIRE

    Бушуев, Сергей Дмитриевич; Рогозина, Виктория Борисовна; Ярошенко, Юрий Федерович

    2013-01-01

    The matrix technology for identification of organisational competencies in project management is presented in the article. Matrix elements are the components of organizational competence in the field of project management and project management methodology represented in the structure of the genome. The matrix model of competence in the framework of the adopted methodologies and scanning method for identifying organizational competences formalised. Proposed methods for building effective proj...

  20. Informed consent in direct-to-consumer personal genome testing: the outline of a model between specific and generic consent.

    Science.gov (United States)

    Bunnik, Eline M; Janssens, A Cecile J W; Schermer, Maartje H N

    2014-09-01

    Broad genome-wide testing is increasingly finding its way to the public through the online direct-to-consumer marketing of so-called personal genome tests. Personal genome tests estimate genetic susceptibilities to multiple diseases and other phenotypic traits simultaneously. Providers commonly make use of Terms of Service agreements rather than informed consent procedures. However, to protect consumers from the potential physical, psychological and social harms associated with personal genome testing and to promote autonomous decision-making with regard to the testing offer, we argue that current practices of information provision are insufficient and that there is a place--and a need--for informed consent in personal genome testing, also when it is offered commercially. The increasing quantity, complexity and diversity of most testing offers, however, pose challenges for information provision and informed consent. Both specific and generic models for informed consent fail to meet its moral aims when applied to personal genome testing. Consumers should be enabled to know the limitations, risks and implications of personal genome testing and should be given control over the genetic information they do or do not wish to obtain. We present the outline of a new model for informed consent which can meet both the norm of providing sufficient information and the norm of providing understandable information. The model can be used for personal genome testing, but will also be applicable to other, future forms of broad genetic testing or screening in commercial and clinical settings. © 2012 John Wiley & Sons Ltd.

  1. Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data.

    Science.gov (United States)

    Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang

    2017-01-01

    Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

  2. Genetic education and the challenge of genomic medicine: development of core competences to support preparation of health professionals in Europe

    DEFF Research Database (Denmark)

    Skirton, Heather; Lewis, Celine; Kent, Alastair

    2010-01-01

    in professional education and regulation between European countries, setting curricula may not be practical. Core competences are used as a basis for health professional education in many fields and settings. An Expert Group working under the auspices of the EuroGentest project and European Society of Human...... and professions has resulted in an adaptable framework for both pre-registration and continuing professional education. This competence framework has the potential to improve the quality of genetic health care for patients globally.......The use of genetics and genomics within a wide range of health-care settings requires health professionals to develop expertise to practise appropriately. There is a need for a common minimum standard of competence in genetics for health professionals in Europe but because of differences...

  3. Multi-population genomic prediction using a multi-task Bayesian learning model.

    Science.gov (United States)

    Chen, Liuhong; Li, Changxi; Miller, Stephen; Schenkel, Flavio

    2014-05-03

    Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to develop a multi-task Bayesian learning model for multi-population genomic prediction with a strategy to effectively share information across populations. Simulation studies and real data from Holstein and Ayrshire dairy breeds with phenotypes on five milk production traits were used to evaluate the proposed multi-task Bayesian learning model and compare with a single-task model and a simple data pooling method. A multi-task Bayesian learning model was proposed for multi-population genomic prediction. Information was shared across populations through a common set of latent indicator variables while SNP effects were allowed to vary in different populations. Both simulation studies and real data analysis showed the effectiveness of the multi-task model in improving genomic prediction accuracy for the smaller Ayshire breed. Simulation studies suggested that the multi-task model was most effective when the number of QTL was small (n = 20), with an increase of accuracy by up to 0.09 when QTL effects were lowly correlated between two populations (ρ = 0.2), and up to 0.16 when QTL effects were highly correlated (ρ = 0.8). When QTL genotypes were included for training and validation, the improvements were 0.16 and 0.22, respectively, for scenarios of the low and high correlation of QTL effects between two populations. When the number of QTL was large (n = 200), improvement was small with a maximum of 0.02 when QTL genotypes were not included for genomic prediction. Reduction in accuracy was observed for the simple pooling method when the number of QTL was small and correlation of QTL effects between the two populations was low. For the real data, the multi-task model achieved an

  4. Genomic analysis of cow mortality and milk production using a threshold-linear model.

    Science.gov (United States)

    Tsuruta, S; Lourenco, D A L; Misztal, I; Lawlor, T J

    2017-09-01

    The objective of this study was to investigate the feasibility of genomic evaluation for cow mortality and milk production using a single-step methodology. Genomic relationships between cow mortality and milk production were also analyzed. Data included 883,887 (866,700) first-parity, 733,904 (711,211) second-parity, and 516,256 (492,026) third-parity records on cow mortality (305-d milk yields) of Holsteins from Northeast states in the United States. The pedigree consisted of up to 1,690,481 animals including 34,481 bulls genotyped with 36,951 SNP markers. Analyses were conducted with a bivariate threshold-linear model for each parity separately. Genomic information was incorporated as a genomic relationship matrix in the single-step BLUP. Traditional and genomic estimated breeding values (GEBV) were obtained with Gibbs sampling using fixed variances, whereas reliabilities were calculated from variances of GEBV samples. Genomic EBV were then converted into single nucleotide polymorphism (SNP) marker effects. Those SNP effects were categorized according to values corresponding to 1 to 4 standard deviations. Moving averages and variances of SNP effects were calculated for windows of 30 adjacent SNP, and Manhattan plots were created for SNP variances with the same window size. Using Gibbs sampling, the reliability for genotyped bulls for cow mortality was 28 to 30% in EBV and 70 to 72% in GEBV. The reliability for genotyped bulls for 305-d milk yields was 53 to 65% to 81 to 85% in GEBV. Correlations of SNP effects between mortality and 305-d milk yields within categories were the highest with the largest SNP effects and reached >0.7 at 4 standard deviations. All SNP regions explained less than 0.6% of the genetic variance for both traits, except regions close to the DGAT1 gene, which explained up to 2.5% for cow mortality and 4% for 305-d milk yields. Reliability for GEBV with a moderate number of genotyped animals can be calculated by Gibbs samples. Genomic

  5. Animal models in genomic research: Techniques, applications, and roles for nurses.

    Science.gov (United States)

    Osier, Nicole D; Pham, Lan; Savarese, Amanda; Sayles, Kendra; Alexander, Sheila A

    2016-11-01

    Animal research has been conducted by scientists for over two millennia resulting in a better understanding of human anatomy, physiology, and pathology, as well as testing of novel therapies. In the molecular genomic era, pre-clinical models represent a key tool for understanding the genomic underpinnings of health and disease and are relevant to precision medicine initiatives. Nurses contribute to improved health by collecting and translating evidence from clinically relevant pre-clinical models. Using animal models, nurses can ask questions that would not be feasible or ethical to address in humans, and establish the safety and efficacy of interventions before translating them to clinical trials. Two advantages of using pre-clinical models are reduced variability between test subjects and the opportunity for precisely controlled experimental exposures. Standardized care controls the effects of diet and environment, while the availability of inbred strains significantly reduces the confounding effects of genetic differences. Outside the laboratory, nurses can contribute to the approval and oversight of animal studies, as well as translation to clinical trials and, ultimately, patient care. This review is intended as a primer on the use of animal models to advance nursing science; specifically, the paper discusses the utility of preclinical models for studying the pathophysiologic and genomic contributors to health and disease, testing interventions, and evaluating effects of environmental exposures. Considerations specifically geared to nurse researchers are also introduced, including discussion of how to choose an appropriate model and controls, potential confounders, as well as legal and ethical concerns. Finally, roles for nurse clinicians in pre-clinical research are also highlighted. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Exploiting the functional and taxonomic structure of genomic data by probabilistic topic modeling.

    Science.gov (United States)

    Chen, Xin; Hu, Xiaohua; Lim, Tze Y; Shen, Xiajiong; Park, E K; Rosen, Gail L

    2012-01-01

    In this paper, we present a method that enable both homology-based approach and composition-based approach to further study the functional core (i.e., microbial core and gene core, correspondingly). In the proposed method, the identification of major functionality groups is achieved by generative topic modeling, which is able to extract useful information from unlabeled data. We first show that generative topic model can be used to model the taxon abundance information obtained by homology-based approach and study the microbial core. The model considers each sample as a “document,” which has a mixture of functional groups, while each functional group (also known as a “latent topic”) is a weight mixture of species. Therefore, estimating the generative topic model for taxon abundance data will uncover the distribution over latent functions (latent topic) in each sample. Second, we show that, generative topic model can also be used to study the genome-level composition of “N-mer” features (DNA subreads obtained by composition-based approaches). The model consider each genome as a mixture of latten genetic patterns (latent topics), while each functional pattern is a weighted mixture of the “N-mer” features, thus the existence of core genomes can be indicated by a set of common N-mer features. After studying the mutual information between latent topics and gene regions, we provide an explanation of the functional roles of uncovered latten genetic patterns. The experimental results demonstrate the effectiveness of proposed method.

  7. Minipig and beagle animal model genomes aid species selection in pharmaceutical discovery and development

    Energy Technology Data Exchange (ETDEWEB)

    Vamathevan, Jessica J., E-mail: jessica.j.vamathevan@gsk.com [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Stevenage (United Kingdom); Hall, Matthew D.; Hasan, Samiul; Woollard, Peter M. [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Stevenage (United Kingdom); Xu, Meng; Yang, Yulan; Li, Xin; Wang, Xiaoli [BGI-Shenzen, Shenzhen (China); Kenny, Steve [Safety Assessment, PTS, GlaxoSmithKline, Ware (United Kingdom); Brown, James R. [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Collegeville, PA (United States); Huxley-Jones, Julie [UK Platform Technology Sciences (PTS) Operations and Planning, PTS, GlaxoSmithKline, Stevenage (United Kingdom); Lyon, Jon; Haselden, John [Safety Assessment, PTS, GlaxoSmithKline, Ware (United Kingdom); Min, Jiumeng [BGI-Shenzen, Shenzhen (China); Sanseau, Philippe [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Stevenage (United Kingdom)

    2013-07-15

    Improving drug attrition remains a challenge in pharmaceutical discovery and development. A major cause of early attrition is the demonstration of safety signals which can negate any therapeutic index previously established. Safety attrition needs to be put in context of clinical translation (i.e. human relevance) and is negatively impacted by differences between animal models and human. In order to minimize such an impact, an earlier assessment of pharmacological target homology across animal model species will enhance understanding of the context of animal safety signals and aid species selection during later regulatory toxicology studies. Here we sequenced the genomes of the Sus scrofa Göttingen minipig and the Canis familiaris beagle, two widely used animal species in regulatory safety studies. Comparative analyses of these new genomes with other key model organisms, namely mouse, rat, cynomolgus macaque, rhesus macaque, two related breeds (S. scrofa Duroc and C. familiaris boxer) and human reveal considerable variation in gene content. Key genes in toxicology and metabolism studies, such as the UGT2 family, CYP2D6, and SLCO1A2, displayed unique duplication patterns. Comparisons of 317 known human drug targets revealed surprising variation such as species-specific positive selection, duplication and higher occurrences of pseudogenized targets in beagle (41 genes) relative to minipig (19 genes). These data will facilitate the more effective use of animals in biomedical research. - Highlights: • Genomes of the minipig and beagle dog, two species used in pharmaceutical studies. • First systematic comparative genome analysis of human and six experimental animals. • Key drug toxicology genes display unique duplication patterns across species. • Comparison of 317 drug targets show species-specific evolutionary patterns.

  8. Minipig and beagle animal model genomes aid species selection in pharmaceutical discovery and development

    International Nuclear Information System (INIS)

    Vamathevan, Jessica J.; Hall, Matthew D.; Hasan, Samiul; Woollard, Peter M.; Xu, Meng; Yang, Yulan; Li, Xin; Wang, Xiaoli; Kenny, Steve; Brown, James R.; Huxley-Jones, Julie; Lyon, Jon; Haselden, John; Min, Jiumeng; Sanseau, Philippe

    2013-01-01

    Improving drug attrition remains a challenge in pharmaceutical discovery and development. A major cause of early attrition is the demonstration of safety signals which can negate any therapeutic index previously established. Safety attrition needs to be put in context of clinical translation (i.e. human relevance) and is negatively impacted by differences between animal models and human. In order to minimize such an impact, an earlier assessment of pharmacological target homology across animal model species will enhance understanding of the context of animal safety signals and aid species selection during later regulatory toxicology studies. Here we sequenced the genomes of the Sus scrofa Göttingen minipig and the Canis familiaris beagle, two widely used animal species in regulatory safety studies. Comparative analyses of these new genomes with other key model organisms, namely mouse, rat, cynomolgus macaque, rhesus macaque, two related breeds (S. scrofa Duroc and C. familiaris boxer) and human reveal considerable variation in gene content. Key genes in toxicology and metabolism studies, such as the UGT2 family, CYP2D6, and SLCO1A2, displayed unique duplication patterns. Comparisons of 317 known human drug targets revealed surprising variation such as species-specific positive selection, duplication and higher occurrences of pseudogenized targets in beagle (41 genes) relative to minipig (19 genes). These data will facilitate the more effective use of animals in biomedical research. - Highlights: • Genomes of the minipig and beagle dog, two species used in pharmaceutical studies. • First systematic comparative genome analysis of human and six experimental animals. • Key drug toxicology genes display unique duplication patterns across species. • Comparison of 317 drug targets show species-specific evolutionary patterns

  9. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Science.gov (United States)

    Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

    2017-01-01

    Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

  10. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Directory of Open Access Journals (Sweden)

    Marko Budinich

    Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.

  11. Predicting growth of the healthy infant using a genome scale metabolic model.

    Science.gov (United States)

    Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

    2017-01-01

    An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

  12. FDTD method and models in optical education

    Science.gov (United States)

    Lin, Xiaogang; Wan, Nan; Weng, Lingdong; Zhu, Hao; Du, Jihe

    2017-08-01

    In this paper, finite-difference time-domain (FDTD) method has been proposed as a pedagogical way in optical education. Meanwhile, FDTD solutions, a simulation software based on the FDTD algorithm, has been presented as a new tool which helps abecedarians to build optical models and to analyze optical problems. The core of FDTD algorithm is that the time-dependent Maxwell's equations are discretized to the space and time partial derivatives, and then, to simulate the response of the interaction between the electronic pulse and the ideal conductor or semiconductor. Because the solving of electromagnetic field is in time domain, the memory usage is reduced and the simulation consequence on broadband can be obtained easily. Thus, promoting FDTD algorithm in optical education is available and efficient. FDTD enables us to design, analyze and test modern passive and nonlinear photonic components (such as bio-particles, nanoparticle and so on) for wave propagation, scattering, reflection, diffraction, polarization and nonlinear phenomena. The different FDTD models can help teachers and students solve almost all of the optical problems in optical education. Additionally, the GUI of FDTD solutions is so friendly to abecedarians that learners can master it quickly.

  13. Income Distribution Over Educational Levels: A Simple Model.

    Science.gov (United States)

    Tinbergen, Jan

    An econometric model is formulated that explains income per person in various compartments of the labor market defined by three main levels of education and by education required. The model enables an estimation of the effect of increased access to education on that distribution. The model is based on a production for the economy as a whole; a…

  14. Theories and Frameworks for Online Education: Seeking an Integrated Model

    Science.gov (United States)

    Picciano, Anthony G.

    2017-01-01

    This article examines theoretical frameworks and models that focus on the pedagogical aspects of online education. After a review of learning theory as applied to online education, a proposal for an integrated "Multimodal Model for Online Education" is provided based on pedagogical purpose. The model attempts to integrate the work of…

  15. MODELING OF INNOVATION EDUCATIONAL ENVIRONMENT OF GENERAL EDUCATIONAL INSTITUTION: THE SCIENTIFIC APPROACHES

    OpenAIRE

    Anzhelika D. Tsymbalaru

    2010-01-01

    In the paper the scientific approaches to modeling of innovation educational environment of a general educational institution – system (analysis of object, process and result of modeling as system objects), activity (organizational and psychological structure) and synergetic (aspects and principles).

  16. Principles of proteome allocation are revealed using proteomic data and genome-scale models

    DEFF Research Database (Denmark)

    Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.

    2016-01-01

    to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the "generalist" (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions......Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked...... of these sectors for the general stress response sigma factor sigma(S). Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally...

  17. Reconstruction of genome-scale human metabolic models using omics data

    DEFF Research Database (Denmark)

    Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup

    2015-01-01

    used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods......, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic...... refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model....

  18. From cultured to uncultured genome sequences: metagenomics and modeling microbial ecosystems.

    Science.gov (United States)

    Garza, Daniel R; Dutilh, Bas E

    2015-11-01

    Microorganisms and the viruses that infect them are the most numerous biological entities on Earth and enclose its greatest biodiversity and genetic reservoir. With strength in their numbers, these microscopic organisms are major players in the cycles of energy and matter that sustain all life. Scientists have only scratched the surface of this vast microbial world through culture-dependent methods. Recent developments in generating metagenomes, large random samples of nucleic acid sequences isolated directly from the environment, are providing comprehensive portraits of the composition, structure, and functioning of microbial communities. Moreover, advances in metagenomic analysis have created the possibility of obtaining complete or nearly complete genome sequences from uncultured microorganisms, providing important means to study their biology, ecology, and evolution. Here we review some of the recent developments in the field of metagenomics, focusing on the discovery of genetic novelty and on methods for obtaining uncultured genome sequences, including through the recycling of previously published datasets. Moreover we discuss how metagenomics has become a core scientific tool to characterize eco-evolutionary patterns of microbial ecosystems, thus allowing us to simultaneously discover new microbes and study their natural communities. We conclude by discussing general guidelines and challenges for modeling the interactions between uncultured microorganisms and viruses based on the information contained in their genome sequences. These models will significantly advance our understanding of the functioning of microbial ecosystems and the roles of microbes in the environment.

  19. Modeling Human Bone Marrow Failure Syndromes Using Pluripotent Stem Cells and Genome Engineering.

    Science.gov (United States)

    Jung, Moonjung; Dunbar, Cynthia E; Winkler, Thomas

    2015-12-01

    The combination of epigenetic reprogramming with advanced genome editing technologies opened a new avenue to study disease mechanisms, particularly of disorders with depleted target tissue. Bone marrow failure syndromes (BMFS) typically present with a marked reduction of peripheral blood cells due to a destroyed or dysfunctional bone marrow compartment. Somatic and germline mutations have been etiologically linked to many cases of BMFS. However, without the ability to study primary patient material, the exact pathogenesis for many entities remained fragmentary. Capturing the pathological genotype in induced pluripotent stem cells (iPSCs) allows studying potential developmental defects leading to a particular phenotype. The lack of hematopoietic stem and progenitor cells in these patients can also be overcome by differentiating patient-derived iPSCs into hematopoietic lineages. With fast growing genome editing techniques, such as CRISPR/Cas9, correction of disease-causing mutations in iPSCs or introduction of mutations in cells from healthy individuals enable comparative studies that may identify other genetic or epigenetic events contributing to a specific disease phenotype. In this review, we present recent progresses in disease modeling of inherited and acquired BMFS using reprogramming and genome editing techniques. We also discuss the challenges and potential shortcomings of iPSC-based models for hematological diseases.

  20. Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

    Science.gov (United States)

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

    2016-05-01

    Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. © 2015 Wiley Periodicals, Inc.

  1. Modeling biological problems in computer science: a case study in genome assembly.

    Science.gov (United States)

    Medvedev, Paul

    2018-01-30

    As computer scientists working in bioinformatics/computational biology, we often face the challenge of coming up with an algorithm to answer a biological question. This occurs in many areas, such as variant calling, alignment and assembly. In this tutorial, we use the example of the genome assembly problem to demonstrate how to go from a question in the biological realm to a solution in the computer science realm. We show the modeling process step-by-step, including all the intermediate failed attempts. Please note this is not an introduction to how genome assembly algorithms work and, if treated as such, would be incomplete and unnecessarily long-winded. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  2. Genomic outlier profile analysis: mixture models, null hypotheses, and nonparametric estimation.

    Science.gov (United States)

    Ghosh, Debashis; Chinnaiyan, Arul M

    2009-01-01

    In most analyses of large-scale genomic data sets, differential expression analysis is typically assessed by testing for differences in the mean of the distributions between 2 groups. A recent finding by Tomlins and others (2005) is of a different type of pattern of differential expression in which a fraction of samples in one group have overexpression relative to samples in the other group. In this work, we describe a general mixture model framework for the assessment of this type of expression, called outlier profile analysis. We start by considering the single-gene situation and establishing results on identifiability. We propose 2 nonparametric estimation procedures that have natural links to familiar multiple testing procedures. We then develop multivariate extensions of this methodology to handle genome-wide measurements. The proposed methodologies are compared using simulation studies as well as data from a prostate cancer gene expression study.

  3. Personal genome testing in medical education: student experiences with genotyping in the classroom.

    Science.gov (United States)

    Vernez, Simone Lucia; Salari, Keyan; Ormond, Kelly E; Lee, Sandra Soo-Jin

    2013-01-01

    Direct-to-consumer (DTC) personal genotyping services are beginning to be adopted by educational institutions as pedagogical tools for learning about human genetics. However, there is little known about student reactions to such testing. This study investigated student experiences and attitudes towards DTC personal genome testing. Individual interviews were conducted with students who chose to undergo personal genotyping in the context of an elective genetics course. Ten medical and graduate students were interviewed before genotyping occurred, and at 2 weeks and 6 months after receiving their genotype results. Qualitative analysis of interview transcripts assessed the expectations and experiences of students who underwent personal genotyping, how they interpreted and applied their results; how the testing affected the quality of their learning during the course, and what were their perceived needs for support. Students stated that personal genotyping enhanced their engagement with the course content. Although students expressed skepticism over the clinical utility of some test results, they expressed significant enthusiasm immediately after receiving their personal genetic analysis, and were particularly interested in results such as drug response and carrier testing. However, few reported making behavioral changes or following up on specific results through a healthcare provider. Students did not report utilizing genetic counseling, despite feeling strongly that the 'general public' would need these services. In follow-up interviews, students exhibited poor recall on details of the consent and biobanking agreements, but expressed little regret over their decision to undergo genotyping. Students reported mining their raw genetic data, and conveyed a need for further consultation support in their exploration of genetic variants. Personal genotyping may improve students' self-reported motivation and engagement with course material. However, consultative support that

  4. Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.

    Science.gov (United States)

    Bandeira E Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

    2017-06-07

    Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. Copyright © 2017 Bandeira e Sousa et al.

  5. Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction

    Directory of Open Access Journals (Sweden)

    Massaine Bandeira e Sousa

    2017-06-01

    Full Text Available Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1 single-environment, main genotypic effect model (SM; (2 multi-environment, main genotypic effects model (MM; (3 multi-environment, single variance G×E deviation model (MDs; and (4 multi-environment, environment-specific variance G×E deviation model (MDe. Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB, and a nonlinear kernel Gaussian kernel (GK. The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets, having different numbers of maize hybrids evaluated in different environments for grain yield (GY, plant height (PH, and ear height (EH. Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied.

  6. Heritage Education in Museums: an Inclusion- Focused Model

    OpenAIRE

    Fontal Merillas, Olaia; Marín Cepeda, Sofía

    2016-01-01

    Heritage Education in Museums: Inclusion Model (HEM-INMO) is one of the research conclusions of the Spanish Heritage Education Observatory (SHEO), funded by Spain’s Ministry of Economy and Competitiveness. The Observatory evaluates educational programs generated in Spain and in the international area in the last two decades, especially in museums as heritage education non-formal contexts. Also, the HEM-INMO model is included within the aims of the National Education and Heritage Plan (NE&HP),...

  7. Genome-scale modeling of the protein secretory machinery in yeast

    DEFF Research Database (Denmark)

    Feizi, Amir; Österlund, Tobias; Petranovic, Dina

    2013-01-01

    The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking....... Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm...

  8. Agent Based Modeling as an Educational Tool

    Science.gov (United States)

    Fuller, J. H.; Johnson, R.; Castillo, V.

    2012-12-01

    Motivation is a key element in high school education. One way to improve motivation and provide content, while helping address critical thinking and problem solving skills, is to have students build and study agent based models in the classroom. This activity visually connects concepts with their applied mathematical representation. "Engaging students in constructing models may provide a bridge between frequently disconnected conceptual and mathematical forms of knowledge." (Levy and Wilensky, 2011) We wanted to discover the feasibility of implementing a model based curriculum in the classroom given current and anticipated core and content standards.; Simulation using California GIS data ; Simulation of high school student lunch popularity using aerial photograph on top of terrain value map.

  9. Genomic selection in mink yield higher accuracies with a Bayesian approach allowing for heterogeneous variance than a GBLUP model

    DEFF Research Database (Denmark)

    Villumsen, Trine Michelle; Su, Guosheng; Cai, Zexi

    2018-01-01

    by sequencing. Four live grading traits and four traits on dried pelts for size and quality were analysed. GWAS analysis detected significant SNPs for all the traits. The single-trait Bayesian model resulted in higher accuracies for the genomic predictions than the single-trait GBLUP model, especially......The accuracy of genomic prediction for mink was compared for single-trait and multiple-trait GBLUP models and Bayesian models that allowed for heterogeneous (co)variance structure over the genome. The mink population consisted of 2,103 brown minks genotyped with the method of genotyping...... for the traits measured on dried pelts. We expected the multiple-trait models to be superior to the single trait models since the multiple-trait model can make use of information when traits are correlated. However, we did not find a general improvement in accuracies with the multiple-trait models compared...

  10. Econometric Models of Education, Some Applications. Education and Development, Technical Reports.

    Science.gov (United States)

    Tinbergen, Jan; And Others

    This report contains five papers which describe mathematical models of the educational system as it relates to economic growth. Experimental applications of the models to particular educational systems are discussed. Three papers, by L. J. Emmerij, J. Blum, and G. Williams, discuss planning models for the calculation of educational requirements…

  11. National Human Genome Research Institute

    Science.gov (United States)

    ... Care Genomic Medicine Working Group New Horizons and Research Patient Management Policy and Ethics Issues Quick Links for Patient Care Education All About the Human Genome Project Fact Sheets Genetic Education Resources for ...

  12. On the representability of complete genomes by multiple competing finite-context (Markov models.

    Directory of Open Access Journals (Sweden)

    Armando J Pinho

    Full Text Available A finite-context (Markov model of order k yields the probability distribution of the next symbol in a sequence of symbols, given the recent past up to depth k. Markov modeling has long been applied to DNA sequences, for example to find gene-coding regions. With the first studies came the discovery that DNA sequences are non-stationary: distinct regions require distinct model orders. Since then, Markov and hidden Markov models have been extensively used to describe the gene structure of prokaryotes and eukaryotes. However, to our knowledge, a comprehensive study about the potential of Markov models to describe complete genomes is still lacking. We address this gap in this paper. Our approach relies on (i multiple competing Markov models of different orders (ii careful programming techniques that allow orders as large as sixteen (iii adequate inverted repeat handling (iv probability estimates suited to the wide range of context depths used. To measure how well a model fits the data at a particular position in the sequence we use the negative logarithm of the probability estimate at that position. The measure yields information profiles of the sequence, which are of independent interest. The average over the entire sequence, which amounts to the average number of bits per base needed to describe the sequence, is used as a global performance measure. Our main conclusion is that, from the probabilistic or information theoretic point of view and according to this performance measure, multiple competing Markov models explain entire genomes almost as well or even better than state-of-the-art DNA compression methods, such as XM, which rely on very different statistical models. This is surprising, because Markov models are local (short-range, contrasting with the statistical models underlying other methods, where the extensive data repetitions in DNA sequences is explored, and therefore have a non-local character.

  13. Optimization of multi-environment trials for genomic selection based on crop models.

    Science.gov (United States)

    Rincent, R; Kuhn, E; Monod, H; Oury, F-X; Rousset, M; Allard, V; Le Gouis, J

    2017-08-01

    We propose a statistical criterion to optimize multi-environment trials to predict genotype × environment interactions more efficiently, by combining crop growth models and genomic selection models. Genotype × environment interactions (GEI) are common in plant multi-environment trials (METs). In this context, models developed for genomic selection (GS) that refers to the use of genome-wide information for predicting breeding values of selection candidates need to be adapted. One promising way to increase prediction accuracy in various environments is to combine ecophysiological and genetic modelling thanks to crop growth models (CGM) incorporating genetic parameters. The efficiency of this approach relies on the quality of the parameter estimates, which depends on the environments composing this MET used for calibration. The objective of this study was to determine a method to optimize the set of environments composing the MET for estimating genetic parameters in this context. A criterion called OptiMET was defined to this aim, and was evaluated on simulated and real data, with the example of wheat phenology. The MET defined with OptiMET allowed estimating the genetic parameters with lower error, leading to higher QTL detection power and higher prediction accuracies. MET defined with OptiMET was on average more efficient than random MET composed of twice as many environments, in terms of quality of the parameter estimates. OptiMET is thus a valuable tool to determine optimal experimental conditions to best exploit MET and the phenotyping tools that are currently developed.

  14. Probabilistic topic modeling for the analysis and classification of genomic sequences

    Science.gov (United States)

    2015-01-01

    Background Studies on genomic sequences for classification and taxonomic identification have a leading role in the biomedical field and in the analysis of biodiversity. These studies are focusing on the so-called barcode genes, representing a well defined region of the whole genome. Recently, alignment-free techniques are gaining more importance because they are able to overcome the drawbacks of sequence alignment techniques. In this paper a new alignment-free method for DNA sequences clustering and classification is proposed. The method is based on k-mers representation and text mining techniques. Methods The presented method is based on Probabilistic Topic Modeling, a statistical technique originally proposed for text documents. Probabilistic topic models are able to find in a document corpus the topics (recurrent themes) characterizing classes of documents. This technique, applied on DNA sequences representing the documents, exploits the frequency of fixed-length k-mers and builds a generative model for a training group of sequences. This generative model, obtained through the Latent Dirichlet Allocation (LDA) algorithm, is then used to classify a large set of genomic sequences. Results and conclusions We performed classification of over 7000 16S DNA barcode sequences taken from Ribosomal Database Project (RDP) repository, training probabilistic topic models. The proposed method is compared to the RDP tool and Support Vector Machine (SVM) classification algorithm in a extensive set of trials using both complete sequences and short sequence snippets (from 400 bp to 25 bp). Our method reaches very similar results to RDP classifier and SVM for complete sequences. The most interesting results are obtained when short sequence snippets are considered. In these conditions the proposed method outperforms RDP and SVM with ultra short sequences and it exhibits a smooth decrease of performance, at every taxonomic level, when the sequence length is decreased. PMID:25916734

  15. A model species for agricultural pest genomics: the genome of the Colorado potato beetle, Leptinotarsa decemlineata (Coleoptera: Chrysomelidae).

    Science.gov (United States)

    Schoville, Sean D; Chen, Yolanda H; Andersson, Martin N; Benoit, Joshua B; Bhandari, Anita; Bowsher, Julia H; Brevik, Kristian; Cappelle, Kaat; Chen, Mei-Ju M; Childers, Anna K; Childers, Christopher; Christiaens, Olivier; Clements, Justin; Didion, Elise M; Elpidina, Elena N; Engsontia, Patamarerk; Friedrich, Markus; García-Robles, Inmaculada; Gibbs, Richard A; Goswami, Chandan; Grapputo, Alessandro; Gruden, Kristina; Grynberg, Marcin; Henrissat, Bernard; Jennings, Emily C; Jones, Jeffery W; Kalsi, Megha; Khan, Sher A; Kumar, Abhishek; Li, Fei; Lombard, Vincent; Ma, Xingzhou; Martynov, Alexander; Miller, Nicholas J; Mitchell, Robert F; Munoz-Torres, Monica; Muszewska, Anna; Oppert, Brenda; Palli, Subba Reddy; Panfilio, Kristen A; Pauchet, Yannick; Perkin, Lindsey C; Petek, Marko; Poelchau, Monica F; Record, Éric; Rinehart, Joseph P; Robertson, Hugh M; Rosendale, Andrew J; Ruiz-Arroyo, Victor M; Smagghe, Guy; Szendrei, Zsofia; Thomas, Gregg W C; Torson, Alex S; Vargas Jentzsch, Iris M; Weirauch, Matthew T; Yates, Ashley D; Yocum, George D; Yoon, June-Sun; Richards, Stephen

    2018-01-31

    The Colorado potato beetle is one of the most challenging agricultural pests to manage. It has shown a spectacular ability to adapt to a variety of solanaceaeous plants and variable climates during its global invasion, and, notably, to rapidly evolve insecticide resistance. To examine evidence of rapid evolutionary change, and to understand the genetic basis of herbivory and insecticide resistance, we tested for structural and functional genomic changes relative to other arthropod species using genome sequencing, transcriptomics, and community annotation. Two factors that might facilitate rapid evolutionary change include transposable elements, which comprise at least 17% of the genome and are rapidly evolving compared to other Coleoptera, and high levels of nucleotide diversity in rapidly growing pest populations. Adaptations to plant feeding are evident in gene expansions and differential expression of digestive enzymes in gut tissues, as well as expansions of gustatory receptors for bitter tasting. Surprisingly, the suite of genes involved in insecticide resistance is similar to other beetles. Finally, duplications in the RNAi pathway might explain why Leptinotarsa decemlineata has high sensitivity to dsRNA. The L. decemlineata genome provides opportunities to investigate a broad range of phenotypes and to develop sustainable methods to control this widely successful pest.

  16. Positioning genomics in biology education: content mapping of undergraduate biology textbooks.

    Science.gov (United States)

    Wernick, Naomi L B; Ndung'u, Eric; Haughton, Dominique; Ledley, Fred D

    2014-12-01

    Biological thought increasingly recognizes the centrality of the genome in constituting and regulating processes ranging from cellular systems to ecology and evolution. In this paper, we ask whether genomics is similarly positioned as a core concept in the instructional sequence for undergraduate biology. Using quantitative methods, we analyzed the order in which core biological concepts were introduced in textbooks for first-year general and human biology. Statistical analysis was performed using self-organizing map algorithms and conventional methods to identify clusters of terms and their relative position in the books. General biology textbooks for both majors and nonmajors introduced genome-related content after text related to cell biology and biological chemistry, but before content describing higher-order biological processes. However, human biology textbooks most often introduced genomic content near the end of the books. These results suggest that genomics is not yet positioned as a core concept in commonly used textbooks for first-year biology and raises questions about whether such textbooks, or courses based on the outline of these textbooks, provide an appropriate foundation for understanding contemporary biological science.

  17. Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

    Directory of Open Access Journals (Sweden)

    Sriram Chandrasekaran

    2017-12-01

    Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

  18. Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

    Science.gov (United States)

    Martínez, C A; Khare, K; Rahman, S; Elzo, M A

    2017-10-01

    Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.

  19. Continuous Certification Within Residency: An Educational Model.

    Science.gov (United States)

    Rachlin, Susan; Schonberger, Alison; Nocera, Nicole; Acharya, Jay; Shah, Nidhi; Henkel, Jacqueline

    2015-10-01

    Given that maintaining compliance with Maintenance of Certification is necessary for maintaining licensure to practice as a radiologist and provide quality patient care, it is important for radiology residents to practice fulfilling each part of the program during their training not only to prepare for success after graduation but also to adequately learn best practices from the beginning of their professional careers. This article discusses ways to implement continuous certification (called Continuous Residency Certification) as an educational model within the residency training program. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

  20. [Educational model to develop trustworthy professional activities].

    Science.gov (United States)

    Hamui-Sutton, Alicia; Varela-Ruiz, Margarita; Ortiz-Montalvo, Armando; Torruco-García, Uri

    2015-01-01

    The reorganization of the national health system (SNS), enforces reflection and transformation on medical education in clinical contexts. The study presents an educational model to develop entrusted professionals activities (MEDAPROC) to train human resources in health with reliable knowledge, skills and attitudes to work in the shifting scenario of the SNS. The paper discusses international and national documents on skills in medicine. Based on the analysis of 8 domains, 50 skills and 13 entrusted professional activities (RPA) proposed by the Association of the American Medical College (AAMC) we propose a curriculum design, with the example of the undergraduate program of Gynecology and Obstetrics, with the intention to advance to internship and residency in a continuum that marks milestones and clinical practices. The pedagogical design of MEDAPROC was developed within three areas: 1) proposal of the AAMC; 2) curricular content of programs in pre and postgraduate education 3) organization of the daily agenda with academic mechanisms to develop the competencies, cover program items and develop clinical practice in deliberate learning activities, as well as milestones. The MEDAPROC offers versatility, student mobility and curricular flexibility in a system planed by academic units in diverse clinical settings.

  1. Assessment of the Quality Management Models in Higher Education

    Science.gov (United States)

    Basar, Gulsun; Altinay, Zehra; Dagli, Gokmen; Altinay, Fahriye

    2016-01-01

    This study involves the assessment of the quality management models in Higher Education by explaining the importance of quality in higher education and by examining the higher education quality assurance system practices in other countries. The qualitative study was carried out with the members of the Higher Education Planning, Evaluation,…

  2. Modelling of information processes management of educational complex

    Directory of Open Access Journals (Sweden)

    Оксана Николаевна Ромашкова

    2014-12-01

    Full Text Available This work concerns information model of the educational complex which includes several schools. A classification of educational complexes formed in Moscow is given. There are also a consideration of the existing organizational structure of the educational complex and a suggestion of matrix management structure. Basic management information processes of the educational complex were conceptualized.

  3. GenoGAM: genome-wide generalized additive models for ChIP-Seq analysis.

    Science.gov (United States)

    Stricker, Georg; Engelhardt, Alexander; Schulz, Daniel; Schmid, Matthias; Tresch, Achim; Gagneur, Julien

    2017-08-01

    Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a widely used approach to study protein-DNA interactions. Often, the quantities of interest are the differential occupancies relative to controls, between genetic backgrounds, treatments, or combinations thereof. Current methods for differential occupancy of ChIP-Seq data rely however on binning or sliding window techniques, for which the choice of the window and bin sizes are subjective. Here, we present GenoGAM (Genome-wide Generalized Additive Model), which brings the well-established and flexible generalized additive models framework to genomic applications using a data parallelism strategy. We model ChIP-Seq read count frequencies as products of smooth functions along chromosomes. Smoothing parameters are objectively estimated from the data by cross-validation, eliminating ad hoc binning and windowing needed by current approaches. GenoGAM provides base-level and region-level significance testing for full factorial designs. Application to a ChIP-Seq dataset in yeast showed increased sensitivity over existing differential occupancy methods while controlling for type I error rate. By analyzing a set of DNA methylation data and illustrating an extension to a peak caller, we further demonstrate the potential of GenoGAM as a generic statistical modeling tool for genome-wide assays. Software is available from Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/GenoGAM.html . gagneur@in.tum.de. Supplementary information is available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  4. DESCARTES' RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA.

    Science.gov (United States)

    Bhaskar, Anand; Song, Yun S

    2014-01-01

    The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the "folded" SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes' rule of signs for polynomials to the Laplace transform of piecewise continuous functions.

  5. DESCARTES’ RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA1

    Science.gov (United States)

    Bhaskar, Anand; Song, Yun S.

    2016-01-01

    The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the “folded” SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes’ rule of signs for polynomials to the Laplace transform of piecewise continuous functions. PMID:28018011

  6. FACS-Assisted CRISPR-Cas9 Genome Editing Facilitates Parkinson's Disease Modeling

    Directory of Open Access Journals (Sweden)

    Jonathan Arias-Fuenzalida

    2017-11-01

    Full Text Available Genome editing and human induced pluripotent stem cells hold great promise for the development of isogenic disease models and the correction of disease-associated mutations for isogenic tissue therapy. CRISPR-Cas9 has emerged as a versatile and simple tool for engineering human cells for such purposes. However, the current protocols to derive genome-edited lines require the screening of a great number of clones to obtain one free of random integration or on-locus non-homologous end joining (NHEJ-containing alleles. Here, we describe an efficient method to derive biallelic genome-edited populations by the use of fluorescent markers. We call this technique FACS-assisted CRISPR-Cas9 editing (FACE. FACE allows the derivation of correctly edited polyclones carrying a positive selection fluorescent module and the exclusion of non-edited, random integrations and on-target allele NHEJ-containing cells. We derived a set of isogenic lines containing Parkinson's-disease-associated mutations in α-synuclein and present their comparative phenotypes.

  7. A Genomics-Based Model for Prediction of Severe Bioprosthetic Mitral Valve Calcification.

    Science.gov (United States)

    Ponasenko, Anastasia V; Khutornaya, Maria V; Kutikhin, Anton G; Rutkovskaya, Natalia V; Tsepokina, Anna V; Kondyukova, Natalia V; Yuzhalin, Arseniy E; Barbarash, Leonid S

    2016-08-31

    Severe bioprosthetic mitral valve calcification is a significant problem in cardiovascular surgery. Unfortunately, clinical markers did not demonstrate efficacy in prediction of severe bioprosthetic mitral valve calcification. Here, we examined whether a genomics-based approach is efficient in predicting the risk of severe bioprosthetic mitral valve calcification. A total of 124 consecutive Russian patients who underwent mitral valve replacement surgery were recruited. We investigated the associations of the inherited variation in innate immunity, lipid metabolism and calcium metabolism genes with severe bioprosthetic mitral valve calcification. Genotyping was conducted utilizing the TaqMan assay. Eight gene polymorphisms were significantly associated with severe bioprosthetic mitral valve calcification and were therefore included into stepwise logistic regression which identified male gender, the T/T genotype of the rs3775073 polymorphism within the TLR6 gene, the C/T genotype of the rs2229238 polymorphism within the IL6R gene, and the A/A genotype of the rs10455872 polymorphism within the LPA gene as independent predictors of severe bioprosthetic mitral valve calcification. The developed genomics-based model had fair predictive value with area under the receiver operating characteristic (ROC) curve of 0.73. In conclusion, our genomics-based approach is efficient for the prediction of severe bioprosthetic mitral valve calcification.

  8. Endogenous retroviruses of sheep: a model system for understanding physiological adaptation to an evolving ruminant genome.

    Science.gov (United States)

    Spencer, Thomas E; Palmarini, Massimo

    2012-01-01

    Endogenous retroviruses (ERVs) are present in the genome of all vertebrates and are remnants of ancient exogenous retroviral infections of the host germline transmitted vertically from generation to generation. Sheep betaretroviruses offer a unique model system to study the complex interaction between retroviruses and their host. The sheep genome contains 27 endogenous betaretroviruses (enJSRVs) related to the exogenous and pathogenic Jaagsiekte sheep retrovirus (JSRV), the causative agent of a transmissible lung cancer in sheep. The enJSRVs can protect their host against JSRV infection by blocking early and late steps of the JSRV replication cycle. In the female reproductive tract, enJSRVs are specifically expressed in the uterine luminal and glandular epithelia as well as in the conceptus (embryo and associated extraembryonic membranes) trophectoderm and in utero loss-of-function experiments found the enJSRVs envelope (env) to be essential for conceptus elongation and trophectoderm growth and development. Collectively, available evidence in sheep and other mammals indicate that ERVs coevolved with their hosts for millions of years and were positively selected for biological roles in genome plasticity and evolution, protection of the host against infection of related pathogenic and exogenous retroviruses, and placental development.

  9. [Genomics innovative teaching pattern based upon amalgamation between modern educational technology and constructivism studying theory].

    Science.gov (United States)

    Liang, Xu-Fang; Peng, Jing; Zhou, Tian-Hong

    2007-04-01

    In order to overcome various malpractices in the traditional teaching methods, and also as part of the Guangdong province molecular biology perfect course project, some reforms were carried out to the teaching pattern of genomics. The reforms include using the foreign original teaching materials, bilingual teaching, as well as taking the constructivism-directed discussion teaching method and the multimedia computer-assisted instruction. To improve the scoring way and the laboratory course of the subject, we carried on a multiplex inspection systems and a self-designing experiments. Through the teaching reform on Genomics, we have gradually consummated the construction of molecular biology curriculum system.

  10. Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

    Science.gov (United States)

    Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

    2014-01-01

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

  11. Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species.

    Science.gov (United States)

    Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin

    2016-06-01

    We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Genome-wide association study of handedness excludes simple genetic models

    Science.gov (United States)

    Armour, J AL; Davison, A; McManus, I C

    2014-01-01

    Handedness is a human behavioural phenotype that appears to be congenital, and is often assumed to be inherited, but for which the developmental origin and underlying causation(s) have been elusive. Models of the genetic basis of variation in handedness have been proposed that fit different features of the observed resemblance between relatives, but none has been decisively tested or a corresponding causative locus identified. In this study, we applied data from well-characterised individuals studied at the London Twin Research Unit. Analysis of genome-wide SNP data from 3940 twins failed to identify any locus associated with handedness at a genome-wide level of significance. The most straightforward interpretation of our analyses is that they exclude the simplest formulations of the ‘right-shift' model of Annett and the ‘dextral/chance' model of McManus, although more complex modifications of those models are still compatible with our observations. For polygenic effects, our study is inadequately powered to reliably detect alleles with effect sizes corresponding to an odds ratio of 1.2, but should have good power to detect effects at an odds ratio of 2 or more. PMID:24065183

  13. Educational productivity in higher education : An examination of part of the Walberg Educational Productivity Model

    NARCIS (Netherlands)

    Bruinsma, M.; Jansen, E. P. W. A.

    Several factors in the H. J. Walberg Educational Productivity Model, which assumes that 9 factors affect academic achievement, were examined with a limited sample of 1st-year students in the University of Groningen. Information concerning 8 of these factors - grades, motivation, age, prior

  14. Funding medical education: should we follow a different model to general higher education?

    Directory of Open Access Journals (Sweden)

    Kieran Walsh

    2015-09-01

    Full Text Available ISSUE. There has been much recent discussion on the funding of medical education. There has also been much discussion about the funding of higher education more generally. EVIDENCE. The topics of discussion have included the rising costs of education; who should pay; the various potential models of funding; and how best to ensure maximum returns from investment. IMPLICATIONS. Medical education has largely followed the emerging models of funding for higher education. However there are important reasons why the funding models for higher education may not suit medical education. These reasons include the fact that medical education is as important to the public as it is to the learner; the range of funding sources available to medical schools; the strict regulation of medical education; and the fact that the privatisation and commercialisation of higher education may not been in keeping with the social goals of medical schools and the agenda of diversification within the medical student population.

  15. Funding medical education: should we follow a different model to general higher education? Commentary.

    Science.gov (United States)

    Walsh, Kieran

    2015-01-01

    There has been much recent discussion on the funding of medical education. There has also been much discussion about the funding of higher education more generally. The topics of discussion have included the rising costs of education; who should pay; the various potential models of funding; and how best to ensure maximum returns from investment. Medical education has largely followed the emerging models of funding for higher education. However there are important reasons why the funding models for higher education may not suit medical education. These reasons include the fact that medical education is as important to the public as it is to the learner; the range of funding sources available to medical schools; the strict regulation of medical education; and the fact that the privatisation and commercialisation of higher education may not been in keeping with the social goals of medical schools and the agenda of diversification within the medical student population.

  16. In silico method for modelling metabolism and gene product expression at genome scale

    Energy Technology Data Exchange (ETDEWEB)

    Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

    2012-07-03

    Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

  17. Calibration and analysis of genome-based models for microbial ecology.

    Science.gov (United States)

    Louca, Stilianos; Doebeli, Michael

    2015-10-16

    Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology.

  18. Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

    DEFF Research Database (Denmark)

    Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

    2017-01-01

    orders of magnitude. Data values also have greatly varying magnitudes. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME......Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many...... models have 70,000 constraints and variables and will grow larger). We have developed a quadrupleprecision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging...

  19. Speciation in the Derrida-Higgs model with finite genomes and spatial populations

    Science.gov (United States)

    de Aguiar, Marcus A. M.

    2017-02-01

    The speciation model proposed by Derrida and Higgs demonstrated that a sexually reproducing population can split into different species in the absence of natural selection or any type of geographic isolation, provided that mating is assortative and the number of genes involved in the process is infinite. Here we revisit this model and simulate it for finite genomes, focusing on the question of how many genes it actually takes to trigger neutral sympatric speciation. We find that, for typical parameters used in the original model, it takes the order of 105 genes. We compare the results with a similar spatially explicit model where about 100 genes suffice for speciation. We show that when the number of genes is small the species that emerge are strongly segregated in space. For a larger number of genes, on the other hand, the spatial structure of the population is less important and the species distribution overlap considerably.

  20. Two Models of Engineering Education for the Professional Practice

    NARCIS (Netherlands)

    Ir. Dick van Schenk Brill; Ir Peter Boots; Ir. Peter van Kollenburg

    2002-01-01

    Two models for engineering education that may answer the needs for "Renaissance Engineers" are described in this paper. They were the outcome of an educational renewal project, funded by the Dutch Ministry of Education and industrial companies. The first model (Corporate Curriculum) aims to bring

  1. Three Models of Education: Rights, Capabilities and Human Capital

    Science.gov (United States)

    Robeyns, Ingrid

    2006-01-01

    This article analyses three normative accounts that can underlie educational policies, with special attention to gender issues. These three models of education are human capital theory, rights discourses and the capability approach. I first outline five different roles that education can play. Then I analyse these three models of educational…

  2. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

    International Nuclear Information System (INIS)

    Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

    2011-01-01

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species, multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  3. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model.

    Science.gov (United States)

    Fang, Yilin; Scheibe, Timothy D; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E; Lovley, Derek R

    2011-03-25

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  4. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

    Science.gov (United States)

    Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

    2011-03-01

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  5. Genomic selection models for directional dominance: an example for litter size in pigs.

    Science.gov (United States)

    Varona, Luis; Legarra, Andrés; Herring, William; Vitezica, Zulma G

    2018-01-26

    The quantitative genetics theory argues that inbreeding depression and heterosis are founded on the existence of directional dominance. However, most procedures for genomic selection that have included dominance effects assumed prior symmetrical distributions. To address this, two alternatives can be considered: (1) assume the mean of dominance effects different from zero, and (2) use skewed distributions for the regularization of dominance effects. The aim of this study was to compare these approaches using two pig datasets and to confirm the presence of directional dominance. Four alternative models were implemented in two datasets of pig litter size that consisted of 13,449 and 11,581 records from 3631 and 2612 sows genotyped with the Illumina PorcineSNP60 BeadChip. The models evaluated included (1) a model that does not consider directional dominance (Model SN), (2) a model with a covariate b for the average individual homozygosity (Model SC), (3) a model with a parameter λ that reflects asymmetry in the context of skewed Gaussian distributions (Model AN), and (4) a model that includes both b and λ (Model Full). The results of the analysis showed that posterior probabilities of a negative b or a positive λ under Models SC and AN were higher than 0.99, which indicate positive directional dominance. This was confirmed with the predictions of inbreeding depression under Models Full, SC and AN, that were higher than in the SN Model. In spite of differences in posterior estimates of variance components between models, comparison of models based on LogCPO and DIC indicated that Model SC provided the best fit for the two datasets analyzed. Our results confirmed the presence of positive directional dominance for pig litter size and suggested that it should be taken into account when dominance effects are included in genomic evaluation procedures. The consequences of ignoring directional dominance may affect predictions of breeding values and can lead to biased

  6. Flexible Programmes in Higher Professional Education: Expert Validation of a Flexible Educational Model

    Science.gov (United States)

    Schellekens, Ad; Paas, Fred; Verbraeck, Alexander; van Merrienboer, Jeroen J. G.

    2010-01-01

    In a preceding case study, a process-focused demand-driven approach for organising flexible educational programmes in higher professional education (HPE) was developed. Operations management and instructional design contributed to designing a flexible educational model by means of discrete-event simulation. Educational experts validated the model…

  7. Design of the Model of Constructivist Learning Theory for Moral Education in Physical Education Teaching

    Science.gov (United States)

    Wang, Chenyu

    2011-01-01

    In order to achieve better effect of moral education in physical education teaching, this article employed constructivist learning theory to design the model of moral education according to the characteristics of physical education teaching, in order that the majority of P.E. teachers draw lessons from it in their teaching practice, and service to…

  8. Filling the knowledge gap: Integrating quantitative genetics and genomics in graduate education and outreach

    Science.gov (United States)

    The genomics revolution provides vital tools to address global food security. Yet to be incorporated into livestock breeding, molecular techniques need to be integrated into a quantitative genetics framework. Within the U.S., with shrinking faculty numbers with the requisite skills, the capacity to ...

  9. From Mendel to the Human Genome Project: The Implications for Nurse Education.

    Science.gov (United States)

    Burton, Hilary; Stewart, Alison

    2003-01-01

    The Human Genome Project is brining new opportunities to predict and prevent diseases. Although pediatric nurses are the closest to these developments, most nurses will encounter genetic aspects of practice and must understand the basic science and its ethical, legal, and social dimensions. (Includes commentary by Peter Birchenall.) (SK)

  10. Genome-Wide Association Studies and Comparison of Models and Cross-Validation Strategies for Genomic Prediction of Quality Traits in Advanced Winter Wheat Breeding Lines

    Directory of Open Access Journals (Sweden)

    Peter S. Kristensen

    2018-02-01

    Full Text Available The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number, and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

  11. Genome-scale model guided design of Propionibacterium for enhanced propionic acid production

    Directory of Open Access Journals (Sweden)

    Laura Navone

    2018-06-01

    Full Text Available Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp. shermanii and the pan-Propionibacterium genome-scale metabolic models (GEMs to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp. shermanii, two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP, Zwf (glucose-6-phosphate 1-dehydrogenase and Pgl (6-phosphogluconolactonase. Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK and sodium-pumping methylmalonyl-CoA decarboxylase (MMD was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in

  12. High performance computation of landscape genomic models including local indicators of spatial association.

    Science.gov (United States)

    Stucki, S; Orozco-terWengel, P; Forester, B R; Duruz, S; Colli, L; Masembe, C; Negrini, R; Landguth, E; Jones, M R; Bruford, M W; Taberlet, P; Joost, S

    2017-09-01

    With the increasing availability of both molecular and topo-climatic data, the main challenges facing landscape genomics - that is the combination of landscape ecology with population genomics - include processing large numbers of models and distinguishing between selection and demographic processes (e.g. population structure). Several methods address the latter, either by estimating a null model of population history or by simultaneously inferring environmental and demographic effects. Here we present samβada, an approach designed to study signatures of local adaptation, with special emphasis on high performance computing of large-scale genetic and environmental data sets. samβada identifies candidate loci using genotype-environment associations while also incorporating multivariate analyses to assess the effect of many environmental predictor variables. This enables the inclusion of explanatory variables representing population structure into the models to lower the occurrences of spurious genotype-environment associations. In addition, samβada calculates local indicators of spatial association for candidate loci to provide information on whether similar genotypes tend to cluster in space, which constitutes a useful indication of the possible kinship between individuals. To test the usefulness of this approach, we carried out a simulation study and analysed a data set from Ugandan cattle to detect signatures of local adaptation with samβada, bayenv, lfmm and an F ST outlier method (FDIST approach in arlequin) and compare their results. samβada - an open source software for Windows, Linux and Mac OS X available at http://lasig.epfl.ch/sambada - outperforms other approaches and better suits whole-genome sequence data processing. © 2016 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

  13. Genomic comparison of closely related Giant Viruses supports an accordion-like model of evolution

    OpenAIRE

    Filée, Jonathan

    2015-01-01

    Genome gigantism occurs so far in Phycodnaviridae and Mimiviridae (order Megavirales). Origin and evolution of these Giant Viruses (GVs) remain open questions. Interestingly, availability of a collection of closely related GV genomes enabling genomic comparisons offer the opportunity to better understand the different evolutionary forces acting on these genomes. Whole genome alignment for five groups of viruses belonging to the Mimiviridae and Phycodnaviridae families show that there is no tr...

  14. Comparative Genomics

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 11; Issue 8. Comparative Genomics - A Powerful New Tool in Biology. Anand K Bachhawat. General Article Volume 11 Issue 8 August 2006 pp 22-40. Fulltext. Click here to view fulltext PDF. Permanent link:

  15. Personalized Whole-Cell Kinetic Models of Metabolism for Discovery in Genomics and Pharmacodynamics

    DEFF Research Database (Denmark)

    Bordbar, Aarash; McCloskey, Douglas; Zielinski, Daniel C

    2015-01-01

    Understanding individual variation is fundamental to personalized medicine. Yet interpreting complex phenotype data, such as multi-compartment metabolomic profiles, in the context of genotype data for an individual is complicated by interactions within and between cells and remains an unresolved...... challenge. Here, we constructed multi-omic, data-driven, personalized whole-cell kinetic models of erythrocyte metabolism for 24 healthy individuals based on fasting-state plasma and erythrocyte metabolomics and whole-genome genotyping. We show that personalized kinetic rate constants, rather than...

  16. Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits

    DEFF Research Database (Denmark)

    Gebreyesus, Grum; Lund, Mogens Sandø; Buitenhuis, Albert Johannes

    2017-01-01

    Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci...... of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we...... developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls...

  17. Genome-Wide Expression Profiling of Five Mouse Models Identifies Similarities and Differences with Human Psoriasis

    Science.gov (United States)

    Swindell, William R.; Johnston, Andrew; Carbajal, Steve; Han, Gangwen; Wohn, Christian; Lu, Jun; Xing, Xianying; Nair, Rajan P.; Voorhees, John J.; Elder, James T.; Wang, Xiao-Jing; Sano, Shigetoshi; Prens, Errol P.; DiGiovanni, John; Pittelkow, Mark R.; Ward, Nicole L.; Gudjonsson, Johann E.

    2011-01-01

    Development of a suitable mouse model would facilitate the investigation of pathomechanisms underlying human psoriasis and would also assist in development of therapeutic treatments. However, while many psoriasis mouse models have been proposed, no single model recapitulates all features of the human disease, and standardized validation criteria for psoriasis mouse models have not been widely applied. In this study, whole-genome transcriptional profiling is used to compare gene expression patterns manifested by human psoriatic skin lesions with those that occur in five psoriasis mouse models (K5-Tie2, imiquimod, K14-AREG, K5-Stat3C and K5-TGFbeta1). While the cutaneous gene expression profiles associated with each mouse phenotype exhibited statistically significant similarity to the expression profile of psoriasis in humans, each model displayed distinctive sets of similarities and differences in comparison to human psoriasis. For all five models, correspondence to the human disease was strong with respect to genes involved in epidermal development and keratinization. Immune and inflammation-associated gene expression, in contrast, was more variable between models as compared to the human disease. These findings support the value of all five models as research tools, each with identifiable areas of convergence to and divergence from the human disease. Additionally, the approach used in this paper provides an objective and quantitative method for evaluation of proposed mouse models of psoriasis, which can be strategically applied in future studies to score strengths of mouse phenotypes relative to specific aspects of human psoriasis. PMID:21483750

  18. Barriers in Sustainable Knowledge Management Model in Education

    Directory of Open Access Journals (Sweden)

    Gratiela Dana BOCA

    2016-12-01

    Full Text Available The paper present a comprehensive model in education using the data base collected from 101 students from Turkey. The target group was students involved in academic life system. Results are used to design a model where education transfer of knowledge it is investigated in function of possible barriers as internal, external and knowledge management factors of influence in education selection and students vision for education development. As a conclusion, the evaluation of the barriers in sustainable knowledge management in education present a cross-educational model which seems to indicate its highly effective resource for environmental education focused on sustainability, and favours the development of knowledge, attitudes and future intentions of inspiring educational environment. The model can be useful on passing of knowledge from one generation to the next generation, managing succession and distributing the competencies and responsibilities to a repetitive change.

  19. Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

    Science.gov (United States)

    Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

    2017-01-01

    Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

  20. Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

    Science.gov (United States)

    Henson, Michael A

    2015-12-01

    Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

  1. Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

    Directory of Open Access Journals (Sweden)

    Leonardo de Azevedo Peixoto

    Full Text Available Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY and the weight of 100 seeds (W100S using restricted maximum likelihood (REML; to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

  2. An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies.

    Directory of Open Access Journals (Sweden)

    Wesley K Thompson

    2015-12-01

    Full Text Available Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD and the other for schizophrenia (SZ. A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the

  3. An Empirical Bayes Mixture Model for Effect Size Distributions in Genome-Wide Association Studies.

    Science.gov (United States)

    Thompson, Wesley K; Wang, Yunpeng; Schork, Andrew J; Witoelar, Aree; Zuber, Verena; Xu, Shujing; Werge, Thomas; Holland, Dominic; Andreassen, Ole A; Dale, Anders M

    2015-12-01

    Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD) on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the implications of

  4. Ice Sheet System Model as Educational Entertainment

    Science.gov (United States)

    Perez, G.

    2013-12-01

    Understanding the importance of polar ice sheets and their role in the evolution of Sea Level Rise (SLR), as well as Climate Change, is of paramount importance for policy makers as well as the public and schools at large. For example, polar ice sheets and glaciers currently account for 1/3 of the SLR signal, a ratio that will increase in the near to long-term future, which has tremendous societal ramifications. Consequently, it is important to increase awareness about our changing planet. In our increasingly digital society, mobile and web applications are burgeoning venues for such outreach. The Ice Sheet System Model (ISSM) is a software that was developed at the Jet Propulsion Laboratory/CalTech/NASA, in collaboration with University of California Irvine (UCI), with the goal of better understanding the evolution of polar ice sheets. It is a state-of-the-art framework, which relies on higher-end cluster-computing to address some of the aforementioned challenges. In addition, it is a flexible framework that can be deployed on any hardware; in particular, on mobile platforms such as Android or iOS smart phones. Here, we look at how the ISSM development team managed to port their model to these platforms, what the implications are for improving how scientists disseminate their results, and how a broader audience may familiarize themselves with running complex climate models in simplified scenarios which are highly educational and entertaining in content. We also look at the future plans toward a web portal fully integrated with mobile technologies to deliver the best content to the public, and to provide educational plans/lessons that can be used in grades K-12 as well as collegiate under-graduate and graduate programs.

  5. Modeling student success in engineering education

    Science.gov (United States)

    Jin, Qu

    student's first year of college was about a half of a grade point for both models. The predictors of retention and cumulative GPA while being similar differ in that high school academic metrics play a more important role in predicting cumulative GPA with the affective measures playing a more important role in predicting retention. In the last investigation, multi-outcome neural network models were used to understand and to predict engineering students' retention, GPA, and graduation from entry to departure. The participants were more than 4000 engineering students (cohort years 2004 - 2006) enrolled in a large Midwestern university. Different patterns of important predictors were identified for GPA, retention, and graduation. Overall, this research explores the feasibility of using modeling to enhance a student's educational experience in engineering. Student success modeling was used to identify the most important cognitive and affective predictors for a student's first calculus course retention, GPA, and graduation. The results suggest that the statistical modeling methods have great potential to assist decision making and help ensure student success in engineering education.

  6. Dealing with selection bias in educational transition models

    DEFF Research Database (Denmark)

    Holm, Anders; Jæger, Mads Meier

    2011-01-01

    This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational tr...... account for selection on unobserved variables and high-quality data are both required in order to estimate credible educational transition models.......This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational...... transitions to be correlated across transitions. We use simulated and real data to illustrate how the BPSM improves on the traditional Mare model in terms of correcting for selection bias and providing credible estimates of the effect of family background on educational success. We conclude that models which...

  7. BUSINESS MODEL INNOVATION IN NIGERIAN HIGHER EDUCATION INSTITUTIONS

    OpenAIRE

    Nonso Ochinanwata; Patrick Oseloka Ezepue

    2017-01-01

    This paper explores business model innovation that aims to innovate the Nigerian higher education sector. A focus group and semi-structured interviews among higher education Nigerian academics, students and graduates are used to explore the new business model for Nigerian higher education. The study found that, to achieve efficient and effective innovation, Nigerian higher education institutions need to collaborate with industry, professionals and other stakeholders, such as company managemen...

  8. Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

    Science.gov (United States)

    Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

    2017-07-01

    High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

  9. Public health and valorization of genome-based technologies: a new model.

    Science.gov (United States)

    Lal, Jonathan A; Schulte In den Bäumen, Tobias; Morré, Servaas A; Brand, Angela

    2011-12-05

    The success rate of timely translation of genome-based technologies to commercially feasible products/services with applicability in health care systems is significantly low. We identified both industry and scientists neglect health policy aspects when commercializing their technology, more specifically, Public Health Assessment Tools (PHAT) and early on involvement of decision makers through which market authorization and reimbursements are dependent. While Technology Transfer (TT) aims to facilitate translation of ideas into products, Health Technology Assessment, one component of PHAT, for example, facilitates translation of products/processes into healthcare services and eventually comes up with recommendations for decision makers. We aim to propose a new model of valorization to optimize integration of genome-based technologies into the healthcare system. The method used to develop our model is an adapted version of the Fish Trap Model and the Basic Design Cycle. We found although different, similarities exist between TT and PHAT. Realizing the potential of being mutually beneficial justified our proposal of their relative parallel initiation. We observed that the Public Health Genomics Wheel should be included in this relative parallel activity to ensure all societal/policy aspects are dealt with preemptively by both stakeholders. On further analysis, we found out this whole process is dependent on the Value of Information. As a result, we present our LAL (Learning Adapting Leveling) model which proposes, based on market demand; TT and PHAT by consultation/bi-lateral communication should advocate for relevant technologies. This can be achieved by public-private partnerships (PPPs). These widely defined PPPs create the innovation network which is a developing, consultative/collaborative-networking platform between TT and PHAT. This network has iterations and requires learning, assimilating and using knowledge developed and is called absorption capacity. We

  10. Genome association study through nonlinear mixed models revealed new candidate genes for pig growth curves

    Directory of Open Access Journals (Sweden)

    Fabyano Fonseca e Silva

    Full Text Available ABSTRACT: Genome association analyses have been successful in identifying quantitative trait loci (QTLs for pig body weights measured at a single age. However, when considering the whole weight trajectories over time in the context of genome association analyses, it is important to look at the markers that affect growth curve parameters. The easiest way to consider them is via the two-step method, in which the growth curve parameters and marker effects are estimated separately, thereby resulting in a reduction of the statistical power and the precision of estimates. One efficient solution is to adopt nonlinear mixed models (NMM, which enables a joint modeling of the individual growth curves and marker effects. Our aim was to propose a genome association analysis for growth curves in pigs based on NMM as well as to compare it with the traditional two-step method. In addition, we also aimed to identify the nearest candidate genes related to significant SNP (single nucleotide polymorphism markers. The NMM presented a higher number of significant SNPs for adult weight (A and maturity rate (K, and provided a direct way to test SNP significance simultaneously for both the A and K parameters. Furthermore, all significant SNPs from the two-step method were also reported in the NMM analysis. The ontology of the three candidate genes (SH3BGRL2, MAPK14, and MYL9 derived from significant SNPs (simultaneously affecting A and K allows us to make inferences with regards to their contribution to the pig growth process in the population studied.

  11. Modeling structure of G protein-coupled receptors in huan genome

    KAUST Repository

    Zhang, Yang

    2016-01-26

    G protein-coupled receptors (or GPCRs) are integral transmembrane proteins responsible to various cellular signal transductions. Human GPCR proteins are encoded by 5% of human genes but account for the targets of 40% of the FDA approved drugs. Due to difficulties in crystallization, experimental structure determination remains extremely difficult for human GPCRs, which have been a major barrier in modern structure-based drug discovery. We proposed a new hybrid protocol, GPCR-I-TASSER, to construct GPCR structure models by integrating experimental mutagenesis data with ab initio transmembrane-helix assembly simulations, assisted by the predicted transmembrane-helix interaction networks. The method was tested in recent community-wide GPCRDock experiments and constructed models with a root mean square deviation 1.26 Å for Dopamine-3 and 2.08 Å for Chemokine-4 receptors in the transmembrane domain regions, which were significantly closer to the native than the best templates available in the PDB. GPCR-I-TASSER has been applied to model all 1,026 putative GPCRs in the human genome, where 923 are found to have correct folds based on the confidence score analysis and mutagenesis data comparison. The successfully modeled GPCRs contain many pharmaceutically important families that do not have previously solved structures, including Trace amine, Prostanoids, Releasing hormones, Melanocortins, Vasopressin and Neuropeptide Y receptors. All the human GPCR models have been made publicly available through the GPCR-HGmod database at http://zhanglab.ccmb.med.umich.edu/GPCR-HGmod/ The results demonstrate new progress on genome-wide structure modeling of transmembrane proteins which should bring useful impact on the effort of GPCR-targeted drug discovery.

  12. A Model Collaborative Platform for Geoscience Education

    Science.gov (United States)

    Fox, S.; Manduca, C. A.; Iverson, E. A.

    2012-12-01

    generated author profiles highlight the contributions an individual has made through any of the projects with an option for customization by the author. An overarching portal site provides a unified view of resources within this diverse set of geoscience education projects. The SERC CMS provides a common platform upon which individual projects can build their own identities, while allowing cross-project pollination and synergies to be realized without significant extra investment by each project. This is a sustainable model for a collaborative platform that takes advantage of the energy and resources of individual projects to advance larger community goals.

  13. Software engineering the mixed model for genome-wide association studies on large samples.

    Science.gov (United States)

    Zhang, Zhiwu; Buckler, Edward S; Casstevens, Terry M; Bradbury, Peter J

    2009-11-01

    Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample size and number of markers used for GWAS is increasing dramatically, resulting in greater statistical power to detect those associations. The use of mixed models with increasingly large data sets depends on the availability of software for analyzing those models. While multiple software packages implement the mixed model method, no single package provides the best combination of fast computation, ability to handle large samples, flexible modeling and ease of use. Key elements of association analysis with mixed models are reviewed, including modeling phenotype-genotype associations using mixed models, population stratification, kinship and its estimation, variance component estimation, use of best linear unbiased predictors or residuals in place of raw phenotype, improving efficiency and software-user interaction. The available software packages are evaluated, and suggestions made for future software development.

  14. Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata.

    Science.gov (United States)

    Leempoel, Kevin; Parisod, Christian; Geiser, Céline; Joost, Stéphane

    2018-02-01

    Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine-scale models to evaluate environmental heterogeneity may help detecting adaptation to micro-habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata . The two gene pools identified, experiencing limited gene flow along a 1-km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine-scale topography. Using a large panel of DEM-derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high-resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.

  15. Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.

    Science.gov (United States)

    Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S

    2013-05-01

    Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Genome-scale metabolic models applied to human health and disease.

    Science.gov (United States)

    Cook, Daniel J; Nielsen, Jens

    2017-11-01

    Advances in genome sequencing, high throughput measurement of gene and protein expression levels, data accessibility, and computational power have allowed genome-scale metabolic models (GEMs) to become a useful tool for understanding metabolic alterations associated with many different diseases. Despite the proven utility of GEMs, researchers confront multiple challenges in the use of GEMs, their application to human health and disease, and their construction and simulation in an organ-specific and disease-specific manner. Several approaches that researchers are taking to address these challenges include using proteomic and transcriptomic-informed methods to build GEMs for individual organs, diseases, and patients and using constraints on model behavior during simulation to match observed metabolic fluxes. We review the challenges facing researchers in the use of GEMs, review the approaches used to address these challenges, and describe advances that are on the horizon and could lead to a better understanding of human metabolism. WIREs Syst Biol Med 2017, 9:e1393. doi: 10.1002/wsbm.1393 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

  17. Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

    Science.gov (United States)

    Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

    2016-01-01

    Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic

  18. Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

    Directory of Open Access Journals (Sweden)

    Shiori Yabe

    Full Text Available Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS, which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the

  19. CGDM: collaborative genomic data model for molecular profiling data using NoSQL.

    Science.gov (United States)

    Wang, Shicai; Mares, Mihaela A; Guo, Yi-Ke

    2016-12-01

    High-throughput molecular profiling has greatly improved patient stratification and mechanistic understanding of diseases. With the increasing amount of data used in translational medicine studies in recent years, there is a need to improve the performance of data warehouses in terms of data retrieval and statistical processing. Both relational and Key Value models have been used for managing molecular profiling data. Key Value models such as SeqWare have been shown to be particularly advantageous in terms of query processing speed for large datasets. However, more improvement can be achieved, particularly through better indexing techniques of the Key Value models, taking advantage of the types of queries which are specific for the high-throughput molecular profiling data. In this article, we introduce a Collaborative Genomic Data Model (CGDM), aimed at significantly increasing the query processing speed for the main classes of queries on genomic databases. CGDM creates three Collaborative Global Clustering Index Tables (CGCITs) to solve the velocity and variety issues at the cost of limited extra volume. Several benchmarking experiments were carried out, comparing CGDM implemented on HBase to the traditional SQL data model (TDM) implemented on both HBase and MySQL Cluster, using large publicly available molecular profiling datasets taken from NCBI and HapMap. In the microarray case, CGDM on HBase performed up to 246 times faster than TDM on HBase and 7 times faster than TDM on MySQL Cluster. In single nucleotide polymorphism case, CGDM on HBase outperformed TDM on HBase by up to 351 times and TDM on MySQL Cluster by up to 9 times. The CGDM source code is available at https://github.com/evanswang/CGDM. y.guo@imperial.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  20. Assessment of Genetic Heterogeneity in Structured Plant Populations Using Multivariate Whole-Genome Regression Models.

    Science.gov (United States)

    Lehermeier, Christina; Schön, Chris-Carolin; de Los Campos, Gustavo

    2015-09-01

    Plant breeding populations exhibit varying levels of structure and admixture; these features are likely to induce heterogeneity of marker effects across subpopulations. Traditionally, structure has been dealt with as a potential confounder, and various methods exist to "correct" for population stratification. However, these methods induce a mean correction that does not account for heterogeneity of marker effects. The animal breeding literature offers a few recent studies that consider modeling genetic heterogeneity in multibreed data, using multivariate models. However, these methods have received little attention in plant breeding where population structure can have different forms. In this article we address the problem of analyzing data from heterogeneous plant breeding populations, using three approaches: (a) a model that ignores population structure [A-genome-based best linear unbiased prediction (A-GBLUP)], (b) a stratified (i.e., within-group) analysis (W-GBLUP), and (c) a multivariate approach that uses multigroup data and accounts for heterogeneity (MG-GBLUP). The performance of the three models was assessed on three different data sets: a diversity panel of rice (Oryza sativa), a maize (Zea mays L.) half-sib panel, and a wheat (Triticum aestivum L.) data set that originated from plant breeding programs. The estimated genomic correlations between subpopulations varied from null to moderate, depending on the genetic distance between subpopulations and traits. Our assessment of prediction accuracy features cases where ignoring population structure leads to a parsimonious more powerful model as well as others where the multivariate and stratified approaches have higher predictive power. In general, the multivariate approach appeared slightly more robust than either the A- or the W-GBLUP. Copyright © 2015 by the Genetics Society of America.

  1. Dynamics in Higher Education Politics: A Theoretical Model

    Science.gov (United States)

    Kauko, Jaakko

    2013-01-01

    This article presents a model for analysing dynamics in higher education politics (DHEP). Theoretically the model draws on the conceptual history of political contingency, agenda-setting theories and previous research on higher education dynamics. According to the model, socio-historical complexity can best be analysed along two dimensions: the…

  2. Quality Assurance Model for Digital Adult Education Materials

    Science.gov (United States)

    Dimou, Helen; Kameas, Achilles

    2016-01-01

    Purpose: This paper aims to present a model for the quality assurance of digital educational material that is appropriate for adult education. The proposed model adopts the software quality standard ISO/IEC 9126 and takes into account adult learning theories, Bloom's taxonomy of learning objectives and two instructional design models: Kolb's model…

  3. A Model of Comparative Ethics Education for Social Workers

    Science.gov (United States)

    Pugh, Greg L.

    2017-01-01

    Social work ethics education models have not effectively engaged social workers in practice in formal ethical reasoning processes, potentially allowing personal bias to affect ethical decisions. Using two of the primary ethical models from medicine, a new social work ethics model for education and practical application is proposed. The strengths…

  4. Small RNA pathways and diversity in model legumes: lessons from genomics.

    Directory of Open Access Journals (Sweden)

    Pilar eBustos-Sanmamed

    2013-07-01

    Full Text Available Small non coding RNAs (smRNA participate in the regulation of development, cell differentiation, adaptation to environmental constraints and defense responses in plants. They negatively regulate gene expression by degrading specific mRNA targets, repressing their translation or modifying chromatin conformation through homologous interaction with target loci. MicroRNAs (miRNA and short-interfering RNAs (siRNA are generated from long double stranded RNA (dsRNA that are cleaved into 20- to 24-nucleotide dsRNAs by RNase III proteins called DICERs (DCL. One strand of the duplex is then loaded onto effective complexes containing different ARGONAUTE (AGO proteins. In this review, we explored smRNA diversity in model legumes and compiled available data from miRBAse, the miRNA database, and from 22 reports of smRNA deep sequencing or miRNA identification genome-wide in Medicago truncatula, Glycine max and Lotus japonicus. In addition to conserved miRNAs present in other plant species, 229, 179 and 35 novel miRNA families were identified respectively in these 3 legumes, among which several seems legume-specific. New potential functions of several miRNAs in the legume-specific nodulation process are discussed. Furthermore, a new category of siRNA, the phased siRNAs, which seems to mainly regulate disease-resistance genes, was recently discovered in legumes. Despite that the genome sequence of model legumes are not yet fully completed, further analysis was performed by database mining of gene families and protein characteristics of DCLs and AGOs in these genomes. Although most components of the smRNA pathways are conserved, identifiable homologs of key smRNA players from non-legumes could not yet be detected in M. truncatula available genomic and expressed sequence databases. In addition, an important gene diversification was observed in the three legumes. Functional significance of these variant isoforms may reflect peculiarities of smRNA biogenesis in

  5. A Quantitative Genomic Approach for Analysis of Fitness and Stress Related Traits in a Drosophila melanogaster Model Population

    Directory of Open Access Journals (Sweden)

    Palle Duun Rohde

    2016-01-01

    Full Text Available The ability of natural populations to withstand environmental stresses relies partly on their adaptive ability. In this study, we used a subset of the Drosophila Genetic Reference Panel, a population of inbred, genome-sequenced lines derived from a natural population of Drosophila melanogaster, to investigate whether this population harbors genetic variation for a set of stress resistance and life history traits. Using a genomic approach, we found substantial genetic variation for metabolic rate, heat stress resistance, expression of a major heat shock protein, and egg-to-adult viability investigated at a benign and a higher stressful temperature. This suggests that these traits will be able to evolve. In addition, we outline an approach to conduct pathway associations based on genomic linear models, which has potential to identify adaptive genes and pathways, and therefore can be a valuable tool in conservation genomics.

  6. Anticipation of Personal Genomics Data Enhances Interest and Learning Environment in Genomics and Molecular Biology Undergraduate Courses.

    Science.gov (United States)

    Weber, K Scott; Jensen, Jamie L; Johnson, Steven M

    2015-01-01

    An important discussion at colleges is centered on determining more effective models for teaching undergraduates. As personalized genomics has become more common, we hypothesized it could be a valuable tool to make science education more hands on, personal, and engaging for college undergraduates. We hypothesized that providing students with personal genome testing kits would enhance the learning experience of students in two undergraduate courses at Brigham Young University: Advanced Molecular Biology and Genomics. These courses have an emphasis on personal genomics the last two weeks of the semester. Students taking these courses were given the option to receive personal genomics kits in 2014, whereas in 2015 they were not. Students sent their personal genomics samples in on their own and received the data after the course ended. We surveyed students in these courses before and after the two-week emphasis on personal genomics to collect data on whether anticipation of obtaining their own personal genomic data impacted undergraduate student learning. We also tested to see if specific personal genomic assignments improved the learning experience by analyzing the data from the undergraduate students who completed both the pre- and post-course surveys. Anticipation of personal genomic data significantly enhanced student interest and the learning environment based on the time students spent researching personal genomic material and their self-reported attitudes compared to those who did not anticipate getting their own data. Personal genomics homework assignments significantly enhanced the undergraduate student interest and learning based on the same criteria and a personal genomics quiz. We found that for the undergraduate students in both molecular biology and genomics courses, incorporation of personal genomic testing can be an effective educational tool in undergraduate science education.

  7. Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

    Science.gov (United States)

    Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

    2012-12-01

    In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

  8. The Genome-Based Metabolic Systems Engineering to Boost Levan Production in a Halophilic Bacterial Model.

    Science.gov (United States)

    Aydin, Busra; Ozer, Tugba; Oner, Ebru Toksoy; Arga, Kazim Yalcin

    2018-03-01

    Metabolic systems engineering is being used to redirect microbial metabolism for the overproduction of chemicals of interest with the aim of transforming microbial hosts into cellular factories. In this study, a genome-based metabolic systems engineering approach was designed and performed to improve biopolymer biosynthesis capability of a moderately halophilic bacterium Halomonas smyrnensis AAD6 T producing levan, which is a fructose homopolymer with many potential uses in various industries and medicine. For this purpose, the genome-scale metabolic model for AAD6 T was used to characterize the metabolic resource allocation, specifically to design metabolic engineering strategies for engineered bacteria with enhanced levan production capability. Simulations were performed in silico to determine optimal gene knockout strategies to develop new strains with enhanced levan production capability. The majority of the gene knockout strategies emphasized the vital role of the fructose uptake mechanism, and pointed out the fructose-specific phosphotransferase system (PTS fru ) as the most promising target for further metabolic engineering studies. Therefore, the PTS fru of AAD6 T was restructured with insertional mutagenesis and triparental mating techniques to construct a novel, engineered H. smyrnensis strain, BMA14. Fermentation experiments were carried out to demonstrate the high efficiency of the mutant strain BMA14 in terms of final levan concentration, sucrose consumption rate, and sucrose conversion efficiency, when compared to the AAD6 T . The genome-based metabolic systems engineering approach presented in this study might be considered an efficient framework to redirect microbial metabolism for the overproduction of chemicals of interest, and the novel strain BMA14 might be considered a potential microbial cell factory for further studies aimed to design levan production processes with lower production costs.

  9. Brachypodium distachyon. A New Model System for Functional Genomics in Grasses1

    Science.gov (United States)

    Draper, John; Mur, Luis A.J.; Jenkins, Glyn; Ghosh-Biswas, Gadab C.; Bablak, Pauline; Hasterok, Robert; Routledge, Andrew P.M.

    2001-01-01

    A new model for grass functional genomics is described based on Brachypodium distachyon, which in the evolution of the Pooideae diverged just prior to the clade of “core pooid” genera that contain the majority of important temperate cereals and forage grasses. Diploid ecotypes of B. distachyon (2n = 10) have five easily distinguishable chromosomes that display high levels of chiasma formation at meiosis. The B. distachyon nuclear genome was indistinguishable in size from that of Arabidopsis, making it the simplest genome described in grasses to date. B. distachyon is a self-fertile, inbreeding annual with a life cycle of less than 4 months. These features, coupled with its small size (approximately 20 cm at maturity), lack of seed-head shatter, and undemanding growth requirements should make it amenable to high-throughput genetics and mutant screens. Immature embryos exhibited a high capacity for plant regeneration via somatic embryogenesis. Regenerated plants display very low levels of albinism and have normal fertility. A simple transformation system has been developed based on microprojectile bombardment of embryogenic callus and hygromycin selection. Selected B. distachyon ecotypes were resistant to all tested cereal-adapted Blumeria graminis species and cereal brown rusts (Puccinia reconditia). In contrast, different ecotypes displayed resistance or disease symptoms following challenge with the rice blast pathogen (Magnaporthe grisea) and wheat/barley yellow stripe rusts (Puccinia striformis). Despite its small stature, B. distachyon has large seeds that should prove useful for studies on grain filling. Such biological characteristics represent important traits for study in temperate cereals. PMID:11743099

  10. Genome Sequencing and Comparative Transcriptomics of the Model Entomopathogenic Fungi Metarhizium anisopliae and M. acridum

    Science.gov (United States)

    Shang, Yanfang; Duan, Zhibing; Hu, Xiao; Xie, Xue-Qin; Zhou, Gang; Peng, Guoxiong; Luo, Zhibing; Huang, Wei; Wang, Bing; Fang, Weiguo; Wang, Sibao; Zhong, Yi; Ma, Li-Jun; St. Leger, Raymond J.; Zhao, Guo-Ping; Pei, Yan; Feng, Ming-Guang; Xia, Yuxian; Wang, Chengshu

    2011-01-01

    Metarhizium spp. are being used as environmentally friendly alternatives to chemical insecticides, as model systems for studying insect-fungus interactions, and as a resource of genes for biotechnology. We present a comparative analysis of the genome sequences of the broad-spectrum insect pathogen Metarhizium anisopliae and the acridid-specific M. acridum. Whole-genome analyses indicate that the genome structures of these two species are highly syntenic and suggest that the genus Metarhizium evolved from plant endophytes or pathogens. Both M. anisopliae and M. acridum have a strikingly larger proportion of genes encoding secreted proteins than other fungi, while ∼30% of these have no functionally characterized homologs, suggesting hitherto unsuspected interactions between fungal pathogens and insects. The analysis of transposase genes provided evidence of repeat-induced point mutations occurring in M. acridum but not in M. anisopliae. With the help of pathogen-host interaction gene database, ∼16% of Metarhizium genes were identified that are similar to experimentally verified genes involved in pathogenicity in other fungi, particularly plant pathogens. However, relative to M. acridum, M. anisopliae has evolved with many expanded gene families of proteases, chitinases, cytochrome P450s, polyketide synthases, and nonribosomal peptide synthetases for cuticle-degradation, detoxification, and toxin biosynthesis that may facilitate its ability to adapt to heterogenous environments. Transcriptional analysis of both fungi during early infection processes provided further insights into the genes and pathways involved in infectivity and specificity. Of particular note, M. acridum transcribed distinct G-protein coupled receptors on cuticles from locusts (the natural hosts) and cockroaches, whereas M. anisopliae transcribed the same receptor on both hosts. This study will facilitate the identification of virulence genes and the development of improved biocontrol strains

  11. Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation.

    Directory of Open Access Journals (Sweden)

    Frank Technow

    Full Text Available Genomic selection, enabled by whole genome prediction (WGP methods, is revolutionizing plant breeding. Existing WGP methods have been shown to deliver accurate predictions in the most common settings, such as prediction of across environment performance for traits with additive gene effects. However, prediction of traits with non-additive gene effects and prediction of genotype by environment interaction (G×E, continues to be challenging. Previous attempts to increase prediction accuracy for these particularly difficult tasks employed prediction methods that are purely statistical in nature. Augmenting the statistical methods with biological knowledge has been largely overlooked thus far. Crop growth models (CGMs attempt to represent the impact of functional relationships between plant physiology and the environment in the formation of yield and similar output traits of interest. Thus, they can explain the impact of G×E and certain types of non-additive gene effects on the expressed phenotype. Approximate Bayesian computation (ABC, a novel and powerful computational procedure, allows the incorporation of CGMs directly into the estimation of whole genome marker effects in WGP. Here we provide a proof of concept study for this novel approach and demonstrate its use with synthetic data sets. We show that this novel approach can be considerably more accurate than the benchmark WGP method GBLUP in predicting performance in environments represented in the estimation set as well as in previously unobserved environments for traits determined by non-additive gene effects. We conclude that this proof of concept demonstrates that using ABC for incorporating biological knowledge in the form of CGMs into WGP is a very promising and novel approach to improving prediction accuracy for some of the most challenging scenarios in plant breeding and applied genetics.

  12. Predicting effects of structural stress in a genome-reduced model bacterial metabolism

    Science.gov (United States)

    Güell, Oriol; Sagués, Francesc; Serrano, M. Ángeles

    2012-08-01

    Mycoplasma pneumoniae is a human pathogen recently proposed as a genome-reduced model for bacterial systems biology. Here, we study the response of its metabolic network to different forms of structural stress, including removal of individual and pairs of reactions and knockout of genes and clusters of co-expressed genes. Our results reveal a network architecture as robust as that of other model bacteria regarding multiple failures, although less robust against individual reaction inactivation. Interestingly, metabolite motifs associated to reactions can predict the propagation of inactivation cascades and damage amplification effects arising in double knockouts. We also detect a significant correlation between gene essentiality and damages produced by single gene knockouts, and find that genes controlling high-damage reactions tend to be expressed independently of each other, a functional switch mechanism that, simultaneously, acts as a genetic firewall to protect metabolism. Prediction of failure propagation is crucial for metabolic engineering or disease treatment.

  13. Combinations of chromosome transfer and genome editing for the development of cell/animal models of human disease and humanized animal models.

    Science.gov (United States)

    Uno, Narumi; Abe, Satoshi; Oshimura, Mitsuo; Kazuki, Yasuhiro

    2018-02-01

    Chromosome transfer technology, including chromosome modification, enables the introduction of Mb-sized or multiple genes to desired cells or animals. This technology has allowed innovative developments to be made for models of human disease and humanized animals, including Down syndrome model mice and humanized transchromosomic (Tc) immunoglobulin mice. Genome editing techniques are developing rapidly, and permit modifications such as gene knockout and knockin to be performed in various cell lines and animals. This review summarizes chromosome transfer-related technologies and the combined technologies of chromosome transfer and genome editing mainly for the production of cell/animal models of human disease and humanized animal models. Specifically, these include: (1) chromosome modification with genome editing in Chinese hamster ovary cells and mouse A9 cells for efficient transfer to desired cell types; (2) single-nucleotide polymorphism modification in humanized Tc mice with genome editing; and (3) generation of a disease model of Down syndrome-associated hematopoiesis abnormalities by the transfer of human chromosome 21 to normal human embryonic stem cells and the induction of mutation(s) in the endogenous gene(s) with genome editing. These combinations of chromosome transfer and genome editing open up new avenues for drug development and therapy as well as for basic research.

  14. Postgraduate education for nurses: the Middlesex model.

    Science.gov (United States)

    Caldwell, K

    2001-04-01

    Nurse education has been subject to many changes and much debate and criticism over recent years. What has become increasingly evident is that with the changing nature of nursing within society, nursing curricula have to be more flexible and dynamic if they are to meet a multiplicity of needs. There is also a need to recognize that many levels of curricula will be required to prepare the nurses of the future. At Middlesex University the development of specialist practice programmes at postgraduate diploma level, and preparation of nurses for a higher level of practice at masters level has required the development of a new curriculum model which allows both the individualization of academic programmes to meet the needs of nurses, their clients and the organization in which they work, and the integration of development and learning through practice. This model is built on the results of an evaluation of an existing postgraduate programme in interprofessional health care. Key features of the curriculum development include a structured collaboration between student, practice mentor and academic supervisor, and the use of a professional development portfolio to individualize the academic programme and facilitate autonomous learning. Copyright 2001 Harcourt Publishers Ltd.

  15. Warburg effect and translocation-induced genomic instability: two yeast models for cancer cells

    International Nuclear Information System (INIS)

    Tosato, Valentina; Grüning, Nana-Maria; Breitenbach, Michael; Arnak, Remigiusz; Ralser, Markus; Bruschi, Carlo V.

    2013-01-01

    Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression (i) the activity of pyruvate kinase (PK), which recapitulates metabolic features of cancer cells, including the Warburg effect, and (ii) chromosome bridge-induced translocation (BIT) mimiking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect), and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, PK, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and post-translational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants (“translocants”), between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the BIT system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.

  16. WARBURG EFFECT AND TRANSLOCATION-INDUCED GENOMIC INSTABILITY: TWO YEAST MODELS FOR CANCER CELLS

    Directory of Open Access Journals (Sweden)

    Valentina eTosato

    2013-01-01

    Full Text Available Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression i the activity of pyruvate kinase (PK, which recapitulates metabolic features of cancer cells, including the Warburg effect, and ii Bridge-Induced chromosome Translocation (BIT mimicking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect, and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, pyruvate kinase, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and posttranslational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants (translocants, between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the Bridge-Induced Translocation system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.

  17. Network thermodynamic curation of human and yeast genome-scale metabolic models.

    Science.gov (United States)

    Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

    2014-07-15

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  18. Warburg effect and translocation-induced genomic instability: two yeast models for cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Tosato, Valentina [International Centre for Genetic Engineering and Biotechnology, Trieste (Italy); Grüning, Nana-Maria [Cambridge System Biology Center, Department of Biochemistry, University of Cambridge, Cambridge (United Kingdom); Breitenbach, Michael [Division of Genetics, Department of Cell Biology, University of Salzburg, Salzburg (Austria); Arnak, Remigiusz [International Centre for Genetic Engineering and Biotechnology, Trieste (Italy); Ralser, Markus [Cambridge System Biology Center, Department of Biochemistry, University of Cambridge, Cambridge (United Kingdom); Bruschi, Carlo V., E-mail: bruschi@icgeb.org [International Centre for Genetic Engineering and Biotechnology, Trieste (Italy)

    2013-01-18

    Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression (i) the activity of pyruvate kinase (PK), which recapitulates metabolic features of cancer cells, including the Warburg effect, and (ii) chromosome bridge-induced translocation (BIT) mimiking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect), and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, PK, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and post-translational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants (“translocants”), between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the BIT system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.

  19. The I3E Model for Embedding Education for Sustainability within Higher Education Institutions

    Science.gov (United States)

    Cebrián, Gisela

    2018-01-01

    This paper presents an evidence-based model (the I3E model) for embedding education for sustainability (EfS) within a higher education institution. This model emerged from a doctoral research that examined organisational learning and change processes at the University of Southampton to build EfS into the university curriculum. The researcher aimed…

  20. Towards a more effective model for distance education

    NARCIS (Netherlands)

    Koper, Rob

    2014-01-01

    Reference: Koper, E.J.R. (2014). Towards a more effective model for distance education. e-Learning and Education. e-Learning and Education, 10. urn:nbn:de:0009-5-40105 http://eleed.campussource.de/archive/10/4010

  1. Business Models Associated with Distance Learning in Higher Education

    Science.gov (United States)

    Wang, Shouhong; Wang, Hai

    2017-01-01

    Textbook prices are continuously rising in higher education. This paper analyzes a business model which makes commercial textbooks more expensive, and explains why this issue tends to be more severe in the field of distance learning in higher education. It reports a case of adoption of open educational resources (OER) textbook for an online course…

  2. Building Bridges between Neuroscience, Cognition and Education with Predictive Modeling

    Science.gov (United States)

    Stringer, Steve; Tommerdahl, Jodi

    2015-01-01

    As the field of Mind, Brain, and Education seeks new ways to credibly bridge the gap between neuroscience, the cognitive sciences, and education, various connections are being developed and tested. This article presents a framework and offers examples of one approach, predictive modeling within a virtual educational system that can include…

  3. Levels of Interaction Provided by Online Distance Education Models

    Science.gov (United States)

    Alhih, Mohammed; Ossiannilsson, Ebba; Berigel, Muhammet

    2017-01-01

    Interaction plays a significant role to foster usability and quality in online education. It is one of the quality standard to reveal the evidence of practice in online distance education models. This research study aims to evaluate levels of interaction in the practices of distance education centres. It is aimed to provide online distance…

  4. Structure modeling of all identified G protein-coupled receptors in the human genome.

    Science.gov (United States)

    Zhang, Yang; Devries, Mark E; Skolnick, Jeffrey

    2006-02-01

    G protein-coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha) root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness

  5. Structure modeling of all identified G protein-coupled receptors in the human genome.

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2006-02-01

    Full Text Available G protein-coupled receptors (GPCRs, encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness

  6. Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing

    Directory of Open Access Journals (Sweden)

    María P. Cortés

    2017-12-01

    Full Text Available Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen’s biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.

  7. Features of genomic organization in a nucleotide-resolution molecular model of the Escherichia coli chromosome.

    Science.gov (United States)

    Hacker, William C; Li, Shuxiang; Elcock, Adrian H

    2017-07-27

    We describe structural models of the Escherichia coli chromosome in which the positions of all 4.6 million nucleotides of each DNA strand are resolved. Models consistent with two basic chromosomal orientations, differing in their positioning of the origin of replication, have been constructed. In both types of model, the chromosome is partitioned into plectoneme-abundant and plectoneme-free regions, with plectoneme lengths and branching patterns matching experimental distributions, and with spatial distributions of highly-transcribed chromosomal regions matching recent experimental measurements of the distribution of RNA polymerases. Physical analysis of the models indicates that the effective persistence length of the DNA and relative contributions of twist and writhe to the chromosome's negative supercoiling are in good correspondence with experimental estimates. The models exhibit characteristics similar to those of 'fractal globules,' and even the most genomically-distant parts of the chromosome can be physically connected, through paths combining linear diffusion and inter-segmental transfer, by an average of only ∼10 000 bp. Finally, macrodomain structures and the spatial distributions of co-expressed genes are analyzed: the latter are shown to depend strongly on the overall orientation of the chromosome. We anticipate that the models will prove useful in exploring other static and dynamic features of the bacterial chromosome. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Genomic prediction using subsampling

    OpenAIRE

    Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin

    2017-01-01

    Background Genome-wide assisted selection is a critical tool for the?genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each rou...

  9. Kinetic theory approach to modeling of cellular repair mechanisms under genome stress.

    Directory of Open Access Journals (Sweden)

    Jinpeng Qi

    Full Text Available Under acute perturbations from outer environment, a normal cell can trigger cellular self-defense mechanism in response to genome stress. To investigate the kinetics of cellular self-repair process at single cell level further, a model of DNA damage generating and repair is proposed under acute Ion Radiation (IR by using mathematical framework of kinetic theory of active particles (KTAP. Firstly, we focus on illustrating the profile of Cellular Repair System (CRS instituted by two sub-populations, each of which is made up of the active particles with different discrete states. Then, we implement the mathematical framework of cellular self-repair mechanism, and illustrate the dynamic processes of Double Strand Breaks (DSBs and Repair Protein (RP generating, DSB-protein complexes (DSBCs synthesizing, and toxins accumulating. Finally, we roughly analyze the capability of cellular self-repair mechanism, cellular activity of transferring DNA damage, and genome stability, especially the different fates of a certain cell before and after the time thresholds of IR perturbations that a cell can tolerate maximally under different IR perturbation circumstances.

  10. Kinetic theory approach to modeling of cellular repair mechanisms under genome stress.

    Science.gov (United States)

    Qi, Jinpeng; Ding, Yongsheng; Zhu, Ying; Wu, Yizhi

    2011-01-01

    Under acute perturbations from outer environment, a normal cell can trigger cellular self-defense mechanism in response to genome stress. To investigate the kinetics of cellular self-repair process at single cell level further, a model of DNA damage generating and repair is proposed under acute Ion Radiation (IR) by using mathematical framework of kinetic theory of active particles (KTAP). Firstly, we focus on illustrating the profile of Cellular Repair System (CRS) instituted by two sub-populations, each of which is made up of the active particles with different discrete states. Then, we implement the mathematical framework of cellular self-repair mechanism, and illustrate the dynamic processes of Double Strand Breaks (DSBs) and Repair Protein (RP) generating, DSB-protein complexes (DSBCs) synthesizing, and toxins accumulating. Finally, we roughly analyze the capability of cellular self-repair mechanism, cellular activity of transferring DNA damage, and genome stability, especially the different fates of a certain cell before and after the time thresholds of IR perturbations that a cell can tolerate maximally under different IR perturbation circumstances.

  11. The Sequences of 1504 Mutants in the Model Rice Variety Kitaake Facilitate Rapid Functional Genomic Studies.

    Science.gov (United States)

    Li, Guotian; Jain, Rashmi; Chern, Mawsheng; Pham, Nikki T; Martin, Joel A; Wei, Tong; Schackwitz, Wendy S; Lipzen, Anna M; Duong, Phat Q; Jones, Kyle C; Jiang, Liangrong; Ruan, Deling; Bauer, Diane; Peng, Yi; Barry, Kerrie W; Schmutz, Jeremy; Ronald, Pamela C

    2017-06-01

    The availability of a whole-genome sequenced mutant population and the cataloging of mutations of each line at a single-nucleotide resolution facilitate functional genomic analysis. To this end, we generated and sequenced a fast-neutron-induced mutant population in the model rice cultivar Kitaake ( Oryza sativa ssp japonica ), which completes its life cycle in 9 weeks. We sequenced 1504 mutant lines at 45-fold coverage and identified 91,513 mutations affecting 32,307 genes, i.e., 58% of all rice genes. We detected an average of 61 mutations per line. Mutation types include single-base substitutions, deletions, insertions, inversions, translocations, and tandem duplications. We observed a high proportion of loss-of-function mutations. We identified an inversion affecting a single gene as the causative mutation for the short-grain phenotype in one mutant line. This result reveals the usefulness of the resource for efficient, cost-effective identification of genes conferring specific phenotypes. To facilitate public access to this genetic resource, we established an open access database called KitBase that provides access to sequence data and seed stocks. This population complements other available mutant collections and gene-editing technologies. This work demonstrates how inexpensive next-generation sequencing can be applied to generate a high-density catalog of mutations. © 2017 American Society of Plant Biologists. All rights reserved.

  12. Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program

    Directory of Open Access Journals (Sweden)

    Elliot L. Heffner

    2011-03-01

    Full Text Available Genomic selection (GS uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotypes of lines from each cross before conducting GS. This will prolong the selection cycle and may result in lower gains per year than approaches that estimate marker-effects with multiple families from previous selection cycles. In this study, phenotypic selection (PS, conventional marker-assisted selection (MAS, and GS prediction accuracy were compared for 13 agronomic traits in a population of 374 winter wheat ( L. advanced-cycle breeding lines. A cross-validation approach that trained and validated prediction accuracy across years was used to evaluate effects of model selection, training population size, and marker density in the presence of genotype × environment interactions (G×E. The average prediction accuracies using GS were 28% greater than with MAS and were 95% as accurate as PS. For net merit, the average accuracy across six selection indices for GS was 14% greater than for PS. These results provide empirical evidence that multifamily GS could increase genetic gain per unit time and cost in plant breeding.

  13. The genome of Aiptasia, a sea anemone model for coral symbiosis

    KAUST Repository

    Baumgarten, Sebastian

    2015-08-31

    The most diverse marine ecosystems, coral reefs, depend upon a functional symbiosis between a cnidarian animal host (the coral) and intracellular photosynthetic dinoflagellate algae. The molecular and cellular mechanisms underlying this endosymbiosis are not well understood, in part because of the difficulties of experimental work with corals. The small sea anemone Aiptasia provides a tractable laboratory model for investigating these mechanisms. Here we report on the assembly and analysis of the Aiptasia genome, which will provide a foundation for future studies and has revealed several features that may be key to understanding the evolution and function of the endosymbiosis. These features include genomic rearrangements and taxonomically restricted genes that may be functionally related to the symbiosis, aspects of host dependence on alga-derived nutrients, a novel and expanded cnidarian-specific family of putative pattern-recognition receptors that might be involved in the animal–algal interactions, and extensive lineage-specific horizontal gene transfer. Extensive integration of genes of prokaryotic origin, including genes for antimicrobial peptides, presumably reflects an intimate association of the animal–algal pair also with its prokaryotic microbiome.

  14. MIPS plant genome information resources.

    Science.gov (United States)

    Spannagl, Manuel; Haberer, Georg; Ernst, Rebecca; Schoof, Heiko; Mayer, Klaus F X

    2007-01-01

    The Munich Institute for Protein Sequences (MIPS) has been involved in maintaining plant genome databases since the Arabidopsis thaliana genome project. Genome databases and analysis resources have focused on individual genomes and aim to provide flexible and maintainable data sets for model plant genomes as a backbone against which experimental data, for example from high-throughput functional genomics, can be organized and evaluated. In addition, model genomes also form a scaffold for comparative genomics, and much can be learned from genome-wide evolutionary studies.

  15. Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

    Science.gov (United States)

    Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

    2017-01-01

    The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

  16. Research on Educational Standards in German Science Education--Towards a Model of Student Competences

    Science.gov (United States)

    Kulgemeyer, Christoph; Schecker, Horst

    2014-01-01

    This paper gives an overview of research on modelling science competence in German science education. Since the first national German educational standards for physics, chemistry and biology education were released in 2004 research projects dealing with competences have become prominent strands. Most of this research is about the structure of…

  17. Using and Developing Measurement Instruments in Science Education: A Rasch Modeling Approach. Science & Engineering Education Sources

    Science.gov (United States)

    Liu, Xiufeng

    2010-01-01

    This book meets a demand in the science education community for a comprehensive and introductory measurement book in science education. It describes measurement instruments reported in refereed science education research journals, and introduces the Rasch modeling approach to developing measurement instruments in common science assessment domains,…

  18. DL-ADR: a novel deep learning model for classifying genomic variants into adverse drug reactions.

    Science.gov (United States)

    Liang, Zhaohui; Huang, Jimmy Xiangji; Zeng, Xing; Zhang, Gang

    2016-08-10

    Genomic variations are associated with the metabolism and the occurrence of adverse reactions of many therapeutic agents. The polymorphisms on over 2000 locations of cytochrome P450 enzymes (CYP) due to many factors such as ethnicity, mutations, and inheritance attribute to the diversity of response and side effects of various drugs. The associations of the single nucleotide polymorphisms (SNPs), the internal pharmacokinetic patterns and the vulnerability of specific adverse reactions become one of the research interests of pharmacogenomics. The conventional genomewide association studies (GWAS) mainly focuses on the relation of single or multiple SNPs to a specific risk factors which are a one-to-many relation. However, there are no robust methods to establish a many-to-many network which can combine the direct and indirect associations between multiple SNPs and a serial of events (e.g. adverse reactions, metabolic patterns, prognostic factors etc.). In this paper, we present a novel deep learning model based on generative stochastic networks and hidden Markov chain to classify the observed samples with SNPs on five loci of two genes (CYP2D6 and CYP1A2) respectively to the vulnerable population of 14 types of adverse reactions. A supervised deep learning model is proposed in this study. The revised generative stochastic networks (GSN) model with transited by the hidden Markov chain is used. The data of the training set are collected from clinical observation. The training set is composed of 83 observations of blood samples with the genotypes respectively on CYP2D6*2, *10, *14 and CYP1A2*1C, *1 F. The samples are genotyped by the polymerase chain reaction (PCR) method. A hidden Markov chain is used as the transition operator to simulate the probabilistic distribution. The model can perform learning at lower cost compared to the conventional maximal likelihood method because the transition distribution is conditional on the previous state of the hidden Markov

  19. THE MODEL OF LIFELONG EDUCATION IN A TECHNICAL UNIVERSITY AS A MULTILEVEL EDUCATIONAL COMPLEX

    Directory of Open Access Journals (Sweden)

    Svetlana V. Sergeyeva

    2016-06-01

    Full Text Available Introduction: the current leading trend of the educational development is characterised by its continuity. Institutions of higher education as multi-level educational complexes nurture favourable conditions for realisation of the strategy of lifelong education. Today a technical university offering training of future engineers is facing a topic issue of creating a multilevel educational complex. Materials and Methods: this paper is put together on the basis of modern Russian and foreign scientific literature about lifelong education. The authors used theoretical methods of scientific research: systemstructural analysis, synthesis, modeling, analysis and generalisations of concepts. Results: the paper presents a model of lifelong education developed by authors for a technical university as a multilevel educational complex. It is realised through a set of principles: multi-level and continuity, integration, conformity and quality, mobility, anticipation, openness, social partnership and feedback. In accordance with the purpose, objectives and principles, the content part of the model is formed. The syllabi following the described model are run in accordance with the training levels undertaken by a technical university as a multilevel educational complex. All syllabi are based on the gradual nature of their implementation. In this regard, the authors highlight three phases: diagnostic, constructive and transformative, assessing. Discussion and Conclusions: the expected result of the created model of lifelong education development in a technical university as a multilevel educational complex is presented by a graduate trained for effective professional activity, competitive, prepared and sought-after at the regional labour market.

  20. Modelling Mathematical Reasoning in Physics Education

    Science.gov (United States)

    Uhden, Olaf; Karam, Ricardo; Pietrocola, Maurício; Pospiech, Gesche

    2012-04-01

    Many findings from research as well as reports from teachers describe students' problem solving strategies as manipulation of formulas by rote. The resulting dissatisfaction with quantitative physical textbook problems seems to influence the attitude towards the role of mathematics in physics education in general. Mathematics is often seen as a tool for calculation which hinders a conceptual understanding of physical principles. However, the role of mathematics cannot be reduced to this technical aspect. Hence, instead of putting mathematics away we delve into the nature of physical science to reveal the strong conceptual relationship between mathematics and physics. Moreover, we suggest that, for both prospective teaching and further research, a focus on deeply exploring such interdependency can significantly improve the understanding of physics. To provide a suitable basis, we develop a new model which can be used for analysing different levels of mathematical reasoning within physics. It is also a guideline for shifting the attention from technical to structural mathematical skills while teaching physics. We demonstrate its applicability for analysing physical-mathematical reasoning processes with an example.

  1. Service Quality in Distance Education using the Gronroos Model

    OpenAIRE

    Hamid, Fazelina Sahul; Yip, Nick

    2016-01-01

    Demand for distance education programs have been increasing rapidly over the years. As a result, assessment of the quality of distance education programs has become a strategic issue that is very pertinent for program survival. This study uses Gronroos Model for assessing the service quality of the Malaysian distance education institutions. This model is chosen because it takes into account of the service delivery process and also service outcome. Our study confirms the multidimensional natur...

  2. The Sport Education Model: A Track and Field Unit Application

    Science.gov (United States)

    O'Neil, Kason; Krause, Jennifer M.

    2016-01-01

    Track and field is a traditional instructional unit often taught in secondary physical education settings due to its history, variety of events, and potential for student interest. This article provides an approach to teaching this unit using the sport education model (SEM) of instruction, which has traditionally been presented as a model for team…

  3. A Model for the Education of Gifted Learners in Lebanon

    Science.gov (United States)

    Sarouphim, Ketty M.

    2010-01-01

    The purpose of this paper is to present a model for developing a comprehensive system of education for gifted learners in Lebanon. The model consists of three phases and includes key elements for establishing gifted education in the country, such as raising community awareness, adopting valid identification measures, and developing effective…

  4. Sustainable Competitive Advantage for Educational Institutions: A Suggested Model.

    Science.gov (United States)

    Mazzarol, Tim; Soutar, Geoffrey Norman

    1999-01-01

    Outlines a model of factors critical to establishing and maintaining sustainable competitive advantage for education-services enterprises in international markets. The model, which combines industrial economics, management theory, and services marketing, seeks to explain the strategic decision-making environment in which the education exporter…

  5. The copepod Tigriopus: A promising marine model organism for ecotoxicology and environmental genomics

    Energy Technology Data Exchange (ETDEWEB)

    Raisuddin, Sheikh [Department of Chemistry and the National Research Lab of Marine Molecular and Environmental Bioscience, College of Natural Sciences, Hanyang University, Seoul 133-791 (Korea, Republic of); Kwok, Kevin W.H. [Swire Institute of Marine Science, Department of Ecology and Biodiversity, University of Hong Kong, Pokfulam, Hong Kong (China); Leung, Kenneth M.Y. [Swire Institute of Marine Science, Department of Ecology and Biodiversity, University of Hong Kong, Pokfulam, Hong Kong (China); Schlenk, Daniel [Department of Environmental Sciences, University of California, Riverside, CA 92521 (United States); Lee, Jae-Seong [Department of Chemistry and the National Research Lab of Marine Molecular and Environmental Bioscience, College of Natural Sciences, Hanyang University, Seoul 133-791 (Korea, Republic of)]. E-mail: jslee2@hanyang.ac.kr

    2007-07-20

    There is an increasing body of evidence to support the significant role of invertebrates in assessing impacts of environmental contaminants on marine ecosystems. Therefore, in recent years massive efforts have been directed to identify viable and ecologically relevant invertebrate toxicity testing models. Tigriopus, a harpacticoid copepod has a number of promising characteristics which make it a candidate worth consideration in such efforts. Tigriopus and other copepods are widely distributed and ecologically important organisms. Their position in marine food chains is very prominent, especially with regard to the transfer of energy. Copepods also play an important role in the transportation of aquatic pollutants across the food chains. In recent years there has been a phenomenal increase in the knowledge base of Tigriopus spp., particularly in the areas of their ecology, geophylogeny, genomics and their behavioural, biochemical and molecular responses following exposure to environmental stressors and chemicals. Sequences of a number of important marker genes have been studied in various Tigriopus spp., notably T. californicus and T. japonicus. These genes belong to normal biophysiological functions (e.g. electron transport system enzymes) as well as stress and toxic chemical exposure responses (heat shock protein 20, glutathione reductase, glutathione S-transferase). Recently, 40,740 expressed sequenced tags (ESTs) from T. japonicus, have been sequenced and of them, 5673 ESTs showed significant hits (E-value, >1.0E-05) to the red flour beetle Tribolium genome database. Metals and organic pollutants such as antifouling agents, pesticides, polycyclic aromatic hydrocarbons (PAH) and polychrlorinated biphenyls (PCB) have shown reproducible biological responses when tested in Tigriopus spp. Promising results have been obtained when Tigriopus was used for assessment of risk associated with exposure to endocrine-disrupting chemicals (EDCs). Application of environmental

  6. The copepod Tigriopus: A promising marine model organism for ecotoxicology and environmental genomics

    International Nuclear Information System (INIS)

    Raisuddin, Sheikh; Kwok, Kevin W.H.; Leung, Kenneth M.Y.; Schlenk, Daniel; Lee, Jae-Seong

    2007-01-01

    There is an increasing body of evidence to support the significant role of invertebrates in assessing impacts of environmental contaminants on marine ecosystems. Therefore, in recent years massive efforts have been directed to identify viable and ecologically relevant invertebrate toxicity testing models. Tigriopus, a harpacticoid copepod has a number of promising characteristics which make it a candidate worth consideration in such efforts. Tigriopus and other copepods are widely distributed and ecologically important organisms. Their position in marine food chains is very prominent, especially with regard to the transfer of energy. Copepods also play an important role in the transportation of aquatic pollutants across the food chains. In recent years there has been a phenomenal increase in the knowledge base of Tigriopus spp., particularly in the areas of their ecology, geophylogeny, genomics and their behavioural, biochemical and molecular responses following exposure to environmental stressors and chemicals. Sequences of a number of important marker genes have been studied in various Tigriopus spp., notably T. californicus and T. japonicus. These genes belong to normal biophysiological functions (e.g. electron transport system enzymes) as well as stress and toxic chemical exposure responses (heat shock protein 20, glutathione reductase, glutathione S-transferase). Recently, 40,740 expressed sequenced tags (ESTs) from T. japonicus, have been sequenced and of them, 5673 ESTs showed significant hits (E-value, >1.0E-05) to the red flour beetle Tribolium genome database. Metals and organic pollutants such as antifouling agents, pesticides, polycyclic aromatic hydrocarbons (PAH) and polychrlorinated biphenyls (PCB) have shown reproducible biological responses when tested in Tigriopus spp. Promising results have been obtained when Tigriopus was used for assessment of risk associated with exposure to endocrine-disrupting chemicals (EDCs). Application of environmental

  7. Genome-scale model guided design of Propionibacterium for enhanced propionic acid production.

    Science.gov (United States)

    Navone, Laura; McCubbin, Tim; Gonzalez-Garcia, Ricardo A; Nielsen, Lars K; Marcellin, Esteban

    2018-06-01

    Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp . shermanii and the pan- Propionibacterium genome-scale metabolic models (GEMs) to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp . shermanii , two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP), Zwf (glucose-6-phosphate 1-dehydrogenase) and Pgl (6-phosphogluconolactonase). Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK) and sodium-pumping methylmalonyl-CoA decarboxylase (MMD) was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in

  8. High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model.

    Directory of Open Access Journals (Sweden)

    Chiao-Ling Lo

    2016-08-01

    Full Text Available Investigations on the influence of nature vs. nurture on Alcoholism (Alcohol Use Disorder in human have yet to provide a clear view on potential genomic etiologies. To address this issue, we sequenced a replicated animal model system bidirectionally-selected for alcohol preference (AP. This model is uniquely suited to map genetic effects with high reproducibility, and resolution. The origin of the rat lines (an 8-way cross resulted in small haplotype blocks (HB with a corresponding high level of resolution. We sequenced DNAs from 40 samples (10 per line of each replicate to determine allele frequencies and HB. We achieved ~46X coverage per line and replicate. Excessive differentiation in the genomic architecture between lines, across replicates, termed signatures of selection (SS, were classified according to gene and region. We identified SS in 930 genes associated with AP. The majority (50% of the SS were confined to single gene regions, the greatest numbers of which were in promoters (284 and intronic regions (169 with the least in exon's (4, suggesting that differences in AP were primarily due to alterations in regulatory regions. We confirmed previously identified genes and found many new genes associated with AP. Of those newly identified genes, several demonstrated neuronal function involved in synaptic memory and reward behavior, e.g. ion channels (Kcnf1, Kcnn3, Scn5a, excitatory receptors (Grin2a, Gria3, Grip1, neurotransmitters (Pomc, and synapses (Snap29. This study not only reveals the polygenic architecture of AP, but also emphasizes the importance of regulatory elements, consistent with other complex traits.

  9. High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model.

    Science.gov (United States)

    Lo, Chiao-Ling; Lossie, Amy C; Liang, Tiebing; Liu, Yunlong; Xuei, Xiaoling; Lumeng, Lawrence; Zhou, Feng C; Muir, William M

    2016-08-01

    Investigations on the influence of nature vs. nurture on Alcoholism (Alcohol Use Disorder) in human have yet to provide a clear view on potential genomic etiologies. To address this issue, we sequenced a replicated animal model system bidirectionally-selected for alcohol preference (AP). This model is uniquely suited to map genetic effects with high reproducibility, and resolution. The origin of the rat lines (an 8-way cross) resulted in small haplotype blocks (HB) with a corresponding high level of resolution. We sequenced DNAs from 40 samples (10 per line of each replicate) to determine allele frequencies and HB. We achieved ~46X coverage per line and replicate. Excessive differentiation in the genomic architecture between lines, across replicates, termed signatures of selection (SS), were classified according to gene and region. We identified SS in 930 genes associated with AP. The majority (50%) of the SS were confined to single gene regions, the greatest numbers of which were in promoters (284) and intronic regions (169) with the least in exon's (4), suggesting that differences in AP were primarily due to alterations in regulatory regions. We confirmed previously identified genes and found many new genes associated with AP. Of those newly identified genes, several demonstrated neuronal function involved in synaptic memory and reward behavior, e.g. ion channels (Kcnf1, Kcnn3, Scn5a), excitatory receptors (Grin2a, Gria3, Grip1), neurotransmitters (Pomc), and synapses (Snap29). This study not only reveals the polygenic architecture of AP, but also emphasizes the importance of regulatory elements, consistent with other complex traits.

  10. A 'joint venture' model of recontacting in clinical genomics: challenges for responsible implementation.

    Science.gov (United States)

    Dheensa, Sandi; Carrieri, Daniele; Kelly, Susan; Clarke, Angus; Doheny, Shane; Turnpenny, Peter; Lucassen, Anneke

    2017-07-01

    Advances in genomics often lead healthcare professionals (HCPs) to learn new information, e.g., about reinterpreted variants that could have clinical significance for patients seen previously. A question arises of whether HCPs should recontact these former patients. We present some findings interrogating the views of patients (or parents of patients) with a rare or undiagnosed condition about how such recontacting might be organised ethically and practically. Forty-one interviews were analysed thematically. Participants suggested a 'joint venture' model in which efforts to recontact are shared with HCPs. Some proposed an ICT-approach involving an electronic health record that automatically alerts them to potentially relevant updates. The need for rigorous privacy controls and transparency about who could access their data was emphasised. Importantly, these findings highlight that the lack of clarity about recontacting is a symptom of a wider problem: the lack of necessary infrastructure to pool genomic data responsibly, to aggregate it with other health data, and to enable patients/parents to receive updates. We hope that our findings will instigate a debate about the way responsibilities for recontacting under any joint venture model could be allocated, as well as the limitations and normative implications of using ICT as a solution to this intractable problem. As a first step to delineating responsibilities in the clinical setting, we suggest HCPs should routinely discuss recontacting with patients/parents, including the new information that should trigger a HCP to initiate recontact, as part of the consent process for genetic testing. Copyright © 2017 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

  11. Gamification in online education: proposal for a participatory learning model

    Directory of Open Access Journals (Sweden)

    Fabiana Bigão Silva

    2017-09-01

    Full Text Available Empirical studies have suggested limitations on the form of application of gamification mechanics in the context of online education. These mechanics have been applied without reference to a theoretical model dedicated to this type of education. The objective of the paper is to propose a model for a gamified platform for online education that contributes to a more participatory learning, taking into account the different student profiles. Based on literature review about approaches to gamification systems design, a set of steps was followed in order to develop a generic model for a framework dedicated to online education. The model proposed is based on the Educational Gamification Design Principles proposed by Dicheva et al. (2015. The model may contribute to the promotion of participatory learning, taking into account the different student profiles. The results of such evaluation will be published in the future.

  12. Itinerant deaf educator and general educator perceptions of the D/HH push-in model.

    Science.gov (United States)

    Rabinsky, Rebecca J

    2013-01-01

    A qualitative case study using the deaf and hard of hearing (D/HH) push-in model was conducted on the perceptions of 3 itinerant deaf educators and 3 general educators working in 1 school district. Participants worked in pairs of 1 deaf educator and 1 general educator at 3 elementary schools. Open-ended research questions guided the study, which was concerned with teachers' perceptions of the model in general and with the model's advantages, disadvantages, and effectiveness. Data collected from observations, one-to-one interviews, and a focus group interview enabled the investigator to uncover 4 themes: Participants (a) had an overall positive experience, (b) viewed general education immersion as an advantage, (c) considered high noise levels a disadvantage, and (d) believed the effectiveness of the push-in model was dependent on several factors, in particular, the needs of the student and the nature of the general education classroom environment.

  13. Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model

    Science.gov (United States)

    Meilijson, Isaac; Kupiec, Martin; Ruppin, Eytan

    2011-01-01

    We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative (‘non-physical’) approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host. PMID:21909250

  14. Expanding a dynamic flux balance model of yeast fermentation to genome-scale

    Science.gov (United States)

    2011-01-01

    Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919

  15. Evidence that personal genome testing enhances student learning in a course on genomics and personalized medicine.

    Directory of Open Access Journals (Sweden)

    Keyan Salari

    Full Text Available An emerging debate in academic medical centers is not about the need for providing trainees with fundamental education on genomics, but rather the most effective educational models that should be deployed. At Stanford School of Medicine, a novel hands-on genomics course was developed in 2010 that provided students the option to undergo personal genome testing as part of the course curriculum. We hypothesized that use of personal genome testing in the classroom would enhance the learning experience of students. No data currently exist on how such methods impact student learning; thus, we surveyed students before and after the course to determine its impact. We analyzed responses using paired statistics from the 31 medical and graduate students who completed both pre-course and post-course surveys. Participants were stratified by those who did (N = 23 or did not (N = 8 undergo personal genome testing. In reflecting on the experience, 83% of students who underwent testing stated that they were pleased with their decision compared to 12.5% of students who decided against testing (P = 0.00058. Seventy percent of those who underwent personal genome testing self-reported a better understanding of human genetics on the basis of having undergone testing. Further, students who underwent personal genome testing demonstrated an average 31% increase in pre- to post-course scores on knowledge questions (P = 3.5×10(-6; this was significantly higher (P = 0.003 than students who did not undergo testing, who showed a non-significant improvement. Undergoing personal genome testing and using personal genotype data in the classroom enhanced students' self-reported and assessed knowledge of genomics, and did not appear to cause significant anxiety. At least for self-selected students, the incorporation of personal genome testing can be an effective educational tool to teach important concepts of clinical genomic testing.

  16. eQETIC: a Maturity Model for Online Education

    Directory of Open Access Journals (Sweden)

    Rogério Rossi

    2015-08-01

    Full Text Available Digital solutions have substantially contributed to the growth and dissemination of education. The distance education modality has been presented as an opportunity for worldwide students in many types of courses. However, projects of digital educational platforms require different expertise including knowledge areas such as pedagogy, psychology, computing, and digital technologies associated with education that allow the correct development and application of these solutions. To support the evolution of such solutions with satisfactory quality indicators, this research presents a model focused on quality of online educational solutions grounded in an approach aimed to continuous process improvement. The model considers of three maturity levels and six common entities that address the specific practices for planning and developing digital educational solutions, targeting quality standards that satisfy their users, such as students, teachers, tutors, and other people involved in development and use of these kinds of educational solutions.

  17. A New State Model of Teacher Education.

    Science.gov (United States)

    Guthrie, James W.

    1983-01-01

    A new California law, Senate Bill 813, implies sweeping changes for teacher education in that state. The law permits districts to hire college graduates without teaching credentials and train them. It also requires all teachers to renew certification periodically. Implications for schools of education are discussed. (Author/PP)

  18. Mathematics Teacher Education: A Model from Crimea.

    Science.gov (United States)

    Ferrucci, Beverly J.; Evans, Richard C.

    1993-01-01

    Reports on the mathematics teacher preparation program at Simferopol State University, the largest institution of higher education in the Crimea. The article notes the value of investigating what other countries consider essential in mathematics teacher education to improve the mathematical competence of students in the United States. (SM)

  19. Modeling Strategies for Enhancing Educational Quality

    Science.gov (United States)

    Cummings, William K.; Bain, Olga

    2017-01-01

    With the strengthening of the global economy, contemporary societies have come to view the educational achievements of their young people as a major component of national competiveness. But there are substantial variations in the strategies employed by different nations. To maximize educational achievements, some nations believe that the provision…

  20. Education and Industry Links: A Tripartite Model.

    Science.gov (United States)

    Bishop, Pam

    1996-01-01

    Describes a project in which a British industrial organization, the Boots Company, a family of schools, and the one-year Post-Graduate Certificate in Education (PGCE) teacher training course at the School of Education at the University of Nottingham cooperated in developing science-focused material in the area of Economic and Industrial…

  1. Planning for Online Education: A Systems Model

    Science.gov (United States)

    Picciano, Anthony G.

    2015-01-01

    The purpose of this article is to revisit the basic principles of technology planning as applied to online education initiatives. While not meant to be an exhaustive treatment of the topic, the article is timely because many colleges and universities are considering the development and expansion of online education as part of their planning…

  2. Comparative BAC-based mapping in the white-throated sparrow, a novel behavioral genomics model, using interspecies overgo hybridization

    Directory of Open Access Journals (Sweden)

    Gonser Rusty A

    2011-06-01

    Full Text Available Abstract Background The genomics era has produced an arsenal of resources from sequenced organisms allowing researchers to target species that do not have comparable mapping and sequence information. These new "non-model" organisms offer unique opportunities to examine environmental effects on genomic patterns and processes. Here we use comparative mapping as a first step in characterizing the genome organization of a novel animal model, the white-throated sparrow (Zonotrichia albicollis, which occurs as white or tan morphs that exhibit alternative behaviors and physiology. Morph is determined by the presence or absence of a complex chromosomal rearrangement. This species is an ideal model for behavioral genomics because the association between genotype and phenotype is absolute, making it possible to identify the genomic bases of phenotypic variation. Findings We initiated a genomic study in this species by characterizing the white-throated sparrow BAC library via filter hybridization with overgo probes designed for the chicken, turkey, and zebra finch. Cross-species hybridization resulted in 640 positive sparrow BACs assigned to 77 chicken loci across almost all macro-and microchromosomes, with a focus on the chromosomes associated with morph. Out of 216 overgos, 36% of the probes hybridized successfully, with an average number of 3.0 positive sparrow BACs per overgo. Conclusions These data will be utilized for determining chromosomal architecture and for fine-scale mapping of candidate genes associated with phenotypic differences. Our research confirms the utility of interspecies hybridization for developing comparative maps in other non-model organisms.

  3. Quality assessment in higher education using the SERVQUALQ model

    Directory of Open Access Journals (Sweden)

    Sabina Đonlagić

    2015-01-01

    Full Text Available Economy in Bosnia and Herzegovina is striving towards growth and increased employment and it has been proven by empirical studies worldwide that higher education contributes to socio-economic development of a country. Universities are important for generation, preservation and dissemination of knowledge in order to contribute to socio-economic benefits of a country. Higher education institutions are being pressured to improve value for their activities and providing quality higher education service to students should be taken seriously. In this paper we will address the emerging demand for quality in higher education. Higher education institutions should assess quality of their services and establish methods for improving quality. Activities of quality assurance should be integrated into the management process at higher education institutions. This paper is addressing the issue of service quality measurement in higher education institutions. The most frequently used model in this context is the SERVQUAL model. This model is measuring quality from the students' point of view, since students are considered to be one of the most important stakeholders for a higher education institution. The main objective of this research is to provide empirical evidence that the adapted SERVQAL model can be used in higher education and to identify the service quality gap based on its application at one institution of higher education (Faculty of Economics in Bosnia and Herzegovina. Furthermore, results of the gap analysis using the SERVQUAL methodology provide relevant information in which areas improvement is necessary in order to enhance service quality.

  4. 4Cin: A computational pipeline for 3D genome modeling and virtual Hi-C analyses from 4C data.

    Directory of Open Access Journals (Sweden)

    Ibai Irastorza-Azcarate

    2018-03-01

    Full Text Available The use of 3C-based methods has revealed the importance of the 3D organization of the chromatin for key aspects of genome biology. However, the different caveats of the variants of 3C techniques have limited their scope and the range of scientific fields that could benefit from these approaches. To address these limitations, we present 4Cin, a method to generate 3D models and derive virtual Hi-C (vHi-C heat maps of genomic loci based on 4C-seq or any kind of 4C-seq-like data, such as those derived from NG Capture-C. 3D genome organization is determined by integrative consideration of the spatial distances derived from as few as four 4C-seq experiments. The 3D models obtained from 4C-seq data, together with their associated vHi-C maps, allow the inference of all chromosomal contacts within a given genomic region, facilitating the identification of Topological Associating Domains (TAD boundaries. Thus, 4Cin offers a much cheaper, accessible and versatile alternative to other available techniques while providing a comprehensive 3D topological profiling. By studying TAD modifications in genomic structural variants associated to disease phenotypes and performing cross-species evolutionary comparisons of 3D chromatin structures in a quantitative manner, we demonstrate the broad potential and novel range of applications of our method.

  5. Smoking education and prevention: a developmental model.

    Science.gov (United States)

    Oei, T P; Baldwin, A R

    1992-01-01

    A developmental approach to smoking education and prevention for children and adolescents is proposed. Literature is reviewed concerning the most appropriate agent, content, and presentation, of anti-smoking education for each of three age groups: children to age ten, pre/early adolescents eleven to fifteen, and adolescents fifteen to eighteen. For children to age ten, it is suggested that parents are the best agents of education, with teachers, peers, and the mass media, also playing some role. For pre/early adolescents, peers are suggested as the best agents of education, building onto the earlier and ongoing work of the agents mentioned above. For adolescents, the role of the media hero-figure is discussed. It is emphasized that sources of influence may function additively in affecting the child or adolescent's decisions about smoking, and that education in each stage must build on the stage before.

  6. Education, Equality and the European Social Model

    DEFF Research Database (Denmark)

    Rasmussen, Palle; Lynch, Kathleen; Brine, Jacky

    2009-01-01

    and employment. The importance of education is often mentioned in EU documents on social welfare. However, European policies in the areas of welfare and education are marked by a fundamental tension between the pursuit of capitalist growth on one hand, the pursuit of social justice and equality on the other......Social welfare and education have been themes in European collaboration since the early days of the Treaty of Rome. Especially after the establishment in 2000 of the Lisbon agenda the EU has stepped up its efforts in these two areas and has integrated both of them in a strategy for growth....... This often leads to an impoverished conceptualisation of education as just another service to be delivered on the market. A more holistic approach to education policy is necessary, an approach which takes account of the broader conditions of equality and includes not only the economic, but also the political...

  7. From bedside to classroom: the nurse educator transition model.

    Science.gov (United States)

    Schoening, Anne M

    2013-01-01

    The purpose of this qualitative study was to generate a theoretical model that describes the social process that occurs during the role transition from nurse to nurse educator. Recruitment and retention of qualified nurse educators is essential in order to remedy the current staff nurse and faculty shortage in the United States, yet nursing schools face many challenges in this area. This grounded theory study utilized purposive, theoretical sampling to identify 20 nurse educators teaching in baccalaureate nursing programs in the Midwest. The Nurse Educator Transition (NET) model was created from these data.This model identifies four phases in the role transition from nurse to nurse educator: a) the Anticipatory/Expectation Phase, b) the Disorientation Phase, c) the Information-Seeking Phase, and d) the Identity Formation Phase. Recommendations include integrating formal pedagogical education into nursing graduate programs and creating evidence-based orientation and mentoring programs for novice nurse faculty.

  8. Beijing Model of Gifted Education and Talent Development

    DEFF Research Database (Denmark)

    Fang, Zhongxiong; Zhang, Yi; Du, Xiangyun

    In China, talent development has been one of the key points in national plans for the development of science and technology, education, and other areas over the last three decades and is especially emphasized in the national outline for medium- and long-term educational reform and development....... Beijing is the leading city in educational reform, especially in the area of gifted education in mainland China. Over the past 35 years, through constant exploration and research, a comprehensive gifted education system called the Beijing Model of Gifted Education and Talent Development (BMGETD) has...... gradually been developed. This book is a summary of the educational practices used in and research done on the BMGETD over the decades. These include several patterns for gifted education, such as acceleration in special classes, special classes without acceleration, enrichment within regular classes...

  9. Student Identification with Business Education Models: Measurement and Relationship to Educational Outcomes

    Science.gov (United States)

    Halbesleben, Jonathon R. B.; Wheeler, Anthony R.

    2009-01-01

    Although management scholars have provided a variety of metaphors to describe the role of students in management courses, researchers have yet to explore students' identification with the models and how they are linked to educational outcomes. This article develops a measurement tool for students' identification with business education models and…

  10. PHYSICAL EDUCATION - PHYSICAL CULTURE. TWO MODELS, TWO DIDACTIC

    Directory of Open Access Journals (Sweden)

    Manuel Vizuete Carrizosa

    2014-11-01

    The survival of these conflicting positions and their interests and different views on education, in a lengthy space of time, as a consequence threw two teaching approaches and two different educational models, in which the objectives and content of education differ , and with them the forms and methods of teaching. The need to define the cultural and educational approach, in every time and place, is now a pressing need and challenge the processes of teacher training, as responsible for shaping an advanced physical education, adjusted to the time and place, the interests and needs of citizens and the democratic values of modern society.

  11. Statistical power of model selection strategies for genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Zheyang Wu

    2009-07-01

    Full Text Available Genome-wide association studies (GWAS aim to identify genetic variants related to diseases by examining the associations between phenotypes and hundreds of thousands of genotyped markers. Because many genes are potentially involved in common diseases and a large number of markers are analyzed, it is crucial to devise an effective strategy to identify truly associated variants that have individual and/or interactive effects, while controlling false positives at the desired level. Although a number of model selection methods have been proposed in the literature, including marginal search, exhaustive search, and forward search, their relative performance has only been evaluated through limited simulations due to the lack of an analytical approach to calculating the power of these methods. This article develops a novel statistical approach for power calculation, derives accurate formulas for the power of different model selection strategies, and then uses the formulas to evaluate and compare these strategies in genetic model spaces. In contrast to previous studies, our theoretical framework allows for random genotypes, correlations among test statistics, and a false-positive control based on GWAS practice. After the accuracy of our analytical results is validated through simulations, they are utilized to systematically evaluate and compare the performance of these strategies in a wide class of genetic models. For a specific genetic model, our results clearly reveal how different factors, such as effect size, allele frequency, and interaction, jointly affect the statistical power of each strategy. An example is provided for the application of our approach to empirical research. The statistical approach used in our derivations is general and can be employed to address the model selection problems in other random predictor settings. We have developed an R package markerSearchPower to implement our formulas, which can be downloaded from the

  12. Complete Genome Sequence of the Methanococcus maripaludis Type Strain JJ (DSM 2067), a Model for Selenoprotein Synthesis in Archaea.

    Science.gov (United States)

    Poehlein, Anja; Heym, Daniel; Quitzke, Vivien; Fersch, Julia; Daniel, Rolf; Rother, Michael

    2018-04-05

    Methanococcus maripaludis type strain JJ (DSM 2067) is an important organism because it serves as a model for primary energy metabolism and hydrogenotrophic methanogenesis and is amenable to genetic manipulation. The complete genome (1.7 Mb) harbors 1,815 predicted protein-encoding genes, including 9 encoding selenoproteins. Copyright © 2018 Poehlein et al.

  13. A Site Specific Model And Analysis Of The Neutral Somatic Mutation Rate In Whole-Genome Cancer Data

    DEFF Research Database (Denmark)

    Bertl, Johanna; Guo, Qianyun; Rasmussen, Malene Juul

    2017-01-01

    Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation ra...

  14. Influence of model specifications on the reliabilities of genomic prediction in a Swedish-Finnish red breed cattle population

    DEFF Research Database (Denmark)

    Rius-Vilarrasa, E; Strandberg, E; Fikse, W F

    2012-01-01

    Using a combined multi-breed reference population, this study explored the influence of model specification and the effect of including a polygenic effect on the reliability of genomic breeding values (DGV and GEBV). The combined reference population consisted of 2986 Swedish Red Breed (SRB) and ...

  15. An information-theoretic approach to the modeling and analysis of whole-genome bisulfite sequencing data.

    Science.gov (United States)

    Jenkinson, Garrett; Abante, Jordi; Feinberg, Andrew P; Goutsias, John

    2018-03-07

    DNA methylation is a stable form of epigenetic memory used by cells to control gene expression. Whole genome bisulfite sequencing (WGBS) has emerged as a gold-standard experimental technique for studying DNA methylation by producing high resolution genome-wide methylation profiles. Statistical modeling and analysis is employed to computationally extract and quantify information from these profiles in an effort to identify regions of the genome that demonstrate crucial or aberrant epigenetic behavior. However, the performance of most currently available methods for methylation analysis is hampered by their inability to directly account for statistical dependencies between neighboring methylation sites, thus ignoring significant information available in WGBS reads. We present a powerful information-theoretic approach for genome-wide modeling and analysis of WGBS data based on the 1D Ising model of statistical physics. This approach takes into account correlations in methylation by utilizing a joint probability model that encapsulates all information available in WGBS methylation reads and produces accurate results even when applied on single WGBS samples with low coverage. Using the Shannon entropy, our approach provides a rigorous quantification of methylation stochasticity in individual WGBS samples genome-wide. Furthermore, it utilizes the Jensen-Shannon distance to evaluate differences in methylation distributions between a test and a reference sample. Differential performance assessment using simulated and real human lung normal/cancer data demonstrate a clear superiority of our approach over DSS, a recently proposed method for WGBS data analysis. Critically, these results demonstrate that marginal methods become statistically invalid when correlations are present in the data. This contribution demonstrates clear benefits and the necessity of modeling joint probability distributions of methylation using the 1D Ising model of statistical physics and of

  16. Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model.

    Science.gov (United States)

    Gürsoy, Gamze; Xu, Yun; Liang, Jie

    2017-07-01

    Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.

  17. Foxtail millet: a model crop for genetic and genomic studies in bioenergy grasses.

    Science.gov (United States)

    Lata, Charu; Gupta, Sarika; Prasad, Manoj

    2013-09-01

    Foxtail millet is one of the oldest domesticated diploid C4 Panicoid crops having a comparatively small genome size of approximately 515 Mb, short life cycle, and inbreeding nature. Its two species, Setaria italica (domesticated) and Setaria viridis (wild progenitor), have characteristics that classify them as excellent model systems to examine several aspects of architectural, evolutionary, and physiological importance in Panicoid grasses especially the biofuel crops such as switchgrass and napiergrass. Foxtail millet is a staple crop used extensively for food and fodder in parts of Asia and Africa. In its long history of cultivation, it has been adapted to arid and semi-arid areas of Asia, North Africa, South and North America. Foxtail millet has one of the largest collections of cultivated as well as wild-type germplasm rich with phenotypic variations and hence provides prospects for association mapping and allele-mining of elite and novel variants to be incorporated in crop improvement programs. Most of the foxtail millet accessions can be primarily abiotic stress tolerant particularly to drought and salinity, and therefore exploiting these agronomic traits can enhance its efficacy in marker-aided breeding as well as in genetic engineering for abiotic stress tolerance. In addition, the release of draft genome sequence of foxtail millet would be useful to the researchers worldwide in not only discerning the molecular basis of biomass production in biofuel crops and the methods to improve it, but also for the introgression of beneficial agronomically important characteristics in foxtail millet as well as in related Panicoid bioenergy grasses.

  18. Genome organization in the nucleus: From dynamic measurements to a functional model.

    Science.gov (United States)

    Vivante, Anat; Brozgol, Eugene; Bronshtein, Irena; Garini, Yuval

    2017-07-01

    A biological system is by definition a dynamic environment encompassing kinetic processes that occur at different length scales and time ranges. To explore this type of system, spatial information needs to be acquired at different time scales. This means overcoming significant hurdles, including the need for stable and precise labeling of the required probes and the use of state of the art optical methods. However, to interpret the acquired data, biophysical models that can account for these biological mechanisms need to be developed. The structure and function of a biological system are closely related to its dynamic properties, thus further emphasizing the importance of identifying the rules governing the dynamics that cannot be directly deduced from information on the structure itself. In eukaryotic cells, tens of thousands of genes are packed in the small volume of the nucleus. The genome itself is organized in chromosomes that occupy specific volumes referred to as chromosome territories. This organization is preserved throughout the cell cycle, even though there are no sub-compartments in the nucleus itself. This organization, which is still not fully understood, is crucial for a large number of cellular functions such as gene regulation, DNA breakage repair and error-free cell division. Various techniques are in use today, including imaging, live cell imaging and molecular methods such as chromosome conformation capture (3C) methods to better understand these mechanisms. Live cell imaging methods are becoming well established. These include methods such as Single Particle Tracking (SPT), Continuous Photobleaching (CP), Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Correlation Spectroscopy (FCS) that are currently used for studying proteins, RNA, DNA, gene loci and nuclear bodies. They provide crucial information on its mobility, reorganization, interactions and binding properties. Here we describe how these dynamic methods can be used to

  19. Continuing Education of the UNAE: A model that contribute to the Educational Transformation of Ecuador. Studies on Education

    Directory of Open Access Journals (Sweden)

    Oscar Antonio Martínez Molina

    2018-05-01

    Full Text Available This paper presents the Model that contributes to the educational transformation of Ecuador: Continuing Education of the National University of Education, designed with the objective of satisfying the needs of teachers based on training strategies aimed at the improvement and transformation of education from the reflection of their pedagogical practice, from a cooperative and collaborative approach. Participatory action research was carried out with the objective of improving and learning from one 's experience from reflection - action. Finally, phases for the operation of Continuing Education with society are included.

  20. Four discourse models of physics teacher education

    OpenAIRE

    Larsson, Johanna; Airey, John

    2017-01-01

    In Sweden, as in many other countries, the education of high-school physics teachers is typically carried out in three different environments; the education department, the physics department and school itself during teaching practice. Trainee physics teachers are in the process of building their professional identity as they move between these three environments. Although much has been written about teacher professional identity (see overview in Beijaard, Meijer, & Verloop, 2004) little ...

  1. A tutorial of diverse genome analysis tools found in the CoGe web-platform using Plasmodium spp. as a model

    Science.gov (United States)

    Castillo, Andreina I; Nelson, Andrew D L; Haug-Baltzell, Asher K; Lyons, Eric

    2018-01-01

    Abstract Integrated platforms for storage, management, analysis and sharing of large quantities of omics data have become fundamental to comparative genomics. CoGe (https://genomevolution.org/coge/) is an online platform designed to manage and study genomic data, enabling both data- and hypothesis-driven comparative genomics. CoGe’s tools and resources can be used to organize and analyse both publicly available and private genomic data from any species. Here, we demonstrate the capabilities of CoGe through three example workflows using 17 Plasmodium genomes as a model. Plasmodium genomes present unique challenges for comparative genomics due to their rapidly evolving and highly variable genomic AT/GC content. These example workflows are intended to serve as templates to help guide researchers who would like to use CoGe to examine diverse aspects of genome evolution. In the first workflow, trends in genome composition and amino acid usage are explored. In the second, changes in genome structure and the distribution of synonymous (Ks) and non-synonymous (Kn) substitution values are evaluated across species with different levels of evolutionary relatedness. In the third workflow, microsyntenic analyses of multigene families’ genomic organization are conducted using two Plasmodium-specific gene families—serine repeat antigen, and cytoadherence-linked asexual gene—as models. In general, these example workflows show how to achieve quick, reproducible and shareable results using the CoGe platform. We were able to replicate previously published results, as well as leverage CoGe’s tools and resources to gain additional insight into various aspects of Plasmodium genome evolution. Our results highlight the usefulness of the CoGe platform, particularly in understanding complex features of genome evolution. Database URL: https://genomevolution.org/coge/

  2. Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica.

    Science.gov (United States)

    Mishra, Pranjul; Lee, Na-Rae; Lakshmanan, Meiyappan; Kim, Minsuk; Kim, Byung-Gee; Lee, Dong-Yup

    2018-03-19

    Recently, there have been several attempts to produce long-chain dicarboxylic acids (DCAs) in various microbial hosts. Of these, Yarrowia lipolytica has great potential due to its oleaginous characteristics and unique ability to utilize hydrophobic substrates. However, Y. lipolytica should be further engineered to make it more competitive: the current approaches are mostly intuitive and cumbersome, thus limiting its industrial application. In this study, we proposed model-guided metabolic engineering strategies for enhanced production of DCAs in Y. lipolytica. At the outset, we reconstructed genome-scale metabolic model (GSMM) of Y. lipolytica (iYLI647) by substantially expanding the previous models. Subsequently, the model was validated using three sets of published culture experiment data. It was finally exploited to identify genetic engineering targets for overexpression, knockout, and cofactor modification by applying several in silico strain design methods, which potentially give rise to high yield production of the industrially relevant long-chain DCAs, e.g., dodecanedioic acid (DDDA). The resultant targets include (1) malate dehydrogenase and malic enzyme genes and (2) glutamate dehydrogenase gene, in silico overexpression of which generated additional NADPH required for fatty acid synthesis, leading to the increased DDDA fluxes by 48% and 22% higher, respectively, compared to wild-type. We further investigated the effect of supplying branched-chain amino acids on the acetyl-CoA turn-over rate which is key metabolite for fatty acid synthesis, suggesting their significance for production of DDDA in Y. lipolytica. In silico model-based strain design strategies allowed us to identify several metabolic engineering targets for overproducing DCAs in lipid accumulating yeast, Y. lipolytica. Thus, the current study can provide a methodological framework that is applicable to other oleaginous yeasts for value-added biochemical production.

  3. Ensembl Genomes 2016: more genomes, more complexity.

    Science.gov (United States)

    Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M

    2016-01-04

    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  4. Generation of an ICF syndrome model by efficient genome editing of human induced pluripotent stem cells using the CRISPR system.

    Science.gov (United States)

    Horii, Takuro; Tamura, Daiki; Morita, Sumiyo; Kimura, Mika; Hatada, Izuho

    2013-09-30

    Genome manipulation of human induced pluripotent stem (iPS) cells is essential to achieve their full potential as tools for regenerative medicine. To date, however, gene targeting in human pluripotent stem cells (hPSCs) has proven to be extremely difficult. Recently, an efficient genome manipulation technology using the RNA-guided DNase Cas9, the clustered regularly interspaced short palindromic repeats (CRISPR) system, has been developed. Here we report the efficient generation of an iPS cell model for immunodeficiency, centromeric region instability, facial anomalies syndrome (ICF) syndrome using the CRISPR system. We obtained iPS cells with mutations in both alleles of DNA methyltransferase 3B (DNMT3B) in 63% of transfected clones. Our data suggest that the CRISPR system is highly efficient and useful for genome engineering of human iPS cells.

  5. Generation of an ICF Syndrome Model by Efficient Genome Editing of Human Induced Pluripotent Stem Cells Using the CRISPR System

    Directory of Open Access Journals (Sweden)

    Izuho Hatada

    2013-09-01

    Full Text Available Genome manipulation of human induced pluripotent stem (iPS cells is essential to achieve their full potential as tools for regenerative medicine. To date, however, gene targeting in human pluripotent stem cells (hPSCs has proven to be extremely difficult. Recently, an efficient genome manipulation technology using the RNA-guided DNase Cas9, the clustered regularly interspaced short palindromic repeats (CRISPR system, has been developed. Here we report the efficient generation of an iPS cell model for immunodeficiency, centromeric region instability, facial anomalies syndrome (ICF syndrome using the CRISPR system. We obtained iPS cells with mutations in both alleles of DNA methyltransferase 3B (DNMT3B in 63% of transfected clones. Our data suggest that the CRISPR system is highly efficient and useful for genome engineering of human iPS cells.

  6. Complete chloroplast genome sequence of green foxtail (Setaria viridis), a promising model system for C4 photosynthesis.

    Science.gov (United States)

    Wang, Shuo; Gao, Li-Zhi

    2016-09-01

    The complete chloroplast genome of green foxtail (Setaria viridis), a promising model system for C4 photosynthesis, is first reported in this study. The genome harbors a large single copy (LSC) region of 81 016 bp and a small single copy (SSC) region of 12 456  bp separated by a pair of inverted repeat (IRa and IRb) regions of 22 315 bp. GC content is 38.92%. The proportion of coding sequence is 57.97%, comprising of 111 (19 duplicated in IR regions) unique genes, 71 of which are protein-coding genes, four are rRNA genes, and 36 are tRNA genes. Phylogenetic analysis indicated that S. viridis was clustered with its cultivated species S. italica in the tribe Paniceae of the family Poaceae. This newly determined chloroplast genome will provide valuable genetic resources to assist future studies on C4 photosynthesis in grasses.

  7. Chromosomally Integrated Human Herpesvirus 6: Models of Viral Genome Release from the Telomere and Impacts on Human Health.

    Science.gov (United States)

    Wood, Michael L; Royle, Nicola J

    2017-07-12

    Human herpesvirus 6A and 6B, alongside some other herpesviruses, have the striking capacity to integrate into telomeres, the terminal repeated regions of chromosomes. The chromosomally integrated forms, ciHHV-6A and ciHHV-6B, are proposed to be a state of latency and it has been shown that they can both be inherited if integration occurs in the germ line. The first step in full viral reactivation must be the release of the integrated viral genome from the telomere and here we propose various models of this release involving transcription of the viral genome, replication fork collapse, and t-circle mediated release. In this review, we also discuss the relationship between ciHHV-6 and the telomere carrying the insertion, particularly how the presence and subsequent partial or complete release of the ciHHV-6 genome may affect telomere dynamics and the risk of disease.

  8. A Quantitative Genomic Approach for Analysis of Fitness and Stress Related Traits in a Drosophila melanogaster Model Population

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Krag, Kristian; Loeschcke, Volker

    2016-01-01

    , to investigate whether this population harbors genetic variation for a set of stress resistance and life history traits. Using a genomic approach, we found substantial genetic variation for metabolic rate, heat stress resistance, expression of a major heat shock protein, and egg-to-adult viability investigated......The ability of natural populations to withstand environmental stresses relies partly on their adaptive ability. In this study, we used a subset of the Drosophila Genetic Reference Panel, a population of inbred, genome-sequenced lines derived from a natural population of Drosophila melanogaster...... at a benign and a higher stressful temperature. This suggests that these traits will be able to evolve. In addition, we outline an approach to conduct pathway associations based on genomic linear models, which has potential to identify adaptive genes and pathways, and therefore can be a valuable tool...

  9. High resolution linkage maps of the model organism Petunia reveal substantial synteny decay with the related genome of tomato.

    Science.gov (United States)

    Bossolini, Eligio; Klahre, Ulrich; Brandenburg, Anna; Reinhardt, Didier; Kuhlemeier, Cris

    2011-04-01

    Two linkage maps were constructed for the model plant Petunia. Mapping populations were obtained by crossing the wild species Petunia axillaris subsp. axillaris with Petunia inflata, and Petunia axillaris subsp. parodii with Petunia exserta. Both maps cover the seven chromosomes of Petunia, and span 970 centimorgans (cM) and 700 cM of the genomes, respectively. In total, 207 markers were mapped. Of these, 28 are multilocus amplified fragment length polymorphism (AFLP) markers and 179 are gene-derived markers. For the first time we report on the development and mapping of 83 Petunia microsatellites. The two maps retain the same marker order, but display significant differences of recombination frequencies at orthologous mapping intervals. A complex pattern of genomic rearrangements was detected with the related genome of tomato (Solanum lycopersicum), indicating that synteny between Petunia and other Solanaceae crops has been considerably disrupted. The newly developed markers will facilitate the genetic characterization of mutants and ecological studies on genetic diversity and speciation within the genus Petunia. The maps will provide a powerful tool to link genetic and genomic information and will be useful to support sequence assembly of the Petunia genome.

  10. A Model for Effective Professional Development of Formal Science Educators

    Science.gov (United States)

    Bleacher, L. V.; Jones, A. J. P.; Farrell, W. M.

    2015-01-01

    The Lunar Workshops for Educators (LWE) series was developed by the Lunar Reconnaissance Orbiter (LRO) education team in 2010 to provide professional development on lunar science and exploration concepts for grades 6-9 science teachers. Over 300 educators have been trained to date. The LWE model incorporates best practices from pedagogical research of science education, thoughtful integration of scientists and engineer subject matter experts for both content presentations and informal networking with educators, access to NASA-unique facilities, hands-on and data-rich activities aligned with education standards, exposure to the practice of science, tools for addressing common misconceptions, follow-up with participants, and extensive evaluation. Evaluation of the LWE model via pre- and post-assessments, daily workshop surveys, and follow-up surveys at 6-month and 1-year intervals indicate that the LWE are extremely effective in increasing educators' content knowledge, confidence in incorporating content into the classroom, understanding of the practice of science, and ability to address common student misconceptions. In order to address the efficacy of the LWE model for other science content areas, the Dynamic Response of Environments at Asteroids, the Moon, and moons of Mars (DREAM2) education team, funded by NASA's Solar System Exploration Research Virtual Institute, developed and ran a pilot workshop called Dream2Explore at NASA's Goddard Space Flight Center in June, 2015. Dream2Explore utilized the LWE model, but incorporated content related to the science and exploration of asteroids and the moons of Mars. Evaluation results indicate that the LWE model was effectively used for educator professional development on non-lunar content. We will present more detail on the LWE model, evaluation results from the Dream2Explore pilot workshop, and suggestions for the application of the model with other science content for robust educator professional development.

  11. A Model for Effective Professional Development of Formal Science Educators

    Science.gov (United States)

    Bleacher, L.; Jones, A. P.; Farrell, W. M.

    2015-12-01

    The Lunar Workshops for Educators (LWE) series was developed by the Lunar Reconnaissance Orbiter (LRO) education team in 2010 to provide professional development on lunar science and exploration concepts for grades 6-9 science teachers. Over 300 educators have been trained to date. The LWE model incorporates best practices from pedagogical research of science education, thoughtful integration of scientists and engineer subject matter experts for both content presentations and informal networking with educators, access to NASA-unique facilities, hands-on and data-rich activities aligned with education standards, exposure to the practice of science, tools for addressing common misconceptions, follow-up with participants, and extensive evaluation. Evaluation of the LWE model via pre- and post-assessments, daily workshop surveys, and follow-up surveys at 6-month and 1-year intervals indicate that the LWE are extremely effective in increasing educators' content knowledge, confidence in incorporating content into the classroom, understanding of the practice of science, and ability to address common student misconceptions. In order to address the efficacy of the LWE model for other science content areas, the Dynamic Response of Environments at Asteroids, the Moon, and moons of Mars (DREAM2) education team, funded by NASA's Solar System Exploration Research Virtual Institute, developed and ran a pilot workshop called Dream2Explore at NASA's Goddard Space Flight Center in June, 2015. Dream2Explore utilized the LWE model, but incorporated content related to the science and exploration of asteroids and the moons of Mars. Evaluation results indicate that the LWE model was effectively used for educator professional development on non-lunar content. We will present more detail on the LWE model, evaluation results from the Dream2Explore pilot workshop, and suggestions for the application of the model with other science content for robust educator professional development.

  12. Building a semantic web-based metadata repository for facilitating detailed clinical modeling in cancer genome studies.

    Science.gov (United States)

    Sharma, Deepak K; Solbrig, Harold R; Tao, Cui; Weng, Chunhua; Chute, Christopher G; Jiang, Guoqian

    2017-06-05

    Detailed Clinical Models (DCMs) have been regarded as the basis for retaining computable meaning when data are exchanged between heterogeneous computer systems. To better support clinical cancer data capturing and reporting, there is an emerging need to develop informatics solutions for standards-based clinical models in cancer study domains. The objective of the study is to develop and evaluate a cancer genome study metadata management system that serves as a key infrastructure in supporting clinical information modeling in cancer genome study domains. We leveraged a Semantic Web-based metadata repository enhanced with both ISO11179 metadata standard and Clinical Information Modeling Initiative (CIMI) Reference Model. We used the common data elements (CDEs) defined in The Cancer Genome Atlas (TCGA) data dictionary, and extracted the metadata of the CDEs using the NCI Cancer Data Standards Repository (caDSR) CDE dataset rendered in the Resource Description Framework (RDF). The ITEM/ITEM_GROUP pattern defined in the latest CIMI Reference Model is used to represent reusable model elements (mini-Archetypes). We produced a metadata repository with 38 clinical cancer genome study domains, comprising a rich collection of mini-Archetype pattern instances. We performed a case study of the domain "clinical pharmaceutical" in the TCGA data dictionary and demonstrated enriched data elements in the metadata repository are very useful in support of building detailed clinical models. Our informatics approach leveraging Semantic Web technologies provides an effective way to build a CIMI-compliant metadata repository that would facilitate the detailed clinical modeling to support use cases beyond TCGA in clinical cancer study domains.

  13. DEFINING AND CONSTRUCTING THE TEACHING MODEL OF ENTREPRENEUR EDUCATION BASED ON ENTREPRENEURIAL INTENTION MODEL

    OpenAIRE

    Henry Pribadi

    2005-01-01

    Concept of entrepreneurship has been widely debated whether to be an entrepreneur one need to get formal entrepreneurial education or not. Most of the formal entrepreneur education yield the same flaw, which is the lack of teaching soft skill and building the necessary entrepreneurship characteristics. Intention-based models of entrepreneurship education try to fill the gap by focusing the education on the human intention of becoming entrepreneur by defining four model of entrepreneurship edu...

  14. Predictive ability of genomic selection models for breeding value estimation on growth traits of Pacific white shrimp Litopenaeus vannamei

    Science.gov (United States)

    Wang, Quanchao; Yu, Yang; Li, Fuhua; Zhang, Xiaojun; Xiang, Jianhai

    2017-09-01

    Genomic selection (GS) can be used to accelerate genetic improvement by shortening the selection interval. The successful application of GS depends largely on the accuracy of the prediction of genomic estimated breeding value (GEBV). This study is a first attempt to understand the practicality of GS in Litopenaeus vannamei and aims to evaluate models for GS on growth traits. The performance of GS models in L. vannamei was evaluated in a population consisting of 205 individuals, which were genotyped for 6 359 single nucleotide polymorphism (SNP) markers by specific length amplified fragment sequencing (SLAF-seq) and phenotyped for body length and body weight. Three GS models (RR-BLUP, BayesA, and Bayesian LASSO) were used to obtain the GEBV, and their predictive ability was assessed by the reliability of the GEBV and the bias of the predicted phenotypes. The mean reliability of the GEBVs for body length and body weight predicted by the different models was 0.296 and 0.411, respectively. For each trait, the performances of the three models were very similar to each other with respect to predictability. The regression coefficients estimated by the three models were close to one, suggesting near to zero bias for the predictions. Therefore, when GS was applied in a L. vannamei population for the studied scenarios, all three models appeared practicable. Further analyses suggested that improved estimation of the genomic prediction could be realized by increasing the size of the training population as well as the density of SNPs.

  15. Genome-enabled Modeling of Microbial Biogeochemistry using a Trait-based Approach. Does Increasing Metabolic Complexity Increase Predictive Capabilities?

    Science.gov (United States)

    King, E.; Karaoz, U.; Molins, S.; Bouskill, N.; Anantharaman, K.; Beller, H. R.; Banfield, J. F.; Steefel, C. I.; Brodie, E.

    2015-12-01

    The biogeochemical functioning of ecosystems is shaped in part by genomic information stored in the subsurface microbiome. Cultivation-independent approaches allow us to extract this information through reconstruction of thousands of genomes from a microbial community. Analysis of these genomes, in turn, gives an indication of the organisms present and their functional roles. However, metagenomic analyses can currently deliver thousands of different genomes that range in abundance/importance, requiring the identification and assimilation of key physiologies and metabolisms to be represented as traits for successful simulation of subsurface processes. Here we focus on incorporating -omics information into BioCrunch, a genome-informed trait-based model that represents the diversity of microbial functional processes within a reactive transport framework. This approach models the rate of nutrient uptake and the thermodynamics of coupled electron donors and acceptors for a range of microbial metabolisms including heterotrophs and chemolithotrophs. Metabolism of exogenous substrates fuels catabolic and anabolic processes, with the proportion of energy used for cellular maintenance, respiration, biomass development, and enzyme production based upon dynamic intracellular and environmental conditions. This internal resource partitioning represents a trade-off against biomass formation and results in microbial community emergence across a fitness landscape. Biocrunch was used here in simulations that included organisms and metabolic pathways derived from a dataset of ~1200 non-redundant genomes reflecting a microbial community in a floodplain aquifer. Metagenomic data was directly used to parameterize trait values related to growth and to identify trait linkages associated with respiration, fermentation, and key enzymatic functions such as plant polymer degradation. Simulations spanned a range of metabolic complexities and highlight benefits originating from simulations

  16. Spiral model of procedural cycle of educational process management

    Directory of Open Access Journals (Sweden)

    Bezrukov Valery I.

    2016-01-01

    Full Text Available The article analyzes the nature and characteristics of the spiral model Procedure educational systems management cycle. The authors identify patterns between the development of information and communication technologies and the transformation of the education management process, give the characteristics of the concept of “information literacy” and “Media Education”. Consider the design function, determine its potential in changing the traditional educational paradigm to the new - information.

  17. A genome-wide longitudinal transcriptome analysis of the aging model Podospora anserina.

    Science.gov (United States)

    Philipp, Oliver; Hamann, Andrea; Servos, Jörg; Werner, Alexandra; Koch, Ina; Osiewacz, Heinz D

    2013-01-01

    Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression). A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i) present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii) suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii) present testable predictions for subsequent experimental investigations.

  18. A genome-wide longitudinal transcriptome analysis of the aging model Podospora anserina.

    Directory of Open Access Journals (Sweden)

    Oliver Philipp

    Full Text Available Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression. A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii present testable predictions for subsequent experimental investigations.

  19. Novel insights into obesity and diabetes through genome-scale metabolic modeling

    Directory of Open Access Journals (Sweden)

    Leif eVäremo

    2013-04-01

    Full Text Available The growing prevalence of metabolic diseases, such as obesity and diabetes, are putting a high strain on global healthcare systems as well as increasing the demand for efficient treatment strategies. More than 360 million people worldwide are suffering from type 2 diabetes and, with the current trends, the projection is that 10% of the global adult population will be affected by 2030. In light of the systemic properties of metabolic diseases as well as the interconnected nature of metabolism, it is necessary to begin taking a holistic approach to study these diseases. Human genome-scale metabolic models (GEMs are topological and mathematical representations of cell metabolism and have proven to be valuable tools in the area of systems biology. Successful applications of GEMs include the process of gaining further biological and mechanistic understanding of diseases, finding potential biomarkers and identifying new drug targets. This review will focus on the modeling of human metabolism in the field of obesity and diabetes, showing its vast range of applications of clinical importance as well as point out future challenges.

  20. Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production.

    Science.gov (United States)

    Agren, Rasmus; Otero, José Manuel; Nielsen, Jens

    2013-07-01

    In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Δmdh1, Δoac1, and Δdic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Δmdh1 and Δoac1 strains failed to produce succinate, Δdic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies.

  1. Hierarchical modeling of genome-wide Short Tandem Repeat (STR) markers infers native American prehistory.

    Science.gov (United States)

    Lewis, Cecil M

    2010-02-01

    This study examines a genome-wide dataset of 678 Short Tandem Repeat loci characterized in 444 individuals representing 29 Native American populations as well as the Tundra Netsi and Yakut populations from Siberia. Using these data, the study tests four current hypotheses regarding the hierarchical distribution of neutral genetic variation in native South American populations: (1) the western region of South America harbors more variation than the eastern region of South America, (2) Central American and western South American populations cluster exclusively, (3) populations speaking the Chibchan-Paezan and Equatorial-Tucanoan language stock emerge as a group within an otherwise South American clade, (4) Chibchan-Paezan populations in Central America emerge together at the tips of the Chibchan-Paezan cluster. This study finds that hierarchical models with the best fit place Central American populations, and populations speaking the Chibchan-Paezan language stock, at a basal position or separated from the South American group, which is more consistent with a serial founder effect into South America than that previously described. Western (Andean) South America is found to harbor similar levels of variation as eastern (Equatorial-Tucanoan and Ge-Pano-Carib) South America, which is inconsistent with an initial west coast migration into South America. Moreover, in all relevant models, the estimates of genetic diversity within geographic regions suggest a major bottleneck or founder effect occurring within the North American subcontinent, before the peopling of Central and South America. 2009 Wiley-Liss, Inc.

  2. LASSIM-A network inference toolbox for genome-wide mechanistic modeling.

    Directory of Open Access Journals (Sweden)

    Rasmus Magnusson

    2017-06-01

    with truly systems-level data. We demonstrate the power of this approach by inferring a mechanistically motivated, genome-wide model of the Th2 transcription regulatory system, which plays an important role in several immune related diseases.

  3. Estimated allele substitution effects underlying genomic evaluation models depend on the scaling of allele counts

    NARCIS (Netherlands)

    Bouwman, Aniek C.; Hayes, Ben J.; Calus, Mario P.L.

    2017-01-01

    Background: Genomic evaluation is used to predict direct genomic values (DGV) for selection candidates in breeding programs, but also to estimate allele substitution effects (ASE) of single nucleotide polymorphisms (SNPs). Scaling of allele counts influences the estimated ASE, because scaling of

  4. Genome-enabled prediction models for yield related traits in chickpea

    Science.gov (United States)

    Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped...

  5. Genomic selection accuracy using multi-family prediction models in a wheat breeding program

    Science.gov (United States)

    Genomic selection (GS) uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotyp...

  6. Alzheimer’s disease models and functional genomics - How many needles are there in the haystack?

    Directory of Open Access Journals (Sweden)

    Jurgen eGotz

    2012-08-01

    Full Text Available Alzheimer's disease (AD and frontotemporal lobar degeneration (FTLD are complex human brain disorders that affect an increasing number of people worldwide. With the identification first of the proteins that aggregate in AD and FTLD brains and subsequently of pathogenic gene mutations that cause their formation in the familial cases, the foundation was laid for the generation of animal models. These recapitulate essential aspects of the human conditions; expression of mutant forms of the amyloid-β protein-encoding APP gene in mice reproduces amyloid-β (Aβ plaque formation in AD, while that of mutant forms of the tau-encoding MAPT gene reproduces tau-containing neurofibrillary tangle formation, a lesion that is also prevalent in FTLD-Tau. The mouse models have been complemented by those in lower species such as C. elegans or Drosophila, highlighting the crucial role for Aβ and tau in human neurodegenerative disease. In this review, we will introduce selected AD/FTLD models and discuss how they were instrumental, by identifying deregulated mRNAs, miRNAs and proteins, in dissecting pathogenic mechanisms in neurodegenerative disease. We will discuss some recent examples, which includes miRNA species that are specifically deregulated by Aβ, mitochondrial proteins that are targets of both Aβ and tau, and the nuclear splicing factor SFPQ that accumulates in the cytoplasm in a tau-dependent manner. These examples illustrate how a functional genomics approach followed by a careful validation in experimental models and human tissue leads to a deeper understanding of the pathogenesis of AD and FTLD and ultimately, may help in finding a cure.

  7. Cross-species genomics matches driver mutations and cell compartments to model ependymoma

    Science.gov (United States)

    Johnson, Robert A.; Wright, Karen D.; Poppleton, Helen; Mohankumar, Kumarasamypet M.; Finkelstein, David; Pounds, Stanley B.; Rand, Vikki; Leary, Sarah E.S.; White, Elsie; Eden, Christopher; Hogg, Twala; Northcott, Paul; Mack, Stephen; Neale, Geoffrey; Wang, Yong-Dong; Coyle, Beth; Atkinson, Jennifer; DeWire, Mariko; Kranenburg, Tanya A.; Gillespie, Yancey; Allen, Jeffrey C.; Merchant, Thomas; Boop, Fredrick A.; Sanford, Robert. A.; Gajjar, Amar; Ellison, David W.; Taylor, Michael D.; Grundy, Richard G.; Gilbertson, Richard J.

    2010-01-01

    Understanding the biology that underlies histologically similar but molecularly distinct subgroups of cancer has proven difficult since their defining genetic alterations are often numerous, and the cellular origins of most cancers remain unknown1–3. We sought to decipher this heterogeneity by integrating matched genetic alterations and candidate cells of origin to generate accurate disease models. First, we identified subgroups of human ependymoma, a form of neural tumor that arises throughout the central nervous system (CNS). Subgroup specific alterations included amplifications and homozygous deletions of genes not yet implicated in ependymoma. To select cellular compartments most likely to give rise to subgroups of ependymoma, we matched the transcriptomes of human tumors to those of mouse neural stem cells (NSCs), isolated from different regions of the CNS at different developmental stages, with an intact or deleted Ink4a/Arf locus. The transcriptome of human cerebral ependymomas with amplified EPHB2 and deleted INK4A/ARF matched only that of embryonic cerebral Ink4a/Arf−/− NSCs. Remarkably, activation of Ephb2 signaling in these, but not other NSCs, generated the first mouse model of ependymoma, which is highly penetrant and accurately models the histology and transcriptome of one subgroup of human cerebral tumor. Further comparative analysis of matched mouse and human tumors revealed selective deregulation in the expression and copy number of genes that control synaptogenesis, pinpointing disruption of this pathway as a critical event in the production of this ependymoma subgroup. Our data demonstrate the power of cross-species genomics to meticulously match subgroup specific driver mutations with cellular compartments to model and interrogate cancer subgroups. PMID:20639864

  8. CHARACTER EDUCATION MODEL BASED ON EDUCATION IN ISLAMIC BOARDING SCHOOL

    Directory of Open Access Journals (Sweden)

    Novrian Satria Perdana

    2015-10-01

      Abstrak, Berbagai upaya untuk menjadikan pendidikan lebih mempunyai makna bagi individu yang menyentuh tataran afektif telah dilakukan melalui mata pelajaran Pendidikan Agama, Pendidikan Kewarganegaraan, Pendidikan IPS, Pendidikan Bahasa Indonesia, dan Pendidikan Jasmani. Namun demikian upaya-upaya tersebut ternyata belum mampu mewadahi pengembangan karakter secara dinamis dan adaptif terhadap perubahan jaman yang sangat cepat. Permasalahan gagalnya pendidikan formal di sekolah dalam membentuk karakter siswa sangat perlu diantisipasi, sehingga perlu dikembangkan suatu model pembelajaran dan system pendidikan yang dapat digunakan untuk membentuk karakter siswa. Permasalahan pendidikan di sekolah yang belum dapat membentuk karakter siswa dipengaruhi oleh beberapa factor, diantaranya factor manajemen sekolah, guru, dan model pembelajaran. Untuk memperoleh model pembelajaran yang cocok, telah dilakukan penelitian tentang best practices pendidikan karakter di beberapa pesantren yang berada di propinsi Sumatera Utara, propinsi Nangroe Aceh Darussalam, propinsi Sumatera Barat, propinsi Riau, propinsi Jambi, dan propinsi Sumatera Selatan. Pengumpulan data dalam penelitian ini dilakukan dengan dua tehnik yang lazim digunakan dalam penelitian dalam penelitian kualitatif, yaitu; observasi dan wawancara mendalam. Ditemukan bahwa pesantren salafiyah lebih mengutamakan keteladanan ustadz, sedangkan pesantren modern menerapkan aturan yang ketat untuk menumbuhkan sikap disiplin dan tanggungjawab. Pesantren menumbuhkan atribut karakter saling tolong menolong, ihklas mengabdi, kesederhanaan, dan kemandirian. Kebijakan yang dapat diambil berdasarkan hasil penelitian ini adalah menerapkan pendidikan karakter secara holistic melalui program sekolah yang harus dipahami dan dipatuhi oleh semua unsur pendidik dan peserta didik.  Untuk itu, lembaga pendidikan seharusnya menetapkan misi yang eksplisit terkait pengembangan karakter siswa.   Kata Kunci: pendidikan karakter, model

  9. A Review of Research on Universal Design Educational Models

    Science.gov (United States)

    Rao, Kavita; Ok, Min Wook; Bryant, Brian R.

    2014-01-01

    Universal design for learning (UDL) has gained considerable attention in the field of special education, acclaimed for its promise to promote inclusion by supporting access to the general curriculum. In addition to UDL, there are two other universal design (UD) educational models referenced in the literature, universal design of instruction (UDI)…

  10. Computer Simulation (Microcultures): An Effective Model for Multicultural Education.

    Science.gov (United States)

    Nelson, Jorge O.

    This paper presents a rationale for using high-fidelity computer simulation in planning for and implementing effective multicultural education strategies. Using computer simulation, educators can begin to understand and plan for the concept of cultural sensitivity in delivering instruction. The model promises to emphasize teachers' understanding…

  11. Clinical Reasoning in Athletic Training Education: Modeling Expert Thinking

    Science.gov (United States)

    Geisler, Paul R.; Lazenby, Todd W.

    2009-01-01

    Objective: To address the need for a more definitive approach to critical thinking during athletic training educational experiences by introducing the clinical reasoning model for critical thinking. Background: Educators are aware of the need to teach students how to think critically. The multiple domains of athletic training are comprehensive and…

  12. An Innovative School Health Education Model Designed for Student Achievement.

    Science.gov (United States)

    Rohwer, John; Wandberg, Bob

    New threats to the health of American children, often psychosocial in nature due to societal changes, must be addressed. The Minnesota School Health Education Model is based on the integration of four primary components: (1) school health education goals aimed at health promotion, disease prevention, and long-term positive health effects on…

  13. МULTI-STAKEHOLDER MODEL OF EDUCATION PROJECT QUALITY MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Юлия Юрьевна ГУСЕВА

    2015-05-01

    Full Text Available The analysis of approaches to the definition of higher education projects’ stakeholders is conducted. A model of education project quality management with the influence of stakeholders is formed. A mechanism of recognition of new groups of project’s stakeholders on the basis of set theory is offered.

  14. Modeling E-learning quality assurance benchmarking in higher education

    NARCIS (Netherlands)

    Alsaif, Fatimah; Clementking, Arockisamy

    2014-01-01

    Online education programs have been growing rapidly. While it is somehow difficult to specifically quantify quality, many recommendations have been suggested to specify and demonstrate quality of online education touching on common areas of program enhancement and administration. To design a model

  15. Inclusion Professional Development Model and Regular Middle School Educators

    Science.gov (United States)

    Royster, Otelia; Reglin, Gary L.; Losike-Sedimo, Nonofo

    2014-01-01

    The purpose of this study was to determine the impact of a professional development model on regular education middle school teachers' knowledge of best practices for teaching inclusive classes and attitudes toward teaching these classes. There were 19 regular education teachers who taught the core subjects. Findings for Research Question 1…

  16. Guiding and Modelling Quality Improvement in Higher Education Institutions

    Science.gov (United States)

    Little, Daniel

    2015-01-01

    The article considers the process of creating quality improvement in higher education institutions from the point of view of current organisational theory and social-science modelling techniques. The author considers the higher education institution as a functioning complex of rules, norms and other organisational features and reviews the social…

  17. Service learning in teacher education: an institutional model for an ...

    African Journals Online (AJOL)

    Interest in service learning is growing at a time of curriculum change in teacher education and institutional change in higher education in South Africa. This raises the question ";What models are available to guide institutions to develop service learning?"; This article outlines Pollack's typology of institutional responses to ...

  18. Applying the Flipped Classroom Model to English Language Arts Education

    Science.gov (United States)

    Young, Carl A., Ed.; Moran, Clarice M., Ed.

    2017-01-01

    The flipped classroom method, particularly when used with digital video, has recently attracted many supporters within the education field. Now more than ever, language arts educators can benefit tremendously from incorporating flipped classroom techniques into their curriculum. "Applying the Flipped Classroom Model to English Language Arts…

  19. Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico.

    Science.gov (United States)

    McAnulty, Michael J; Yen, Jiun Y; Freedman, Benjamin G; Senger, Ryan S

    2012-05-14

    Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

  20. Mathematical Modeling in Mathematics Education: Basic Concepts and Approaches

    Science.gov (United States)

    Erbas, Ayhan Kürsat; Kertil, Mahmut; Çetinkaya, Bülent; Çakiroglu, Erdinç; Alacaci, Cengiz; Bas, Sinem

    2014-01-01

    Mathematical modeling and its role in mathematics education have been receiving increasing attention in Turkey, as in many other countries. The growing body of literature on this topic reveals a variety of approaches to mathematical modeling and related concepts, along with differing perspectives on the use of mathematical modeling in teaching and…

  1. European Models of Bilingual Education: Practice, Theory and Development.

    Science.gov (United States)

    Beardsmore, Hugo Baetens

    1993-01-01

    European Community initiatives in language management include educational models involved in promoting mastery of at least three languages. The Luxembourg model outlines a trilingual program for the whole school population; the European School model, a complex multilingual program; and the Foyer Project, plans for immigrant minorities to move into…

  2. Adopting a Models-Based Approach to Teaching Physical Education

    Science.gov (United States)

    Casey, Ashley; MacPhail, Ann

    2018-01-01

    Background: The popularised notion of models-based practice (MBP) is one that focuses on the delivery of a model, e.g. Cooperative Learning, Sport Education, Teaching Personal and Social Responsibility, Teaching Games for Understanding. Indeed, while an abundance of research studies have examined the delivery of a single model and some have…

  3. Modeling Students' Memory for Application in Adaptive Educational Systems

    Science.gov (United States)

    Pelánek, Radek

    2015-01-01

    Human memory has been thoroughly studied and modeled in psychology, but mainly in laboratory setting under simplified conditions. For application in practical adaptive educational systems we need simple and robust models which can cope with aspects like varied prior knowledge or multiple-choice questions. We discuss and evaluate several models of…

  4. Indoor Air Quality Building Education and Assessment Model

    Science.gov (United States)

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM), released in 2002, is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  5. Indoor Air Quality Building Education and Assessment Model Forms

    Science.gov (United States)

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  6. A MODEL FOR HIGHER EDUCATION CAMPUS HEALTH SERVICES

    African Journals Online (AJOL)

    2010-03-17

    Mar 17, 2010 ... generation was used to develop a holistic healthcare model for a higher education campus' health service. It became ... innovative. Health plays a .... conducted will set the tone for the interactive process of holistic healthcare.

  7. AN INSTRUCTIONAL DESIGN MODEL FOR BLENDED HIGHER EDUCATION

    Directory of Open Access Journals (Sweden)

    George Hack

    2016-07-01

    Full Text Available Instructional design models that are used by many higher education institutions to guide course design are insufficient for the unique opportunities of blended learning. Many established models are not practical tools for college faculty to use independently in the design of courses. Models like A.D.D.I.E., use a linear approach that can translate more easily into practical stages of course design, yet are historically rooted in the rapid prototyping of educational technologies or for designing military training and are inadequate for the complex demands of higher education, where learning outcomes are geared toward higher order thinking, scientific/clinical reasoning, and a syntheses of ideas into new knowledge. Presented here is an instructional design model that strategically incorporates the nuances of higher education, yet is practically framed to assist faculty with design challenges.

  8. A model for education and promoting food science and technology ...

    African Journals Online (AJOL)

    A model for education and promoting food science and technology among high school students and the public. ... at the tertiary stage (retail) directly with the consumer while depending on the product of FST. ... AJOL African Journals Online.

  9. Modeling Academic Education Processes by Dynamic Storyboarding

    Science.gov (United States)

    Sakurai, Yoshitaka; Dohi, Shinichi; Tsuruta, Setsuo; Knauf, Rainer

    2009-01-01

    In high-level education such as university studies, there is a flexible but complicated system of subject offerings and registration rules such as prerequisite subjects. Those offerings, connected with registration rules, should be matched to the students' learning needs and desires, which change dynamically. Students need assistance in such a…

  10. Career Education Models. Trends and Issues Alert.

    Science.gov (United States)

    Brown, Bettina Lankard

    The evolution of the workplace has required changes in the guidance and counseling practices of career education (CE). Basic elements of CE strategies for enhancing students' career awareness, exploration, and planning are still in place, but contemporary issues such as life-work balance, involuntary career transitions, and mentoring have led to…

  11. Contextualising Craft: Pedagogical Models for Craft Education

    Science.gov (United States)

    Pollanen, Sinikka

    2009-01-01

    Craft education in Finland is, in many aspects, in a state of change. This concerns the independent position of craft as a school subject, the content of the compulsory craft courses containing textiles and technical work, the implementation of the new concept of a holistic craft process in the National Core Curriculum and so on. This bears…

  12. Modeling management of research and education networks

    NARCIS (Netherlands)

    Galagan, D.V.

    2004-01-01

    Computer networks and their services have become an essential part of research and education. Nowadays every modern R&E institution must have a computer network and provide network services to its students and staff. In addition to its internal computer network, every R&E institution must have a

  13. An Amotivation Model in Physical Education

    Science.gov (United States)

    Shen, Bo; Wingert, Robert K.; Li, Weidong; Sun, Haichun; Rukavina, Paul Bernard

    2010-01-01

    Amotivation refers to a state in which individuals cannot perceive a relationship between their behavior and that behavior's subsequent outcome. With the belief that considering amotivation as a multidimensional construct could reflect the complexity of motivational deficits in physical education, we developed this study to validate an amotivation…

  14. Advances in Bayesian Modeling in Educational Research

    Science.gov (United States)

    Levy, Roy

    2016-01-01

    In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…

  15. All about the Human Genome Project (HGP)

    Science.gov (United States)

    ... Care Genomic Medicine Working Group New Horizons and Research Patient Management Policy and Ethics Issues Quick Links for Patient Care Education All About the Human Genome Project Fact Sheets Genetic Education Resources for ...

  16. A model for mentoring newly-appointed nurse educators in nursing education institutions in South Africa.

    Science.gov (United States)

    Seekoe, Eunice

    2014-04-24

    South Africa transformed higher education through the enactment of the Higher Education Act (No. 101 of 1997). The researcher identified the need to develop a model for the mentoring of newly-appointed nurse educators in nursing education institutions in South Africa.  To develop and describe the model for mentoring newly-appointed nurse educators in nursing education institutions in South Africa.  A qualitative and theory-generating design was used (following empirical findings regarding needs analysis) in order to develop the model. The conceptualisation of the framework focused on the context, content, process and the theoretical domains that influenced the model. Ideas from different theories were borrowed from and integrated with the literature and deductive and inductive strategies were applied.  The structure of the model is multidimensional and complex in nature (macro, mesoand micro) based on the philosophy of reflective practice, competency-based practice andcritical learning theories. The assumptions are in relation to stakeholders, context, mentoring, outcome, process and dynamic. The stakeholders are the mentor and mentee within an interactive participatory relationship. The mentoring takes place within the process with a sequence of activities such as relationship building, development, engagement, reflective process and assessment. Capacity building and empowerment are outcomes of mentoring driven by motivation.  The implication for nurse managers is that the model can be used to develop mentoring programmes for newly-appointed nurse educators.

  17. A model for mentoring newly-appointed nurse educators in nursing education institutions in South Africa

    Directory of Open Access Journals (Sweden)

    Eunice Seekoe

    2014-02-01

    Full Text Available Background: South Africa transformed higher education through the enactment of the Higher Education Act (No. 101 of 1997. The researcher identified the need to develop a model for the mentoring of newly-appointed nurse educators in nursing education institutions in South Africa. Objectives: To develop and describe the model for mentoring newly-appointed nurse educators in nursing education institutions in South Africa. Method: A qualitative and theory-generating design was used (following empirical findings regarding needs analysis in order to develop the model. The conceptualisation of the framework focused on the context, content, process and the theoretical domains that influenced the model. Ideas from different theories were borrowed from and integrated with the literature and deductive and inductive strategies were applied. Results: The structure of the model is multidimensional and complex in nature (macro, mesoand micro based on the philosophy of reflective practice, competency-based practice andcritical learning theories. The assumptions are in relation to stakeholders, context, mentoring, outcome, process and dynamic. The stakeholders are the mentor and mentee within an interactive participatory relationship. The mentoring takes place within the process with a sequence of activities such as relationship building, development, engagement, reflective process and assessment. Capacity building and empowerment are outcomes of mentoring driven by motivation. Conclusion: The implication for nurse managers is that the model can be used to develop mentoring programmes for newly-appointed nurse educators.

  18. Whole Genome and Global Gene Expression Analyses of the Model Mushroom Flammulina velutipes Reveal a High Capacity for Lignocellulose Degradation

    Science.gov (United States)

    Park, Young-Jin; Baek, Jeong Hun; Lee, Seonwook; Kim, Changhoon; Rhee, Hwanseok; Kim, Hyungtae; Seo, Jeong-Sun; Park, Hae-Ran; Yoon, Dae-Eun; Nam, Jae-Young; Kim, Hong-Il; Kim, Jong-Guk; Yoon, Hyeokjun; Kang, Hee-Wan; Cho, Jae-Yong; Song, Eun-Sung; Sung, Gi-Ho; Yoo, Young-Bok; Lee, Chang-Soo; Lee, Byoung-Moo; Kong, Won-Sik

    2014-01-01

    Flammulina velutipes is a fungus with health and medicinal benefits that has been used for consumption and cultivation in East Asia. F. velutipes is also known to degrade lignocellulose and produce ethanol. The overlapping interests of mushroom production and wood bioconversion make F. velutipes an attractive new model for fungal wood related studies. Here, we present the complete sequence of the F. velutipes genome. This is the first sequenced genome for a commercially produced edible mushroom that also degrades wood. The 35.6-Mb genome contained 12,218 predicted protein-encoding genes and 287 tRNA genes assembled into 11 scaffolds corresponding with the 11 chromosomes of strain KACC42780. The 88.4-kb mitochondrial genome contained 35 genes. Well-developed wood degrading machinery with strong potential for lignin degradation (69 auxiliary activities, formerly FOLymes) and carbohydrate degradation (392 CAZymes), along with 58 alcohol dehydrogenase genes were highly expressed in the mycelium, demonstrating the potential application of this organism to bioethanol production. Thus, the newly uncovered wood degrading capacity and sequential nature of this process in F. velutipes, offer interesting possibilities for more detailed studies on either lignin or (hemi-) cellulose degradation in complex wood substrates. The mutual interest in wood degradation by the mushroom industry and (ligno-)cellulose biomass related industries further increase the significance of F. velutipes as a new model. PMID:24714189

  19. Looping and clustering model for the organization of protein-DNA complexes on the bacterial genome

    Science.gov (United States)

    Walter, Jean-Charles; Walliser, Nils-Ole; David, Gabriel; Dorignac, Jérôme; Geniet, Frédéric; Palmeri, John; Parmeggiani, Andrea; Wingreen, Ned S.; Broedersz, Chase P.

    2018-03-01

    The bacterial genome is organized by a variety of associated proteins inside a structure called the nucleoid. These proteins can form complexes on DNA that play a central role in various biological processes, including chromosome segregation. A prominent example is the large ParB-DNA complex, which forms an essential component of the segregation machinery in many bacteria. ChIP-Seq experiments show that ParB proteins localize around centromere-like parS sites on the DNA to which ParB binds specifically, and spreads from there over large sections of the chromosome. Recent theoretical and experimental studies suggest that DNA-bound ParB proteins can interact with each other to condense into a coherent 3D complex on the DNA. However, the structural organization of this protein-DNA complex remains unclear, and a predictive quantitative theory for the distribution of ParB proteins on DNA is lacking. Here, we propose the looping and clustering model, which employs a statistical physics approach to describe protein-DNA complexes. The looping and clustering model accounts for the extrusion of DNA loops from a cluster of interacting DNA-bound proteins that is organized around a single high-affinity binding site. Conceptually, the structure of the protein-DNA complex is determined by a competition between attractive protein interactions and loop closure entropy of this protein-DNA cluster on the one hand, and the positional entropy for placing loops within the cluster on the other. Indeed, we show that the protein interaction strength determines the ‘tightness’ of the loopy protein-DNA complex. Thus, our model provides a theoretical framework for quantitatively computing the binding profiles of ParB-like proteins around a cognate (parS) binding site.

  20. A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction

    Science.gov (United States)

    De Oliveira Martins, Leonardo; Mallo, Diego; Posada, David

    2016-01-01

    Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models. PMID:25281847

  1. Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

    Energy Technology Data Exchange (ETDEWEB)

    Racle, Julien; Hatzimanikatis, Vassily, E-mail: vassily.hatzimanikatis@epfl.ch [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland); Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne (Switzerland); Stefaniuk, Adam Jan [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland)

    2015-07-28

    Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.

  2. A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction.

    Science.gov (United States)

    De Oliveira Martins, Leonardo; Mallo, Diego; Posada, David

    2016-05-01

    Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

  3. Public Health Genomics education in post-graduate schools of hygiene and preventive medicine: a cross-sectional survey.

    Science.gov (United States)

    Ianuale, Carolina; Leoncini, Emanuele; Mazzucco, Walter; Marzuillo, Carolina; Villari, Paolo; Ricciardi, Walter; Boccia, Stefania

    2014-10-10

    The relevance of Public Health Genomics (PHG) education among public health specialists has been recently acknowledged by the Association of Schools of Public Health in the European Region. The aim of this cross-sectional survey was to assess the prevalence of post-graduate public health schools for medical doctors which offer PHG training in Italy. The directors of the 33 Italian public health schools were interviewed for the presence of a PHG course in place. We stratified by geographical area (North, Centre and South) of the schools. We performed comparisons of categorical data using the chi-squared test. The response rate was 73% (24/33 schools). Among respondents, 15 schools (63%) reported to have at least one dedicated course in place, while nine (38%) did not, with a significant geographic difference. Results showed a good implementation of courses in PHG discipline in Italian post-graduate public health schools. However further harmonization of the training programs of schools in public health at EU level is needed.

  4. Model SNP development for complex genomes based on hexaploid oat using high-throughput 454 sequencing technology

    Directory of Open Access Journals (Sweden)

    Chao Shiaoman

    2011-01-01

    a model for SNP discovery and genotyping in other species with complex and poorly-characterized genomes.

  5. In search of a Croatian model of nursing education.

    Science.gov (United States)

    Simunovic, Vladimir J; Zupanovic, Marija; Mihanovic, Frane; Zemunik, Tatijana; Bradaric, Nikola; Jankovic, Stipan

    2010-10-01

    To analyze the present status and ongoing reforms of nursing education in Europe, to compare it with the situation in Croatia, and to propose a new educational model that corresponds to the needs of the Croatian health care system. The literature on contemporary nursing education in Europe and North America was reviewed, together with European Commission directives and regulations, as well as pertinent World Health Organization documents. In addition, 20 recent annual reports from 2003-2009, submitted by national nursing associations to the Workgroup of European Nurse Researchers (WERN), were studied. After appraisal of current trends, the Working Group on Reform of Nursing Education drafted The Croatian Model for Education in Nursing and developed a three-cycle curriculum with syllabus. The proposed curriculum is radically different from traditional ones. Responding to modern demands, it focuses on outcomes (developing competencies) and is evidence-based. A new, Croatian concept of nursing education is presented that is concordant with reforms in nursing education in other European countries. It holds promise for making nursing education an integral part of a unified European system of higher education.

  6. Models in Science Education: Applications of Models in Learning and Teaching Science

    Science.gov (United States)

    Ornek, Funda

    2008-01-01

    In this paper, I discuss different types of models in science education and applications of them in learning and teaching science, in particular physics. Based on the literature, I categorize models as conceptual and mental models according to their characteristics. In addition to these models, there is another model called "physics model" by the…

  7. Phenotypic and genomic comparison of Mycobacterium aurum and surrogate model species to Mycobacterium tuberculosis: implications for drug discovery.

    Science.gov (United States)

    Namouchi, Amine; Cimino, Mena; Favre-Rochex, Sandrine; Charles, Patricia; Gicquel, Brigitte

    2017-07-13

    Tuberculosis (TB) is caused by Mycobacterium tuberculosis and represents one of the major challenges facing drug discovery initiatives worldwide. The considerable rise in bacterial drug resistance in recent years has led to the need of new drugs and drug regimens. Model systems are regularly used to speed-up the drug discovery process and circumvent biosafety issues associated with manipulating M. tuberculosis. These include the use of strains such as Mycobacterium smegmatis and Mycobacterium marinum that can be handled in biosafety level 2 facilities, making high-throughput screening feasible. However, each of these model species have their own limitations. We report and describe the first complete genome sequence of Mycobacterium aurum ATCC23366, an environmental mycobacterium that can also grow in the gut of humans and animals as part of the microbiota. This species shows a comparable resistance profile to that of M. tuberculosis for several anti-TB drugs. The aims of this study were to (i) determine the drug resistance profile of a recently proposed model species, Mycobacterium aurum, strain ATCC23366, for anti-TB drug discovery as well as Mycobacterium smegmatis and Mycobacterium marinum (ii) sequence and annotate the complete genome sequence of this species obtained using Pacific Bioscience technology (iii) perform comparative genomics analyses of the various surrogate strains with M. tuberculosis (iv) discuss how the choice of the surrogate model used for drug screening can affect the drug discovery process. We describe the complete genome sequence of M. aurum, a surrogate model for anti-tuberculosis drug discovery. Most of the genes already reported to be associated with drug resistance are shared between all the surrogate strains and M. tuberculosis. We consider that M. aurum might be used in high-throughput screening for tuberculosis drug discovery. We also highly recommend the use of different model species during the drug discovery screening process.

  8. The Danish apprenticeship system and the Nordic model of education

    DEFF Research Database (Denmark)

    Jørgensen, Christian Helms

    during the latest decades. This is seen especially in three areas: VET as an instrument for social inclusion of disadvantaged youth, the state initiative to establish school-based training (training centres) and an initiative for unification of vocational and general education (the eux programme)......The paper examines the development of initial vocational education and training (VET) in Denmark in relation to the Nordic model of education. The egalitarian ideal of this model is to provide equal opportunities for education for all at all levels. This ideal has been pursued by policies in all...... the Nordic countries to establish public, free and comprehensive schooling. Key principles are the equal access for all regardless of social background and gender, and full permeability from the lowest to the highest levels with no dead ends in the education system (Blossing et al., 2014). This implies...

  9. Limitations to estimating bacterial cross-speciestransmission using genetic and genomic markers: inferencesfrom simulation modeling

    Science.gov (United States)

    Julio Andre, Benavides; Cross, Paul C.; Luikart, Gordon; Scott, Creel

    2014-01-01

    Cross-species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological scenarios. We used a simulation model with two host species and known transmission rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phylogeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole-genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced.

  10. The Genome Sequence of Leishmania (Leishmania) amazonensis: Functional Annotation and Extended Analysis of Gene Models

    Science.gov (United States)

    Real, Fernando; Vidal, Ramon Oliveira; Carazzolle, Marcelo Falsarella; Mondego, Jorge Maurício Costa; Costa, Gustavo Gilson Lacerda; Herai, Roberto Hirochi; Würtele, Martin; de Carvalho, Lucas Miguel; e Ferreira, Renata Carmona; Mortara, Renato Arruda; Barbiéri, Clara Lucia; Mieczkowski, Piotr; da Silveira, José Franco; Briones, Marcelo Ribeiro da Silva; Pereira, Gonçalo Amarante Guimarães; Bahia, Diana

    2013-01-01

    We present the sequencing and annotation of the Leishmania (Leishmania) amazonensis genome, an etiological agent of human cutaneous leishmaniasis in the Amazon region of Brazil. L. (L.) amazonensis shares features with Leishmania (L.) mexicana but also exhibits unique characteristics regarding geographical distribution and clinical manifestations of cutaneous lesions (e.g. borderline disseminated cutaneous leishmaniasis). Predicted genes were scored for orthologous gene families and conserved domains in comparison with other human pathogenic Leishmania spp. Carboxypeptidase, aminotransferase, and 3′-nucleotidase genes and ATPase, thioredoxin, and chaperone-related domains were represented more abundantly in L. (L.) amazonensis and L. (L.) mexicana species. Phylogenetic analysis revealed that these two species share groups of amastin surface proteins unique to the genus that could be related to specific features of disease outcomes and host cell interactions. Additionally, we describe a hypothetical hybrid interactome of potentially secreted L. (L.) amazonensis proteins and host proteins under the assumption that parasite factors mimic their mammalian counterparts. The model predicts an interaction between an L. (L.) amazonensis heat-shock protein and mammalian Toll-like receptor 9, which is implicated in important immune responses such as cytokine and nitric oxide production. The analysis presented here represents valuable information for future studies of leishmaniasis pathogenicity and treatment. PMID:23857904

  11. ATM-deficiency increases genomic instability and metastatic potential in a mouse model of pancreatic cancer.

    Science.gov (United States)

    Drosos, Yiannis; Escobar, David; Chiang, Ming-Yi; Roys, Kathryn; Valentine, Virginia; Valentine, Marc B; Rehg, Jerold E; Sahai, Vaibhav; Begley, Lesa A; Ye, Jianming; Paul, Leena; McKinnon, Peter J; Sosa-Pineda, Beatriz

    2017-09-11

    Germline mutations in ATM (encoding the DNA-damage signaling kinase, ataxia-telangiectasia-mutated) increase Familial Pancreatic Cancer (FPC) susceptibility, and ATM somatic mutations have been identified in resected human pancreatic tumors. Here we investigated how Atm contributes to pancreatic cancer by deleting this gene in a murine model of the disease expressing oncogenic Kras (Kras G12D ). We show that partial or total ATM deficiency cooperates with Kras G12D to promote highly metastatic pancreatic cancer. We also reveal that ATM is activated in pancreatic precancerous lesions in the context of DNA damage and cell proliferation, and demonstrate that ATM deficiency leads to persistent DNA damage in both precancerous lesions and primary tumors. Using low passage cultures from primary tumors and liver metastases we show that ATM loss accelerates Kras-induced carcinogenesis without conferring a specific phenotype to pancreatic tumors or changing the status of the tumor suppressors p53, p16 Ink4a and p19 Arf . However, ATM deficiency markedly increases the proportion of chromosomal alterations in pancreatic primary tumors and liver metastases. More importantly, ATM deficiency also renders murine pancreatic tumors highly sensitive to radiation. These and other findings in our study conclusively establish that ATM activity poses a major barrier to oncogenic transformation in the pancreas via maintaining genomic stability.

  12. Revisiting the chlorophyll biosynthesis pathway using genome scale metabolic model of Oryza sativa japonica

    Science.gov (United States)

    Chatterjee, Ankita; Kundu, Sudip

    2015-01-01

    Chlorophyll is one of the most important pigments present in green plants and rice is one of the major food crops consumed worldwide. We curated the existing genome scale metabolic model (GSM) of rice leaf by incorporating new compartment, reactions and transporters. We used this modified GSM to elucidate how the chlorophyll is synthesized in a leaf through a series of bio-chemical reactions spanned over different organelles using inorganic macronutrients and light energy. We predicted the essential reactions and the associated genes of chlorophyll synthesis and validated against the existing experimental evidences. Further, ammonia is known to be the preferred source of nitrogen in rice paddy fields. The ammonia entering into the plant is assimilated in the root and leaf. The focus of the present work is centered on rice leaf metabolism. We studied the relative importance of ammonia transporters through the chloroplast and the cytosol and their interlink with other intracellular transporters. Ammonia assimilation in the leaves takes place by the enzyme glutamine synthetase (GS) which is present in the cytosol (GS1) and chloroplast (GS2). Our results provided possible explanation why GS2 mutants show normal growth under minimum photorespiration and appear chlorotic when exposed to air. PMID:26443104

  13. Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

    Science.gov (United States)

    Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

    2014-11-01

    We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science.

  14. Mixture Modeling: Applications in Educational Psychology

    Science.gov (United States)

    Harring, Jeffrey R.; Hodis, Flaviu A.

    2016-01-01

    Model-based clustering methods, commonly referred to as finite mixture modeling, have been applied to a wide variety of cross-sectional and longitudinal data to account for heterogeneity in population characteristics. In this article, we elucidate 2 such approaches: growth mixture modeling and latent profile analysis. Both techniques are…

  15. BOLOGNA MODEL OF MEDICAL EDUCATION-UTOPIA OR REALITY.

    Science.gov (United States)

    Zunic, Lejla; Donev, Doncho

    2016-07-24

    Higher education in Europe and in the Balkan's countries is undergoing major reforms. The Bologna Process was a major reform created with the claimed goal of providing responses to issues such as the public responsibility for higher education and research, higher education governance, the social dimension of higher education and research, and the values and roles of higher education and research in modern, globalized, and increasingly complex societies with the most demanding qualification needs. Changes in the curricula, modernization of facilities and their alignment with the programs of other European universities, employment of a larger number of assistants, especially in the clinical courses at our universities are necessary. Also, it is necessary to continue to conduct further detailed analysis and evaluation of teaching content and outcomes in the future. In this review authors expressed their views and experience of using Bologna model of education in the Balkan's countries with emphasis on Bosnia and Herzegovina and the Republic of Macedonia.

  16. Promoting Excellence in Nursing Education (PENE): Pross evaluation model.

    Science.gov (United States)

    Pross, Elizabeth A

    2010-08-01

    The purpose of this article is to examine the Promoting Excellence in Nursing Education (PENE) Pross evaluation model. A conceptual evaluation model, such as the one described here, may be useful to nurse academicians in the ongoing evaluation of educational programs, especially those with goals of excellence. Frameworks for evaluating nursing programs are necessary because they offer a way to systematically assess the educational effectiveness of complex nursing programs. This article describes the conceptual framework and its tenets of excellence. Copyright 2009 Elsevier Ltd. All rights reserved.

  17. Maturity Model of Software Product with Educational Maturity Model

    OpenAIRE

    R.Manjula; J.Vaideeswaran

    2011-01-01

    Software product line engineering is an inter-disciplinary concept. It spans the dimensions of business, architecture, process,and the organization. Similarly, Education System engineering is also an inter-disciplinary concept, which spans the dimensions of academic, infrastructure, facilities, administration etc. Some of the potential benefits of this approach includecontinuous improvements in System quality and adhering to global standards. The increasing competency in IT and Educational Se...

  18. Leadership Competence Educational Model for a Twenty-First Century Nursing Doctoral Education in Contemporary Turkey

    Science.gov (United States)

    Terzioglu, Fusun

    2011-01-01

    In this article, the author proposes a nursing education model about leadership that can be used to improve the leadership skills of nursing doctoral students. This model is developed at the University of Michigan School of Nursing. In developing this model, the author had the opportunity to observe the University of Michigan, School of Nursing…

  19. Leader as visionary. Leadership education model.

    Science.gov (United States)

    Aroian, Jane

    2002-01-01

    Developing nurse leaders for today and tomorrow is a priority considering the powerful relationship between leadership strength and the influence of the nursing profession in the future of health care. This article addresses leadership theories and research as they relate to visionary leadership. Education for visionary leadership is also addressed including the competencies and skill sets for effective visionary leaders. Visioning is a powerful force for change in shaping organizations and building teams for the future.

  20. Information Life-Cycle Management at the Erasmus Medical Center : Collaboratively Managing Digital Data for Care, Research, Education and the International Development of the GLOBE 3D Genome Viewer

    NARCIS (Netherlands)

    T.A. Knoch (Tobias); P. Walgemoed; H.J.F.M.M. Eussen (Bert)

    2006-01-01

    textabstractInformation Lifecycle Management at the Erasmus University Medical Centre. Collaboratively managing digital data for care, research and education using the international development of the GLOBE 3D Genome Viewer and Erasmus Computing Grid as catalyzing initiatives. The