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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. Genomics Analogy Model for Educators (GAME): From Jumping Genes to Alternative Splicing

    Science.gov (United States)

    Corn, Joanie; Pittendrigh, Barry R.; Orvis, Kathryn S.

    2004-01-01

    Studies have shown that there is usually a lack of understanding concerning the fields of genetics and genomics among high school students (Lewis and Wood-Robinson, 2000). A recent article (Kirkpatrick et al, 2002) introduced the GAME (Genomics Analogy Model for Educators) model and two of its components: (1) explaining sequencing technology with…

  3. Genome-Scale Models

    DEFF Research Database (Denmark)

    Bergdahl, Basti; Sonnenschein, Nikolaus; Machado, Daniel

    2016-01-01

    An introduction to genome-scale models, how to build and use them, will be given in this chapter. Genome-scale models have become an important part of systems biology and metabolic engineering, and are increasingly used in research, both in academica and in industry, both for modeling chemical pr...

  4. Genomic Feature Models

    DEFF Research Database (Denmark)

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

    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-additive g...... 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. Genomics Analogy Model for Educators (GAME): Fuzzy DNA Model to Enable the Learning of Gene Sequencing by Visually-Impaired and Blind Students

    Science.gov (United States)

    Butler, Charles; Bello, Julia; York, Alan; Orvis, Kathryn; Pittendrigh, Barry R.

    2008-01-01

    Much of the general population is aware of terms such as biotechnology, genetic engineering, and genomics. However, there is a lack of understanding concerning these fields among many secondary school students. Few teaching models exist to explain concepts behind genomics and even less are available for teaching the visually impaired and blind.…

  8. 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)

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

  12. Modern Media Education Models

    Science.gov (United States)

    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,…

  13. 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.

  14. Cancer genomics object model: an object model for multiple functional genomics data for cancer research.

    Science.gov (United States)

    Park, Yu Rang; Lee, Hye Won; Cho, Sung Bum; Kim, Ju Han

    2007-01-01

    The development of functional genomics including transcriptomics, proteomics and metabolomics allow us to monitor a large number of key cellular pathways simultaneously. Several technology-specific data models have been introduced for the representation of functional genomics experimental data, including the MicroArray Gene Expression-Object Model (MAGE-OM), the Proteomics Experiment Data Repository (PEDRo), and the Tissue MicroArray-Object Model (TMA-OM). Despite the increasing number of cancer studies using multiple functional genomics technologies, there is still no integrated data model for multiple functional genomics experimental and clinical data. We propose an object-oriented data model for cancer genomics research, Cancer Genomics Object Model (CaGe-OM). We reference four data models: Functional Genomic-Object Model, MAGE-OM, TMAOM and PEDRo. The clinical and histopathological information models are created by analyzing cancer management workflow and referencing the College of American Pathology Cancer Protocols and National Cancer Institute Common Data Elements. The CaGe-OM provides a comprehensive data model for integrated storage and analysis of clinical and multiple functional genomics data.

  15. Teaching strategies to incorporate genomics education into academic nursing curricula.

    Science.gov (United States)

    Quevedo Garcia, Sylvia P; Greco, Karen E; Loescher, Lois J

    2011-11-01

    The translation of genomic science into health care has expanded our ability to understand the effects of genomics on human health and disease. As genomic advances continue, nurses are expected to have the knowledge and skills to translate genomic information into improved patient care. This integrative review describes strategies used to teach genomics in academic nursing programs and their facilitators and barriers to inclusion in nursing curricula. The Learning Engagement Model and the Diffusion of Innovations Theory guided the interpretation of findings. CINAHL, Medline, and Web of Science were resources for articles published during the past decade that included strategies for teaching genomics in academic nursing programs. Of 135 articles, 13 met criteria for review. Examples of effective genomics teaching strategies included clinical application through case studies, storytelling, online genomics resources, student self-assessment, guest lecturers, and a genetics focus group. Most strategies were not evaluated for effectiveness.

  16. MODERN MEDIA EDUCATION MODELS

    Directory of Open Access Journals (Sweden)

    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.

  17. Advances in Swine biomedical Model Genomics

    Science.gov (United States)

    This manuscript is a short update on the diversity of swine biomedical models and the importance of genomics in their continued development. The swine has been used as a major mammalian model for human studies because of the similarity in size and physiology, and in organ development and disease pro...

  18. 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 markers...... are unsatisfactory. Here we address this problem and describe a reparameterization of a WGRR model, based on an eigenvalue decomposition, for simultaneous inference of parameters and unobserved population structure. This allows estimation of genomic parameters with and without inclusion of marker......-derived eigenvectors that account for stratification. The method is illustrated with grain yield in wheat typed for 1279 genetic markers, and with height, HDL cholesterol and systolic blood pressure from the British 1958 cohort study typed for 1 million SNP genotypes. Both sets of data show signs of population...

  19. 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.

  20. Disentangling Pleiotropy along the Genome using Sparse Latent Variable Models

    DEFF Research Database (Denmark)

    Janss, Luc

    Bayesian models are described that use atent variables to model covariances. These models are flexible, scale up linearly in the number of traits, and allow separating covariance structures in different components at the trait level and at the genomic level. Multi-trait version of the BayesA (MT......-BA) and Bayesian LASSO (MT-BL) are described that model heterogeneous variance and covariance over the genome, and a model that directly models multiple genomic breeding values (MT-MG), representing different genomic covariance structures. The models are demonstrated on a mouse data set to model the genomic...

  1. Genome scale metabolic modeling of cancer

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens

    2016-01-01

    been used as scaffolds for analysis of high throughput data to allow mechanistic interpretation of changes in expression. Finally, GEMs allow quantitative flux predictions using flux balance analysis (FBA). Here we critically review the requirements for successful FBA simulations of cancer cells......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...... 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...

  2. Merging Marine Ecosystem Models and Genomics

    Science.gov (United States)

    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.

  3. Testing the effects of educational strategies on comprehension of a genomic concept using virtual reality technology.

    Science.gov (United States)

    Kaphingst, Kimberly A; Persky, Susan; McCall, Cade; Lachance, Christina; Loewenstein, Johanna; Beall, Andrew C; Blascovich, Jim

    2009-11-01

    Applying genetic susceptibility information to improve health will likely require educating patients about abstract concepts, for which there is little existing research. This experimental study examined the effect of learning mode on comprehension of a genomic concept. 156 individuals aged 18-40 without specialized knowledge were randomly assigned to either a virtual reality active learning or didactic learning condition. The outcome was comprehension (recall, transfer, mental models). Change in recall was greater for didactic learning than for active learning (pconcepts. Didactic, interpersonal health education approaches may be more effective than interactive games in educating patients about abstract, unfamiliar concepts. These findings indicate the importance of traditional health education approaches in emerging areas like genomics.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. 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

    Genotyping-by-sequencing (GBSeq) is becoming a cost-effective genotyping platform for species without available SNP arrays. GBSeq considers to sequence short reads from restriction sites covering a limited part of the genome (e.g., 5-10%) with low sequencing depth per individual (e.g., 5-10X per....... 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...

  6. 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)

  7. The human genome, implications for oral health and diseases, and dental education.

    Science.gov (United States)

    Slavkin, H C

    2001-05-01

    We are living in an extraordinary time in human history punctuated by the convergence of major scientific and technological progress in the physical, chemical, and biological ways of knowing. Equally extraordinary are the sparkling intellectual developments at the interface between fields of study. One major example of an emerging influence on the future of oral health education is at the interface between the human genome, information technology, and biotechnology with miniaturizations (nanotechnology), suggesting new oral health professional competencies for a new century. A great deal has recently been learned from human and non-human genomics. Genome databases are being "mined" to prompt hypothesis-driven "postgenomic" or functional genomic science in microbial models such as Candida albicans related to oral candidiasis and in human genomics related to biological processes found in craniofacial, oral, and dental diseases and disorders. This growing body of knowledge is already providing the gene content of many oral microbial and human genomes and the knowledge of genetic variants or polymorphisms related to disease, disease progression, and disease response to therapeutics (pharmacogenomics). The knowledge base from human and non-human genomics, functional genomics, biotechnology, and associated information technologies is serving to revolutionize oral health promotion, risk assessment using biomarkers and disease prevention, diagnostics, treatments, and the full range of therapeutics for craniofacial, oral, and dental diseases and disorders. Education, training, and research opportunities are already transforming the curriculum and pedagogy for undergraduate science majors, predoctoral health professional programs, residency and specialty programs, and graduate programs within the health professions. In the words of Bob Dylan, "the times they are a-changing."

  8. 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...... 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...... 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...

  9. 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…

  10. 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 proces

  11. Models of educational institutions' networking

    OpenAIRE

    Shilova Olga Nikolaevna

    2015-01-01

    The importance of educational institutions' networking in modern sociocultural conditions and a definition of networking in education are presented in the article. The results of research levels, methods and models of educational institutions' networking are presented and substantially disclosed.

  12. Models of educational institutions' networking

    OpenAIRE

    Shilova Olga Nikolaevna

    2015-01-01

    The importance of educational institutions' networking in modern sociocultural conditions and a definition of networking in education are presented in the article. The results of research levels, methods and models of educational institutions' networking are presented and substantially disclosed.

  13. 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.

  14. 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.

  15. 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

  16. An Integrative Breakage Model of genome architecture, reshuffling and evolution: The Integrative Breakage Model of genome evolution, a novel multidisciplinary hypothesis for the study of genome plasticity.

    Science.gov (United States)

    Farré, Marta; Robinson, Terence J; Ruiz-Herrera, Aurora

    2015-05-01

    Our understanding of genomic reorganization, the mechanics of genomic transmission to offspring during germ line formation, and how these structural changes contribute to the speciation process, and genetic disease is far from complete. Earlier attempts to understand the mechanism(s) and constraints that govern genome remodeling suffered from being too narrowly focused, and failed to provide a unified and encompassing view of how genomes are organized and regulated inside cells. Here, we propose a new multidisciplinary Integrative Breakage Model for the study of genome evolution. The analysis of the high-level structural organization of genomes (nucleome), together with the functional constrains that accompany genome reshuffling, provide insights into the origin and plasticity of genome organization that may assist with the detection and isolation of therapeutic targets for the treatment of complex human disorders. © 2015 WILEY Periodicals, Inc.

  17. Educational Data Mining Model Using Rattle

    Directory of Open Access Journals (Sweden)

    Sadiq Hussain

    2014-07-01

    Full Text Available Data Mining is the extraction of knowledge from the large databases. Data Mining had affected all the fields from combating terror attacks to the human genome databases. For different data analysis, R programming has a key role to play. Rattle, an effective GUI for R Programming is used extensively for generating reports based on several current trends models like random forest, support vector machine etc. It is otherwise hard to compare which model to choose for the data that needs to be mined. This paper proposes a method using Rattle for selection of Educational Data Mining Model.

  18. Modeling genomic regulatory networks with big data.

    Science.gov (United States)

    Bolouri, Hamid

    2014-05-01

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

  19. Modeling cancer metabolism on a genome scale

    Science.gov (United States)

    Yizhak, Keren; Chaneton, Barbara; Gottlieb, Eyal; Ruppin, Eytan

    2015-01-01

    Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome-scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network-level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field. PMID:26130389

  20. 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.

  1. 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

  2. Building a data sharing model for global genomic research.

    Science.gov (United States)

    Kosseim, Patricia; Dove, Edward S; Baggaley, Carman; Meslin, Eric M; Cate, Fred H; Kaye, Jane; Harris, Jennifer R; Knoppers, Bartha M

    2014-08-11

    Data sharing models designed to facilitate global business provide insights for improving transborder genomic data sharing. We argue that a flexible, externally endorsed, multilateral arrangement, combined with an objective third-party assurance mechanism, can effectively balance privacy with the need to share genomic data globally.

  3. 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

  4. 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

  5. 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

  6. Teacher educators modelling their teachers?

    NARCIS (Netherlands)

    Timmerman, Greetje

    2009-01-01

    The teacher educator is always also a teacher, and as a role model may have an important impact on student teachers' views on teaching. However, what is the impact of these teacher educator's own role models on their teaching views and practices? Do teacher educators simply imitate the positive role

  7. Modeling Educational Usage of Facebook

    Science.gov (United States)

    Mazman, Sacide Guzin; Usluel, Yasemin Kocak

    2010-01-01

    The purpose of this study is to design a structural model explaining how users could utilize Facebook for educational purposes. In order to shed light on the educational usage of Facebook, in constructing the model, the relationship between users' Facebook adoption processes and their educational use of Facebook were included indirectly while the…

  8. Modeling Educational Usage of Facebook

    Science.gov (United States)

    Mazman, Sacide Guzin; Usluel, Yasemin Kocak

    2010-01-01

    The purpose of this study is to design a structural model explaining how users could utilize Facebook for educational purposes. In order to shed light on the educational usage of Facebook, in constructing the model, the relationship between users' Facebook adoption processes and their educational use of Facebook were included indirectly while the…

  9. Teacher educators modelling their teachers?

    NARCIS (Netherlands)

    Timmerman, Greetje

    2009-01-01

    The teacher educator is always also a teacher, and as a role model may have an important impact on student teachers' views on teaching. However, what is the impact of these teacher educator's own role models on their teaching views and practices? Do teacher educators simply imitate the positive role

  10. Healthcare management-training and education in the genomic era.

    Science.gov (United States)

    Betta, Michela; Clulow, Val

    2005-01-01

    Increasingly the rapid developments by scientists working in the new business sector of biotechnology are being thrust into mainstream news reports. The incredible pace of the creation of neo-knowledge recently leads us to believe there has not been enough time between events for the healthcare sector, the general public, the legislators or the ethicists to reflect and conduct the checks and balances required for thoughtful progress. The decline of the hospital and the emergence of the laboratory as a consequence of the advent of the genomic era signal a profound shift, which will have unprecedented impacts on professionals in the healthcare system and its repercussions will force explicit changes in their education.

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

    DEFF Research Database (Denmark)

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

    2004-01-01

    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.......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 metabolic...

  12. Electronic Education System Model-2

    Science.gov (United States)

    Güllü, Fatih; Kuusik, Rein; Laanpere, Mart

    2015-01-01

    In this study we presented new EES Model-2 extended from EES model for more productive implementation in e-learning process design and modelling in higher education. The most updates were related to uppermost instructional layer. We updated learning processes object of the layer for adaptation of educational process for young and old people,…

  13. Azolla - A Model Organism for Plant Genomic Studies

    Institute of Scientific and Technical Information of China (English)

    Yin-Long Qiu; Jun Yu

    2003-01-01

    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.

  14. Azolla—A Model Organism for Plant Genomic Studies

    Institute of Scientific and Technical Information of China (English)

    Yin-LongQiu; JunYu

    2003-01-01

    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.

  15. 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...

  16. Educational Game Development Models

    Directory of Open Access Journals (Sweden)

    Mehmet Emin Korkusuz

    2013-12-01

    Full Text Available Recent research on the subject shows that students spend more time on computer games than other activities such as reading book or watching TV. It is possible that this time-consuming activity can become much more effective by educator-game sector cooperation. Which type of game students prefer mostly; how the educational content can be articulated the games without diminishing the playability and enjoyableness of it; and the impact of the competition in the games on process and students are just several titles examined in the studies. This scope presents the types of computer game, qualities of educational games, and educational games designs which are recommended for developing educational games. It also presents a set of knowledge about the importance of educational games in mathematics and physic education, and some studies on this field. In the scope, some strategies, about educational game development process, are recommended educators and software developers in the sector who intend to develop educational games based on the literature.

  17. Network Based Prediction Model for Genomics Data Analysis*

    OpenAIRE

    Huang, Ying; Wang, Pei

    2012-01-01

    Biological networks, such as genetic regulatory networks and protein interaction networks, provide important information for studying gene/protein activities. In this paper, we propose a new method, NetBoosting, for incorporating a priori biological network information in analyzing high dimensional genomics data. Specially, we are interested in constructing prediction models for disease phenotypes of interest based on genomics data, and at the same time identifying disease susceptible genes. ...

  18. An infinitesimal model for quantitative trait genomic value prediction.

    Directory of Open Access Journals (Sweden)

    Zhiqiu Hu

    Full Text Available We developed a marker based infinitesimal model for quantitative trait analysis. In contrast to the classical infinitesimal model, we now have new information about the segregation of every individual locus of the entire genome. Under this new model, we propose that the genetic effect of an individual locus is a function of the genome location (a continuous quantity. The overall genetic value of an individual is the weighted integral of the genetic effect function along the genome. Numerical integration is performed to find the integral, which requires partitioning the entire genome into a finite number of bins. Each bin may contain many markers. The integral is approximated by the weighted sum of all the bin effects. We now turn the problem of marker analysis into bin analysis so that the model dimension has decreased from a virtual infinity to a finite number of bins. This new approach can efficiently handle virtually unlimited number of markers without marker selection. The marker based infinitesimal model requires high linkage disequilibrium of all markers within a bin. For populations with low or no linkage disequilibrium, we develop an adaptive infinitesimal model. Both the original and the adaptive models are tested using simulated data as well as beef cattle data. The simulated data analysis shows that there is always an optimal number of bins at which the predictability of the bin model is much greater than the original marker analysis. Result of the beef cattle data analysis indicates that the bin model can increase the predictability from 10% (multiple marker analysis to 33% (multiple bin analysis. The marker based infinitesimal model paves a way towards the solution of genetic mapping and genomic selection using the whole genome sequence data.

  19. Gremlin: an interactive visualization model for analyzing genomic rearrangements.

    Science.gov (United States)

    O'Brien, Trevor M; Ritz, Anna M; Raphael, Benjamin J; Laidlaw, David H

    2010-01-01

    In this work we present, apply, and evaluate a novel, interactive visualization model for comparative analysis of structural variants and rearrangements in human and cancer genomes, with emphasis on data integration and uncertainty visualization. To support both global trend analysis and local feature detection, this model enables explorations continuously scaled from the high-level, complete genome perspective, down to the low-level, structural rearrangement view, while preserving global context at all times. We have implemented these techniques in Gremlin, a genomic rearrangement explorer with multi-scale, linked interactions, which we apply to four human cancer genome data sets for evaluation. Using an insight-based evaluation methodology, we compare Gremlin to Circos, the state-of-the-art in genomic rearrangement visualization, through a small user study with computational biologists working in rearrangement analysis. Results from user study evaluations demonstrate that this visualization model enables more total insights, more insights per minute, and more complex insights than the current state-of-the-art for visual analysis and exploration of genome rearrangements.

  20. Quantitative genetics model as the unifying model for defining genomic relationship and inbreeding coefficient.

    Science.gov (United States)

    Wang, Chunkao; Da, Yang

    2014-01-01

    The traditional quantitative genetics model was used as the unifying approach to derive six existing and new definitions of genomic additive and dominance relationships. The theoretical differences of these definitions were in the assumptions of equal SNP effects (equivalent to across-SNP standardization), equal SNP variances (equivalent to within-SNP standardization), and expected or sample SNP additive and dominance variances. The six definitions of genomic additive and dominance relationships on average were consistent with the pedigree relationships, but had individual genomic specificity and large variations not observed from pedigree relationships. These large variations may allow finding least related genomes even within the same family for minimizing genomic relatedness among breeding individuals. The six definitions of genomic relationships generally had similar numerical results in genomic best linear unbiased predictions of additive effects (GBLUP) and similar genomic REML (GREML) estimates of additive heritability. Predicted SNP dominance effects and GREML estimates of dominance heritability were similar within definitions assuming equal SNP effects or within definitions assuming equal SNP variance, but had differences between these two groups of definitions. We proposed a new measure of genomic inbreeding coefficient based on parental genomic co-ancestry coefficient and genomic additive correlation as a genomic approach for predicting offspring inbreeding level. This genomic inbreeding coefficient had the highest correlation with pedigree inbreeding coefficient among the four methods evaluated for calculating genomic inbreeding coefficient in a Holstein sample and a swine sample.

  1. Genomics Education in Practice: Evaluation of a Mobile Lab Design

    Science.gov (United States)

    Van Mil, Marc H. W.; Boerwinkel, Dirk Jan; Buizer-Voskamp, Jacobine E.; Speksnijder, Annelies; Waarlo, Arend Jan

    2010-01-01

    Dutch genomics research centers have developed the "DNA labs on the road" to bridge the gap between modern genomics research practice and secondary-school curriculum in the Netherlands. These mobile DNA labs offer upper-secondary students the opportunity to experience genomics research through experiments with laboratory equipment that…

  2. 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.

  3. 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...

  4. An integrated 3-Dimensional Genome Modeling Engine for data-driven simulation of spatial genome organization.

    Science.gov (United States)

    Szałaj, Przemysław; Tang, Zhonghui; Michalski, Paul; Pietal, Michal J; Luo, Oscar J; Sadowski, Michał; Li, Xingwang; Radew, Kamen; Ruan, Yijun; Plewczynski, Dariusz

    2016-12-01

    ChIA-PET is a high-throughput mapping technology that reveals long-range chromatin interactions and provides insights into the basic principles of spatial genome organization and gene regulation mediated by specific protein factors. Recently, we showed that a single ChIA-PET experiment provides information at all genomic scales of interest, from the high-resolution locations of binding sites and enriched chromatin interactions mediated by specific protein factors, to the low resolution of nonenriched interactions that reflect topological neighborhoods of higher-order chromosome folding. This multilevel nature of ChIA-PET data offers an opportunity to use multiscale 3D models to study structural-functional relationships at multiple length scales, but doing so requires a structural modeling platform. Here, we report the development of 3D-GNOME (3-Dimensional Genome Modeling Engine), a complete computational pipeline for 3D simulation using ChIA-PET data. 3D-GNOME consists of three integrated components: a graph-distance-based heat map normalization tool, a 3D modeling platform, and an interactive 3D visualization tool. Using ChIA-PET and Hi-C data derived from human B-lymphocytes, we demonstrate the effectiveness of 3D-GNOME in building 3D genome models at multiple levels, including the entire genome, individual chromosomes, and specific segments at megabase (Mb) and kilobase (kb) resolutions of single average and ensemble structures. Further incorporation of CTCF-motif orientation and high-resolution looping patterns in 3D simulation provided additional reliability of potential biologically plausible topological structures.

  5. Impulsive Neural Networks Algorithm Based on the Artificial Genome Model

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2014-05-01

    Full Text Available To describe gene regulatory networks, this article takes the framework of the artificial genome model and proposes impulsive neural networks algorithm based on the artificial genome model. Firstly, the gene expression and the cell division tree are applied to generate spiking neurons with specific attributes, neural network structure, connection weights and specific learning rules of each neuron. Next, the gene segment duplications and divergence model are applied to design the evolutionary algorithm of impulsive neural networks at the level of the artificial genome. The dynamic changes of developmental gene regulatory networks are controlled during the whole evolutionary process. Finally, the behavior of collecting food for autonomous intelligent agent is simulated, which is driven by nerves. Experimental results demonstrate that the algorithm in this article has the evolutionary ability on large-scale impulsive neural networks

  6. Education through Fiction: Acquiring Opinion-Forming Skills in the Context of Genomics

    Science.gov (United States)

    Knippels, Marie-Christine P. J.; Severiens, Sabine E.; Klop, Tanja

    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 of fiction in the module. The basic hypothesis…

  7. 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

  8. 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...

  9. 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

  10. 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.

  11. Neocaridina denticulata: A Decapod Crustacean Model for Functional Genomics.

    Science.gov (United States)

    Mykles, Donald L; Hui, Jerome H L

    2015-11-01

    A decapod crustacean model is needed for understanding the molecular mechanisms underlying physiological processes, such as reproduction, sex determination, molting and growth, immunity, regeneration, and response to stress. Criteria for selection are: life-history traits, adult size, availability and ease of culture, and genomics and genetic manipulation. Three freshwater species are considered: cherry shrimp, Neocaridina denticulata; red swamp crayfish, Procambarus clarkii; and redclaw crayfish, Cherax quadricarinatus. All three are readily available, reproduce year round, and grow rapidly. The crayfish species require more space for culture than does N. denticulata. The transparent cuticle of cherry shrimp provides for direct assessment of reproductive status, stage of molt, and tissue-specific expression of reporter genes, and facilitates screening of mutations affecting phenotype. Moreover, a preliminary genome of N. denticulata is available and efforts toward complete genome sequencing and transcriptome sequencing have been initiated. Neocaridina denticulata possesses the best combination of traits that make it most suitable as a model for functional genomics. The next step is to obtain the complete genome sequence and to develop molecular technologies for the screening of mutants and for manipulating tissue-specific gene expression.

  12. 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…

  13. 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.

  14. 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

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

    DEFF Research Database (Denmark)

    Denell, Robin; Gibbs, Richard; Muzny, Donna

    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 inte...

  16. 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.

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

    Science.gov (United States)

    King, Zachary A; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A; Ebrahim, Ali; Palsson, Bernhard O; Lewis, Nathan E

    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 repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.

  18. Mathematical Modelling in European Education

    Science.gov (United States)

    Ferri, Rita Borromeo

    2013-01-01

    Teaching and learning of mathematical modelling has become a key competence within school curricula and educational standards in many countries of the world. The term mathematical modelling, its meaning, and how it can be implemented in mathematics lessons have been intensively discussed during several Conferences of the European Society for…

  19. 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; 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, Brge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; St 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; Bonnelykke, 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; Evans, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldorsson, 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.; Kahonen, Mika; Kanoni, Stavroula; Keltigangas-Jarvinen, Liisa; Kiemeney, Lambertus A. L. M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Mael P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C. M.; Loukola, Anu; Madden, Pamela A.; Magi, Reedik; Maki-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.; Raikkonen, 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.; Volker, Uwe; Volzke, Henry; Vonk, Judith M.; 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-Jorgen; Gratten, Jacob; Groenen, Patrick J. F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppnen, Elina; Iacono, William G.; Jacobsson, Bo; Jarvelin, Marjo-Riitta; Jockel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L. R.; Lehtimaki, 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; Sorensen, Thorkild I. A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, Andre 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, Tonu; Koellinger, Philipp D.; Cesarini, David; Benjamin, Daniel 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(1). Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends

  20. 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; 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, Brge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; St 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; Bonnelykke, 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; Evans, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldorsson, 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.; Kahonen, Mika; Kanoni, Stavroula; Keltigangas-Jarvinen, Liisa; Kiemeney, Lambertus A. L. M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Mael P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C. M.; Loukola, Anu; Madden, Pamela A.; Magi, Reedik; Maki-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.; Raikkonen, 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.; Volker, Uwe; Volzke, Henry; Vonk, Judith M.; 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-Jorgen; Gratten, Jacob; Groenen, Patrick J. F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppnen, Elina; Iacono, William G.; Jacobsson, Bo; Jarvelin, Marjo-Riitta; Jockel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L. R.; Lehtimaki, 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; Sorensen, Thorkild I. A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, Andre 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.

    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

  1. 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); M. Abdellaoui (Mohammed); 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. 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; 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; 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 (Cock); 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)

    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

  2. Genome Editing and Its Applications in Model Organisms

    Directory of Open Access Journals (Sweden)

    Dongyuan Ma

    2015-12-01

    Full Text Available Technological advances are important for innovative biological research. Development of molecular tools for DNA manipulation, such as zinc finger nucleases (ZFNs, transcription activator-like effector nucleases (TALENs, and the clustered regularly-interspaced short palindromic repeat (CRISPR/CRISPR-associated (Cas, has revolutionized genome editing. These approaches can be used to develop potential therapeutic strategies to effectively treat heritable diseases. In the last few years, substantial progress has been made in CRISPR/Cas technology, including technical improvements and wide application in many model systems. This review describes recent advancements in genome editing with a particular focus on CRISPR/Cas, covering the underlying principles, technological optimization, and its application in zebrafish and other model organisms, disease modeling, and gene therapy used for personalized medicine.

  3. Genome Editing and Its Applications in Model Organisms.

    Science.gov (United States)

    Ma, Dongyuan; Liu, Feng

    2015-12-01

    Technological advances are important for innovative biological research. Development of molecular tools for DNA manipulation, such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and the clustered regularly-interspaced short palindromic repeat (CRISPR)/CRISPR-associated (Cas), has revolutionized genome editing. These approaches can be used to develop potential therapeutic strategies to effectively treat heritable diseases. In the last few years, substantial progress has been made in CRISPR/Cas technology, including technical improvements and wide application in many model systems. This review describes recent advancements in genome editing with a particular focus on CRISPR/Cas, covering the underlying principles, technological optimization, and its application in zebrafish and other model organisms, disease modeling, and gene therapy used for personalized medicine.

  4. 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.

  5. Modeling protein network evolution under genome duplication and domain shuffling

    Directory of Open Access Journals (Sweden)

    Isambert Hervé

    2007-11-01

    Full Text Available Abstract Background Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such exponential evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI networks by outweighing, in particular, all time-linear network growths modeled so far. Results We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from i prevailing exponential network dynamics under duplication and ii asymmetric divergence of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of direct and indirect PPI networks of S. cerevisiae are well reproduced numerically with only two adjusted parameters of clear biological significance (i.e. network effective growth rate and average number of protein-binding domains per protein. Conclusion This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale

  6. Genome-scale modeling for metabolic engineering

    Energy Technology Data Exchange (ETDEWEB)

    Simeonidis, E; Price, ND

    2015-01-13

    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.

  7. 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.

  8. Empirical genome evolution models root the tree of life.

    Science.gov (United States)

    Harish, Ajith; Kurland, Charles G

    2017-07-01

    A reliable phylogenetic reconstruction of the evolutionary history of contemporary species depends on a robust identification of the universal common ancestor (UCA) at the root of the Tree of Life (ToL). That root polarizes the tree so that the evolutionary succession of ancestors to descendants is discernable. In effect, the root determines the branching order and the direction of character evolution. Typically, conventional phylogenetic analyses implement time-reversible models of evolution for which character evolution is un-polarized. Such practices leave the root and the direction of character evolution undefined by the data used to construct such trees. In such cases, rooting relies on theoretic assumptions and/or the use of external data to interpret unrooted trees. The most common rooting method, the outgroup method is clearly inapplicable to the ToL, which has no outgroup. Both here and in the accompanying paper (Harish and Kurland, 2017) we have explored the theoretical and technical issues related to several rooting methods. We demonstrate (1) that Genome-level characters and evolution models are necessary for species phylogeny reconstructions. By the same token, standard practices exploiting sequence-based methods that implement gene-scale substitution models do not root species trees; (2) Modeling evolution of complex genomic characters and processes that are non-reversible and non-stationary is required to reconstruct the polarized evolution of the ToL; (3) Rooting experiments and Bayesian model selection tests overwhelmingly support the earlier finding that akaryotes and eukaryotes are sister clades that descend independently from UCA (Harish and Kurland, 2013); (4) Consistent ancestral state reconstructions from independent genome samplings confirm the previous finding that UCA features three fourths of the unique protein domain-superfamilies encoded by extant genomes. Copyright © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie

  9. Genome-scale constraint-based modeling of Geobacter metallireducens

    Directory of Open Access Journals (Sweden)

    Famili Iman

    2009-01-01

    Full Text Available Abstract Background Geobacter metallireducens was the first organism that can be grown in pure culture to completely oxidize organic compounds with Fe(III oxide serving as electron acceptor. Geobacter species, including G. sulfurreducens and G. metallireducens, are used for bioremediation and electricity generation from waste organic matter and renewable biomass. The constraint-based modeling approach enables the development of genome-scale in silico models that can predict the behavior of complex biological systems and their responses to the environments. Such a modeling approach was applied to provide physiological and ecological insights on the metabolism of G. metallireducens. Results The genome-scale metabolic model of G. metallireducens was constructed to include 747 genes and 697 reactions. Compared to the G. sulfurreducens model, the G. metallireducens metabolic model contains 118 unique reactions that reflect many of G. metallireducens' specific metabolic capabilities. Detailed examination of the G. metallireducens model suggests that its central metabolism contains several energy-inefficient reactions that are not present in the G. sulfurreducens model. Experimental biomass yield of G. metallireducens growing on pyruvate was lower than the predicted optimal biomass yield. Microarray data of G. metallireducens growing with benzoate and acetate indicated that genes encoding these energy-inefficient reactions were up-regulated by benzoate. These results suggested that the energy-inefficient reactions were likely turned off during G. metallireducens growth with acetate for optimal biomass yield, but were up-regulated during growth with complex electron donors such as benzoate for rapid energy generation. Furthermore, several computational modeling approaches were applied to accelerate G. metallireducens research. For example, growth of G. metallireducens with different electron donors and electron acceptors were studied using the genome

  10. A Thermodynamic Model for Genome Packaging in Hepatitis B Virus.

    Science.gov (United States)

    Kim, Jehoon; Wu, Jianzhong

    2015-10-20

    Understanding the fundamentals of genome packaging in viral capsids is important for finding effective antiviral strategies and for utilizing benign viral particles for gene therapy. While the structure of encapsidated genomic materials has been routinely characterized with experimental techniques such as cryo-electron microscopy and x-ray diffraction, much less is known about the molecular driving forces underlying genome assembly in an intracellular environment and its in vivo interactions with the capsid proteins. Here we study the thermodynamic basis of the pregenomic RNA encapsidation in human Hepatitis B virus in vivo using a coarse-grained molecular model that captures the essential components of nonspecific intermolecular interactions. The thermodynamic model is used to examine how the electrostatic interaction between the packaged RNA and the highly charged C-terminal domains (CTD) of capsid proteins regulate the nucleocapsid formation. The theoretical model predicts optimal RNA content in Hepatitis B virus nucleocapsids with different CTD lengths in good agreement with mutagenesis measurements, confirming the predominant role of electrostatic interactions and molecular excluded-volume effects in genome packaging. We find that the amount of encapsidated RNA is not linearly correlated with the net charge of CTD tails as suggested by earlier theoretical studies. Our thermodynamic analysis of the nucleocapsid structure and stability indicates that ∼10% of the CTD residues are free from complexation with RNA, resulting in partially exposed CTD tails. The thermodynamic model also predicts the free energy of complex formation between macromolecules, which corroborates experimental results for the impact of CTD truncation on the nucleocapsid stability.

  11. A mixture copula Bayesian network model for multimodal genomic data

    Directory of Open Access Journals (Sweden)

    Qingyang Zhang

    2017-04-01

    Full Text Available Gaussian Bayesian networks have become a widely used framework to estimate directed associations between joint Gaussian variables, where the network structure encodes the decomposition of multivariate normal density into local terms. However, the resulting estimates can be inaccurate when the normality assumption is moderately or severely violated, making it unsuitable for dealing with recent genomic data such as the Cancer Genome Atlas data. In the present paper, we propose a mixture copula Bayesian network model which provides great flexibility in modeling non-Gaussian and multimodal data for causal inference. The parameters in mixture copula functions can be efficiently estimated by a routine expectation–maximization algorithm. A heuristic search algorithm based on Bayesian information criterion is developed to estimate the network structure, and prediction can be further improved by the best-scoring network out of multiple predictions from random initial values. Our method outperforms Gaussian Bayesian networks and regular copula Bayesian networks in terms of modeling flexibility and prediction accuracy, as demonstrated using a cell signaling data set. We apply the proposed methods to the Cancer Genome Atlas data to study the genetic and epigenetic pathways that underlie serous ovarian cancer.

  12. Distance Education Instructional Model Applications.

    Science.gov (United States)

    Jackman, Diane H.; Swan, Michael K.

    1995-01-01

    A survey of graduate students involved in distance education on North Dakota State University's Interactive Video Network included 80 on campus and 13 off. The instructional models rated most effective were role playing, simulation, jurisprudential (Socratic method), memorization, synectics, and inquiry. Direct instruction was rated least…

  13. Radiation induced genome instability: multiscale modelling and data analysis

    Science.gov (United States)

    Andreev, Sergey; Eidelman, Yuri

    2012-07-01

    Genome instability (GI) is thought to be an important step in cancer induction and progression. Radiation induced GI is usually defined as genome alterations in the progeny of irradiated cells. The aim of this report is to demonstrate an opportunity for integrative analysis of radiation induced GI on the basis of multiscale modelling. Integrative, systems level modelling is necessary to assess different pathways resulting in GI in which a variety of genetic and epigenetic processes are involved. The multilevel modelling includes the Monte Carlo based simulation of several key processes involved in GI: DNA double strand breaks (DSBs) generation in cells initially irradiated as well as in descendants of irradiated cells, damage transmission through mitosis. Taking the cell-cycle-dependent generation of DNA/chromosome breakage into account ensures an advantage in estimating the contribution of different DNA damage response pathways to GI, as to nonhomologous vs homologous recombination repair mechanisms, the role of DSBs at telomeres or interstitial chromosomal sites, etc. The preliminary estimates show that both telomeric and non-telomeric DSB interactions are involved in delayed effects of radiation although differentially for different cell types. The computational experiments provide the data on the wide spectrum of GI endpoints (dicentrics, micronuclei, nonclonal translocations, chromatid exchanges, chromosome fragments) similar to those obtained experimentally for various cell lines under various experimental conditions. The modelling based analysis of experimental data demonstrates that radiation induced GI may be viewed as processes of delayed DSB induction/interaction/transmission being a key for quantification of GI. On the other hand, this conclusion is not sufficient to understand GI as a whole because factors of DNA non-damaging origin can also induce GI. Additionally, new data on induced pluripotent stem cells reveal that GI is acquired in normal mature

  14. Russian and Western Media Literacy Education Models

    Directory of Open Access Journals (Sweden)

    Alexander Fedorov

    2014-04-01

    Full Text Available In different countries there is a wide range of the prospective media literacy education models, which are used in the process of education and upbringing. With that the analysis of the central models demonstrates that the most typical synthetic models belong to three groups: Group A. Media education models, representing the synthesis of the aesthetical and sociocultural models. Group B. Media education models, representing the synthesis of the aesthetical, informative and ethical models. Group C. Media education models, representing the synthesis of the sociocultural, informative and practical-pragmatic models. Therewith the models of group C are most spread and supported today in the majority of countries. Modern media education models lean towards the maximum usage of the potential possibilities of media education depending on the aims and objectives; they are characterized by the variability, options of the entire or fragmental integration into the education process.

  15. 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; Elgin, Sarah C. R.

    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…

  16. 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…

  17. 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…

  18. Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation.

    Science.gov (United States)

    Fitzpatrick, Matthew C; Keller, Stephen R

    2015-01-01

    Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism-environment relationships that combines genomic data and community-level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA-5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community-level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species-level assessments of climate change vulnerability.

  19. Feature selection and survival modeling in The Cancer Genome Atlas

    Directory of Open Access Journals (Sweden)

    Kim H

    2013-09-01

    Full Text Available Hyunsoo Kim,1 Markus Bredel2 1Department of Pathology, The University of Alabama at Birmingham, Birmingham, AL, USA; 2Department of Radiation Oncology, and Comprehensive Cancer Center, The University of Alabama at Birmingham, Birmingham, AL, USA Purpose: Personalized medicine is predicated on the concept of identifying subgroups of a common disease for better treatment. Identifying biomarkers that predict disease subtypes has been a major focus of biomedical science. In the era of genome-wide profiling, there is controversy as to the optimal number of genes as an input of a feature selection algorithm for survival modeling. Patients and methods: The expression profiles and outcomes of 544 patients were retrieved from The Cancer Genome Atlas. We compared four different survival prediction methods: (1 1-nearest neighbor (1-NN survival prediction method; (2 random patient selection method and a Cox-based regression method with nested cross-validation; (3 least absolute shrinkage and selection operator (LASSO optimization using whole-genome gene expression profiles; or (4 gene expression profiles of cancer pathway genes. Results: The 1-NN method performed better than the random patient selection method in terms of survival predictions, although it does not include a feature selection step. The Cox-based regression method with LASSO optimization using whole-genome gene expression data demonstrated higher survival prediction power than the 1-NN method, but was outperformed by the same method when using gene expression profiles of cancer pathway genes alone. Conclusion: The 1-NN survival prediction method may require more patients for better performance, even when omitting censored data. Using preexisting biological knowledge for survival prediction is reasonable as a means to understand the biological system of a cancer, unless the analysis goal is to identify completely unknown genes relevant to cancer biology. Keywords: brain, feature selection

  20. Genomic responses in mouse models poorly mimic human inflammatory diseases.

    Science.gov (United States)

    Seok, Junhee; Warren, H Shaw; Cuenca, Alex G; Mindrinos, Michael N; Baker, Henry V; Xu, Weihong; Richards, Daniel R; McDonald-Smith, Grace P; Gao, Hong; Hennessy, Laura; Finnerty, Celeste C; López, Cecilia M; Honari, Shari; Moore, Ernest E; Minei, Joseph P; Cuschieri, Joseph; Bankey, Paul E; Johnson, Jeffrey L; Sperry, Jason; Nathens, Avery B; Billiar, Timothy R; West, Michael A; Jeschke, Marc G; Klein, Matthew B; Gamelli, Richard L; Gibran, Nicole S; Brownstein, Bernard H; Miller-Graziano, Carol; Calvano, Steve E; Mason, Philip H; Cobb, J Perren; Rahme, Laurence G; Lowry, Stephen F; Maier, Ronald V; Moldawer, Lyle L; Herndon, David N; Davis, Ronald W; Xiao, Wenzhong; Tompkins, Ronald G

    2013-02-26

    A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R(2) between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases.

  1. Genomic responses in mouse models poorly mimic human inflammatory diseases

    Science.gov (United States)

    Seok, Junhee; Warren, H. Shaw; Cuenca, Alex G.; Mindrinos, Michael N.; Baker, Henry V.; Xu, Weihong; Richards, Daniel R.; McDonald-Smith, Grace P.; Gao, Hong; Hennessy, Laura; Finnerty, Celeste C.; López, Cecilia M.; Honari, Shari; Moore, Ernest E.; Minei, Joseph P.; Cuschieri, Joseph; Bankey, Paul E.; Johnson, Jeffrey L.; Sperry, Jason; Nathens, Avery B.; Billiar, Timothy R.; West, Michael A.; Jeschke, Marc G.; Klein, Matthew B.; Gamelli, Richard L.; Gibran, Nicole S.; Brownstein, Bernard H.; Miller-Graziano, Carol; Calvano, Steve E.; Mason, Philip H.; Cobb, J. Perren; Rahme, Laurence G.; Lowry, Stephen F.; Maier, Ronald V.; Moldawer, Lyle L.; Herndon, David N.; Davis, Ronald W.; Xiao, Wenzhong; Tompkins, Ronald G.; Abouhamze, Amer; Balis, Ulysses G. J.; Camp, David G.; De, Asit K.; Harbrecht, Brian G.; Hayden, Douglas L.; Kaushal, Amit; O’Keefe, Grant E.; Kotz, Kenneth T.; Qian, Weijun; Schoenfeld, David A.; Shapiro, Michael B.; Silver, Geoffrey M.; Smith, Richard D.; Storey, John D.; Tibshirani, Robert; Toner, Mehmet; Wilhelmy, Julie; Wispelwey, Bram; Wong, Wing H

    2013-01-01

    A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R2 between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases. PMID:23401516

  2. Cancer models, genomic instability and somatic cellular Darwinian evolution

    Directory of Open Access Journals (Sweden)

    Little Mark P

    2010-04-01

    Full Text Available Abstract The biology of cancer is critically reviewed and evidence adduced that its development can be modelled as a somatic cellular Darwinian evolutionary process. The evidence for involvement of genomic instability (GI is also reviewed. A variety of quasi-mechanistic models of carcinogenesis are reviewed, all based on this somatic Darwinian evolutionary hypothesis; in particular, the multi-stage model of Armitage and Doll (Br. J. Cancer 1954:8;1-12, the two-mutation model of Moolgavkar, Venzon, and Knudson (MVK (Math. Biosci. 1979:47;55-77, the generalized MVK model of Little (Biometrics 1995:51;1278-1291 and various generalizations of these incorporating effects of GI (Little and Wright Math. Biosci. 2003:183;111-134; Little et al. J. Theoret. Biol. 2008:254;229-238. Reviewers This article was reviewed by RA Gatenby and M Kimmel.

  3. 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.

  4. Current state of genome-scale modeling in filamentous fungi.

    Science.gov (United States)

    Brandl, Julian; Andersen, Mikael R

    2015-06-01

    The group of filamentous fungi contains important species used in industrial biotechnology for acid, antibiotics and enzyme production. Their unique lifestyle turns these organisms into a valuable genetic reservoir of new natural products and biomass degrading enzymes that has not been used to full capacity. One of the major bottlenecks in the development of new strains into viable industrial hosts is the alteration of the metabolism towards optimal production. Genome-scale models promise a reduction in the time needed for metabolic engineering by predicting the most potent targets in silico before testing them in vivo. The increasing availability of high quality models and molecular biological tools for manipulating filamentous fungi renders the model-guided engineering of these fungal factories possible with comprehensive metabolic networks. A typical fungal model contains on average 1138 unique metabolic reactions and 1050 ORFs, making them a vast knowledge-base of fungal metabolism. In the present review we focus on the current state as well as potential future applications of genome-scale models in filamentous fungi.

  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. 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.

  7. Mediated Modeling in Science Education

    Science.gov (United States)

    Halloun, Ibrahim A.

    2007-08-01

    Following two decades of corroboration, modeling theory is presented as a pedagogical theory that promotes mediated experiential learning of model-laden theory and inquiry in science education. Students develop experiential knowledge about physical realities through interplay between their own ideas about the physical world and particular patterns in this world. Under teacher mediation, they represent each pattern with a particular model that they develop through a five-phase learning cycle, following particular modeling schemata of well-defined dimensions and rules of engagement. Significantly greater student achievement has been increasingly demonstrated under mediated modeling than under conventional instruction of lecture and demonstration, especially in secondary school and university physics courses. The improved achievement is reflected in more meaningful understanding of course materials, better learning styles, higher success rates, lower attrition rates and narrower gaps between students of different backgrounds.

  8. Genomic Heritability of Bovine Growth Using a Mixed Model

    Directory of Open Access Journals (Sweden)

    Jihye Ryu

    2014-11-01

    Full Text Available This study investigated heritability for bovine growth estimated with genomewide single nucleotide polymorphism (SNP information obtained from a DNA microarray chip. Three hundred sixty seven Korean cattle were genotyped with the Illumina BovineSNP50 BeadChip, and 39,112 SNPs of 364 animals filtered by quality assurance were analyzed to estimate heritability of body weights at 6, 9, 12, 15, 18, 21, and 24 months of age. Restricted maximum likelihood estimate of heritability was obtained using covariance structure of genomic relationships among animals in a mixed model framework. Heritability estimates ranged from 0.58 to 0.76 for body weights at different ages. The heritability estimates using genomic information in this study were larger than those which had been estimated previously using pedigree information. The results revealed a trend that the heritability for body weight increased at a younger age (6 months. This suggests an early genetic evaluation for bovine growth using genomic information to increase genetic merits of animals.

  9. Current state of genome-scale modeling in filamentous fungi

    DEFF Research Database (Denmark)

    Brandl, Julian; Andersen, Mikael Rørdam

    2015-01-01

    The group of filamentous fungi contains important species used in industrial biotechnology for acid, antibiotics and enzyme production. Their unique lifestyle turns these organisms into a valuable genetic reservoir of new natural products and biomass degrading enzymes that has not been used to full...... testing them in vivo. The increasing availability of high quality models and molecular biological tools for manipulating filamentous fungi renders the model-guided engineering of these fungal factories possible with comprehensive metabolic networks. A typical fungal model contains on average 1138 unique...... metabolic reactions and 1050 ORFs, making them a vast knowledge-base of fungal metabolism. In the present review we focus on the current state as well as potential future applications of genome-scale models in filamentous fungi....

  10. Green Education Concepts & Strategies in Higher Education Model

    OpenAIRE

    Sreeramana Aithal; Prithi Rao

    2016-01-01

    Green Education in the service sector is expected to transform education sector and is combined with the trend of world economy development. Environmental benefits and sustainability are two characteristics of Green education. In the green education model, service is expanded as, what kinds of education is provided by organizations (the process of service creation), how such services are transferred to the customers, how will the benefits be captured by providers around service...

  11. A computer-based education intervention to enhance surrogates' informed consent for genomics research.

    Science.gov (United States)

    Shelton, Ann K; Freeman, Bradley D; Fish, Anne F; Bachman, Jean A; Richardson, Lloyd I

    2015-03-01

    Many research studies conducted today in critical care have a genomics component. Patients' surrogates asked to authorize participation in genomics research for a loved one in the intensive care unit may not be prepared to make informed decisions about a patient's participation in the research. To examine the effectiveness of a new, computer-based education module on surrogates' understanding of the process of informed consent for genomics research. A pilot study was conducted with visitors in the waiting rooms of 2 intensive care units in a Midwestern tertiary care medical center. Visitors were randomly assigned to the experimental (education module plus a sample genomics consent form; n = 65) or the control (sample genomics consent form only; n = 69) group. Participants later completed a test on informed genomics consent. Understanding the process of informed consent was greater (P = .001) in the experimental group than in the control group. Specifically, compared with the control group, the experimental group had a greater understanding of 8 of 13 elements of informed consent: intended benefits of research (P = .02), definition of surrogate consenter (P= .001), withdrawal from the study (P = .001), explanation of risk (P = .002), purpose of the institutional review board (P = .001), definition of substituted judgment (P = .03), compensation for harm (P = .001), and alternative treatments (P = .004). Computer-based education modules may be an important addition to conventional approaches for obtaining informed consent in the intensive care unit. Preparing patients' family members who may consider serving as surrogate consenters is critical to facilitating genomics research in critical care. ©2015 American Association of Critical-Care Nurses.

  12. 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…

  13. 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…

  14. 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…

  15. An Integrative Pathway-based Clinical-genomic Model for Cancer Survival Prediction.

    Science.gov (United States)

    Chen, Xi; Wang, Lily; Ishwaran, Hemant

    2010-09-01

    Prediction models that use gene expression levels are now being proposed for personalized treatment of cancer, but building accurate models that are easy to interpret remains a challenge. In this paper, we describe an integrative clinical-genomic approach that combines both genomic pathway and clinical information. First, we summarize information from genes in each pathway using Supervised Principal Components (SPCA) to obtain pathway-based genomic predictors. Next, we build a prediction model based on clinical variables and pathway-based genomic predictors using Random Survival Forests (RSF). Our rationale for this two-stage procedure is that the underlying disease process may be influenced by environmental exposure (measured by clinical variables) and perturbations in different pathways (measured by pathway-based genomic variables), as well as their interactions. Using two cancer microarray datasets, we show that the pathway-based clinical-genomic model outperforms gene-based clinical-genomic models, with improved prediction accuracy and interpretability.

  16. 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...... optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed. -. encompassing many biological processes and simulation strategies. -. and next-generation models enable new types of predictions. Here, three key...... 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....

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

    Science.gov (United States)

    King, Zachary A; Lloyd, Colton J; Feist, Adam M; Palsson, Bernhard O

    2015-12-01

    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 optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed--encompassing many biological processes and simulation strategies-and next-generation models enable new types of predictions. Here, three key 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.

  18. The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models

    Science.gov (United States)

    Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.

    2015-01-01

    The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318

  19. 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.

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

    DEFF Research Database (Denmark)

    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...

  1. Diagnostics for stochastic genome-scale modeling via model slicing and debugging.

    Directory of Open Access Journals (Sweden)

    Kevin J Tsai

    Full Text Available Modeling of biological behavior has evolved from simple gene expression plots represented by mathematical equations to genome-scale systems biology networks. However, due to obstacles in complexity and scalability of creating genome-scale models, several biological modelers have turned to programming or scripting languages and away from modeling fundamentals. In doing so, they have traded the ability to have exchangeable, standardized model representation formats, while those that remain true to standardized model representation are faced with challenges in model complexity and analysis. We have developed a model diagnostic methodology inspired by program slicing and debugging and demonstrate the effectiveness of the methodology on a genome-scale metabolic network model published in the BioModels database. The computer-aided identification revealed specific points of interest such as reversibility of reactions, initialization of species amounts, and parameter estimation that improved a candidate cell's adenosine triphosphate production. We then compared the advantages of our methodology over other modeling techniques such as model checking and model reduction. A software application that implements the methodology is available at http://gel.ym.edu.tw/gcs/.

  2. Diagnostics for stochastic genome-scale modeling via model slicing and debugging.

    Science.gov (United States)

    Tsai, Kevin J; Chang, Chuan-Hsiung

    2014-01-01

    Modeling of biological behavior has evolved from simple gene expression plots represented by mathematical equations to genome-scale systems biology networks. However, due to obstacles in complexity and scalability of creating genome-scale models, several biological modelers have turned to programming or scripting languages and away from modeling fundamentals. In doing so, they have traded the ability to have exchangeable, standardized model representation formats, while those that remain true to standardized model representation are faced with challenges in model complexity and analysis. We have developed a model diagnostic methodology inspired by program slicing and debugging and demonstrate the effectiveness of the methodology on a genome-scale metabolic network model published in the BioModels database. The computer-aided identification revealed specific points of interest such as reversibility of reactions, initialization of species amounts, and parameter estimation that improved a candidate cell's adenosine triphosphate production. We then compared the advantages of our methodology over other modeling techniques such as model checking and model reduction. A software application that implements the methodology is available at http://gel.ym.edu.tw/gcs/.

  3. An entrepreneurial education model for the Namibian Higher Education system

    Directory of Open Access Journals (Sweden)

    P. Ras

    2007-12-01

    Full Text Available Purpose: The aim of this paper is to develop an entrepreneurial education model for implementation in the Namibian Higher Education system. Namibia, just like South Africa, has an objective to develop small, medium and micro enterprises to enhance economic growth and reduce unemployment. Development of such a model is supported by the government of Namibia. This paper investigates appropriate entrepreneurial education models used in South Africa for this purpose.Design/Methodology/Approach: This research is an exploratory research design based upon secondary data mainly provided by the Namibian Economic Policy Research Unit (NEPRU that enabled the researcher to understand and identify the problems that Namibia encounter in their small business environment. Theories, as developed by the University of Pretoria based on entrepreneurial education, were explored and formed the base of the theory exploration. Findings : The researcher investigated an existing entrepreneurial education model being used for the South African context, as well as a comparison of two models, and an integrated model based on the cited models. These models are used to show the importance of such models and the need to develop one for Namibia. Implications: This paper presents a model that can solve the basic need expressed by the Namibian Higher Education System to find an appropriate model to implement. Originality/Value: This paper provides a foundation from which an entrepreneurial education model can be implemented and improved / customised for the Namibian context.

  4. 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…

  5. Computer models of bacterial cells: from generalized coarsegrained to genome-specific modular models

    Science.gov (United States)

    Nikolaev, Evgeni V.; Atlas, Jordan C.; Shuler, Michael L.

    2006-09-01

    We discuss a modular modelling framework to rapidly develop mathematical models of bacterial cells that would explicitly link genomic details to cell physiology and population response. An initial step in this approach is the development of a coarse-grained model, describing pseudo-chemical interactions between lumped species. A hybrid model of interest can then be constructed by embedding genome-specific detail for a particular cellular subsystem (e.g. central metabolism), called here a module, into the coarse-grained model. Specifically, a new strategy for sensitivity analysis of the cell division limit cycle is introduced to identify which pseudo-molecular processes should be delumped to implement a particular biological function in a growing cell (e.g. ethanol overproduction or pathogen viability). To illustrate the modeling principles and highlight computational challenges, the Cornell coarsegrained model of Escherichia coli B/r-A is used to benchmark the proposed framework.

  6. A single-step genomic model with direct estimation of marker effects.

    Science.gov (United States)

    Liu, Z; Goddard, M E; Reinhardt, F; Reents, R

    2014-09-01

    Compared with the currently widely used multi-step genomic models for genomic evaluation, single-step genomic models can provide more accurate genomic evaluation by jointly analyzing phenotypes and genotypes of all animals and can properly correct for the effect of genomic preselection on genetic evaluations. The objectives of this study were to introduce a single-step genomic model, allowing a direct estimation of single nucleotide polymorphism (SNP) effects, and to develop efficient computing algorithms for solving equations of the single-step SNP model. We proposed an alternative to the current single-step genomic model based on the genomic relationship matrix by including an additional step for estimating the effects of SNP markers. Our single-step SNP model allowed flexible modeling of SNP effects in terms of the number and variance of SNP markers. Moreover, our single-step SNP model included a residual polygenic effect with trait-specific variance for reducing inflation in genomic prediction. A kernel calculation of the SNP model involved repeated multiplications of the inverse of the pedigree relationship matrix of genotyped animals with a vector, for which numerical methods such as preconditioned conjugate gradients can be used. For estimating SNP effects, a special updating algorithm was proposed to separate residual polygenic effects from the SNP effects. We extended our single-step SNP model to general multiple-trait cases. By taking advantage of a block-diagonal (co)variance matrix of SNP effects, we showed how to estimate multivariate SNP effects in an efficient way. A general prediction formula was derived for candidates without phenotypes, which can be used for frequent, interim genomic evaluations without running the whole genomic evaluation process. We discussed various issues related to implementation of the single-step SNP model in Holstein populations with an across-country genomic reference population.

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

    DEFF Research Database (Denmark)

    Pedersen, Jakob Skou; Hein, Jotun

    2003-01-01

    annotation. The modelling of evolution by the existing comparative gene finders leaves room for improvement. Results: A probabilistic model of both genome structure and evolution is designed. This type of model is called an Evolutionary Hidden Markov Model (EHMM), being composed of an HMM and a set of region......Motivation: A growing number of genomes are sequenced. The differences in evolutionary pattern between functional regions can thus be observed genome-wide in a whole set of organisms. The diverse evolutionary pattern of different functional regions can be exploited in the process of genomic...

  8. 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…

  9. 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…

  10. Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

    DEFF Research Database (Denmark)

    Do, Duy Ngoc; Janss, L. L. G.; Strathe, Anders Bjerring

    Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition...... genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL models had similar accuracy and bias as GBLUP method but use...

  11. 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 strong relationship between the “strength” in the struggle for jobs of an educational group, and the change in relative supply. This relationship proves to be significant in the data. Furthermore, when used to forecast employment by education on real data, the model predicts reasonably well even...... for educational groups, where the initial forecast year is a change point for unemployment....

  12. 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 (assessment quality in GBE. PMID:24006400

  13. Genetical Genomics of Behavior: A Novel Chicken Genomic Model for Anxiety Behavior.

    Science.gov (United States)

    Johnsson, Martin; Williams, Michael J; Jensen, Per; Wright, Dominic

    2016-01-01

    The identification of genetic variants responsible for behavioral variation is an enduring goal in biology, with wide-scale ramifications, ranging from medical research to evolutionary theory on personality syndromes. Here, we use for the first time a large-scale genetical genomics analysis in the brains of chickens to identify genes affecting anxiety as measured by an open field test. We combine quantitative trait locus (QTL) analysis in 572 individuals and expression QTL (eQTL) analysis in 129 individuals from an advanced intercross between domestic chickens and Red Junglefowl. We identify 10 putative quantitative trait genes affecting anxiety behavior. These genes were tested for an association in the mouse Heterogeneous Stock anxiety (open field) data set and human GWAS data sets for bipolar disorder, major depressive disorder, and schizophrenia. Although comparisons between species are complex, associations were observed for four of the candidate genes in mice and three of the candidate genes in humans. Using a multimodel approach we have therefore identified a number of putative quantitative trait genes affecting anxiety behavior, principally in chickens but also with some potentially translational effects as well. This study demonstrates that chickens are an excellent model organism for the genetic dissection of behavior.

  14. Model for heart failure education.

    Science.gov (United States)

    Baldonado, Analiza; Dutra, Danette; Abriam-Yago, Katherine

    2014-01-01

    Heart failure (HF) is the heart's inability to meet the body's need for blood and oxygen. According to the American Heart Association 2013 update, approximately 5.1 million people are diagnosed with HF in the United States in 2006. Heart failure is the most common diagnosis for hospitalization. In the United States, the HF direct and indirect costs are estimated to be US $39.2 billion in 2010. To address this issue, nursing educators designed innovative teaching frameworks on HF management both in academia and in clinical settings. The model was based on 2 resources: the American Association of Heart Failure Nurses (2012) national nursing certification and the award-winning Pierce County Responsive Care Coordination Program. The HF educational program is divided into 4 modules. The initial modules offer foundational levels of Bloom's Taxonomy then progress to incorporate higher-levels of learning when modules 3 and 4 are reached. The applicability of the key components within each module allows formatting to enhance learning in all areas of nursing, from the emergency department to intensive care units to the medical-surgical step-down units. Also applicable would be to provide specific aspects of the modules to nurses who care for HF patients in skilled nursing facility, rehabilitation centers, and in the home-health care setting.

  15. 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.

  16. 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…

  17. Mathematical Programming Models in Educational Planning.

    Science.gov (United States)

    McNamara, James F.

    This document begins by defining and discussing educational planning. A brief overview of mathematical programing with an explanation of the general linear programing model is then provided. Some recent applications of mathematical programing techniques to educational planning problems are reviewed, and their implications for educational research…

  18. Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models.

    Science.gov (United States)

    Cuevas, Jaime; Crossa, José; Soberanis, Víctor; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino; Campos, Gustavo de Los; Montesinos-López, O A; Burgueño, Juan

    2016-11-01

    In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this study, we propose using two nonlinear Gaussian kernels: the reproducing kernel Hilbert space with kernel averaging (RKHS KA) and the Gaussian kernel with the bandwidth estimated through an empirical Bayesian method (RKHS EB). We performed single-environment analyses and extended to account for G × E interaction (GBLUP-G × E, RKHS KA-G × E and RKHS EB-G × E) in wheat ( L.) and maize ( L.) data sets. For single-environment analyses of wheat and maize data sets, RKHS EB and RKHS KA had higher prediction accuracy than GBLUP for all environments. For the wheat data, the RKHS KA-G × E and RKHS EB-G × E models did show up to 60 to 68% superiority over the corresponding single environment for pairs of environments with positive correlations. For the wheat data set, the models with Gaussian kernels had accuracies up to 17% higher than that of GBLUP-G × E. For the maize data set, the prediction accuracy of RKHS EB-G × E and RKHS KA-G × E was, on average, 5 to 6% higher than that of GBLUP-G × E. The superiority of the Gaussian kernel models over the linear kernel is due to more flexible kernels that accounts for small, more complex marker main effects and marker-specific interaction effects.

  19. 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, Sys...

  20. An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences.

    Science.gov (United States)

    Lam, Su Datt; Das, Sayoni; Sillitoe, Ian; Orengo, Christine

    2017-08-01

    Computational modelling of proteins has been a major catalyst in structural biology. Bioinformatics groups have exploited the repositories of known structures to predict high-quality structural models with high efficiency at low cost. This article provides an overview of comparative modelling, reviews recent developments and describes resources dedicated to large-scale comparative modelling of genome sequences. The value of subclustering protein domain superfamilies to guide the template-selection process is investigated. Some recent cases in which structural modelling has aided experimental work to determine very large macromolecular complexes are also cited.

  1. Model of Higher GIS Education

    Science.gov (United States)

    Jakab, Imrich; Ševcík, Michal; Grežo, Henrich

    2017-01-01

    The methods of geospatial data processing are being continually innovated, and universities that are focused on educating experts in Environmental Science should reflect this reality with an elaborate and purpose-built modernization of the education process, education content, as well as learning conditions. Geographic Information Systems (GIS)…

  2. Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

    DEFF Research Database (Denmark)

    Do, Duy Ngoc; Janss, Luc L G; Strathe, Anders B

    Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition...... genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL had similar accuracy and bias as GBLUP but power parameters had...

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

    Science.gov (United States)

    Inoue, Jun; Sato, Yukuto; Sinclair, Robert; Tsukamoto, Katsumi; Nishida, Mutsumi

    2015-12-01

    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.

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

    Science.gov (United States)

    Xiangyu, Fan; Yanping, Lin; Guojian, Liao; Jianping, Xie

    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.

  5. Genome downsizing and karyotype constancy in diploid and polyploid congeners: a model of genome size variation.

    Science.gov (United States)

    Poggio, Lidia; Realini, María Florencia; Fourastié, María Florencia; García, Ana María; González, Graciela Esther

    2014-06-26

    Evolutionary chromosome change involves significant variation in DNA amount in diploids and genome downsizing in polyploids. Genome size and karyotype parameters of Hippeastrum species with different ploidy level were analysed. In Hippeastrum, polyploid species show less DNA content per basic genome than diploid species. The rate of variation is lower at higher ploidy levels. All the species have a basic number x = 11 and bimodal karyotypes. The basic karyotypes consist of four short metacentric chromosomes and seven large chromosomes (submetacentric and subtelocentric). The bimodal karyotype is preserved maintaining the relative proportions of members of the haploid chromosome set, even in the presence of genome downsizing. The constancy of the karyotype is maintained because changes in DNA amount are proportional to the length of the whole-chromosome complement and vary independently in the long and short sets of chromosomes. This karyotype constancy in taxa of Hippeastrum with different genome size and ploidy level indicates that the distribution of extra DNA within the complement is not at random and suggests the presence of mechanisms selecting for constancy, or against changes, in karyotype morphology.

  6. 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.

  7. Educational Retrenchment: A Model for Institutions of Higher Education.

    Science.gov (United States)

    Ishler, Richard E.

    1981-01-01

    Due to economic factors, many institutions of higher education may be forced to reduce faculty positions. The procedures used by Emporia State University (Kansas) can be used as a model for colleges needing to pursue various methods of retrenchment. (JN)

  8. 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…

  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. Modeling Human Population Separation History Using Physically Phased Genomes

    Science.gov (United States)

    Song, Shiya; Sliwerska, Elzbieta; Emery, Sarah; Kidd, Jeffrey M.

    2017-01-01

    Phased haplotype sequences are a key component in many population genetic analyses since variation in haplotypes reflects the action of recombination, selection, and changes in population size. In humans, haplotypes are typically estimated from unphased sequence or genotyping data using statistical models applied to large reference panels. To assess the importance of correct haplotype phase on population history inference, we performed fosmid pool sequencing and resolved phased haplotypes of five individuals from diverse African populations (including Yoruba, Esan, Gambia, Maasai, and Mende). We physically phased 98% of heterozygous SNPs into haplotype-resolved blocks, obtaining a block N50 of 1 Mbp. We combined these data with additional phased genomes from San, Mbuti, Gujarati, and Centre de’Etude du Polymorphism Humain European populations and analyzed population size and separation history using the pairwise sequentially Markovian coalescent and multiple sequentially Markovian coalescent models. We find that statistically phased haplotypes yield a more recent split-time estimation compared with experimentally phased haplotypes. To better interpret patterns of cross-population coalescence, we implemented an approximate Bayesian computation approach to estimate population split times and migration rates by fitting the distribution of coalescent times inferred between two haplotypes, one from each population, to a standard isolation-with-migration model. We inferred that the separation between hunter-gatherer populations and other populations happened ∼120–140 KYA, with gene flow continuing until 30–40 KYA; separation between west-African and out-of-African populations happened ∼70–80 KYA; while the separation between Maasai and out-of-African populations happened ∼50 KYA. PMID:28049708

  11. Genomic sequence and experimental tractability of a new decapod shrimp model, Neocaridina denticulata.

    Science.gov (United States)

    Kenny, Nathan J; Sin, Yung Wa; Shen, Xin; Zhe, Qu; Wang, Wei; Chan, Ting Fung; Tobe, Stephen S; Shimeld, Sebastian M; Chu, Ka Hou; Hui, Jerome H L

    2014-03-11

    The speciose Crustacea is the largest subphylum of arthropods on the planet after the Insecta. To date, however, the only publically available sequenced crustacean genome is that of the water flea, Daphnia pulex, a member of the Branchiopoda. While Daphnia is a well-established ecotoxicological model, previous study showed that one-third of genes contained in its genome are lineage-specific and could not be identified in any other metazoan genomes. To better understand the genomic evolution of crustaceans and arthropods, we have sequenced the genome of a novel shrimp model, Neocaridina denticulata, and tested its experimental malleability. A library of 170-bp nominal fragment size was constructed from DNA of a starved single adult and sequenced using the Illumina HiSeq2000 platform. Core eukaryotic genes, the mitochondrial genome, developmental patterning genes (such as Hox) and microRNA processing pathway genes are all present in this animal, suggesting it has not undergone massive genomic loss. Comparison with the published genome of Daphnia pulex has allowed us to reveal 3750 genes that are indeed specific to the lineage containing malacostracans and branchiopods, rather than Daphnia-specific (E-value: 10⁻⁶). We also show the experimental tractability of N. denticulata, which, together with the genomic resources presented here, make it an ideal model for a wide range of further aquacultural, developmental, ecotoxicological, food safety, genetic, hormonal, physiological and reproductive research, allowing better understanding of the evolution of crustaceans and other arthropods.

  12. Genomic Sequence and Experimental Tractability of a New Decapod Shrimp Model, Neocaridina denticulata

    Directory of Open Access Journals (Sweden)

    Nathan J. Kenny

    2014-03-01

    Full Text Available The speciose Crustacea is the largest subphylum of arthropods on the planet after the Insecta. To date, however, the only publically available sequenced crustacean genome is that of the water flea, Daphnia pulex, a member of the Branchiopoda. While Daphnia is a well-established ecotoxicological model, previous study showed that one-third of genes contained in its genome are lineage-specific and could not be identified in any other metazoan genomes. To better understand the genomic evolution of crustaceans and arthropods, we have sequenced the genome of a novel shrimp model, Neocaridina denticulata, and tested its experimental malleability. A library of 170-bp nominal fragment size was constructed from DNA of a starved single adult and sequenced using the Illumina HiSeq2000 platform. Core eukaryotic genes, the mitochondrial genome, developmental patterning genes (such as Hox and microRNA processing pathway genes are all present in this animal, suggesting it has not undergone massive genomic loss. Comparison with the published genome of Daphnia pulex has allowed us to reveal 3750 genes that are indeed specific to the lineage containing malacostracans and branchiopods, rather than Daphnia-specific (E-value: 10−6. We also show the experimental tractability of N. denticulata, which, together with the genomic resources presented here, make it an ideal model for a wide range of further aquacultural, developmental, ecotoxicological, food safety, genetic, hormonal, physiological and reproductive research, allowing better understanding of the evolution of crustaceans and other arthropods.

  13. A reaction norm model for genomic selection using high-dimensional genomic and environmental data

    NARCIS (Netherlands)

    Jarquín, D.; Crossa, J.; Lacaze, X.; Cheyron, du P.; Daucourt, J.; Lorgeou, J.; Piraux, F.; Guerreiro, L.; Pérez, P.; Calus, M.P.L.; Burgueno, J.; Campos, de los G.

    2014-01-01

    In most agricultural crops the effects of genes on traits are modulated by environmental conditions, leading to genetic by environmental interaction (G × E). Modern genotyping technologies allow characterizing genomes in great detail and modern information systems can generate large volumes of

  14. 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...

  15. 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 cellular...... growth capabilities on various substrates and the effect of gene knockouts at the genome scale. Thus, much interest has developed in understanding and applying these methods to areas such as metabolic engineering, antibiotic design, and organismal and enzyme evolution. This Primer will get you started....

  16. A foundation for provitamin A biofortification of maize: genome-wide association and genomic prediction models of carotenoid levels.

    Science.gov (United States)

    Owens, Brenda F; Lipka, Alexander E; Magallanes-Lundback, Maria; Tiede, Tyler; Diepenbrock, Christine H; Kandianis, Catherine B; Kim, Eunha; Cepela, Jason; Mateos-Hernandez, Maria; Buell, C Robin; Buckler, Edward S; DellaPenna, Dean; Gore, Michael A; Rocheford, Torbert

    2014-12-01

    Efforts are underway for development of crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency. As a global staple crop with considerable variation in kernel carotenoid composition, maize (Zea mays L.) could have a widespread impact. We performed a genome-wide association study (GWAS) of quantified seed carotenoids across a panel of maize inbreds ranging from light yellow to dark orange in grain color to identify some of the key genes controlling maize grain carotenoid composition. Significant associations at the genome-wide level were detected within the coding regions of zep1 and lut1, carotenoid biosynthetic genes not previously shown to impact grain carotenoid composition in association studies, as well as within previously associated lcyE and crtRB1 genes. We leveraged existing biochemical and genomic information to identify 58 a priori candidate genes relevant to the biosynthesis and retention of carotenoids in maize to test in a pathway-level analysis. This revealed dxs2 and lut5, genes not previously associated with kernel carotenoids. In genomic prediction models, use of markers that targeted a small set of quantitative trait loci associated with carotenoid levels in prior linkage studies were as effective as genome-wide markers for predicting carotenoid traits. Based on GWAS, pathway-level analysis, and genomic prediction studies, we outline a flexible strategy involving use of a small number of genes that can be selected for rapid conversion of elite white grain germplasm, with minimal amounts of carotenoids, to orange grain versions containing high levels of provitamin A.

  17. 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…

  18. 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…

  19. 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)

  20. DMU - A Package for Analyzing Multivariate Mixed Models in quantitative Genetics and Genomics

    DEFF Research Database (Denmark)

    Madsen, Per; Jensen, Just; Labouriau, Rodrigo;

    The DMU-package for Analyzing Multivariate Mixed Models has been developed over a period of more than 25 years. This paper gives an overview of new features and the recent developments around the DMU-package, including: Genomic prediction (SNP-BLUP, G-BLUP and “One-Step”), Genome-wide association...

  1. 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.

  2. 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......, translation initiation, translation elongation, translation termination, translation elongation, and mRNA decay. Considering these information from the mechanisms of transcription and translation, we will include this stoichiometric reactions into the genome scale model for S. Cerevisiae to obtain the first...

  3. Genome-wide survey of alternative splicing in the grass Brachypodium distachyon: a emerging model biosystem for plant functional genomics.

    Science.gov (United States)

    Sablok, Gaurav; Gupta, P K; Baek, Jong-Min; Vazquez, Franck; Min, Xiang Jia

    2011-03-01

    A draft sequence of the genome of Brachypodium distachyon, the emerging grass model, was recently released. This represents a unique opportunity to determine its functional diversity compared to the genomes of other model species. Using homology mapping of assembled expressed sequence tags with chromosome scale pseudomolecules, we identified 128 alternative splicing events in B. distachyon. Our study identified that retention of introns is the major type of alternative splicing events (53%) in this plant and highlights the prevalence of splicing site recognition for definition of introns in plants. We have analyzed the compositional profiles of exon-intron junctions by base-pairing nucleotides with U1 snRNA which serves as a model for describing the possibility of sequence conservation. The alternative splicing isoforms identified in this study are novel and represent one of the potentially biologically significant means by which B. distachyon controls the function of its genes. Our observations serve as a basis to understand alternative splicing events of cereal crops with more complex genomes, like wheat or barley.

  4. Accomplishments in genome-scale in silico modeling for industrial and medical biotechnology.

    Science.gov (United States)

    Milne, Caroline B; Kim, Pan-Jun; Eddy, James A; Price, Nathan D

    2009-12-01

    Driven by advancements in high-throughput biological technologies and the growing number of sequenced genomes, the construction of in silico models at the genome scale has provided powerful tools to investigate a vast array of biological systems and applications. Here, we review comprehensively the uses of such models in industrial and medical biotechnology, including biofuel generation, food production, and drug development. While the use of in silico models is still in its early stages for delivering to industry, significant initial successes have been achieved. For the cases presented here, genome-scale models predict engineering strategies to enhance properties of interest in an organism or to inhibit harmful mechanisms of pathogens. Going forward, genome-scale in silico models promise to extend their application and analysis scope to become a trans-formative tool in biotechnology.

  5. 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…

  6. 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…

  7. 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.

  8. Genome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom.

    Directory of Open Access Journals (Sweden)

    Jennifer Levering

    Full Text Available Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curated reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. The model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications.

  9. Genome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom.

    Science.gov (United States)

    Levering, Jennifer; Broddrick, Jared; Dupont, Christopher L; Peers, Graham; Beeri, Karen; Mayers, Joshua; Gallina, Alessandra A; Allen, Andrew E; Palsson, Bernhard O; Zengler, Karsten

    2016-01-01

    Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curated reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. The model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications.

  10. Testing the infinitely many genes model for the evolution of the bacterial core genome and pangenome.

    Science.gov (United States)

    Collins, R Eric; Higgs, Paul G

    2012-11-01

    When groups of related bacterial genomes are compared, the number of core genes found in all genomes is usually much less than the mean genome size, whereas the size of the pangenome (the set of genes found on at least one of the genomes) is much larger than the mean size of one genome. We analyze 172 complete genomes of Bacilli and compare the properties of the pangenomes and core genomes of monophyletic subsets taken from this group. We then assess the capabilities of several evolutionary models to predict these properties. The infinitely many genes (IMG) model is based on the assumption that each new gene can arise only once. The predictions of the model depend on the shape of the evolutionary tree that underlies the divergence of the genomes. We calculate results for coalescent trees, star trees, and arbitrary phylogenetic trees of predefined fixed branch length. On a star tree, the pangenome size increases linearly with the number of genomes, as has been suggested in some previous studies, whereas on a coalescent tree, it increases logarithmically. The coalescent tree gives a better fit to the data, for all the examples we consider. In some cases, a fixed phylogenetic tree proved better than the coalescent tree at reproducing structure in the gene frequency spectrum, but little improvement was gained in predictions of the core and pangenome sizes. Most of the data are well explained by a model with three classes of gene: an essential class that is found in all genomes, a slow class whose rate of origination and deletion is slow compared with the time of divergence of the genomes, and a fast class showing rapid origination and deletion. Although the majority of genes originating in a genome are in the fast class, these genes are not retained for long periods, and the majority of genes present in a genome are in the slow or essential classes. In general, we show that the IMG model is useful for comparison with experimental genome data both for species level and

  11. The fiduciary relationship model for managing clinical genomic "incidental" findings.

    Science.gov (United States)

    Lázaro-Muñoz, Gabriel

    2014-01-01

    This paper examines how the application of legal fiduciary principles (e.g., physicians' duty of loyalty and care, duty to inform, and duty act within the scope of authority), can serve as a framework to promote management of clinical genomic "incidental" or secondary target findings that is patient-centered and consistent with recognized patient autonomy rights. The application of fiduciary principles to the clinical genomic testing context gives rise to at least four physician fiduciary duties in conflict with recent recommendations by the American College of Medical Genetics and Genomics (ACMG). These recommendations have generated much debate among lawyers, clinicians, and bioethicists hence I believe this publication will be of value and interest to your readership. © 2014 American Society of Law, Medicine & Ethics, Inc.

  12. Structural Equation Modeling in Special Education Research.

    Science.gov (United States)

    Moore, Alan D.

    1995-01-01

    This article suggests the use of structural equation modeling in special education research, to analyze multivariate data from both nonexperimental and experimental research. It combines a structural model linking latent variables and a measurement model linking observed variables with latent variables. (Author/DB)

  13. Precision cancer mouse models through genome editing with CRISPR-Cas9

    OpenAIRE

    Mou, Haiwei; Kennedy, Zachary; Anderson, Daniel G.; Yin, Hao; Xue, Wen

    2015-01-01

    The cancer genome is highly complex, with hundreds of point mutations, translocations, and chromosome gains and losses per tumor. To understand the effects of these alterations, precise models are needed. Traditional approaches to the construction of mouse models are time-consuming and laborious, requiring manipulation of embryonic stem cells and multiple steps. The recent development of the clustered regularly interspersed short palindromic repeats (CRISPR)-Cas9 system, a powerful genome-edi...

  14. Updating the Model Definition of the Gene in the Modern Genomic Era with Implications for Instruction

    Science.gov (United States)

    Smith, Mike U.; Adkison, Linda R.

    2010-01-01

    Gericke and Hagberg (G & H, "Sci Educ" 16:849-881, 2007) recently published in this journal a thoughtful analysis of the historical progression of our understanding of the nature of the gene for use in instruction. This analysis, however, did not include the findings of the Human Genome Project (HGP), which must be included in any introductory…

  15. Updating the Model Definition of the Gene in the Modern Genomic Era with Implications for Instruction

    Science.gov (United States)

    Smith, Mike U.; Adkison, Linda R.

    2010-01-01

    Gericke and Hagberg (G & H, "Sci Educ" 16:849-881, 2007) recently published in this journal a thoughtful analysis of the historical progression of our understanding of the nature of the gene for use in instruction. This analysis, however, did not include the findings of the Human Genome Project (HGP), which must be included in any introductory…

  16. QTL Analysis and Functional Genomics of Animal Model

    DEFF Research Database (Denmark)

    Farajzadeh, Leila

    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...

  17. Residents as Educators: A Modern Model.

    Science.gov (United States)

    Kensinger, Clark D; McMaster, William G; Vella, Michael A; Sexton, Kevin W; Snyder, Rebecca A; Terhune, Kyla P

    2015-01-01

    Education during surgical residency has changed significantly. As part of the shifting landscape, the importance of an organized and structured curriculum has increased. However, establishing this is often difficult secondary to clinical demands and pressure both on faculty and residents. We present a peer-assisted learning model for academic institutions without professional non-clinical educations. The "resident as educator" (RAE) model empowers residents to be the organizers of the education curriculum. RAE is built on a culture of commitment to education, skill development and team building, allowing the upper level residents to develop and execute the curriculum. Several modules designed to address junior level residents and medical students' educational needs have been implemented, including (1) intern boot camp, (2) summer school, (3) technical skill sessions, (4) trauma orientation, (5) weekly teaching conferences, and (4) a fourth year medical student surgical preparation course. Promoting residents as educators leads to an overall benefit for the program by being cost-effective and time-efficient, while simultaneously promoting professional development of residents and a culture of education. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  18. Parental role models, gender and educational choice.

    Science.gov (United States)

    Dryler, H

    1998-09-01

    Parental role models are often put forward as an explanation for the choice of gender-atypical educational routes. This paper aims to test such explanations by examining the impact of family background variables like parental education and occupation, on choice of educational programme at upper secondary school. Using a sample of around 73,000 Swedish teenagers born between 1972 and 1976, girls' and boys' gender-atypical as well as gender-typical educational choices are analysed by means of logistic regression. Parents working or educated within a specific field increase the probability that a child will make a similar choice of educational programme at upper secondary school. This same-sector effect appeared to be somewhat stronger for fathers and sons, while no such same-sex influence was confirmed for girls. No evidence was found that, in addition to a same-sector effect, it matters whether parents' occupations represent gender-traditional or non-traditional models. Parents of the service classes or highly educated parents--expected to be the most gender egalitarian in attitudes and behaviours--have a positive influence upon children's choice of gender-atypical education.

  19. Educational software design: applying models of learning

    Directory of Open Access Journals (Sweden)

    Stephen Richards

    1996-12-01

    Full Text Available The model of learning adopted within this paper is the 'spreading ripples' (SR model proposed by Race (1994. This model was chosen for two important reasons. First, it makes use of accessible ideas and language, .and is therefore simple. Second, .Race suggests that the model can be used in the design, of educational and training programmes (and can thereby be applied to the design of computer-based learning materials.

  20. Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences.

    Science.gov (United States)

    Ganapathiraju, Madhavi K; Mitchell, Asia D; Thahir, Mohamed; Motwani, Kamiya; Ananthasubramanian, Seshan

    2012-12-01

    Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.

  1. Genome editing revolutionize the creation of genetically modified pigs for modeling human diseases.

    Science.gov (United States)

    Yao, Jing; Huang, Jiaojiao; Zhao, Jianguo

    2016-09-01

    Pigs have anatomical, physiological and genomic characteristics that make them highly suitable for modeling human diseases. Genetically modified (GM) pig models of human diseases are critical for studying pathogenesis, treatment, and prevention. The emergence of nuclease-mediated genome editing technology has been successfully employed for engineering of the pig genome, which has revolutionize the creation of GM pig models with highly complex pathophysiologies and comorbidities. In this review, we summarize the progress of recently developed genome editing technologies, including zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9), which enable highly efficient and precise introduction of genome modifications into pigs, and tailored disease models that have been generated in various disciplines via genome editing technology. We also summarize the GM pig models that have been generated by conventional transgenic strategies. Additionally, perspectives regarding the application of GM pigs in biomedical research are discussed.

  2. The mouse genome database: genotypes, phenotypes, and models of human disease.

    Science.gov (United States)

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

    2013-01-01

    The laboratory mouse is the premier animal model for studying human biology because all life stages can be accessed experimentally, a completely sequenced reference genome is publicly available and there exists a myriad of genomic tools for comparative and experimental research. In the current era of genome scale, data-driven biomedical research, the integration of genetic, genomic and biological data are essential for realizing the full potential of the mouse as an experimental model. The Mouse Genome Database (MGD; http://www.informatics.jax.org), the community model organism database for the laboratory mouse, is designed to facilitate the use of the laboratory mouse as a model system for understanding human biology and disease. To achieve this goal, MGD integrates genetic and genomic data related to the functional and phenotypic characterization of mouse genes and alleles and serves as a comprehensive catalog for mouse models of human disease. Recent enhancements to MGD include the addition of human ortholog details to mouse Gene Detail pages, the inclusion of microRNA knockouts to MGD's catalog of alleles and phenotypes, the addition of video clips to phenotype images, providing access to genotype and phenotype data associated with quantitative trait loci (QTL) and improvements to the layout and display of Gene Ontology annotations.

  3. A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction

    Directory of Open Access Journals (Sweden)

    Osval A. Montesinos-López

    2017-06-01

    Full Text Available There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is very large, while, in non-Bayesian models, there are often important and unsolved convergence problems. The variational Bayes method is popular in machine learning, and, by approximating the probability distributions through optimization, it tends to be faster than Markov Chain Monte Carlo methods. For this reason, in this paper, we propose a new genomic variational Bayes version of the Bayesian genomic model with G×E using half-t priors on each standard deviation (SD term to guarantee highly noninformative and posterior inferences that are not sensitive to the choice of hyper-parameters. We show the complete theoretical derivation of the full conditional and the variational posterior distributions, and their implementations. We used eight experimental genomic maize and wheat data sets to illustrate the new proposed variational Bayes approximation, and compared its predictions and implementation time with a standard Bayesian genomic model with G×E. Results indicated that prediction accuracies are slightly higher in the standard Bayesian model with G×E than in its variational counterpart, but, in terms of computation time, the variational Bayes genomic model with G×E is, in general, 10 times faster than the conventional Bayesian genomic model with G×E. For this reason, the proposed model may be a useful tool for researchers who need to predict and select genotypes in several environments.

  4. 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

  5. Competency model and standards for media education

    Directory of Open Access Journals (Sweden)

    Gerhard TULODZIECKI

    2012-12-01

    Full Text Available In Germany, educational standards for key school subjects have been developed as a consequence of the results of international comparative studies like PISA. Subsequently, supporters of interdisciplinary fields such as media education have also started calling for goals in the form of competency models and standards. In this context a competency standard model for media education will be developed with regard to the discussion about media competence and media education. In doing so the development of a competency model and the formulation of standards is described consequently as a decision making process. In this process decisions have to be made on competence areas and competence aspects to structure the model, on criteria to differentiate certain levels of competence, on the number of competence levels, on the abstraction level of standard formulations and on the tasks to test the standards. It is shown that the discussion on media education as well as on competencies and standards provides different possibilities of structuring, emphasizing and designing a competence standard model. Against this background we describe and give reasons for our decisions and our competency standards model. At the same time our contribution is meant to initiate further developments, testing and discussion.

  6. Mapping condition-dependent regulation of metabolism in yeast through genome-scale modeling

    DEFF Research Database (Denmark)

    Österlund, Tobias; Nookaew, Intawat; Bordel, Sergio

    2013-01-01

    ABSTRACT: BACKGROUND: The genome-scale metabolic model of Saccharomyces cerevisiae, first presented in 2003, was the first genome-scale network reconstruction for a eukaryotic organism. Since then continuous efforts have been made in order to improve and expand the yeast metabolic network. RESULTS......: Here we present iTO977, a comprehensive genome-scale metabolic model that contains more reactions, metabolites and genes than previous models. The model was constructed based on two earlier reconstructions, namely iIN800 and the consensus network, and then improved and expanded using gap......-filling methods and by introducing new reactions and pathways based on studies of the literature and databases. The model was shown to perform well both for growth simulations in different media and gene essentiality analysis for single and double knock-outs. Further, the model was used as a scaffold...

  7. Modelling human regulatory variation in mouse: finding the function in genome-wide association studies and whole-genome sequencing.

    Directory of Open Access Journals (Sweden)

    Jean-François Schmouth

    Full Text Available An increasing body of literature from genome-wide association studies and human whole-genome sequencing highlights the identification of large numbers of candidate regulatory variants of potential therapeutic interest in numerous diseases. Our relatively poor understanding of the functions of non-coding genomic sequence, and the slow and laborious process of experimental validation of the functional significance of human regulatory variants, limits our ability to fully benefit from this information in our efforts to comprehend human disease. Humanized mouse models (HuMMs, in which human genes are introduced into the mouse, suggest an approach to this problem. In the past, HuMMs have been used successfully to study human disease variants; e.g., the complex genetic condition arising from Down syndrome, common monogenic disorders such as Huntington disease and β-thalassemia, and cancer susceptibility genes such as BRCA1. In this commentary, we highlight a novel method for high-throughput single-copy site-specific generation of HuMMs entitled High-throughput Human Genes on the X Chromosome (HuGX. This method can be applied to most human genes for which a bacterial artificial chromosome (BAC construct can be derived and a mouse-null allele exists. This strategy comprises (1 the use of recombineering technology to create a human variant-harbouring BAC, (2 knock-in of this BAC into the mouse genome using Hprt docking technology, and (3 allele comparison by interspecies complementation. We demonstrate the throughput of the HuGX method by generating a series of seven different alleles for the human NR2E1 gene at Hprt. In future challenges, we consider the current limitations of experimental approaches and call for a concerted effort by the genetics community, for both human and mouse, to solve the challenge of the functional analysis of human regulatory variation.

  8. A regional model of interprofessional education

    Directory of Open Access Journals (Sweden)

    Maria Olenick

    2011-01-01

    Full Text Available Maria Olenick1, Edward Foote1, Patricia Vanston1, John Szarek1, Zachary Vaskalis1, Mary Jane Dimattio2, Raymond A Smego Jr21The Commonwealth Medical College, Scranton, PA, USA; Nesbitt College of Pharmacy and Nursing, Wilkes University, Wilkes-Barre, PA, USA; 2University of Scranton, Scranton, PA, USAAbstract: This paper describes the innovative features of the first regional model of interprofessional education (IPE in the US, developed by The Commonwealth Medical College, Scranton, PA, USA, as a new, independent, community-based medical school in northeastern Pennsylvania. Essential educational components include collaborative care seminars, interprofessional sessions, simulations, live web-based seminars and newly innovative virtual environment interactive exercises. All of these elements are being integrated into the curricula of 14 undergraduate and allied professional schools, and three graduate medical education programs located in the region. Activities incorporate simulation, standardized patients, student leadership, and faculty and student facilitation. As this new regional model of interprofessional education is fully implemented, its impact will be assessed using both quantitative and qualitative outcomes measurements. Appropriate ongoing modifications to the model will be made to ensure improvement and further applicability to collaborative learning.Keywords: interprofessional education, regional model, medical education

  9. Instructional Models Effective in Distance Education.

    Science.gov (United States)

    Jackman, Diane H.; Swan, Michael K.

    The purpose of this study was to identify which instructional models based on the framework of Joyce, Weil, and Showers, could be used effectively in distance education over the Interactive Video Network (IVN) system in North Dakota. Instructional models have been organized into families such as Information Processing, Social, Personal, and…

  10. Forecasting Models in the State Education System

    Directory of Open Access Journals (Sweden)

    Gintautas DZEMYDA

    2003-04-01

    Full Text Available This paper presents model-based assessment and forecasting of the Lithuanian education system in the period of 2001-2010. In order to obtain satisfactory forecasting results, constructing of models used for these aims should be grounded on some interactive data mining. Data mining of data stored in the system of the Lithuanian teacher's database and of data from other sources representing the state of education system and the demographic changes in Lithuania was used. The models cover the estimation of data quality in the databases, the analysis of flow of teachers and pupils, the clustering of schools, the model of dynamics of pedagogical staff and pupils, and the quality analysis of teachers. The main results of forecasting and integrated analysis of the Lithuanian teachers' database with other data reflecting the state of the education system and demographic changes in Lithuania are presented.

  11. QTL Analysis and Functional Genomics of Animal Model

    DEFF Research Database (Denmark)

    Farajzadeh, Leila

    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......, 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...

  12. Genome Editing and Its Applications in Model Organisms

    OpenAIRE

    Dongyuan Ma; Feng Liu

    2015-01-01

    Technological advances are important for innovative biological research. Development of molecular tools for DNA manipulation, such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and the clustered regularly-interspaced short palindromic repeat (CRISPR)/CRISPR-associated (Cas), has revolutionized genome editing. These approaches can be used to develop potential therapeutic strategies to effectively treat heritable diseases. In the last few years, subs...

  13. 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.

  14. MultiMetEval : Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

    NARCIS (Netherlands)

    Zakrzewski, Piotr; Medema, Marnix H.; Gevorgyan, Albert; Kierzek, Andrzej M.; Breitling, Rainer; Takano, Eriko; Fong, Stephen S.

    2012-01-01

    Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the co

  15. 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.

  16. Modelling empathy in medical and nursing education.

    Science.gov (United States)

    Malpas, Phillipa J; Corbett, Andrea

    2012-03-30

    Medical and nursing student numbers are expected to increase significantly in NZ over the next few years. The ethical, and professional and clinical skills' training of trainee health practitioners is a central and crucial component in medical and nursing education and is underpinned by a strong commitment to improve patient health and well being. In this discussion we reflect on the virtue of empathy and the importance of role modelling in the education of nurses and doctors. We endorse the claim that as medical educators, how and what we teach matters.

  17. Behavioral and Statistical Models of Educational Inequality

    DEFF Research Database (Denmark)

    Holm, Anders; Breen, Richard

    2016-01-01

    This article 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 to encourage students and their families to make better educational choices. We also establish the conditions under which empirical analysis can distinguish between the three sorts of decision-making, and we illustrate our arguments using data from the National Educational Longitudinal Study....

  18. 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...... to encourage students and their families to make better educational choices. We also establish the conditions under which empirical analysis can distinguish between the three sorts of decision-making and we illustrate our arguments using data from the National Educational Longitudinal Study....

  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, modeling has been discussed in a variety of ways, but often without explicit reference to the diversity of roles models play in scientific practice. We aim to expand and bring clarity to the myriad uses of models in science by presenting a framework from philosopher of biology Jay Odenbaugh that describes five pragmatic strategies of model use in the biological sciences. We then present illustrative examples of each of these roles from an empirical study of an undergraduate biological modeling curriculum, which highlight how students used models to help them frame their research question, explore ideas, and refine their conceptual understanding in an educational setting. Our aim is to begin to explicate the definition of modeling in science in a way that will allow educators and curriculum developers to make informed choices about how and for what purpose modeling enters science classrooms.

  20. 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

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

    Directory of Open Access Journals (Sweden)

    Feixiong Cheng

    2015-09-01

    Full Text Available 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.

  2. Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942

    Directory of Open Access Journals (Sweden)

    Julián Triana

    2014-08-01

    Full Text Available The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942.

  3. Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942

    Science.gov (United States)

    Triana, Julián; Montagud†, Arnau; Siurana, Maria; Fuente, David; Urchueguía, Arantxa; Gamermann, Daniel; Torres, Javier; Tena, Jose; de Córdoba, Pedro Fernández; Urchueguía, Javier F.

    2014-01-01

    The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942. PMID:25141288

  4. Genome-wide prediction, display and refinement of binding sites with information theory-based models

    Directory of Open Access Journals (Sweden)

    Leeder J Steven

    2003-09-01

    . Conclusions Delila-Genome was used to scan the human genome sequence with information weight matrices of transcription factor binding sites, including PXR/RXRα, AHR and NF-κB p50/p65, and matrices for RNA binding sites including splice donor, acceptor, and SC35 recognition sites. Comparisons of genome scans with the original and refined PXR/RXRα information weight matrices indicate that the refined model more accurately predicts the strengths of known binding sites and is more sensitive for detection of novel binding sites.

  5. 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.

  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. A mathematical model of radiation carcinogenesis with induction of genomic instability and cell death.

    Science.gov (United States)

    Ohtaki, M; Niwa, O

    2001-11-01

    We developed a mathematical model of carcinogenesis that incorporates genomic instability, a feature characterized by long-term destabilization of the genome in irradiated cells that leads to an increase in cancer risk in the exposed individuals at the cancer-prone age. This model also considers the induction of cell death, another important effect of radiation on cells. It is assumed that cell killing by radiation may occur at all stages of the carcinogenic process. The resulting model can explain not only the paradoxical relationship between low mutation rates and high cancer incidence but also the low-order dose-response relationship of cancer risk.

  8. 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.   

  9. A Model of Genome Size Evolution for Prokaryotes in Stable and Fluctuating Environments.

    Science.gov (United States)

    Bentkowski, Piotr; Van Oosterhout, Cock; Mock, Thomas

    2015-08-04

    Temporal variability in ecosystems significantly impacts species diversity and ecosystem productivity and therefore the evolution of organisms. Different levels of environmental perturbations such as seasonal fluctuations, natural disasters, and global change have different impacts on organisms and therefore their ability to acclimatize and adapt. Thus, to understand how organisms evolve under different perturbations is a key for predicting how environmental change will impact species diversity and ecosystem productivity. Here, we developed a computer simulation utilizing the individual-based model approach to investigate genome size evolution of a haploid, clonal and free-living prokaryotic population across different levels of environmental perturbations. Our results show that a greater variability of the environment resulted in genomes with a larger number of genes. Environmental perturbations were more effectively buffered by populations of individuals with relatively large genomes. Unpredictable changes of the environment led to a series of population bottlenecks followed by adaptive radiations. Our model shows that the evolution of genome size is indirectly driven by the temporal variability of the environment. This complements the effects of natural selection directly acting on genome optimization. Furthermore, species that have evolved in relatively stable environments may face the greatest risk of extinction under global change as genome streamlining genetically constrains their ability to acclimatize to the new environmental conditions, unless mechanisms of genetic diversification such as horizontal gene transfer will enrich their gene pool and therefore their potential to adapt.

  10. 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

    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...

  11. Interplay between Constraints, Objectives, and Optimality for Genome-Scale Stoichiometric Models

    NARCIS (Netherlands)

    Maarleveld, T.R.; Wortel, M.; Olivier, B.G.; Teusink, B.; Bruggeman, F.J.

    2015-01-01

    High-throughput data generation and genome-scale stoichiometric models have greatly facilitated the comprehensive study of metabolic networks. The computation of all feasible metabolic routes with these models, given stoichiometric, thermodynamic, and steady-state constraints, provides important ins

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

    Directory of Open Access Journals (Sweden)

    Amber L Hartman

    Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: The completed genome sequence, presented here, provides an invaluable tool for further in vivo and in vitro studies of Hfx. volcanii.

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

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim;

    2008-01-01

    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......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...... of hypothetical proteins accounted for more than 50% of the annotated genes. Considering the industrial importance of this fungus, it is therefore valuable to improve the annotation and further integrate genomic information with biochemical and physiological information available for this microorganism and other...

  14. Metal hyperaccumulation and hypertolerance: a model for plant evolutionary genomics.

    Science.gov (United States)

    Hanikenne, Marc; Nouet, Cécile

    2011-06-01

    In the course of evolution, plants adapted to widely differing metal availabilities in soils and therefore represent an important source of natural variation of metal homeostasis networks. Research on plant metal homeostasis can thus provide insights into the functioning, regulation and adaptation of biological networks. Here, we describe major recent breakthroughs in the understanding of the genetic and molecular basis of metal hyperaccumulation and associated hypertolerance, a naturally selected complex trait which represents an extreme adaptation of the metal homeostasis network. Investigations in this field reveal further the molecular alterations underlying the evolution of natural phenotypic diversity and provide a highly relevant framework for comparative genomics. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

    OpenAIRE

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

    2011-01-01

    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 ...

  16. 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…

  17. Models for Continuing Nursing Education in Gerontology.

    Science.gov (United States)

    Beckingham, Ann C.

    1995-01-01

    Gerontological faculty should extend teaching into the clinical field to provide continuing education for nurses. Two models are Train the Trainer and a workplace learning package consisting of videotape, self-study modules, and self-directed, problem-based group study. (SK)

  18. Value-Added Modeling in Physical Education

    Science.gov (United States)

    Hushman, Glenn; Hushman, Carolyn

    2015-01-01

    The educational reform movement in the United States has resulted in a variety of states moving toward a system of value-added modeling (VAM) to measure a teacher's contribution to student achievement. Recently, many states have begun using VAM scores as part of a larger system to evaluate teacher performance. In the past decade, only "core…

  19. 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…

  20. A Storytelling Learning Model for Legal Education

    Science.gov (United States)

    Capuano, Nicola; De Maio, Carmen; Gaeta, Angelo; Mangione, Giuseppina Rita; Salerno, Saverio; Fratesi, Eleonora

    2014-01-01

    The purpose of this paper is to describe a learning model based on "Storytelling" and its application in the context of legal education helping build challenging training resources that explain, to common citizens with little or no background about legal topics, concepts related to "Legal Mediation" in general and in specific…

  1. Conceptualizing Evolving Models of Educational Development

    Science.gov (United States)

    Fraser, Kym; Gosling, David; Sorcinelli, Mary Deane

    2010-01-01

    Educational development, which the authors use to refer to the field of professional and strategic development associated with university and college learning and teaching, can be described in many ways by referring to its different aspects. In this article the authors endeavor to categorize many of the models that have been used to describe…

  2. Models for mergers in higher education

    African Journals Online (AJOL)

    Rigor in qualitative research: the assessment of trustworthiness. The ... A possible model for higher education mergers, based on such ... The South African Universities' Vice-Chancellor's Association ..... the drafting of a merger plan and could prevent a joint culture and .... Creating a merger contract that includes. S.

  3. MIRAGE: a functional genomics-based approach for metabolic network model reconstruction and its application to cyanobacteria networks.

    Science.gov (United States)

    Vitkin, Edward; Shlomi, Tomer

    2012-11-29

    Genome-scale metabolic network reconstructions are considered a key step in quantifying the genotype-phenotype relationship. We present a novel gap-filling approach, MetabolIc Reconstruction via functionAl GEnomics (MIRAGE), which identifies missing network reactions by integrating metabolic flux analysis and functional genomics data. MIRAGE's performance is demonstrated on the reconstruction of metabolic network models of E. coli and Synechocystis sp. and validated via existing networks for these species. Then, it is applied to reconstruct genome-scale metabolic network models for 36 sequenced cyanobacteria amenable for constraint-based modeling analysis and specifically for metabolic engineering. The reconstructed network models are supplied via standard SBML files.

  4. Application of functional genomics to the chimeric mouse model of HCV infection: optimization of microarray protocols and genomics analysis

    Directory of Open Access Journals (Sweden)

    Smith Maria W

    2006-05-01

    Full Text Available Abstract Background Many model systems of human viral disease involve human-mouse chimeric tissue. One such system is the recently developed SCID-beige/Alb-uPA mouse model of hepatitis C virus (HCV infection which involves a human-mouse chimeric liver. The use of functional genomics to study HCV infection in these chimeric tissues is complicated by the potential cross-hybridization of mouse mRNA on human oligonucleotide microarrays. To identify genes affected by mouse liver mRNA hybridization, mRNA from identical human liver samples labeled with either Cy3 or Cy5 was compared in the presence and absence of known amounts of mouse liver mRNA labeled in only one dye. Results The results indicate that hybridization of mouse mRNA to the corresponding human gene probe on Agilent Human 22 K oligonucleotide microarray does occur. The number of genes affected by such cross-hybridization was subsequently reduced to approximately 300 genes both by increasing the hybridization temperature and using liver samples which contain at least 80% human tissue. In addition, Real Time quantitative RT-PCR using human specific probes was shown to be a valid method to verify the expression level in human cells of known cross-hybridizing genes. Conclusion The identification of genes affected by cross-hybridization of mouse liver RNA on human oligonucleotide microarrays makes it feasible to use functional genomics approaches to study the chimeric SCID-beige/Alb-uPA mouse model of HCV infection. This approach used to study cross-species hybridization on oligonucleotide microarrays can be adapted to other chimeric systems of viral disease to facilitate selective analysis of human gene expression.

  5. Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum

    Directory of Open Access Journals (Sweden)

    Hirasawa Takashi

    2009-08-01

    Full Text Available Abstract Background In silico genome-scale metabolic models enable the analysis of the characteristics of metabolic systems of organisms. In this study, we reconstructed a genome-scale metabolic model of Corynebacterium glutamicum on the basis of genome sequence annotation and physiological data. The metabolic characteristics were analyzed using flux balance analysis (FBA, and the results of FBA were validated using data from culture experiments performed at different oxygen uptake rates. Results The reconstructed genome-scale metabolic model of C. glutamicum contains 502 reactions and 423 metabolites. We collected the reactions and biomass components from the database and literatures, and made the model available for the flux balance analysis by filling gaps in the reaction networks and removing inadequate loop reactions. Using the framework of FBA and our genome-scale metabolic model, we first simulated the changes in the metabolic flux profiles that occur on changing the oxygen uptake rate. The predicted production yields of carbon dioxide and organic acids agreed well with the experimental data. The metabolic profiles of amino acid production phases were also investigated. A comprehensive gene deletion study was performed in which the effects of gene deletions on metabolic fluxes were simulated; this helped in the identification of several genes whose deletion resulted in an improvement in organic acid production. Conclusion The genome-scale metabolic model provides useful information for the evaluation of the metabolic capabilities and prediction of the metabolic characteristics of C. glutamicum. This can form a basis for the in silico design of C. glutamicum metabolic networks for improved bioproduction of desirable metabolites.

  6. 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 interpretati

  7. Animal models for human contiguous gene syndromes and other genomic disorders

    Directory of Open Access Journals (Sweden)

    Katherina Walz

    2004-01-01

    Full Text Available Genomic disorders refer to a group of syndromes caused by DNA rearrangements, such as deletions and duplications, which result in an alteration of normal gene dosage. The chromosomal rearrangements are usually relatively small and often difficult to detect cytogenetically. In a subset of such conditions the rearrangements comprise multiple unrelated contiguous genes that are physically linked and thus have been referred to as contiguous gene syndromes (CGS. In general, each syndrome presents a complex clinical phenotype that has been attributed generally to dosage sensitive gene(s present in the responsible chromosomal interval. A common mechanism for CGS resulting from interstitial deletion/duplication has recently been elucidated. The DNA rearrangements result from nonallelic homologous recombination (NAHR utilizing flanking low-copy repeats (LCRs as recombination substrates. The resulting rearrangements often involve the same genomic region, a common deletion or duplication, making it difficult to assign a specific phenotype or endophenotype to a single responsible gene. The human and mouse genome sequencing projects, in conjunction with the ability to engineer mouse chromosome rearrangements, have enabled the production of mouse models for CGS and genomic disorders. In this review we present an overview of different techniques utilized to generate mouse models for selected genomic disorders. These models foment novel insights into the specific genes that convey the phenotype by dosage and/or position effects and provide opportunities to explore therapeutic options.

  8. 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.

  9. 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.

  10. Identification of DNA motifs implicated in maintenance of bacterial core genomes by predictive modeling.

    Science.gov (United States)

    Halpern, David; Chiapello, Hélène; Schbath, Sophie; Robin, Stéphane; Hennequet-Antier, Christelle; Gruss, Alexandra; El Karoui, Meriem

    2007-09-01

    Bacterial biodiversity at the species level, in terms of gene acquisition or loss, is so immense that it raises the question of how essential chromosomal regions are spared from uncontrolled rearrangements. Protection of the genome likely depends on specific DNA motifs that impose limits on the regions that undergo recombination. Although most such motifs remain unidentified, they are theoretically predictable based on their genomic distribution properties. We examined the distribution of the "crossover hotspot instigator," or Chi, in Escherichia coli, and found that its exceptional distribution is restricted to the core genome common to three strains. We then formulated a set of criteria that were incorporated in a statistical model to search core genomes for motifs potentially involved in genome stability in other species. Our strategy led us to identify and biologically validate two distinct heptamers that possess Chi properties, one in Staphylococcus aureus, and the other in several streptococci. This strategy paves the way for wide-scale discovery of other important functional noncoding motifs that distinguish core genomes from the strain-variable regions.

  11. Identification of DNA motifs implicated in maintenance of bacterial core genomes by predictive modeling.

    Directory of Open Access Journals (Sweden)

    David Halpern

    2007-09-01

    Full Text Available Bacterial biodiversity at the species level, in terms of gene acquisition or loss, is so immense that it raises the question of how essential chromosomal regions are spared from uncontrolled rearrangements. Protection of the genome likely depends on specific DNA motifs that impose limits on the regions that undergo recombination. Although most such motifs remain unidentified, they are theoretically predictable based on their genomic distribution properties. We examined the distribution of the "crossover hotspot instigator," or Chi, in Escherichia coli, and found that its exceptional distribution is restricted to the core genome common to three strains. We then formulated a set of criteria that were incorporated in a statistical model to search core genomes for motifs potentially involved in genome stability in other species. Our strategy led us to identify and biologically validate two distinct heptamers that possess Chi properties, one in Staphylococcus aureus, and the other in several streptococci. This strategy paves the way for wide-scale discovery of other important functional noncoding motifs that distinguish core genomes from the strain-variable regions.

  12. Ongoing ecological divergence in an emerging genomic model.

    Science.gov (United States)

    Arnegard, Matthew E

    2009-07-01

    Much of Earth's biodiversity has arisen through adaptive radiation. Important avenues of phenotypic divergence during this process include the evolution of body size and life history (Schluter 2000). Extensive adaptive radiations of cichlid fishes have occurred in the Great Lakes of Africa, giving rise to behaviours that are remarkably sophisticated and diverse across species. In Tanganyikan shell-brooding cichlids of the tribe Lamprologini, tremendous intraspecific variation in body size accompanies complex breeding systems and use of empty snail shells to hide from predators and rear offspring. A study by Takahashi et al. (2009) in this issue of Molecular Ecology reveals the first case of genetic divergence between dwarf and normal-sized morphs of the same nominal lamprologine species, Telmatochromis temporalis. Patterns of population structure suggest that the dwarf, shell-dwelling morph of T. temporalis might have arisen from the normal, rock-dwelling morph independently in more than one region of the lake, and that pairs of morphs at different sites may represent different stages early in the process of ecological speciation. The findings of Takahashi et al. are important first steps towards understanding the evolution of these intriguing morphs, yet many questions remain unanswered about the mating system, gene flow, plasticity and selection. Despite these limitations, descriptive work like theirs takes on much significance in African cichlids due to forthcoming resources for comparative genomics.

  13. Towards a methodology for educational modelling: a case in educational assessment

    NARCIS (Netherlands)

    Giesbers, Bas; Van Bruggen, Jan; Hermans, Henry; Joosten-ten Brinke, Desirée; Burgers, Jan; Koper, Rob; Latour, Ignace

    2005-01-01

    Giesbers, B., van Bruggen, J., Hermans, H., Joosten-ten Brinke, D., Burgers, J., Koper, R., & Latour, I. (2007). Towards a methodology for educational modelling: a case in educational assessment. Educational Technology & Society, 10 (1), 237-247.

  14. Modeling Method for Increased Precision and Scope of Directly Measurable Fluxes at a Genome-Scale

    DEFF Research Database (Denmark)

    McCloskey, Douglas; Young, Jamey D.; Xu, Sibei

    2016-01-01

    Metabolic flux analysis (MFA) is considered to be the gold standard for determining the intracellular flux distribution of biological systems. The majority of work using MFA has been limited to core models of metabolism due to challenges in implementing genome-scale MFA and the undesirable trade...... distributions (MIDs),(1) it was found that a total of 232 net fluxes of central and peripheral metabolism could be resolved in the E. coli network. The increase in scope was shown to cover the full biosynthetic route to an expanded set of bioproduction pathways, which should facilitate applications......-off between increased scope and decreased precision in flux estimations. This work presents a tunable workflow for expanding the scope of MFA to the genome-scale without trade-offs in flux precision. The genome-scale MFA model presented here, iDM2014, accounts for 537 net reactions, which includes the core...

  15. 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.

  16. Modeling chromosomes in mouse to explore the function of genes, genomic disorders, and chromosomal organization.

    Directory of Open Access Journals (Sweden)

    Véronique Brault

    2006-07-01

    Full Text Available One of the challenges of genomic research after the completion of the human genome project is to assign a function to all the genes and to understand their interactions and organizations. Among the various techniques, the emergence of chromosome engineering tools with the aim to manipulate large genomic regions in the mouse model offers a powerful way to accelerate the discovery of gene functions and provides more mouse models to study normal and pathological developmental processes associated with aneuploidy. The combination of gene targeting in ES cells, recombinase technology, and other techniques makes it possible to generate new chromosomes carrying specific and defined deletions, duplications, inversions, and translocations that are accelerating functional analysis. This review presents the current status of chromosome engineering techniques and discusses the different applications as well as the implication of these new techniques in future research to better understand the function of chromosomal organization and structures.

  17. 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.

  18. Modeling Web-based Educational Systems: Process Design Teaching Model

    Directory of Open Access Journals (Sweden)

    Elena Rokou

    2004-01-01

    Full Text Available Using modeling languages is essential to the construction of educational systems based on software engineering principles and methods. Furthermore, the instructional design is undoubtedly the cornerstone of the design and development of educational systems. Although several methodologies and languages have been proposed for the specification of isolated educational multimedia systems, none has optimum results for the description of these systems and, especially, for their pedagogical aspect. Of course this is due primarily to how these systems function and are applied; it is not due to the language itself, although its special characteristics contribute substantially to the development of these systems sometimes positively and sometimes negatively. In this paper, we briefly describe the introduction of stereotypes to the pedagogical design of educational systems and appropriate modifications of the existing package diagrams of UML (Unified Modeling Language. The main objective of these new stereotypes is to describe sufficiently the mechanisms of generation, monitoring and re-adapting of teaching and student’s models which can be used in the educational applications.

  19. Genome-wide analysis of simple sequence repeats in the model medicinal mushroom Ganoderma lucidum.

    Science.gov (United States)

    Qian, Jun; Xu, Haibin; Song, Jingyuan; Xu, Jiang; Zhu, Yingjie; Chen, Shilin

    2013-01-10

    Simple sequence repeats (SSRs) or microsatellites are one of the most popular sources of genetic markers and play a significant role in gene function and genome organization. We identified SSRs in the genome of Ganoderma lucidum and analyzed their frequency and distribution in different genomic regions. We also compared the SSRs in G. lucidum with six other Agaricomycetes genomes: Coprinopsis cinerea, Laccaria bicolor, Phanerochaete chrysosporium, Postia placenta, Schizophyllum commune and Serpula lacrymans. Based on our search criteria, the total number of SSRs found ranged from 1206 to 6104 and covered from 0.04% to 0.15% of the fungal genomes. The SSR abundance was not correlated with the genome size, and mono- to tri-nucleotide repeats outnumbered other SSR categories in all of the species examined. In G. lucidum, a repertoire of 2674 SSRs was detected, with mono-nucleotides being the most abundant. SSRs were found in all genomic regions and were more abundant in non-coding regions than coding regions. The highest SSR relative abundance was found in introns (108 SSRs/Mb), followed by intergenic regions (84 SSRs/Mb). A total of 684 SSRs were found in the protein-coding sequences (CDSs) of 588 gene models, with 81.4% of them being tri- or hexa-nucleotides. After scanning for InterPro domains, 280 of these genes were successfully annotated, and 215 of them could be assigned to Gene Ontology (GO) terms. SSRs were also identified in 28 bioactive compound synthesis-related gene models, including one 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR), three polysaccharide biosynthesis genes and 24 cytochrome P450 monooxygenases (CYPs). Primers were designed for the identified SSR loci, providing the basis for the future development of SSR markers of this medicinal fungus.

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

    DEFF Research Database (Denmark)

    Have, Christian Theil; Mørk, Søren

    using the probabilistic logic programming language and machine learning system PRISM - a fast and efficient model prototyping environment, using bacterial gene finding performance as a benchmark of signal strength. The model is used to prune a set of gene predictions from an underlying gene finder...

  1. 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.

  2. 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.

  3. Pantograph: A template-based method for genome-scale metabolic model reconstruction.

    Science.gov (United States)

    Loira, Nicolas; Zhukova, Anna; Sherman, David James

    2015-04-01

    Genome-scale metabolic models are a powerful tool to study the inner workings of biological systems and to guide applications. The advent of cheap sequencing has brought the opportunity to create metabolic maps of biotechnologically interesting organisms. While this drives the development of new methods and automatic tools, network reconstruction remains a time-consuming process where extensive manual curation is required. This curation introduces specific knowledge about the modeled organism, either explicitly in the form of molecular processes, or indirectly in the form of annotations of the model elements. Paradoxically, this knowledge is usually lost when reconstruction of a different organism is started. We introduce the Pantograph method for metabolic model reconstruction. This method combines a template reaction knowledge base, orthology mappings between two organisms, and experimental phenotypic evidence, to build a genome-scale metabolic model for a target organism. Our method infers implicit knowledge from annotations in the template, and rewrites these inferences to include them in the resulting model of the target organism. The generated model is well suited for manual curation. Scripts for evaluating the model with respect to experimental data are automatically generated, to aid curators in iterative improvement. We present an implementation of the Pantograph method, as a toolbox for genome-scale model reconstruction, curation and validation. This open source package can be obtained from: http://pathtastic.gforge.inria.fr.

  4. 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.…

  5. Reconstruction of genome-scale metabolic models for 126 human tissues using mCADRE.

    Science.gov (United States)

    Wang, Yuliang; Eddy, James A; Price, Nathan D

    2012-12-13

    Human tissues perform diverse metabolic functions. Mapping out these tissue-specific functions in genome-scale models will advance our understanding of the metabolic basis of various physiological and pathological processes. The global knowledgebase of metabolic functions categorized for the human genome (Human Recon 1) coupled with abundant high-throughput data now makes possible the reconstruction of tissue-specific metabolic models. However, the number of available tissue-specific models remains incomplete compared with the large diversity of human tissues. We developed a method called metabolic Context-specificity Assessed by Deterministic Reaction Evaluation (mCADRE). mCADRE is able to infer a tissue-specific network based on gene expression data and metabolic network topology, along with evaluation of functional capabilities during model building. mCADRE produces models with similar or better functionality and achieves dramatic computational speed up over existing methods. Using our method, we reconstructed draft genome-scale metabolic models for 126 human tissue and cell types. Among these, there are models for 26 tumor tissues along with their normal counterparts, and 30 different brain tissues. We performed pathway-level analyses of this large collection of tissue-specific models and identified the eicosanoid metabolic pathway, especially reactions catalyzing the production of leukotrienes from arachidnoic acid, as potential drug targets that selectively affect tumor tissues. This large collection of 126 genome-scale draft metabolic models provides a useful resource for studying the metabolic basis for a variety of human diseases across many tissues. The functionality of the resulting models and the fast computational speed of the mCADRE algorithm make it a useful tool to build and update tissue-specific metabolic models.

  6. Pedigree models for complex human traits involving the mitochrondrial genome

    Energy Technology Data Exchange (ETDEWEB)

    Schork, N.J.; Guo, S.W. (Univ. of Michigan, Ann Arbor, MI (United States))

    1993-12-01

    Recent biochemical and molecular-genetic discoveries concerning variations in human mtDNA have suggested a role for mtDNA mutations in a number of human traits and disorders. Although the importance of these discoveries cannot be emphasized enough, the complex natures of mitochondrial biogenesis, mutant mtDNA phenotype expression, and the maternal inheritance pattern exhibited by mtDNA transmission make it difficult to develop models that can be used routinely in pedigree analyses to quantify and test hypotheses about the role of mtDNA in the expression of a trait. In the present paper, the authors describe complexities inherent in mitochondrial biogenesis and genetic transmission and show how these complexities can be incorporated into appropriate mathematical models. The authors offer a variety of likelihood-based models which account for the complexities discussed. The derivation of the models is meant to stimulate the construction of statistical tests for putative mtDNA contribution to a trait. Results of simulation studies which make use of the proposed models are described. The results of the simulation studies suggest that, although pedigree models of mtDNA effects can be reliable, success in mapping chromosomal determinants of a trait does not preclude the possibility that mtDNA determinants exist for the trait as well. Shortcomings inherent in the proposed models are described in an effort to expose areas in need of additional research. 58 refs., 5 figs., 2 tabs.

  7. Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling

    NARCIS (Netherlands)

    Wodke, J.A.; Puchalka, J.; Lluch-Senar, M.; Marcos, J.; Yus, E.; Godinho, M.; Gutierrez-Gallego, R.; Martins Dos Santos, V.A.P.; Serrano, L.; Klipp, E.; Maier, T.

    2013-01-01

    Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the met

  8. 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...

  9. 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 featu...

  10. 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...

  11. Challenges in experimental data integration within genome-scale metabolic models

    Directory of Open Access Journals (Sweden)

    Képès François

    2010-04-01

    Full Text Available Abstract A report of the meeting "Challenges in experimental data integration within genome-scale metabolic models", Institut Henri Poincaré, Paris, October 10-11 2009, organized by the CNRS-MPG joint program in Systems Biology.

  12. 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...

  13. Draft Genome Sequence of the Phyllosphere Model Bacterium Pantoea agglomerans 299R

    NARCIS (Netherlands)

    Remus-Emsermann, M.N.P.; Kim, E.B.; Marco, M.L.; Tecon, R.; Leveau, J.H.J.

    2013-01-01

    Bacteria belonging to the genus Pantoea are common colonizers of plant leaf surfaces. Here, we present the draft genome sequence of Pantoea agglomerans 299R, a phyllosphere isolate that has become a model strain for studying the ecology of plant leaf-associated bacterial commensals.

  14. Comparative genome-scale metabolic modeling of actinomycetes : The topology of essential core metabolism

    NARCIS (Netherlands)

    Alam, Mohammad Tauqeer; Medema, Marnix H.; Takano, Eriko; Breitling, Rainer; Gojobori, Takashi

    2011-01-01

    Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of act

  15. Comparative genome-scale metabolic modeling of actinomycetes: the topology of essential core metabolism.

    NARCIS (Netherlands)

    Alam, M.T.; Medema, M.H.; Takano, E.; Breitling, R.

    2011-01-01

    Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of act

  16. Comparative genome-scale metabolic modeling of actinomycetes: the topology of essential core metabolism.

    NARCIS (Netherlands)

    Alam, M.T.; Medema, M.H.; Takano, E.; Breitling, R.

    2011-01-01

    Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of

  17. Comparative genome-scale metabolic modeling of actinomycetes : The topology of essential core metabolism

    NARCIS (Netherlands)

    Alam, Mohammad Tauqeer; Medema, Marnix H.; Takano, Eriko; Breitling, Rainer; Gojobori, Takashi

    2011-01-01

    Actinomycetes are highly important bacteria. On one hand, some of them cause severe human and plant diseases, on the other hand, many species are known for their ability to produce antibiotics. Here we report the results of a comparative analysis of genome-scale metabolic models of 37 species of

  18. Cluster model of social partnership in municipal education

    Directory of Open Access Journals (Sweden)

    Romanova Oksana

    2016-03-01

    Full Text Available This article discusses the model of educational clusters that are based on social interaction between educational institutions and public-private partnerships. Particular attention is paid to methods of creating such educational network, which allows not only to educational organizations to obtain the missing for the implementation of educational activities and resources to achieve certain educational outcomes, but also to meet the needs of customers of educational services. Different approaches to the formation of a model educational cluster, based on partnerships.

  19. 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.

  20. 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.

  1. CRISPR-Cas9 Knockin Mice for Genome Editing and Cancer Modeling

    OpenAIRE

    Platt, Randall J.; Chen, Sidi; ZHOU Yang; Yim, Michael J.; Swiech, Lukasz; Kempton, Hannah R.; Dahlman, James E.; Parnas, Oren; Eisenhaure, Thomas M.; Jovanovic, Marko; Graham, Daniel B.; Jhunjhunwala, Siddharth; Xavier, Ramnik J.; Langer, Robert; Anderson, Daniel G.

    2014-01-01

    CRISPR-Cas9 is a versatile genome editing technology for studying the functions of genetic elements. To broadly enable the application of Cas9 in vivo, we established a Cre-dependent Cas9 knockin mouse. We demonstrated in vivo as well as ex vivo genome editing using adeno-associated virus (AAV)-, lentivirus-, or particle-mediated delivery of guide RNA in neurons, immune cells, and endothelial cells. Using these mice, we simultaneously modeled the dynamics of KRAS, p53, and LKB1, the top three...

  2. 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

  3. Discriminative accuracy of genomic profiling comparing multiplicative and additive risk models.

    Science.gov (United States)

    Moonesinghe, Ramal; Khoury, Muin J; Liu, Tiebin; Janssens, A Cecile J W

    2011-02-01

    Genetic prediction of common diseases is based on testing multiple genetic variants with weak effect sizes. Standard logistic regression and Cox Proportional Hazard models that assess the combined effect of multiple variants on disease risk assume multiplicative joint effects of the variants, but this assumption may not be correct. The risk model chosen may affect the predictive accuracy of genomic profiling. We investigated the discriminative accuracy of genomic profiling by comparing additive and multiplicative risk models. We examined genomic profiles of 40 variants with genotype frequencies varying from 0.1 to 0.4 and relative risks varying from 1.1 to 1.5 in separate scenarios assuming a disease risk of 10%. The discriminative accuracy was evaluated by the area under the receiver operating characteristic curve. Predicted risks were more extreme at the lower and higher risks for the multiplicative risk model compared with the additive model. The discriminative accuracy was consistently higher for multiplicative risk models than for additive risk models. The differences in discriminative accuracy were negligible when the effect sizes were small (risk genotypes were common or when they had stronger effects. Unraveling the exact mode of biological interaction is important when effect sizes of genetic variants are moderate at the least, to prevent the incorrect estimation of risks.

  4. Genome Scans for Detecting Footprints of Local Adaptation Using a Bayesian Factor Model

    Science.gov (United States)

    Duforet-Frebourg, Nicolas; Bazin, Eric; Blum, Michael G.B.

    2014-01-01

    There is a considerable impetus in population genomics to pinpoint loci involved in local adaptation. A powerful approach to find genomic regions subject to local adaptation is to genotype numerous molecular markers and look for outlier loci. One of the most common approaches for selection scans is based on statistics that measure population differentiation such as FST. However, there are important caveats with approaches related to FST because they require grouping individuals into populations and they additionally assume a particular model of population structure. Here, we implement a more flexible individual-based approach based on Bayesian factor models. Factor models capture population structure with latent variables called factors, which can describe clustering of individuals into populations or isolation-by-distance patterns. Using hierarchical Bayesian modeling, we both infer population structure and identify outlier loci that are candidates for local adaptation. In order to identify outlier loci, the hierarchical factor model searches for loci that are atypically related to population structure as measured by the latent factors. In a model of population divergence, we show that it can achieve a 2-fold or more reduction of false discovery rate compared with the software BayeScan or with an FST approach. We show that our software can handle large data sets by analyzing the single nucleotide polymorphisms of the Human Genome Diversity Project. The Bayesian factor model is implemented in the open-source PCAdapt software. PMID:24899666

  5. iAK692: A genome-scale metabolic model of Spirulina platensis C1

    Science.gov (United States)

    2012-01-01

    Background Spirulina (Arthrospira) platensis is a well-known filamentous cyanobacterium used in the production of many industrial products, including high value compounds, healthy food supplements, animal feeds, pharmaceuticals and cosmetics, for example. It has been increasingly studied around the world for scientific purposes, especially for its genome, biology, physiology, and also for the analysis of its small-scale metabolic network. However, the overall description of the metabolic and biotechnological capabilities of S. platensis requires the development of a whole cellular metabolism model. Recently, the S. platensis C1 (Arthrospira sp. PCC9438) genome sequence has become available, allowing systems-level studies of this commercial cyanobacterium. Results In this work, we present the genome-scale metabolic network analysis of S. platensis C1, iAK692, its topological properties, and its metabolic capabilities and functions. The network was reconstructed from the S. platensis C1 annotated genomic sequence using Pathway Tools software to generate a preliminary network. Then, manual curation was performed based on a collective knowledge base and a combination of genomic, biochemical, and physiological information. The genome-scale metabolic model consists of 692 genes, 837 metabolites, and 875 reactions. We validated iAK692 by conducting fermentation experiments and simulating the model under autotrophic, heterotrophic, and mixotrophic growth conditions using COBRA toolbox. The model predictions under these growth conditions were consistent with the experimental results. The iAK692 model was further used to predict the unique active reactions and essential genes for each growth condition. Additionally, the metabolic states of iAK692 during autotrophic and mixotrophic growths were described by phenotypic phase plane (PhPP) analysis. Conclusions This study proposes the first genome-scale model of S. platensis C1, iAK692, which is a predictive metabolic platform

  6. iAK692: A genome-scale metabolic model of Spirulina platensis C1

    Directory of Open Access Journals (Sweden)

    Klanchui Amornpan

    2012-06-01

    Full Text Available Abstract Background Spirulina (Arthrospira platensis is a well-known filamentous cyanobacterium used in the production of many industrial products, including high value compounds, healthy food supplements, animal feeds, pharmaceuticals and cosmetics, for example. It has been increasingly studied around the world for scientific purposes, especially for its genome, biology, physiology, and also for the analysis of its small-scale metabolic network. However, the overall description of the metabolic and biotechnological capabilities of S. platensis requires the development of a whole cellular metabolism model. Recently, the S. platensis C1 (Arthrospira sp. PCC9438 genome sequence has become available, allowing systems-level studies of this commercial cyanobacterium. Results In this work, we present the genome-scale metabolic network analysis of S. platensis C1, iAK692, its topological properties, and its metabolic capabilities and functions. The network was reconstructed from the S. platensis C1 annotated genomic sequence using Pathway Tools software to generate a preliminary network. Then, manual curation was performed based on a collective knowledge base and a combination of genomic, biochemical, and physiological information. The genome-scale metabolic model consists of 692 genes, 837 metabolites, and 875 reactions. We validated iAK692 by conducting fermentation experiments and simulating the model under autotrophic, heterotrophic, and mixotrophic growth conditions using COBRA toolbox. The model predictions under these growth conditions were consistent with the experimental results. The iAK692 model was further used to predict the unique active reactions and essential genes for each growth condition. Additionally, the metabolic states of iAK692 during autotrophic and mixotrophic growths were described by phenotypic phase plane (PhPP analysis. Conclusions This study proposes the first genome-scale model of S. platensis C1, iAK692, which is a

  7. Swine models, genomic tools and services to enhance our understanding of human health and diseases.

    Science.gov (United States)

    Walters, Eric M; Wells, Kevin D; Bryda, Elizabeth C; Schommer, Susan; Prather, Randall S

    2017-03-22

    The pig is becoming increasingly important as a biomedical model. Given the similarities between pigs and humans, a greater understanding of the underlying biology of human health and diseases may come from the pig rather than from classical rodent models. With an increasing need for swine models, it is essential that the genomic tools, models and services be readily available to the scientific community. Many of these are available through the National Swine Resource and Research Center (NSRRC), a facility funded by the US National Institutes of Health at the University of Missouri. The goal of the NSRRC is to provide high-quality biomedical swine models to the scientific community.

  8. [Application of CRISPR-Cas9 genome editing for constructing animal models of human diseases].

    Science.gov (United States)

    Ou, Zhanhui; Sun, Xiaofang

    2016-08-01

    The CRISPR-Cas9 system is a new targeted nuclease for genome editing, which can directly introduce modifications at the targeted genomic locus. The system utilizes a short single guide RNA (sgRNA) to direct the endonuclease Cas9 in the genome. Upon targeting, Cas9 can generate DNA double-strand breaks (DSBs). As such DSBs are repaired by non-homologous end joining (NHEJ) or homology directed repair (HDR), therefore facilitates introduction of random or specific mutations, repair of endogenous mutations, or insertion of DNA elements. The system has been successfully used to generate gene targeted cell lines including those of human, animals and plants. This article reviews recent advances made in this rapidly evolving technique for the generation of animal models for human diseases.

  9. 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.

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

    DEFF Research Database (Denmark)

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J.; Shojaosadati, Seyed Abbas;

    2016-01-01

    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...

  11. 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...

  12. LegumeIP: an integrative database for comparative genomics and transcriptomics of model legumes.

    Science.gov (United States)

    Li, Jun; Dai, Xinbin; Liu, Tingsong; Zhao, Patrick Xuechun

    2012-01-01

    Legumes play a vital role in maintaining the nitrogen cycle of the biosphere. They conduct symbiotic nitrogen fixation through endosymbiotic relationships with bacteria in root nodules. However, this and other characteristics of legumes, including mycorrhization, compound leaf development and profuse secondary metabolism, are absent in the typical model plant Arabidopsis thaliana. We present LegumeIP (http://plantgrn.noble.org/LegumeIP/), an integrative database for comparative genomics and transcriptomics of model legumes, for studying gene function and genome evolution in legumes. LegumeIP compiles gene and gene family information, syntenic and phylogenetic context and tissue-specific transcriptomic profiles. The database holds the genomic sequences of three model legumes, Medicago truncatula, Glycine max and Lotus japonicus plus two reference plant species, A. thaliana and Populus trichocarpa, with annotations based on UniProt, InterProScan, Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes databases. LegumeIP also contains large-scale microarray and RNA-Seq-based gene expression data. Our new database is capable of systematic synteny analysis across M. truncatula, G. max, L. japonicas and A. thaliana, as well as construction and phylogenetic analysis of gene families across the five hosted species. Finally, LegumeIP provides comprehensive search and visualization tools that enable flexible queries based on gene annotation, gene family, synteny and relative gene expression.

  13. Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments.

    Science.gov (United States)

    Zhuang, Kai; Izallalen, Mounir; Mouser, Paula; Richter, Hanno; Risso, Carla; Mahadevan, Radhakrishnan; Lovley, Derek R

    2011-02-01

    The advent of rapid complete genome sequencing, and the potential to capture this information in genome-scale metabolic models, provide the possibility of comprehensively modeling microbial community interactions. For example, Rhodoferax and Geobacter species are acetate-oxidizing Fe(III)-reducers that compete in anoxic subsurface environments and this competition may have an influence on the in situ bioremediation of uranium-contaminated groundwater. Therefore, genome-scale models of Geobacter sulfurreducens and Rhodoferax ferrireducens were used to evaluate how Geobacter and Rhodoferax species might compete under diverse conditions found in a uranium-contaminated aquifer in Rifle, CO. The model predicted that at the low rates of acetate flux expected under natural conditions at the site, Rhodoferax will outcompete Geobacter as long as sufficient ammonium is available. The model also predicted that when high concentrations of acetate are added during in situ bioremediation, Geobacter species would predominate, consistent with field-scale observations. This can be attributed to the higher expected growth yields of Rhodoferax and the ability of Geobacter to fix nitrogen. The modeling predicted relative proportions of Geobacter and Rhodoferax in geochemically distinct zones of the Rifle site that were comparable to those that were previously documented with molecular techniques. The model also predicted that under nitrogen fixation, higher carbon and electron fluxes would be diverted toward respiration rather than biomass formation in Geobacter, providing a potential explanation for enhanced in situ U(VI) reduction in low-ammonium zones. These results show that genome-scale modeling can be a useful tool for predicting microbial interactions in subsurface environments and shows promise for designing bioremediation strategies.

  14. 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

  15. Modeling psychiatric disorders: from genomic findings to cellular phenotypes

    Science.gov (United States)

    Falk, A; Heine, V M; Harwood, A J; Sullivan, P F; Peitz, M; Brüstle, O; Shen, S; Sun, Y-M; Glover, J C; Posthuma, D; Djurovic, S

    2016-01-01

    Major programs in psychiatric genetics have identified >150 risk loci for psychiatric disorders. These loci converge on a small number of functional pathways, which span conventional diagnostic criteria, suggesting a partly common biology underlying schizophrenia, autism and other psychiatric disorders. Nevertheless, the cellular phenotypes that capture the fundamental features of psychiatric disorders have not yet been determined. Recent advances in genetics and stem cell biology offer new prospects for cell-based modeling of psychiatric disorders. The advent of cell reprogramming and induced pluripotent stem cells (iPSC) provides an opportunity to translate genetic findings into patient-specific in vitro models. iPSC technology is less than a decade old but holds great promise for bridging the gaps between patients, genetics and biology. Despite many obvious advantages, iPSC studies still present multiple challenges. In this expert review, we critically review the challenges for modeling of psychiatric disorders, potential solutions and how iPSC technology can be used to develop an analytical framework for the evaluation and therapeutic manipulation of fundamental disease processes. PMID:27240529

  16. Improved Evidence-Based Genome-scale Metabolic Models for Maize Leaf, Embryo, and Endosperm

    Energy Technology Data Exchange (ETDEWEB)

    Seaver, Samuel M.D.; Frelin, Oceane; Bradbury, Louis M.T.; 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.

  17. Improved Evidence-Based Genome-scale Metabolic Models for Maize Leaf, Embryo, and Endosperm.

    Directory of Open Access Journals (Sweden)

    Samuel eSeaver

    2015-03-01

    Full Text Available 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.

  18. Universal power law behaviors in genomic sequences and evolutionary models

    CERN Document Server

    Martignetti, L

    2007-01-01

    We study the length distribution of a particular class of DNA sequences known as 5'UTR exons. These exons belong to the messanger RNA of protein coding genes, but they are not coding (they are located upstream of the coding portion of the mRNA) and are thus less constrained from an evolutionary point of view. We show that both in mouse and in human these exons show a very clean power law decay in their length distribution and suggest a simple evolutionary model which may explain this finding. We conjecture that this power law behaviour could indeed be a general feature of higher eukaryotes.

  19. Databases, models, and algorithms for functional genomics: a bioinformatics perspective.

    Science.gov (United States)

    Singh, Gautam B; Singh, Harkirat

    2005-02-01

    A variety of patterns have been observed on the DNA and protein sequences that serve as control points for gene expression and cellular functions. Owing to the vital role of such patterns discovered on biological sequences, they are generally cataloged and maintained within internationally shared databases. Furthermore,the variability in a family of observed patterns is often represented using computational models in order to facilitate their search within an uncharacterized biological sequence. As the biological data is comprised of a mosaic of sequence-levels motifs, it is significant to unravel the synergies of macromolecular coordination utilized in cell-specific differential synthesis of proteins. This article provides an overview of the various pattern representation methodologies and the surveys the pattern databases available for use to the molecular biologists. Our aim is to describe the principles behind the computational modeling and analysis techniques utilized in bioinformatics research, with the objective of providing insight necessary to better understand and effectively utilize the available databases and analysis tools. We also provide a detailed review of DNA sequence level patterns responsible for structural conformations within the Scaffold or Matrix Attachment Regions (S/MARs).

  20. 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...... antimetabolites using two cell lines with different phenotypic origins, and found that it is effective in inhibiting the growth of these cell lines. Using immunohistochemistry, we also showed high or moderate expression levels of proteins targeted by the validated antimetabolite. Identified anti-growth factors...

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

    DEFF Research Database (Denmark)

    Terkelsen, Kasper Munch; Gardner, P. P.; Arctander, Peter;

    2006-01-01

    HMM, 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......]. 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...

  2. 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

    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....... 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...

  3. 3D-GNOME: an integrated web service for structural modeling of the 3D genome.

    Science.gov (United States)

    Szalaj, Przemyslaw; Michalski, Paul J; Wróblewski, Przemysław; Tang, Zhonghui; Kadlof, Michal; Mazzocco, Giovanni; Ruan, Yijun; Plewczynski, Dariusz

    2016-07-08

    Recent advances in high-throughput chromosome conformation capture (3C) technology, such as Hi-C and ChIA-PET, have demonstrated the importance of 3D genome organization in development, cell differentiation and transcriptional regulation. There is now a widespread need for computational tools to generate and analyze 3D structural models from 3C data. Here we introduce our 3D GeNOme Modeling Engine (3D-GNOME), a web service which generates 3D structures from 3C data and provides tools to visually inspect and annotate the resulting structures, in addition to a variety of statistical plots and heatmaps which characterize the selected genomic region. Users submit a bedpe (paired-end BED format) file containing the locations and strengths of long range contact points, and 3D-GNOME simulates the structure and provides a convenient user interface for further analysis. Alternatively, a user may generate structures using published ChIA-PET data for the GM12878 cell line by simply specifying a genomic region of interest. 3D-GNOME is freely available at http://3dgnome.cent.uw.edu.pl/.

  4. Genome-scale modeling of human metabolism - a systems biology approach.

    Science.gov (United States)

    Mardinoglu, Adil; Gatto, Francesco; Nielsen, Jens

    2013-09-01

    Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models - one of the fundamental aspects of systems biology - have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Advances in the integration of transcriptional regulatory information into genome-scale metabolic models.

    Science.gov (United States)

    Vivek-Ananth, R P; Samal, Areejit

    2016-09-01

    A major goal of systems biology is to build predictive computational models of cellular metabolism. Availability of complete genome sequences and wealth of legacy biochemical information has led to the reconstruction of genome-scale metabolic networks in the last 15 years for several organisms across the three domains of life. Due to paucity of information on kinetic parameters associated with metabolic reactions, the constraint-based modelling approach, flux balance analysis (FBA), has proved to be a vital alternative to investigate the capabilities of reconstructed metabolic networks. In parallel, advent of high-throughput technologies has led to the generation of massive amounts of omics data on transcriptional regulation comprising mRNA transcript levels and genome-wide binding profile of transcriptional regulators. A frontier area in metabolic systems biology has been the development of methods to integrate the available transcriptional regulatory information into constraint-based models of reconstructed metabolic networks in order to increase the predictive capabilities of computational models and understand the regulation of cellular metabolism. Here, we review the existing methods to integrate transcriptional regulatory information into constraint-based models of metabolic networks.

  6. Economic Modeling in SocialWork Education

    Directory of Open Access Journals (Sweden)

    Barry R. Cournoyer

    2000-12-01

    Full Text Available Economic modeling provides academic administrators with a logical framework for analyzing costs associated with the processes involved in the delivery of social work education. The specific costs associated with activities such as teaching, research, and service may be determined for a school of social work as a whole or for specific responsibility centers (e.g., programs and services within the school. Economic modeling utilizes modern spreadsheet software that can be configured in relation to the idiosyncratic needs and budgeting strategies that exist in virtually all colleges and universities. As a versatile planning tool, it enables managers to identify specific “cost-drivers” that cause the occurrence of real costs in relation to designated programmatic initiatives. In addition, economic modeling provides academic planners and decision-makers a useful vehicle for considering the economic impact of various projected (“what if” scenarios.

  7. 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,…

  8. A mixed model reduces spurious genetic associations produced by population stratification in genome-wide association studies.

    Science.gov (United States)

    Shin, Jimin; Lee, Chaeyoung

    2015-04-01

    Population stratification can produce spurious genetic associations in genome-wide association studies (GWASs). Mixed model methodology has been regarded useful for correcting population stratification. This study explored statistical power and false discovery rate (FDR) with the data simulated for dichotomous traits. Empirical FDRs and powers were estimated using fixed models with and without genomic control and using mixed models with and without reflecting loci linked to the candidate marker in genetic relationships. Population stratification with admixture degree ranged from 1% to 10% resulted in inflated FDRs from the fixed model analysis without genomic control and decreased power from the fixed model analysis with genomic control (Ppopulation stratification could not change FDR and power estimates from the mixed model analyses (P>0.05). We suggest that the mixed model methodology was useful to reduce spurious genetic associations produced by population stratification in GWAS, even with a high degree of admixture (10%). Copyright © 2015 Elsevier Inc. All rights reserved.

  9. An efficient hierarchical generalized linear mixed model for pathway analysis of genome-wide association studies.

    Science.gov (United States)

    Wang, Lily; Jia, Peilin; Wolfinger, Russell D; Chen, Xi; Grayson, Britney L; Aune, Thomas M; Zhao, Zhongming

    2011-03-01

    In genome-wide association studies (GWAS) of complex diseases, genetic variants having real but weak associations often fail to be detected at the stringent genome-wide significance level. Pathway analysis, which tests disease association with combined association signals from a group of variants in the same pathway, has become increasingly popular. However, because of the complexities in genetic data and the large sample sizes in typical GWAS, pathway analysis remains to be challenging. We propose a new statistical model for pathway analysis of GWAS. This model includes a fixed effects component that models mean disease association for a group of genes, and a random effects component that models how each gene's association with disease varies about the gene group mean, thus belongs to the class of mixed effects models. The proposed model is computationally efficient and uses only summary statistics. In addition, it corrects for the presence of overlapping genes and linkage disequilibrium (LD). Via simulated and real GWAS data, we showed our model improved power over currently available pathway analysis methods while preserving type I error rate. Furthermore, using the WTCCC Type 1 Diabetes (T1D) dataset, we demonstrated mixed model analysis identified meaningful biological processes that agreed well with previous reports on T1D. Therefore, the proposed methodology provides an efficient statistical modeling framework for systems analysis of GWAS. The software code for mixed models analysis is freely available at http://biostat.mc.vanderbilt.edu/LilyWang.

  10. Genomic characterization of explant tumorgraft models derived from fresh patient tumor tissue

    Directory of Open Access Journals (Sweden)

    Monsma David J

    2012-06-01

    Full Text Available Abstract Background There is resurgence within drug and biomarker development communities for the use of primary tumorgraft models as improved predictors of patient tumor response to novel therapeutic strategies. Despite perceived advantages over cell line derived xenograft models, there is limited data comparing the genotype and phenotype of tumorgrafts to the donor patient tumor, limiting the determination of molecular relevance of the tumorgraft model. This report directly compares the genomic characteristics of patient tumors and the derived tumorgraft models, including gene expression, and oncogenic mutation status. Methods Fresh tumor tissues from 182 cancer patients were implanted subcutaneously into immune-compromised mice for the development of primary patient tumorgraft models. Histological assessment was performed on both patient tumors and the resulting tumorgraft models. Somatic mutations in key oncogenes and gene expression levels of resulting tumorgrafts were compared to the matched patient tumors using the OncoCarta (Sequenom, San Diego, CA and human gene microarray (Affymetrix, Santa Clara, CA platforms respectively. The genomic stability of the established tumorgrafts was assessed across serial in vivo generations in a representative subset of models. The genomes of patient tumors that formed tumorgrafts were compared to those that did not to identify the possible molecular basis to successful engraftment or rejection. Results Fresh tumor tissues from 182 cancer patients were implanted into immune-compromised mice with forty-nine tumorgraft models that have been successfully established, exhibiting strong histological and genomic fidelity to the originating patient tumors. Comparison of the transcriptomes and oncogenic mutations between the tumorgrafts and the matched patient tumors were found to be stable across four tumorgraft generations. Not only did the various tumors retain the differentiation pattern, but supporting

  11. 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.

  12. Supporting an Externally Developed Model of Education in Greenland

    Science.gov (United States)

    Wyatt, Tasha R.

    2010-01-01

    This study investigated the adaptation process of an externally developed model of reform in Greenland's educational system. Under investigation was how reform leaders responded to the needs of the community after implementing an educational model developed in the United States by researchers at the Center for Research on Education, Diversity, and…

  13. Models Based Practices in Physical Education: A Sociocritical Reflection

    Science.gov (United States)

    Landi, Dillon; Fitzpatrick, Katie; McGlashan, Hayley

    2016-01-01

    In this paper, we reflect on models-based practices in physical education using a sociocritical lens. Drawing links between neoliberal moves in education, and critical approaches to the body and physicality, we take a view that models are useful tools that are worth integrating into physical education, but we are apprehensive to suggest they…

  14. 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.

  15. Construction of an E. Coli genome-scale atom mapping model for MFA calculations.

    Science.gov (United States)

    Ravikirthi, Prabhasa; Suthers, Patrick F; Maranas, Costas D

    2011-06-01

    Metabolic flux analysis (MFA) has so far been restricted to lumped networks lacking many important pathways, partly due to the difficulty in automatically generating isotope mapping matrices for genome-scale metabolic networks. Here we introduce a procedure that uses a compound matching algorithm based on the graph theoretical concept of pattern recognition along with relevant reaction information to automatically generate genome-scale atom mappings which trace the path of atoms from reactants to products for every reaction. The procedure is applied to the iAF1260 metabolic reconstruction of Escherichia coli yielding the genome-scale isotope mapping model imPR90068. This model maps 90,068 non-hydrogen atoms that span all 2,077 reactions present in iAF1260 (previous largest mapping model included 238 reactions). The expanded scope of the isotope mapping model allows the complete tracking of labeled atoms through pathways such as cofactor and prosthetic group biosynthesis and histidine metabolism. An EMU representation of imPR90068 is also constructed and made available.

  16. Modeling Method for Increased Precision and Scope of Directly Measurable Fluxes at a Genome-Scale.

    Science.gov (United States)

    McCloskey, Douglas; Young, Jamey D; Xu, Sibei; Palsson, Bernhard O; Feist, Adam M

    2016-04-05

    Metabolic flux analysis (MFA) is considered to be the gold standard for determining the intracellular flux distribution of biological systems. The majority of work using MFA has been limited to core models of metabolism due to challenges in implementing genome-scale MFA and the undesirable trade-off between increased scope and decreased precision in flux estimations. This work presents a tunable workflow for expanding the scope of MFA to the genome-scale without trade-offs in flux precision. The genome-scale MFA model presented here, iDM2014, accounts for 537 net reactions, which includes the core pathways of traditional MFA models and also covers the additional pathways of purine, pyrimidine, isoprenoid, methionine, riboflavin, coenzyme A, and folate, as well as other biosynthetic pathways. When evaluating the iDM2014 using a set of measured intracellular intermediate and cofactor mass isotopomer distributions (MIDs),1 it was found that a total of 232 net fluxes of central and peripheral metabolism could be resolved in the E. coli network. The increase in scope was shown to cover the full biosynthetic route to an expanded set of bioproduction pathways, which should facilitate applications such as the design of more complex bioprocessing strains and aid in identifying new antimicrobials. Importantly, it was found that there was no loss in precision of core fluxes when compared to a traditional core model, and additionally there was an overall increase in precision when considering all observable reactions.

  17. 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.

  18. 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…

  19. Identification of allelic imbalance with a statistical model for subtle genomic mosaicism.

    Directory of Open Access Journals (Sweden)

    Rui Xia

    2014-08-01

    Full Text Available Genetic heterogeneity in a mixed sample of tumor and normal DNA can confound characterization of the tumor genome. Numerous computational methods have been proposed to detect aberrations in DNA samples from tumor and normal tissue mixtures. Most of these require tumor purities to be at least 10-15%. Here, we present a statistical model to capture information, contained in the individual's germline haplotypes, about expected patterns in the B allele frequencies from SNP microarrays while fully modeling their magnitude, the first such model for SNP microarray data. Our model consists of a pair of hidden Markov models--one for the germline and one for the tumor genome--which, conditional on the observed array data and patterns of population haplotype variation, have a dependence structure induced by the relative imbalance of an individual's inherited haplotypes. Together, these hidden Markov models offer a powerful approach for dealing with mixtures of DNA where the main component represents the germline, thus suggesting natural applications for the characterization of primary clones when stromal contamination is extremely high, and for identifying lesions in rare subclones of a tumor when tumor purity is sufficient to characterize the primary lesions. Our joint model for germline haplotypes and acquired DNA aberration is flexible, allowing a large number of chromosomal alterations, including balanced and imbalanced losses and gains, copy-neutral loss-of-heterozygosity (LOH and tetraploidy. We found our model (which we term J-LOH to be superior for localizing rare aberrations in a simulated 3% mixture sample. More generally, our model provides a framework for full integration of the germline and tumor genomes to deal more effectively with missing or uncertain features, and thus extract maximal information from difficult scenarios where existing methods fail.

  20. Educational Gaps in Molecular Diagnostics, Genomics, and Personalized Medicine in Dermatopathology Training: A Survey of US Dermatopathology Fellowship Program Directors.

    Science.gov (United States)

    Torre, Kristin; Russomanno, Kristen; Ferringer, Tammie; Elston, Dirk; Murphy, Michael J

    2017-05-02

    Molecular technologies offer clinicians the tools to provide high-quality, cost-effective patient care. We evaluated education focused on molecular diagnostics, genomics, and personalized medicine in dermatopathology fellowship. A 20-question online survey was emailed to all (n = 53) Accreditation Council for Graduate Medical Education (ACGME)-accredited dermatopathology training programs in the United States. Thirty-one of 53 program directors responded (response rate = 58%). Molecular training is undertaken in 74% of responding dermatopathology fellowships, with levels of instruction varying among dermatology-based and pathology-based programs. Education differed for dermatology- and pathology-trained fellows in approximately one-fifth (19%) of programs. Almost half (48%) of responding program directors believe that fellows are not currently receiving adequate molecular education although the majority (97%) expect to incorporate additional instruction in the next 2-5 years. Factors influencing the incorporation of relevant education include perceived clinical utility and Accreditation Council for Graduate Medical Education/residency review committee (RRC) requirements. Potential benefits of molecular education include increased medical knowledge, improved patient care, and promotion of effective communication with other healthcare professionals. More than two-thirds (68%) of responding program directors believe that instruction in molecular technologies should be required in dermatopathology fellowship training. Although all responding dermatopathology fellowship program directors agreed that molecular education is important, only a little over half of survey participants believe that their fellows receive adequate instruction. This represents an important educational gap. Discussion among those who oversee fellow education is necessary to best integrate and evaluate teaching of molecular dermatopathology.

  1. 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

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

    NARCIS (Netherlands)

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

    2007-01-01

    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 achieveme

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

    DEFF Research Database (Denmark)

    Thompson, Wesley K.; Wang, Yunpeng; Schork, Andrew J.

    2015-01-01

    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...... of variance explained by genotyped SNPs, CD and SZ have a broadly dissimilar genetic architecture, due to differing mean effect size and proportion of non-null loci....

  4. 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.

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

    Science.gov (United States)

    Musunuru, Kiran

    2013-07-01

    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.

  6. The future of genome-scale modeling of yeast through integration of a transcriptional regulatory network

    DEFF Research Database (Denmark)

    Liu, Guodong; Marras, Antonio; Nielsen, Jens

    2014-01-01

    regulatory information is necessary to improve the accuracy and predictive ability of metabolic models. Here we review the strategies for the reconstruction of a transcriptional regulatory network (TRN) for yeast and the integration of such a reconstruction into a flux balance analysis-based metabolic model......Metabolism is regulated at multiple levels in response to the changes of internal or external conditions. Transcriptional regulation plays an important role in regulating many metabolic reactions by altering the concentrations of metabolic enzymes. Thus, integration of the transcriptional...... transcriptional regulatory interactions to genome-scale metabolic models in a quantitative manner....

  7. 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.

  8. 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

    2016-06-08

    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 LTM (logical transformation of model) 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.

  9. A conceptual framework for a mentoring model for nurse educators ...

    African Journals Online (AJOL)

    A conceptual framework for a mentoring model for nurse educators. ... recruiting and retaining nurse educators to meet the demands of teaching and learning ... approaches focusing on reasoning strategies, literature control and empirical data ...

  10. Research on Effective Models for Teacher Education. Teacher Education Yearbook VIII.

    Science.gov (United States)

    McIntyre, D. John, Ed.; Byrd, David M., Ed.

    This yearbook addresses the nation's need to train and retain good teachers, exploring exemplary practices in teacher education. There are four sections divided into 12 chapters. The book begins with a forward, "Research on Effective Models for Teacher Education: Powerful Teacher Education Programs" (E.M. Guyton). Section 1, "Models for Enhancing…

  11. Research on Effective Models for Teacher Education. Teacher Education Yearbook VIII.

    Science.gov (United States)

    McIntyre, D. John, Ed.; Byrd, David M., Ed.

    This yearbook addresses the nation's need to train and retain good teachers, exploring exemplary practices in teacher education. There are four sections divided into 12 chapters. The book begins with a forward, "Research on Effective Models for Teacher Education: Powerful Teacher Education Programs" (E.M. Guyton). Section 1, "Models for Enhancing…

  12. Metabolic model for the filamentous ‘Candidatus Microthrix parvicella' based on genomic and metagenomic analyses

    Science.gov (United States)

    Jon McIlroy, Simon; Kristiansen, Rikke; Albertsen, Mads; Michael Karst, Søren; Rossetti, Simona; Lund Nielsen, Jeppe; Tandoi, Valter; James Seviour, Robert; Nielsen, Per Halkjær

    2013-01-01

    ‘Candidatus Microthrix parvicella' is a lipid-accumulating, filamentous bacterium so far found only in activated sludge wastewater treatment plants, where it is a common causative agent of sludge separation problems. Despite attracting considerable interest, its detailed physiology is still unclear. In this study, the genome of the RN1 strain was sequenced and annotated, which facilitated the construction of a theoretical metabolic model based on available in situ and axenic experimental data. This model proposes that under anaerobic conditions, this organism accumulates preferentially long-chain fatty acids as triacylglycerols. Utilisation of trehalose and/or polyphosphate stores or partial oxidation of long-chain fatty acids may supply the energy required for anaerobic lipid uptake and storage. Comparing the genome sequence of this isolate with metagenomes from two full-scale wastewater treatment plants with enhanced biological phosphorus removal reveals high similarity, with few metabolic differences between the axenic and the dominant community ‘Ca. M. parvicella' strains. Hence, the metabolic model presented in this paper could be considered generally applicable to strains in full-scale treatment systems. The genomic information obtained here will provide the basis for future research into in situ gene expression and regulation. Such information will give substantial insight into the ecophysiology of this unusual and biotechnologically important filamentous bacterium. PMID:23446830

  13. Hi-C-constrained physical models of human chromosomes recover functionally-related properties of genome organization

    CERN Document Server

    Di Stefano, Marco; Lien, Tonje G; Hovig, Eivind; Micheletti, Cristian

    2016-01-01

    Combining genome-wide structural models with phenomenological data is at the forefront of efforts to understand the organizational principles regulating the human genome. Here, we use chromosome-chromosome contact data as knowledge-based constraints for large-scale three-dimensional models of the human diploid genome. The resulting models remain minimally entangled and acquire several functional features that are observed in vivo and that were never used as input for the model. We find, for instance, that gene-rich, active regions are drawn towards the nuclear center, while gene poor and lamina-associated domains are pushed to the periphery. These and other properties persist upon adding local contact constraints, suggesting their compatibility with non-local constraints for the genome organization. The results show that suitable combinations of data analysis and physical modelling can expose the unexpectedly rich functionally-related properties implicit in chromosome-chromosome contact data. Specific directi...

  14. 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.

  15. 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...... 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...... account for selection on unobserved variables and high-quality data are both required in order to estimate credible educational transition models....

  16. Genomic resources for a model in adaptation and speciation research: characterization of the Poecilia mexicana transcriptome

    Directory of Open Access Journals (Sweden)

    Kelley Joanna L

    2012-11-01

    Full Text Available Abstract Background Elucidating the genomic basis of adaptation and speciation is a major challenge in natural systems with large quantities of environmental and phenotypic data, mostly because of the scarcity of genomic resources for non-model organisms. The Atlantic molly (Poecilia mexicana, Poeciliidae is a small livebearing fish that has been extensively studied for evolutionary ecology research, particularly because this species has repeatedly colonized extreme environments in the form of caves and toxic hydrogen sulfide containing springs. In such extreme environments, populations show strong patterns of adaptive trait divergence and the emergence of reproductive isolation. Here, we used RNA-sequencing to assemble and annotate the first transcriptome of P. mexicana to facilitate ecological genomics studies in the future and aid the identification of genes underlying adaptation and speciation in the system. Description We provide the first annotated reference transcriptome of P. mexicana. Our transcriptome shows high congruence with other published fish transcriptomes, including that of the guppy, medaka, zebrafish, and stickleback. Transcriptome annotation uncovered the presence of candidate genes relevant in the study of adaptation to extreme environments. We describe general and oxidative stress response genes as well as genes involved in pathways induced by hypoxia or involved in sulfide metabolism. To facilitate future comparative analyses, we also conducted quantitative comparisons between P. mexicana from different river drainages. 106,524 single nucleotide polymorphisms were detected in our dataset, including potential markers that are putatively fixed across drainages. Furthermore, specimens from different drainages exhibited some consistent differences in gene regulation. Conclusions Our study provides a valuable genomic resource to study the molecular underpinnings of adaptation to extreme environments in replicated sulfide

  17. Capturing the Phylogeny of Holometabola with Mitochondrial Genome Data and Bayesian Site-Heterogeneous Mixture Models.

    Science.gov (United States)

    Song, Fan; Li, Hu; Jiang, Pei; Zhou, Xuguo; Liu, Jinpeng; Sun, Changhai; Vogler, Alfried P; Cai, Wanzhi

    2016-05-22

    After decades of debate, a mostly satisfactory resolution of relationships among the 11 recognized holometabolan orders of insects has been reached based on nuclear genes, resolving one of the most substantial branches of the tree-of-life, but the relationships are still not well established with mitochondrial genome data. The main reasons have been the absence of sufficient data in several orders and lack of appropriate phylogenetic methods that avoid the systematic errors from compositional and mutational biases in insect mitochondrial genomes. In this study, we assembled the richest taxon sampling of Holometabola to date (199 species in 11 orders), and analyzed both nucleotide and amino acid data sets using several methods. We find the standard Bayesian inference and maximum-likelihood analyses were strongly affected by systematic biases, but the site-heterogeneous mixture model implemented in PhyloBayes avoided the false grouping of unrelated taxa exhibiting similar base composition and accelerated evolutionary rate. The inclusion of rRNA genes and removal of fast-evolving sites with the observed variability sorting method for identifying sites deviating from the mean rates improved the phylogenetic inferences under a site-heterogeneous model, correctly recovering most deep branches of the Holometabola phylogeny. We suggest that the use of mitochondrial genome data for resolving deep phylogenetic relationships requires an assessment of the potential impact of substitutional saturation and compositional biases through data deletion strategies and by using site-heterogeneous mixture models. Our study suggests a practical approach for how to use densely sampled mitochondrial genome data in phylogenetic analyses. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  18. 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.

  19. 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.

  20. BioStar models of clinical and genomic data for biomedical data warehouse design.

    Science.gov (United States)

    Wang, Liangjiang; Zhang, Aidong; Ramanathan, Murali

    2005-01-01

    Biomedical research is now generating large amounts of data, ranging from clinical test results to microarray gene expression profiles. The scale and complexity of these datasets give rise to substantial challenges in data management and analysis. It is highly desirable that data warehousing and online analytical processing technologies can be applied to biomedical data integration and mining. The major difficulty probably lies in the task of capturing and modelling diverse biological objects and their complex relationships. This paper describes multidimensional data modelling for biomedical data warehouse design. Since the conventional models such as star schema appear to be insufficient for modelling clinical and genomic data, we develop a new model called BioStar schema. The new model can capture the rich semantics of biomedical data and provide greater extensibility for the fast evolution of biological research methodologies.

  1. 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

    , prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and "hedging" against uncertain environments and stresses, as indicated by significant enrichment...... 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......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...

  2. Effectiveness of Peer Education Involving the use of Theoretical Models

    OpenAIRE

    2008-01-01

    The effectiveness of health education among university students who received peer-support training was investigated using four theoretical models : the health belief model, the self-efficacy model, social support and the transtheoretical model of health behavior change. Results suggested that the four theoretical models were useful in evaluating the effect of peer education as an alternative assessment tool. In light of this, it is suggested that the use of the theoretical models may facilita...

  3. 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

    2017-01-01

    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. PMID:28455415

  4. Mixture models of geometric distributions in genomic analysis of inter-nucleotide distances

    Directory of Open Access Journals (Sweden)

    Adelaide Valente Freitas

    2013-11-01

    Full Text Available The mapping defined by inter-nucleotide distances (InD provides a reversible numerical representation of the primary structure of DNA. If nucleotides were independently placed along the genome, a finite mixture model of four geometric distributions could be fitted to the InD where the four marginal distributions would be the expected distributions of the four nucleotide types. We analyze a finite mixture model of geometric distributions (f_2, with marginals not explicitly addressed to the nucleotide types, as an approximation to the InD. We use BIC in the composite likelihood framework for choosing the number of components of the mixture and the EM algorithm for estimating the model parameters. Based on divergence profiles, an experimental study was carried out on the complete genomes of 45 species to evaluate f_2. Although the proposed model is not suited to the InD, our analysis shows that divergence profiles involving the empirical distribution of the InD are also exhibited by profiles involving f_2. It suggests that statistical regularities of the InD can be described by the model f_2. Some characteristics of the DNA sequences captured by the model f_2 are illustrated. In particular, clusterings of subgroups of eukaryotes (primates, mammalians, animals and plants are detected.

  5. Computational modelling of genome-wide [corrected] transcription assembly networks using a fluidics analogy.

    Directory of Open Access Journals (Sweden)

    Yousry Y Azmy

    Full Text Available Understanding how a myriad of transcription regulators work to modulate mRNA output at thousands of genes remains a fundamental challenge in molecular biology. Here we develop a computational tool to aid in assessing the plausibility of gene regulatory models derived from genome-wide expression profiling of cells mutant for transcription regulators. mRNA output is modelled as fluid flow in a pipe lattice, with assembly of the transcription machinery represented by the effect of valves. Transcriptional regulators are represented as external pressure heads that determine flow rate. Modelling mutations in regulatory proteins is achieved by adjusting valves' on/off settings. The topology of the lattice is designed by the experimentalist to resemble the expected interconnection between the modelled agents and their influence on mRNA expression. Users can compare multiple lattice configurations so as to find the one that minimizes the error with experimental data. This computational model provides a means to test the plausibility of transcription regulation models derived from large genomic data sets.

  6. A Genome-Scale Model of Shewanella piezotolerans Simulates Mechanisms of Metabolic Diversity and Energy Conservation.

    Science.gov (United States)

    Dufault-Thompson, Keith; Jian, Huahua; Cheng, Ruixue; Li, Jiefu; Wang, Fengping; Zhang, Ying

    2017-01-01

    Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea. IMPORTANCE The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation

  7. Doubly uniparental inheritance: two mitochondrial genomes, one precious model for organelle DNA inheritance and evolution.

    Science.gov (United States)

    Passamonti, Marco; Ghiselli, Fabrizio

    2009-02-01

    Eukaryotes have exploited several mechanisms for organelle uniparental inheritance, so this feature arose and evolved independently many times in their history. Metazoans' mitochondria commonly experience strict maternal inheritance; that is, they are only transmitted by females. However, the most noteworthy exception comes from some bivalve mollusks, in which two mitochondrial lineages (together with their genomes) are inherited: one through females (F) and the other through males (M). M and F genomes show up to 30% sequence divergence. This inheritance mechanism is known as doubly uniparental inheritance (DUI), because both sexes inherit uniparentally their mitochondria. Here, we review what we know about this unusual system, and we propose a model for evolution of DUI that might account for its origin as sex determination mechanism. Moreover, we propose DUI as a choice model to address many aspects that should be of interest to a wide range of biological subfields, such as mitochondrial inheritance, mtDNA evolution and recombination, genomic conflicts, evolution of sex, and developmental biology. Actually, as research proceeds, mitochondria appear to have acquired a central role in many fundamental processes of life, which are not only in their metabolic activity as cellular power plants, such as cell signaling, fertilization, development, differentiation, ageing, apoptosis, and sex determination. A function of mitochondria in the origin and maintenance of sex has been also proposed.

  8. 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.

  9. 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.

  10. Elements of a Model State Education Agency Diffusion System.

    Science.gov (United States)

    Mojkowski, Charles

    A study, presented to the National Dissemination Conference, provides a conceptualization of a model diffusion system as it might exist within a state education agency (SEA) and places this diffusion model within the context of the SEA's expanding role as an educational service. Five conclusions were reached regarding a model diffusion system.…

  11. 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…

  12. 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…

  13. 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…

  14. Integrating teacher education effectiveness research into educational effectiveness models

    NARCIS (Netherlands)

    Scheerens, Jaap; Blömeke, Sigrid

    2016-01-01

    The purpose of this article is to review and to connect research about teacher education effectiveness and school effectiveness to arrive at an integrative conceptualization that has the potential of improving empirical research in both fields. Teacher education effectiveness addresses effects of te

  15. Integrating teacher education effectiveness research into educational effectiveness models

    NARCIS (Netherlands)

    Scheerens, Jaap; Blömeke, Sigrid

    2016-01-01

    The purpose of this article is to review and to connect research about teacher education effectiveness and school effectiveness to arrive at an integrative conceptualization that has the potential of improving empirical research in both fields. Teacher education effectiveness addresses effects of

  16. 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

    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......-induced anemia) and how genetic variation (inosine triphosphatase deficiency) may protect against this side effect. This study demonstrates the feasibility of personalized kinetic models, and we anticipate their use will accelerate discoveries in characterizing individual metabolic variation....

  17. Comparisons of Shewanella strains based on genome annotations, modeling and experiments

    Energy Technology Data Exchange (ETDEWEB)

    Ong, Wai Kit; Vu, Trang; Lovendahl, Klaus N.; Llull, Jenna; Serres, Margaret; Romine, Margaret F.; Reed, Jennifer L.

    2014-01-01

    Shewanella is a genus of facultatively anaerobic, Gram-negative bacteria that have highly adaptable metabolism which allows them to thrive in diverse environments. This quality makes them attractive target bacteria for research in bioremediation and microbial fuel cell applications. Constraint-based modeling is a useful tool for helping researchers gain insights into the metabolic capabilities of these bacteria. However, Shewanella oneidensis MR-1 is the only strain with a genome-scale metabolic model constructed out of the 22 sequenced Shewanella strains.

  18. Progress and knowledge gaps in Culicoides genetics, genomics and population modelling: 2003 to 2014.

    Science.gov (United States)

    Carpenter, Simon

    2016-09-30

    In the 10 years, since the last international meeting on Bluetongue virus (BTV) and related Orbiviruses in Sicily, there have been huge advances in explorations of the genetics and genomics of Culicoides, culminating in the imminent release of the rst full genome de novo assembly for the genus. In parallel, mathematical models used to predict Culicoides adult distribution, seasonality, and dispersal have also increased in sophistication, re ecting advances in available computational power and expertise. While these advances have focused upon the outbreaks of BTV in Europe, there is an opportunity to extend these techniques to other regions as part of global studies of the genus. This review takes a selective approach to examining the past decade of research in these areas and provides a personal viewpoint of future directions of research that may prove productive.

  19. 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.

  20. Microteaching: a model for employee counseling education.

    Science.gov (United States)

    Fiedler, K M; Beach, B L

    1979-12-01

    An instructional model for the implementation and use of videotape simulation to improve dietetic students' skills in employee counseling was explored in the coordinated undergraduate program at the University of Tennessee, Knoxville. A five-day intensive workshop was conducted for senior students in the program, utilizing the microteaching technique. Students and actors simulated an employee counseling session on videotape; then, a small group and a clinical instructor evaluated the session. Suggestions from these evaluations were used in a repeat of the situation on videotape. A team of experts randomly viewed all the situations, judging a significant improvement in composite scores for the workshop participants. The students indicated on a Self-Perception of Confidence (SPOC) scale that they felt a higher degree of comfort in handling potential employee counseling after completing the workshop. They were pleased with the workshop and suggested expansion of the technique to other phases of their dietetic education.

  1. 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.

  2. Genome assembly and annotation of Arabidopsis halleri, a model for heavy metal hyperaccumulation and evolutionary ecology.

    Science.gov (United States)

    Briskine, Roman V; Paape, Timothy; Shimizu-Inatsugi, Rie; Nishiyama, Tomoaki; Akama, Satoru; Sese, Jun; Shimizu, Kentaro K

    2016-09-27

    The self-incompatible species Arabidopsis halleri is a close relative of the self-compatible model plant Arabidopsis thaliana. The broad European and Asian distribution and heavy metal hyperaccumulation ability make A. halleri a useful model for ecological genomics studies. We used long-insert mate-pair libraries to improve the genome assembly of the A. halleri ssp. gemmifera Tada mine genotype (W302) collected from a site with high contamination by heavy metals in Japan. After five rounds of forced selfing, heterozygosity was reduced to 0.04%, which facilitated subsequent genome assembly. Our assembly now covers 196 Mb or 78% of the estimated genome size and achieved scaffold N50 length of 712 kb. To validate assembly and annotation, we used synteny of A. halleri Tada mine with a previously published high-quality reference assembly of a closely related species, Arabidopsis lyrata. Further validation of the assembly quality comes from synteny and phylogenetic analysis of the HEAVY METAL ATPASE4 (HMA4) and METAL TOLERANCE PROTEIN1 (MTP1) regions using published sequences from European A. halleri for comparison. Three tandemly duplicated copies of HMA4, key gene involved in cadmium and zinc hyperaccumulation, were assembled on a single scaffold. The assembly will enhance the genomewide studies of A. halleri as well as the allopolyploid Arabidopsis kamchatica derived from A. lyrata and A. halleri. © 2016 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

  3. Complete Genome Sequence of Pseudomonas sp. UK4, a Model Organism for Studies of Functional Amyloids in Pseudomonas

    DEFF Research Database (Denmark)

    Dueholm, Morten Simonsen; Danielsen, Heidi Nolsøe; Nielsen, Per Halkjær

    2014-01-01

    Here, we present the complete genome of Pseudomonas sp. UK4. This bacterium was the first Pseudomonas strain shown to produce functional amyloids, and it represents a model organism for studies of functional amyloids in Pseudomonas (Fap).......Here, we present the complete genome of Pseudomonas sp. UK4. This bacterium was the first Pseudomonas strain shown to produce functional amyloids, and it represents a model organism for studies of functional amyloids in Pseudomonas (Fap)....

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

    Science.gov (United States)

    Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.; Thiele, Ines; Palsson, Bernhard O.; Saunders, Michael A.

    2017-01-01

    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 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 models have 70,000 constraints and variables and will grow larger). We have developed a quadruple-precision 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 problems tested here. DQQ will enable extensive use of large linear and nonlinear models in systems biology and other applications involving multiscale data.

  5. Genomic analyses with biofilter 2.0: knowledge driven filtering, annotation, and model development.

    Science.gov (United States)

    Pendergrass, Sarah A; Frase, Alex; Wallace, John; Wolfe, Daniel; Katiyar, Neerja; Moore, Carrie; Ritchie, Marylyn D

    2013-12-30

    The ever-growing wealth of biological information available through multiple comprehensive database repositories can be leveraged for advanced analysis of data. We have now extensively revised and updated the multi-purpose software tool Biofilter that allows researchers to annotate and/or filter data as well as generate gene-gene interaction models based on existing biological knowledge. Biofilter now has the Library of Knowledge Integration (LOKI), for accessing and integrating existing comprehensive database information, including more flexibility for how ambiguity of gene identifiers are handled. We have also updated the way importance scores for interaction models are generated. In addition, Biofilter 2.0 now works with a range of types and formats of data, including single nucleotide polymorphism (SNP) identifiers, rare variant identifiers, base pair positions, gene symbols, genetic regions, and copy number variant (CNV) location information. Biofilter provides a convenient single interface for accessing multiple publicly available human genetic data sources that have been compiled in the supporting database of LOKI. Information within LOKI includes genomic locations of SNPs and genes, as well as known relationships among genes and proteins such as interaction pairs, pathways and ontological categories.Via Biofilter 2.0 researchers can:• Annotate genomic location or region based data, such as results from association studies, or CNV analyses, with relevant biological knowledge for deeper interpretation• Filter genomic location or region based data on biological criteria, such as filtering a series SNPs to retain only SNPs present in specific genes within specific pathways of interest• Generate Predictive Models for gene-gene, SNP-SNP, or CNV-CNV interactions based on biological information, with priority for models to be tested based on biological relevance, thus narrowing the search space and reducing multiple hypothesis-testing. Biofilter is a software

  6. caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

    Directory of Open Access Journals (Sweden)

    Xuan Jianhua

    2008-09-01

    Full Text Available Abstract Background The main limitations of most existing clustering methods used in genomic data analysis include heuristic or random algorithm initialization, the potential of finding poor local optima, the lack of cluster number detection, an inability to incorporate prior/expert knowledge, black-box and non-adaptive designs, in addition to the curse of dimensionality and the discernment of uninformative, uninteresting cluster structure associated with confounding variables. Results In an effort to partially address these limitations, we develop the VIsual Statistical Data Analyzer (VISDA for cluster modeling, visualization, and discovery in genomic data. VISDA performs progressive, coarse-to-fine (divisive hierarchical clustering and visualization, supported by hierarchical mixture modeling, supervised/unsupervised informative gene selection, supervised/unsupervised data visualization, and user/prior knowledge guidance, to discover hidden clusters within complex, high-dimensional genomic data. The hierarchical visualization and clustering scheme of VISDA uses multiple local visualization subspaces (one at each node of the hierarchy and consequent subspace data modeling to reveal both global and local cluster structures in a "divide and conquer" scenario. Multiple projection methods, each sensitive to a distinct type of clustering tendency, are used for data visualization, which increases the likelihood that cluster structures of interest are revealed. Initialization of the full dimensional model is based on first learning models with user/prior knowledge guidance on data projected into the low-dimensional visualization spaces. Model order selection for the high dimensional data is accomplished by Bayesian theoretic criteria and user justification applied via the hierarchy of low-dimensional visualization subspaces. Based on its complementary building blocks and flexible functionality, VISDA is generally applicable for gene clustering, sample

  7. caBIG VISDA: modeling, visualization, and discovery for cluster analysis of genomic data.

    Science.gov (United States)

    Zhu, Yitan; Li, Huai; Miller, David J; Wang, Zuyi; Xuan, Jianhua; Clarke, Robert; Hoffman, Eric P; Wang, Yue

    2008-09-18

    The main limitations of most existing clustering methods used in genomic data analysis include heuristic or random algorithm initialization, the potential of finding poor local optima, the lack of cluster number detection, an inability to incorporate prior/expert knowledge, black-box and non-adaptive designs, in addition to the curse of dimensionality and the discernment of uninformative, uninteresting cluster structure associated with confounding variables. In an effort to partially address these limitations, we develop the VIsual Statistical Data Analyzer (VISDA) for cluster modeling, visualization, and discovery in genomic data. VISDA performs progressive, coarse-to-fine (divisive) hierarchical clustering and visualization, supported by hierarchical mixture modeling, supervised/unsupervised informative gene selection, supervised/unsupervised data visualization, and user/prior knowledge guidance, to discover hidden clusters within complex, high-dimensional genomic data. The hierarchical visualization and clustering scheme of VISDA uses multiple local visualization subspaces (one at each node of the hierarchy) and consequent subspace data modeling to reveal both global and local cluster structures in a "divide and conquer" scenario. Multiple projection methods, each sensitive to a distinct type of clustering tendency, are used for data visualization, which increases the likelihood that cluster structures of interest are revealed. Initialization of the full dimensional model is based on first learning models with user/prior knowledge guidance on data projected into the low-dimensional visualization spaces. Model order selection for the high dimensional data is accomplished by Bayesian theoretic criteria and user justification applied via the hierarchy of low-dimensional visualization subspaces. Based on its complementary building blocks and flexible functionality, VISDA is generally applicable for gene clustering, sample clustering, and phenotype clustering

  8. High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling

    Science.gov (United States)

    Watanabe, Kakeru; Guo, Wei; Arai, Keigo; Takanashi, Hideki; Kajiya-Kanegae, Hiromi; Kobayashi, Masaaki; Yano, Kentaro; Tokunaga, Tsuyoshi; Fujiwara, Toru; Tsutsumi, Nobuhiro; Iwata, Hiroyoshi

    2017-01-01

    Genomics-assisted breeding methods have been rapidly developed with novel technologies such as next-generation sequencing, genomic selection and genome-wide association study. However, phenotyping is still time consuming and is a serious bottleneck in genomics-assisted breeding. In this study, we established a high-throughput phenotyping system for sorghum plant height and its response to nitrogen availability; this system relies on the use of unmanned aerial vehicle (UAV) remote sensing with either an RGB or near-infrared, green and blue (NIR-GB) camera. We evaluated the potential of remote sensing to provide phenotype training data in a genomic prediction model. UAV remote sensing with the NIR-GB camera and the 50th percentile of digital surface model, which is an indicator of height, performed well. The correlation coefficient between plant height measured by UAV remote sensing (PHUAV) and plant height measured with a ruler (PHR) was 0.523. Because PHUAV was overestimated (probably because of the presence of taller plants on adjacent plots), the correlation coefficient between PHUAV and PHR was increased to 0.678 by using one of the two replications (that with the lower PHUAV value). Genomic prediction modeling performed well under the low-fertilization condition, probably because PHUAV overestimation was smaller under this condition due to a lower plant height. The predicted values of PHUAV and PHR were highly correlated with each other (r = 0.842). This result suggests that the genomic prediction models generated with PHUAV were almost identical and that the performance of UAV remote sensing was similar to that of traditional measurements in genomic prediction modeling. UAV remote sensing has a high potential to increase the throughput of phenotyping and decrease its cost. UAV remote sensing will be an important and indispensable tool for high-throughput genomics-assisted plant breeding.

  9. High-Throughput Phenotyping of Sorghum Plant Height Using an Unmanned Aerial Vehicle and Its Application to Genomic Prediction Modeling.

    Science.gov (United States)

    Watanabe, Kakeru; Guo, Wei; Arai, Keigo; Takanashi, Hideki; Kajiya-Kanegae, Hiromi; Kobayashi, Masaaki; Yano, Kentaro; Tokunaga, Tsuyoshi; Fujiwara, Toru; Tsutsumi, Nobuhiro; Iwata, Hiroyoshi

    2017-01-01

    Genomics-assisted breeding methods have been rapidly developed with novel technologies such as next-generation sequencing, genomic selection and genome-wide association study. However, phenotyping is still time consuming and is a serious bottleneck in genomics-assisted breeding. In this study, we established a high-throughput phenotyping system for sorghum plant height and its response to nitrogen availability; this system relies on the use of unmanned aerial vehicle (UAV) remote sensing with either an RGB or near-infrared, green and blue (NIR-GB) camera. We evaluated the potential of remote sensing to provide phenotype training data in a genomic prediction model. UAV remote sensing with the NIR-GB camera and the 50th percentile of digital surface model, which is an indicator of height, performed well. The correlation coefficient between plant height measured by UAV remote sensing (PHUAV) and plant height measured with a ruler (PHR) was 0.523. Because PHUAV was overestimated (probably because of the presence of taller plants on adjacent plots), the correlation coefficient between PHUAV and PHR was increased to 0.678 by using one of the two replications (that with the lower PHUAV value). Genomic prediction modeling performed well under the low-fertilization condition, probably because PHUAV overestimation was smaller under this condition due to a lower plant height. The predicted values of PHUAV and PHR were highly correlated with each other (r = 0.842). This result suggests that the genomic prediction models generated with PHUAV were almost identical and that the performance of UAV remote sensing was similar to that of traditional measurements in genomic prediction modeling. UAV remote sensing has a high potential to increase the throughput of phenotyping and decrease its cost. UAV remote sensing will be an important and indispensable tool for high-throughput genomics-assisted plant breeding.

  10. Positioning Genomics in Biology Education: Content Mapping of Undergraduate Biology Textbooks

    Directory of Open Access Journals (Sweden)

    Naomi L. B. Wernick

    2014-07-01

    Full Text Available 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.

  11. 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

  12. 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…

  13. Universal Instructional Design as a Model for Educational Programs

    Science.gov (United States)

    Higbee, Jeanne L.

    2007-01-01

    This article describes Universal Instructional Design as an inclusive pedagogical model for use in educational programs, whether provided by traditional educational institutions, community-based initiatives, or workplace literacy projects. For the benefit of public relations specialists and classroom educators alike, the article begins with a…

  14. 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…

  15. A second generation integrated map of the rainbow trout (Oncorhynchus mykiss) genome: analysis of synteny with model fish genomes

    Science.gov (United States)

    In this paper we generated DNA fingerprints and end sequences from bacterial artificial chromosomes (BACs) from two new libraries to improve the first generation integrated physical and genetic map of the rainbow trout (Oncorhynchus mykiss) genome. The current version of the physical map is compose...

  16. Determination Effective Elements of Continuing Interprofessional Education Models

    Directory of Open Access Journals (Sweden)

    Leila Safabakhsh

    2017-08-01

    Full Text Available Background: Traditional continuing education (CE approaches have limited impact on patient management and outcomes. Continuing interprofessional education is an innovated educational approach that can improve patient care and outcomes related to health care. There is a need to provide guidance to continuing education professionals in the development, implementation, and evaluation of continuing interprofessional education activities. Objectives: This study attempted to identity effective elements of continuing interprofessional education in programs or models. Study Design: Database searches of published papers using Eric. Ovid, Science direct and PubMed (1990-2016 were conducted for existing IPE model post-registration. Broad search terms were used, including interprofessional education, continuing interprofessional education models and interprofessional education post-registration models. Results: Seven continuing interprofessional education models were identified in the literature. Topic, Goals, Content, learning strategy and Evaluation strategy were the components used in these patterns. Conclusions: Healthy topics, Content sharing between the participating professions, common educational goals for all professions, interactive learning and interprofessional learning methods and diverse assessment methods with feedback to learners, helps to make better be implemented inter-professional training programs.

  17. Humanism model of education on a physical culture in the institute of higher education

    Directory of Open Access Journals (Sweden)

    Strel'tsov V.A.

    2010-06-01

    Full Text Available Humanistic approach to the modeling of educational process in physical training at the institute of higher education is exposed in the article. The article defines new contents of key categories aimed at transformation of pedagogical consciousness and practice. The article positions the integrity of the student's physical culture formation as the basis of the humanistic-oriented model of education. The realization of the given model shows improved results of students' personality development in comparison with the traditional technocratic approach.

  18. 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.

  19. Genome-scale Metabolic Reaction Modeling: a New Approach to Geomicrobial Kinetics

    Science.gov (United States)

    McKernan, S. E.; Shapiro, B.; Jin, Q.

    2014-12-01

    Geomicrobial rates, rates of microbial metabolism in natural environments, are a key parameter of theoretical and practical problems in geobiology and biogeochemistry. Both laboratory- and field-based approaches have been applied to study rates of geomicrobial processes. Laboratory-based approaches analyze geomicrobial kinetics by incubating environmental samples under controlled laboratory conditions. Field methods quantify geomicrobial rates by observing the progress of geomicrobial processes. To take advantage of recent development in biogeochemical modeling and genome-scale metabolic modeling, we suggest that geomicrobial rates can also be predicted by simulating metabolic reaction networks of microbes. To predict geomicrobial rates, we developed a genome-scale metabolic model that describes enzyme reaction networks of microbial metabolism, and simulated the network model by accounting for the kinetics and thermodynamics of enzyme reactions. The model is simulated numerically to solve cellular enzyme abundance and hence metabolic rates under the constraints of cellular physiology. The new modeling approach differs from flux balance analysis of system biology in that it accounts for the thermodynamics and kinetics of enzymatic reactions. It builds on subcellular metabolic reaction networks, and hence also differs from classical biogeochemical reaction modeling. We applied the new approach to Methanosarcina acetivorans, an anaerobic, marine methanogen capable of disproportionating acetate to carbon dioxide and methane. The input of the new model includes (1) enzyme reaction network of acetoclastic methanogenesis, and (2) representative geochemical conditions of freshwater sedimentary environments. The output of the simulation includes the proteomics, metabolomics, and energy and matter fluxes of M. acetivorans. Our simulation results demonstrate the predictive power of the new modeling approach. Specifically, the results illustrate how methanogenesis rates vary

  20. [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.

  1. 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

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

    Science.gov (United States)

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

    2013-01-01

    Summary: 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. Availability: 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. Contact: johnmay@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23766418

  3. Comparison of mortality and incidence cancer risk and models of genomic instability: the Techa River cohort

    Energy Technology Data Exchange (ETDEWEB)

    Eidemueller, Markus; Jacob, Peter [Helmholtz Zentrum Muenchen, Institut fuer Strahlenschutz, Neuherberg (Germany); Ostroumova, Zhenia; Krestinina, Ludmila; Akleyev, Alexander [Urals Research Center for Radiation Medicine, Chelyabinsk (Russian Federation)

    2009-07-01

    Solid cancer mortality and incidence risk after radiation exposure in the Techa River Cohort in the Southern Urals region of Russia is analyzed. Residents along the Techa River received protracted exposure in the 1950s due to the releases of radioactive materials from the Mayak plutonium complex. The analysis is performed within the framework of the biologically based two-stage clonal expansion (TSCE) model and with excess relative risk models. TSCE models including effects of radiation-induced genomic instability are applied to the data and it is found that the best description of the radiation risk is achieved with the same model of genomic instability both for the mortality and incidence cohort. By a direct comparison of the cancer risk in both cohorts it is shown how the mortality and incidence rates and excess relative risk can be related. The TSCE parameters, that describe effective biological time scales in the process of cancer development, turn out to be similar for the mortality and incidence data sets.

  4. Integrating Environmental Genomics and Biogeochemical Models: a Gene-centric Approach

    Science.gov (United States)

    Reed, D. C.; Algar, C. K.; Huber, J. A.; Dick, G.

    2013-12-01

    Rapid advances in molecular microbial ecology have yielded an unprecedented amount of data about the evolutionary relationships and functional traits of microbial communities that regulate global geochemical cycles. Biogeochemical models, however, are trailing in the wake of the environmental genomics revolution and such models rarely incorporate explicit representations of bacteria and archaea, nor are they compatible with nucleic acid or protein sequence data. Here, we present a functional gene-based framework for describing microbial communities in biogeochemical models that uses genomics data and provides predictions that are readily testable using cutting-edge molecular tools. To demonstrate the approach in practice, nitrogen cycling in the Arabian Sea oxygen minimum zone (OMZ) was modelled to examine key questions about cryptic sulphur cycling and dinitrogen production pathways in OMZs. By directly linking geochemical dynamics to the genetic composition of microbial communities, the method provides mechanistic insights into patterns and biogeochemical consequences of marine microbes. Such an approach is critical for informing our understanding of the key role microbes play in modulating Earth's biogeochemistry.

  5. A genome-scale metabolic model of the lipid-accumulating yeast Yarrowia lipolytica

    Directory of Open Access Journals (Sweden)

    Loira Nicolas

    2012-05-01

    Full Text Available Abstract Background Yarrowia lipolytica is an oleaginous yeast which has emerged as an important microorganism for several biotechnological processes, such as the production of organic acids, lipases and proteases. It is also considered a good candidate for single-cell oil production. Although some of its metabolic pathways are well studied, its metabolic engineering is hindered by the lack of a genome-scale model that integrates the current knowledge about its metabolism. Results Combining in silico tools and expert manual curation, we have produced an accurate genome-scale metabolic model for Y. lipolytica. Using a scaffold derived from a functional metabolic model of the well-studied but phylogenetically distant yeast S. cerevisiae, we mapped conserved reactions, rewrote gene associations, added species-specific reactions and inserted specialized copies of scaffold reactions to account for species-specific expansion of protein families. We used physiological measures obtained under lab conditions to validate our predictions. Conclusions Y. lipolytica iNL895 represents the first well-annotated metabolic model of an oleaginous yeast, providing a base for future metabolic improvement, and a starting point for the metabolic reconstruction of other species in the Yarrowia clade and other oleaginous yeasts.

  6. 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

  7. 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.

  8. Knowledge Management Model on Educational Organization

    Directory of Open Access Journals (Sweden)

    Elsina Ferdinandus

    2015-12-01

    Key Words: model, knowledge management, educational organizations Abstrak: Penelitian ini bertujuan mendeskripsikan proses knowledge management yang dilakukan pada SMA Negeri 1 Pulau-pulau Aru dan SMA Yos Sudarso Dobo di Kabupaten Kepulauan Aru. Penelitian ini menggunakan jenis penelitian kualitatif dengan rancangan studi multi kasus. Data dikumpulkan dengan teknik observasi, wawancara mendalam dan dokumentasi kemudian dianalisis dengan teknik analisis data kasus individu dan analisis data lintas kasus. Temuan penelitian ini menggambarkan (1 guru-guru sudah melakukan transformasi pengetahuan explicit to tacit dengan baik ketika melakukan persiapan pembelajaran, transformasi pengetahuan tacit to explicit belum dilakukan dengan baik, dan transformasi pengetahuan tacit to tacit sudah dilakukan dengan baik; (2  sosialisasi dilakukan dengan baik, namun belum maksimal; (3  kepala sekolah SMA Negeri 1 Pulau-pulau Aru lebih demokratis dan kepala sekolah SMA Yos Sudarso Dobo lebih paternalistis; (4 peningkatan berupa upaya memasukan pengetahuan dari luar sekolah sudah dilakukan oleh kedua sekolah; dan (5  proses knowledge capture di kedua sekolah sudah berjalan dengan baik. Kata kunci: model, knowledge management, organisasi pendidikan

  9. 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.

  10. The Effects of Role Modeling on Technology Integration within Physical Education Teacher Education

    Science.gov (United States)

    Baert, Helena

    2014-01-01

    The national standards for physical education teacher education (PETE) in the US state that teacher candidates should be able to plan and implement technology infused lessons that meet lesson objectives and enhance learning in physical education (standard 3.7). Research shows that role modeling of technology integration can have a positive impact…

  11. Waves of Educational Model Production: The Case of Higher Education Institutionalization in Malawi, 1964-2004

    Science.gov (United States)

    Holland, Dana G.

    2010-01-01

    The domain of national education systems has been identified as one of the richest areas for exploring questions about globalization, particularly the degree of worldwide convergence in educational institutions. This article addresses questions about the transnational production and institutionalization of educational models through a historical…

  12. 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.

  13. Genome-wide expression profiling of five mouse models identifies similarities and differences with human psoriasis.

    Directory of Open Access Journals (Sweden)

    William R Swindell

    Full Text Available 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.

  14. Understanding What We Do: Emerging Models for Human Rights Education

    Science.gov (United States)

    Tibbitts, Felisa

    2002-07-01

    The author presents three approaches to contemporary human rights education practice: the Values and Awareness Model, the Accountability Model and the Transformational Model. Each model is associated with particular target groups, contents and strategies. The author suggests that these models can lend themselves to theory development and research in what might be considered an emerging educational field. Human rights education can be further strengthened through the appropriate use oflearning theory, as well as through the setting of standards for trainer preparation and program content, and through evaluating the impact of programs in terms of reaching learner goals (knowledge, values and skills) and contributing to social change.

  15. 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

    2016-11-01

    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 FST 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.

  16. Epigenomic model of cardiac enhancers with application to genome wide association studies.

    Science.gov (United States)

    Sahu, Avinash Das; Aniba, Radhouane; Chang, Yen-Pei Christy; Hannenhalli, Sridhar

    2013-01-01

    Mammalian gene regulation is often mediated by distal enhancer elements, in particular, for tissue specific and developmental genes. Computational identification of enhancers is difficult because they do not exhibit clear location preference relative to their target gene and also because they lack clearly distinguishing genomic features. This represents a major challenge in deciphering transcriptional regulation. Recent ChIP-seq based genome-wide investigation of epigenomic modifications have revealed that enhancers are often enriched for certain epigenomic marks. Here we utilize the epigenomic data in human heart tissue along with validated human heart enhancers to develop a Support Vector Machine (SVM) model of cardiac enhancers. Cross-validation classification accuracy of our model was 84% and 92% on positive and negative sets respectively with ROC AUC = 0.92. More importantly, while P300 binding has been used as gold standard for enhancers, our model can distinguish P300-bound validated enhancers from other P300-bound regions that failed to exhibit enhancer activity in transgenic mouse. While GWAS studies reveal polymorphic regions associated with certain phenotypes, they do not immediately provide causality. Next, we hypothesized that genomic regions containing a GWAS SNP associated with a cardiac phenotype might contain another SNP in a cardiac enhancer, which presumably mediates the phenotype. Starting with a comprehensive set of SNPs associated with cardiac phenotypes in GWAS studies, we scored other SNPs in LD with the GWAS SNP according to its probability of being an enhancer and choose one with best score in the LD as enhancer. We found that our predicted enhancers are enriched for known cardiac transcriptional regulator motifs and are likely to regulate the nearby gene. Importantly, these tendencies are more favorable for the predicted enhancers compared with an approach that uses P300 binding as a marker of enhancer activity.

  17. In vivo genome editing improves muscle function in a mouse model of Duchenne muscular dystrophy

    OpenAIRE

    Nelson, Christopher E.; Hakim, Chady H.; Ousterout, David G.; Thakore, Pratiksha I.; Moreb, Eirik A.; Rivera, Ruth M. Castellanos; Madhavan, Sarina; Pan, Xiufang; Ran, F. Ann; Yan, Winston X.; Asokan, Aravind; Zhang, Feng; Duan, Dongsheng; Gersbach, Charles A.

    2015-01-01

    Duchenne muscular dystrophy (DMD) is a devastating disease affecting about 1 out of 5000 male births and caused by mutations in the dystrophin gene. Genome editing has the potential to restore expression of a modified dystrophin gene from the native locus to modulate disease progression. In this study, adeno-associated virus was used to deliver the CRISPR/Cas9 system to the mdx mouse model of DMD to remove the mutated exon 23 from the dystrophin gene. This includes local and systemic delivery...

  18. Untangling statistical and biological models to understand network inference: the need for a genomics network ontology.

    Science.gov (United States)

    Emmert-Streib, Frank; Dehmer, Matthias; Haibe-Kains, Benjamin

    2014-01-01

    In this paper, we shed light on approaches that are currently used to infer networks from gene expression data with respect to their biological meaning. As we will show, the biological interpretation of these networks depends on the chosen theoretical perspective. For this reason, we distinguish a statistical perspective from a mathematical modeling perspective and elaborate their differences and implications. Our results indicate the imperative need for a genomic network ontology in order to avoid increasing confusion about the biological interpretation of inferred networks, which can be even enhanced by approaches that integrate multiple data sets, respectively, data types.

  19. In vivo genome editing improves muscle function in a mouse model of Duchenne muscular dystrophy

    OpenAIRE

    Nelson, Christopher E.; Hakim, Chady H.; Ousterout, David G.; Thakore, Pratiksha I; Moreb, Eirik A.; Rivera, Ruth M. Castellanos; Madhavan, Sarina; Pan, Xiufang; Ran, F. Ann; Yan, Winston X.; Asokan, Aravind; Zhang, Feng; Duan, Dongsheng; Gersbach, Charles A.

    2015-01-01

    Duchenne muscular dystrophy (DMD) is a devastating disease affecting about 1 out of 5000 male births and caused by mutations in the dystrophin gene. Genome editing has the potential to restore expression of a modified dystrophin gene from the native locus to modulate disease progression. In this study, adeno-associated virus was used to deliver the CRISPR/Cas9 system to the mdx mouse model of DMD to remove the mutated exon 23 from the dystrophin gene. This includes local and systemic delivery...

  20. 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…

  1. 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…

  2. The Open Flip--A Digital Economic Model for Education

    Science.gov (United States)

    Weller, Martin

    2016-01-01

    The advent of the internet and digital technologies has given rise to a number of new economic models. These have often been applied to education, but either through faults in the initial models or differences in the characteristics of the education sector, they have not proven to be widely applicable. The use of digital, network technologies…

  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. ezRAD: a simplified method for genomic genotyping in non-model organisms

    Directory of Open Access Journals (Sweden)

    Robert J. Toonen

    2013-11-01

    Full Text Available Here, we introduce ezRAD, a novel strategy for restriction site–associated DNA (RAD that requires little technical expertise or investment in laboratory equipment, and demonstrate its utility for ten non-model organisms across a wide taxonomic range. ezRAD differs from other RAD methods primarily through its use of standard Illumina TruSeq library preparation kits, which makes it possible for any laboratory to send out to a commercial genomic core facility for library preparation and next-generation sequencing with virtually no additional investment beyond the cost of the service itself. This simplification opens RADseq to any lab with the ability to extract DNA and perform a restriction digest. ezRAD also differs from others in its flexibility to use any restriction enzyme (or combination of enzymes that cuts frequently enough to generate fragments of the desired size range, without requiring the purchase of separate adapters for each enzyme or a sonication step, which can further decrease the cost involved in choosing optimal enzymes for particular species and research questions. We apply this method across a wide taxonomic diversity of non-model organisms to demonstrate the utility and flexibility of our approach. The simplicity of ezRAD makes it particularly useful for the discovery of single nucleotide polymorphisms and targeted amplicon sequencing in natural populations of non-model organisms that have been historically understudied because of lack of genomic information.

  5. ezRAD: a simplified method for genomic genotyping in non-model organisms.

    Science.gov (United States)

    Toonen, Robert J; Puritz, Jonathan B; Forsman, Zac H; Whitney, Jonathan L; Fernandez-Silva, Iria; Andrews, Kimberly R; Bird, Christopher E

    2013-01-01

    Here, we introduce ezRAD, a novel strategy for restriction site-associated DNA (RAD) that requires little technical expertise or investment in laboratory equipment, and demonstrate its utility for ten non-model organisms across a wide taxonomic range. ezRAD differs from other RAD methods primarily through its use of standard Illumina TruSeq library preparation kits, which makes it possible for any laboratory to send out to a commercial genomic core facility for library preparation and next-generation sequencing with virtually no additional investment beyond the cost of the service itself. This simplification opens RADseq to any lab with the ability to extract DNA and perform a restriction digest. ezRAD also differs from others in its flexibility to use any restriction enzyme (or combination of enzymes) that cuts frequently enough to generate fragments of the desired size range, without requiring the purchase of separate adapters for each enzyme or a sonication step, which can further decrease the cost involved in choosing optimal enzymes for particular species and research questions. We apply this method across a wide taxonomic diversity of non-model organisms to demonstrate the utility and flexibility of our approach. The simplicity of ezRAD makes it particularly useful for the discovery of single nucleotide polymorphisms and targeted amplicon sequencing in natural populations of non-model organisms that have been historically understudied because of lack of genomic information.

  6. The non-power model of the genetic code: a paradigm for interpreting genomic information.

    Science.gov (United States)

    Gonzalez, Diego Luis; Giannerini, Simone; Rosa, Rodolfo

    2016-03-13

    In this article, we present a mathematical framework based on redundant (non-power) representations of integer numbers as a paradigm for the interpretation of genomic information. The core of the approach relies on modelling the degeneracy of the genetic code. The model allows one to explain many features and symmetries of the genetic code and to uncover hidden symmetries. Also, it provides us with new tools for the analysis of genomic sequences. We review briefly three main areas: (i) the Euplotid nuclear code, (ii) the vertebrate mitochondrial code, and (iii) the main coding/decoding strategies used in the three domains of life. In every case, we show how the non-power model is a natural unified framework for describing degeneracy and deriving sound biological hypotheses on protein coding. The approach is rooted on number theory and group theory; nevertheless, we have kept the technical level to a minimum by focusing on key concepts and on the biological implications. © 2016 The Author(s).

  7. Dual model of vocational education: Austrian example

    Directory of Open Access Journals (Sweden)

    Tomić Milica

    2015-01-01

    Full Text Available Dual education, as a form of secondary vocational education means that education and practical training are held on two locations - in school and in a company (organization, factory and that these two institutions jointly participate in the realization of vocational education. The paper presents an account of the functioning of dual education in Austria. In that framework special attention was paid to law regulations in this field, the modes of dual education, progression through the system and the perspectives of the young in the labour market. Among the key features of dual education which are, at the same time, considered the factors of its successfulness, the following stand out: active role of social partners in the conceptualization and realization of vocational education; intensive practical training of high quality; systemic interrelatedness of vocational schools and firms where practical training is provided, the compliance of the offer of educational profiles and the needs of labour market; the system of stimulation for the firms that provide professional training for students, clear legislation and the system of professional qualifications. Yet, the challenges of dual educations are not neglected in the paper.

  8. The Karyote physico-chemical genomic, proteomic, metabolic cell modeling system.

    Science.gov (United States)

    Ortoleva, P; Berry, E; Brun, Y; Fan, J; Fontus, M; Hubbard, K; Jaqaman, K; Jarymowycz, L; Navid, A; Sayyed-Ahmad, A; Shreif, Z; Stanley, F; Tuncay, K; Weitzke, E; Wu, L-C

    2003-01-01

    Modeling approaches to the dynamics of a living cell are presented that are strongly based on its underlying physical and chemical processes and its hierarchical spatio-temporal organization. Through the inclusion of a broad spectrum of processes and a rigorous analysis of the multiple scale nature of cellular dynamics, we are attempting to advance cell modeling and its applications. The presentation focuses on our cell modeling system, which integrates data archiving and quantitative physico-chemical modeling and information theory to provide a seamless approach to the modeling/data analysis endeavor. Thereby the rapidly growing mess of genomic, proteomic, metabolic, and cell physiological data can be automatically used to develop and calibrate a predictive cell model. The discussion focuses on the Karyote cell modeling system and an introduction to the CellX and VirusX models. The Karyote software system integrates three elements: (1) a model-building and data archiving module that allows one to define a cell type to be modeled through its reaction network, structure, and transport processes as well as to choose the surrounding medium and other parameters of the phenomenon to be modeled; (2) a genomic, proteomic, metabolic cell simulator that solves the equations of metabolic reaction, transcription/translation polymerization and the exchange of molecules between parts of the cell and with the surrounding medium; and (3) an information theory module (ITM) that automates model calibration and development, and integrates a variety of data types with the cell dynamic computations. In Karyote, reactions may be fast (equilibrated) or slow (finite rate), and the special effects of enzymes and other minority species yielding steady-state cycles of arbitrary complexities are accounted for. These features of the dynamics are handled via rigorous multiple scale analysis. A user interface allows for an automated generation and solution of the equations of multiple timescale

  9. Orientating cooperative learning model on social responsibility in physical education

    Directory of Open Access Journals (Sweden)

    Yi Chuan Chiu

    2014-05-01

    Full Text Available Five alternative generic models on Physical Education were addressed by Jewett et al. (1995. Although these five generic models enumerate the main curriculum design, it rarely presents well the full view of it. Cooperative learning (CL is generally adopted by the teachers in social science field and receives splendid effects. In the field of physical education, there are also numerous successful examples applied on CL model. On the other hand, CL curriculum emphasizes on active learning that involves the processes of social interaction, making decision, and cognitive outcome to provide students with a holistic education; that was expelled from the five generic models. Therefore, this study adopts content analysis to explore the link between cooperative learning and social responsibility in physical education. Aforementioned, the contribution of this study is preliminarily building up CL model on social responsibility value orientation in physical education for the extension of Jewett et al. (1995 to complete the structure of the theoretical integrity.

  10. Genome Editing: From Drosophila to Non-Model Insects and Beyond.

    Science.gov (United States)

    Huang, Yueping; Liu, Zhiping; Rong, Yikang S

    2016-05-20

    Insect is the largest group of animals on land. Many insect species inflict economical and health losses to humans. Yet many more benefit us by helping to maintain balances in our ecosystem. The benefits that insects offer remain largely untapped, justifying our continuing efforts to develop tools to better understand their biology and to better manage their activities. Here we focus on reviewing the progresses made in the development of genome engineering tools for model insects. Instead of detailed descriptions of the molecular mechanisms underlying each technical advance, we focus our discussion on the logistics for implementing similar tools in non-model insects. Since none of the tools were developed specific for insects, similar approaches can be applied to other non-model organisms.

  11. Integration of gene expression data into genome-scale metabolic models

    DEFF Research Database (Denmark)

    Åkesson, M.; Förster, Jochen; Nielsen, Jens

    2004-01-01

    of gene expression from chemostat and batch cultures of Saccharomyces cerevisiae were combined with a recently developed genome-scale model, and the computed metabolic flux distributions were compared to experimental values from carbon labeling experiments and metabolic network analysis. The integration......A framework for integration of transcriptome data into stoichiometric metabolic models to obtain improved flux predictions is presented. The key idea is to exploit the regulatory information in the expression data to give additional constraints on the metabolic fluxes in the model. Measurements...... of expression data resulted in improved predictions of metabolic behavior in batch cultures, enabling quantitative predictions of exchange fluxes as well as qualitative estimations of changes in intracellular fluxes. A critical discussion of correlation between gene expression and metabolic fluxes is given....

  12. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Zhang, Xi-Cheng; Nilsson, Avlant

    2017-01-01

    Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics......, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance...... with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between...

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

    Science.gov (United States)

    Feizi, Amir; Österlund, Tobias; Petranovic, Dina; Bordel, Sergio; Nielsen, Jens

    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 was developed which mimics secretory machinery and assigns each secretory protein to a particular secretory class that determines the set of PTMs and transport steps specific to each protein. Protein abundances were integrated with the model in order to gain system level estimation of the metabolic demands associated with the processing of each specific protein as well as a quantitative estimation of the activity of each component of the secretory machinery.

  14. 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.

  15. A metabolite-centric view on flux distributions in genome-scale metabolic models.

    Science.gov (United States)

    Riemer, S Alexander; Rex, René; Schomburg, Dietmar

    2013-04-12

    Genome-scale metabolic models are important tools in systems biology. They permit the in-silico prediction of cellular phenotypes via mathematical optimisation procedures, most importantly flux balance analysis. Current studies on metabolic models mostly consider reaction fluxes in isolation. Based on a recently proposed metabolite-centric approach, we here describe a set of methods that enable the analysis and interpretation of flux distributions in an integrated metabolite-centric view. We demonstrate how this framework can be used for the refinement of genome-scale metabolic models. We applied the metabolite-centric view developed here to the most recent metabolic reconstruction of Escherichia coli. By compiling the balance sheets of a small number of currency metabolites, we were able to fully characterise the energy metabolism as predicted by the model and to identify a possibility for model refinement in NADPH metabolism. Selected branch points were examined in detail in order to demonstrate how a metabolite-centric view allows identifying functional roles of metabolites. Fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass were identified as enzymatic reactions that can carry high fluxes in the model but are unlikely to exhibit significant activity in vivo. Performing a metabolite essentiality analysis, unconstrained import and export of iron ions could be identified as potentially problematic for the quality of model predictions. The system-wide analysis of split ratios and branch points allows a much deeper insight into the metabolic network than reaction-centric analyses. Extending an earlier metabolite-centric approach, the methods introduced here establish an integrated metabolite-centric framework for the interpretation of flux distributions in genome-scale metabolic networks that can complement the classical reaction-centric framework. Analysing fluxes and their metabolic context simultaneously opens the door to systems biological

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

    Directory of Open Access Journals (Sweden)

    Lal Jonathan A

    2011-12-01

    Full Text Available Abstract Background 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. Methods The method used to develop our model is an adapted version of the Fish Trap Model and the Basic Design Cycle. Results 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

  17. 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.

  18. Utilizing Educational Theoretical Models to Support Effective Physical Education Pedagogy

    Science.gov (United States)

    Usher, Wayne; Edwards, Allan; de Meyrick, Bianca

    2015-01-01

    Physical education (PE) pedagogy has traditionally been viewed as drillstyle teaching. Whilst this traditional pedagogical approach provides exposure to various skills, used within a school-based PE and sporting context, it does not demonstrate a student's competence associated with their ability to apply these skills in complex game situations.…

  19. Utilizing Educational Theoretical Models to Support Effective Physical Education Pedagogy

    Science.gov (United States)

    Usher, Wayne; Edwards, Allan; de Meyrick, Bianca

    2015-01-01

    Physical education (PE) pedagogy has traditionally been viewed as drillstyle teaching. Whilst this traditional pedagogical approach provides exposure to various skills, used within a school-based PE and sporting context, it does not demonstrate a student's competence associated with their ability to apply these skills in complex game situations.…

  20. 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...

  1. Report on three Genomes to Life Workshops: Data Infrastructure, Modeling and Simulation, and Protein Structure Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Geist, GA

    2003-09-16

    On July 22, 23, 24, 2003, three one day workshops were held in Gaithersburg, Maryland. Each was attended by about 30 computational biologists, mathematicians, and computer scientists who were experts in the respective workshop areas The first workshop discussed the data infrastructure needs for the Genomes to Life (GTL) program with the objective to identify gaps in the present GTL data infrastructure and define the GTL data infrastructure required for the success of the proposed GTL facilities. The second workshop discussed the modeling and simulation needs for the next phase of the GTL program and defined how these relate to the experimental data generated by genomics, proteomics, and metabolomics. The third workshop identified emerging technical challenges in computational protein structure prediction for DOE missions and outlining specific goals for the next phase of GTL. The workshops were attended by representatives from both OBER and OASCR. The invited experts at each of the workshops made short presentations on what they perceived as the key needs in the GTL data infrastructure, modeling and simulation, and structure prediction respectively. Each presentation was followed by a lively discussion by all the workshop attendees. The following findings and recommendations were derived from the three workshops. A seamless integration of GTL data spanning the entire range of genomics, proteomics, and metabolomics will be extremely challenging but it has to be treated as the first-class component of the GTL program to assure GTL's chances for success. High-throughput GTL facilities and ultrascale computing will make it possible to address the ultimate goal of modern biology: to achieve a fundamental, comprehensive, and systematic understanding of life. But first the GTL community needs to address the problem of the massive quantities and increased complexity of biological data produced by experiments and computations. Genome-scale collection, analysis

  2. A Model for Educating Systems Engineers

    Science.gov (United States)

    2012-03-01

    M.D. Engelhart, E.J. Furst, W.H. Hill, and D. R. Krathwohl, Taxonomy of educational objectives the classification of educational goals handbook I... Educating Systems Engineers 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f...Shaw, “Advancing Software Engineering Professional Education ”, IEEE Software, vol. 23, no. 6, pp. 58-63, July/August 2011. [6] B.S. Bloom , B.S

  3. 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.

  4. Predictive Models of Recombination Rate Variation across the Drosophila melanogaster Genome

    Science.gov (United States)

    Adrian, Andrew B.; Corchado, Johnny Cruz; Comeron, Josep M.

    2016-01-01

    In all eukaryotic species examined, meiotic recombination, and crossovers in particular, occur non‐randomly along chromosomes. The cause for this non-random distribution remains poorly understood but some specific DNA sequence motifs have been shown to be enriched near crossover hotspots in a number of species. We present analyses using machine learning algorithms to investigate whether DNA motif distribution across the genome can be used to predict crossover variation in Drosophila melanogaster, a species without hotspots. Our study exposes a combinatorial non-linear influence of motif presence able to account for a significant fraction of the genome-wide variation in crossover rates at all genomic scales investigated, from 20% at 5-kb to almost 70% at 2,500-kb scale. The models are particularly predictive for regions with the highest and lowest crossover rates and remain highly informative after removing sub-telomeric and -centromeric regions known to have strongly reduced crossover rates. Transcriptional activity during early meiosis and differences in motif use between autosomes and the X chromosome add to the predictive power of the models. Moreover, we show that population-specific differences in crossover rates can be partly explained by differences in motif presence. Our results suggest that crossover distribution in Drosophila is influenced by both meiosis-specific chromatin dynamics and very local constitutive open chromatin associated with DNA motifs that prevent nucleosome stabilization. These findings provide new information on the genetic factors influencing variation in recombination rates and a baseline to study epigenetic mechanisms responsible for plastic recombination as response to different biotic and abiotic conditions and stresses. PMID:27492232

  5. 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…

  6. 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.

  7. Hi-C-constrained physical models of human chromosomes recover functionally-related properties of genome organization

    Science.gov (United States)

    di Stefano, Marco; Paulsen, Jonas; Lien, Tonje G.; Hovig, Eivind; Micheletti, Cristian

    2016-10-01

    Combining genome-wide structural models with phenomenological data is at the forefront of efforts to understand the organizational principles regulating the human genome. Here, we use chromosome-chromosome contact data as knowledge-based constraints for large-scale three-dimensional models of the human diploid genome. The resulting models remain minimally entangled and acquire several functional features that are observed in vivo and that were never used as input for the model. We find, for instance, that gene-rich, active regions are drawn towards the nuclear center, while gene poor and lamina associated domains are pushed to the periphery. These and other properties persist upon adding local contact constraints, suggesting their compatibility with non-local constraints for the genome organization. The results show that suitable combinations of data analysis and physical modelling can expose the unexpectedly rich functionally-related properties implicit in chromosome-chromosome contact data. Specific directions are suggested for further developments based on combining experimental data analysis and genomic structural modelling.

  8. Genomic risk models improve prediction of longitudinal lipid levels in children and young adults

    Directory of Open Access Journals (Sweden)

    Nathan E. Wineinger

    2013-05-01

    Full Text Available In clinical medicine, lipids are commonly measured biomarkers used to assess an individual’s risk for cardiovascular disease, heart attack, and stroke. Accurately predicting longitudinal lipid levels based on genomic information can inform therapeutic practices and decrease cardiovascular risk by identifying high-risk patients prior to onset. Using genotyped and imputed genetic data from 523 unrelated Caucasian Americans from the Bogalusa Heart Study, surveyed on 4,026 occasions from 4 to 48 years of age, we generated various lipid genomic risk models based on previously reported markers. We observed a significant improvement in prediction over non-genetic risk models in high density lipoprotein cholesterol (increase in the squared correlation between observed and predicted values, d=0.032, low density lipoprotein cholesterol (d=0.053, total cholesterol (d=0.043, and triglycerides (d=0.031. Many of our approaches are based on an n-fold cross-validation procedure that are, by design, adaptable to a clinical environment.

  9. Fisher's model and the genomics of adaptation: restricted pleiotropy, heterogenous mutation, and parallel evolution.

    Science.gov (United States)

    Chevin, Luis-Miguel; Martin, Guillaume; Lenormand, Thomas

    2010-11-01

    Genetic theories of adaptation generally overlook the genes in which beneficial substitutions occur, and the likely variation in their mutational effects. We investigate the consequences of heterogeneous mutational effects among loci on the genetics of adaptation. We use a generalization of Fisher's geometrical model, which assumes multivariate Gaussian stabilizing selection on multiple characters. In our model, mutation has a distinct variance-covariance matrix of phenotypic effects for each locus. Consequently, the distribution of selection coefficients s varies across loci. We assume each locus can only affect a limited number of independent linear combinations of phenotypic traits (restricted pleiotropy), which differ among loci, an effect we term "orientation heterogeneity." Restricted pleiotropy can sharply reduce the overall proportion of beneficial mutations. Orientation heterogeneity has little impact on the shape of the genomic distribution, but can substantially increase the probability of parallel evolution (the repeated fixation of beneficial mutations at the same gene in independent populations), which is highest with low pleiotropy. We also consider variation in the degree of pleiotropy and in the mean s across loci. The latter impacts the genomic distribution of s, but has a much milder effect on parallel evolution. We discuss these results in the light of evolution experiments. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.

  10. Incorporating biological pathways via a Markov random field model in genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Min Chen

    2011-04-01

    Full Text Available Genome-wide association studies (GWAS examine a large number of markers across the genome to identify associations between genetic variants and disease. Most published studies examine only single markers, which may be less informative than considering multiple markers and multiple genes jointly because genes may interact with each other to affect disease risk. Much knowledge has been accumulated in the literature on biological pathways and interactions. It is conceivable that appropriate incorporation of such prior knowledge may improve the likelihood of making genuine discoveries. Although a number of methods have been developed recently to prioritize genes using prior biological knowledge, such as pathways, most methods treat genes in a specific pathway as an exchangeable set without considering the topological structure of a pathway. However, how genes are related with each other in a pathway may be very informative to identify association signals. To make use of the connectivity information among genes in a pathway in GWAS analysis, we propose a Markov Random Field (MRF model to incorporate pathway topology for association analysis. We show that the conditional distribution of our MRF model takes on a simple logistic regression form, and we propose an iterated conditional modes algorithm as well as a decision theoretic approach for statistical inference of each gene's association with disease. Simulation studies show that our proposed framework is more effective to identify genes associated with disease than a single gene-based method. We also illustrate the usefulness of our approach through its applications to a real data example.

  11. Genome engineering of isogenic human ES cells to model autism disorders.

    Science.gov (United States)

    Martinez, Refugio A; Stein, Jason L; Krostag, Anne-Rachel F; Nelson, Angelique M; Marken, John S; Menon, Vilas; May, Ryan C; Yao, Zizhen; Kaykas, Ajamete; Geschwind, Daniel H; Grimley, Joshua S

    2015-05-26

    Isogenic pluripotent stem cells are critical tools for studying human neurological diseases by allowing one to study the effects of a mutation in a fixed genetic background. Of particular interest are the spectrum of autism disorders, some of which are monogenic such as Timothy syndrome (TS); others are multigenic such as the microdeletion and microduplication syndromes of the 16p11.2 chromosomal locus. Here, we report engineered human embryonic stem cell (hESC) lines for modeling these two disorders using locus-specific endonucleases to increase the efficiency of homology-directed repair (HDR). We developed a system to: (1) computationally identify unique transcription activator-like effector nuclease (TALEN) binding sites in the genome using a new software program, TALENSeek, (2) assemble the TALEN genes by combining golden gate cloning with modified constructs from the FLASH protocol, and (3) test the TALEN pairs in an amplification-based HDR assay that is more sensitive than the typical non-homologous end joining assay. We applied these methods to identify, construct, and test TALENs that were used with HDR donors in hESCs to generate an isogenic TS cell line in a scarless manner and to model the 16p11.2 copy number disorder without modifying genomic loci with high sequence similarity.

  12. A Method to Constrain Genome-Scale Models with 13C Labeling Data.

    Directory of Open Access Journals (Sweden)

    Héctor García Martín

    2015-09-01

    Full Text Available Current limitations in quantitatively predicting biological behavior hinder our efforts to engineer biological systems to produce biofuels and other desired chemicals. Here, we present a new method for calculating metabolic fluxes, key targets in metabolic engineering, that incorporates data from 13C labeling experiments and genome-scale models. The data from 13C labeling experiments provide strong flux constraints that eliminate the need to assume an evolutionary optimization principle such as the growth rate optimization assumption used in Flux Balance Analysis (FBA. This effective constraining is achieved by making the simple but biologically relevant assumption that flux flows from core to peripheral metabolism and does not flow back. The new method is significantly more robust than FBA with respect to errors in genome-scale model reconstruction. Furthermore, it can provide a comprehensive picture of metabolite balancing and predictions for unmeasured extracellular fluxes as constrained by 13C labeling data. A comparison shows that the results of this new method are similar to those found through 13C Metabolic Flux Analysis (13C MFA for central carbon metabolism but, additionally, it provides flux estimates for peripheral metabolism. The extra validation gained by matching 48 relative labeling measurements is used to identify where and why several existing COnstraint Based Reconstruction and Analysis (COBRA flux prediction algorithms fail. We demonstrate how to use this knowledge to refine these methods and improve their predictive capabilities. This method provides a reliable base upon which to improve the design of biological systems.

  13. 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.

  14. Portfolio Assessment: A Model for Counselor Education.

    Science.gov (United States)

    Baltimore, Michael L.; And Others

    1996-01-01

    Discusses the benefits of portfolio assessment to counselor education programs. Provides a definition of portfolio and outlines a portfolio approach in counselor education. Asserts that portfolio assessment relies on performance in measuring learning outcomes. Gives an example of portfolio content, along with strategies for evaluating student…

  15. 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…

  16. Modeling PMESII Factors to Support Strategic Education

    Science.gov (United States)

    2008-06-11

    Government Friendly Faction Cuban Americans Support for Ruling Govt Support for Ruling Govt Havana Santiago de Cuba Camaguey Support for the ruling...distract from ongoing exercise cycle – Implement running start Scenario authors: pursue PMESII trial: notional educational Cuba scenario Several emerging...educational scenario – PMESII capability brief – JFCOM and USAWC had independent Cuba representations – Provided scenario documentation Iterative

  17. 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)

  18. Strategic Model for Future Geospatial Education.

    Science.gov (United States)

    2007-11-02

    successful collaboration between NCGIA and CITC/CGITC could lead to the next discussion point of " franchising " educational programs. 4. Development...which would all be designed to run in a PC environment. Thus is the initial set-up for geospatial education franchising -creation of a core curriculum

  19. A Portfolio Model for Music Educators

    Science.gov (United States)

    Hill, Cheryl Frazes

    2008-01-01

    In recent years, portfolios in paper or digital form have become a requirement for teachers. Many university teacher education programs throughout the United States, including music education, require a portfolio as a graduation requirement. For practicing teachers interested in National Board Certification, a portfolio is part of the assessment…

  20. Innovative Developmental Education Programs: A Texas Model

    Science.gov (United States)

    Booth, Eric A.; Capraro, Mary Margaret; Capraro, Robert M.; Chaudhuri, Nandita; Dyer, James; Marchbanks, Miner P., III

    2014-01-01

    This article provides insights from a 2-year, cross-site evaluation of state funded developmental education sites and serves as a focus article for response by those sites. Receiving grants from the Texas Higher Education Coordinating Board (THECB), nine sites (5 community colleges and 4 universities) implemented innovative developmental education…

  1. Curricular Models of CLIL Education in Poland

    Science.gov (United States)

    Czura, Anna; Papaja, Katarzyna

    2013-01-01

    Bilingual education in Poland gained in popularity after the political changes in 1989 when Polish society started noticing the importance of foreign language learning. With the emergence of content and language integrated learning (CLIL) in the 1990s, which in the Polish context is still termed as "bilingual education", foreign…

  2. Curricular Models of CLIL Education in Poland

    Science.gov (United States)

    Czura, Anna; Papaja, Katarzyna

    2013-01-01

    Bilingual education in Poland gained in popularity after the political changes in 1989 when Polish society started noticing the importance of foreign language learning. With the emergence of content and language integrated learning (CLIL) in the 1990s, which in the Polish context is still termed as "bilingual education", foreign languages other…

  3. 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...

  4. Improved prediction of genetic predisposition to psychiatric disorders using genomic feature best linear unbiased prediction models

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Demontis, Ditte; Børglum, Anders

    Introduction: Accurate prediction of unobserved phenotypes from observed genotypes is essential for the success in predicting disease risk from genotypes. However, the performance is somewhat limited. Genomic feature best linear unbiased prediction (GFBLUP) models separate the total genomic...... is enriched for causal variants. Here we apply the GFBLUP model to a small schizophrenia case-control study to test the promise of this model on psychiatric disorders, and hypothesize that the performance will be increased when applying the model to a larger ADHD case-control study if the genomic feature...... contains the causal variants. Materials and Methods: The schizophrenia study consisted of 882 controls and 888 schizophrenia cases genotyped for 520,000 SNPs. The ADHD study contained 25,954 controls and 16,663 ADHD cases with 8,4 million imputed genotypes. Results: The predictive ability for schizophrenia...

  5. A Genomic Bayesian Multi-trait and Multi-environment Model.

    Science.gov (United States)

    Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Toledo, Fernando H; Pérez-Hernández, Oscar; Eskridge, Kent M; Rutkoski, Jessica

    2016-09-08

    When information on multiple genotypes evaluated in multiple environments is recorded, a multi-environment single trait model for assessing genotype × environment interaction (G × E) is usually employed. Comprehensive models that simultaneously take into account the correlated traits and trait × genotype × environment interaction (T × G × E) are lacking. In this research, we propose a Bayesian model for analyzing multiple traits and multiple environments for whole-genome prediction (WGP) model. For this model, we used Half-[Formula: see text] priors on each standard deviation term and uniform priors on each correlation of the covariance matrix. These priors were not informative and led to posterior inferences that were insensitive to the choice of hyper-parameters. We also developed a computationally efficient Markov Chain Monte Carlo (MCMC) under the above priors, which allowed us to obtain all required full conditional distributions of the parameters leading to an exact Gibbs sampling for the posterior distribution. We used two real data sets to implement and evaluate the proposed Bayesian method and found that when the correlation between traits was high (>0.5), the proposed model (with unstructured variance-covariance) improved prediction accuracy compared to the model with diagonal and standard variance-covariance structures. The R-software package Bayesian Multi-Trait and Multi-Environment (BMTME) offers optimized C++ routines to efficiently perform the analyses. Copyright © 2016 Montesinos-López et al.

  6. 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.

  7. A Path Analysis of Educator Perceptions of Open Educational Resources Using the Technology Acceptance Model

    Directory of Open Access Journals (Sweden)

    Hope Kelly

    2014-04-01

    Full Text Available Open educational resources (OER are making their way into a variety of educational contexts from formal lesson planning to just in time learning. Educators and training professionals have been recognized as an important audience for these materials. The concepts of self-efficacy and outcome judgment from social cognitive learning theory serve as theoretical constructs to measure educator perceptions of OER. This study uses a path analysis, based on the technology acceptance model, to understand adoption of these resources by this audience with a particular emphasis on self-efficacy. Among the participants, three main groups were identified: K-12 educators, higher education professionals, and those involved in workplace training. A discriminant function analysis found that K-12 educators stood out as finding OER relevant to improving their practice. Recommendations are made in regards to an emphasis on easy to use designs to improve application self-efficacy of OER and instructional messaging for future K-12 educators.

  8. 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

  9. A collaborative model for supporting community-based interdisciplinary education.

    Science.gov (United States)

    Carney, Patricia A; Schifferdecker, Karen E; Pipas, Catherine F; Fall, Leslie H; Poor, Daniel A; Peltier, Deborah A; Nierenberg, David W; Brooks, W Blair

    2002-07-01

    Development and support of community-based, interdisciplinary ambulatory medical education has achieved high priority due to on-site capacity and the unique educational experiences community sites contribute to the educational program. The authors describe the collaborative model their school developed and implemented in 2000 to integrate institution- and community-based interdisciplinary education through a centralized office, the strengths and challenges faced in applying it, the educational outcomes that are being tracked to evaluate its effectiveness, and estimates of funds needed to ensure its success. Core funding of $180,000 is available annually for a centralized office, the keystone of the model described here. With this funding, the office has (1) addressed recruitment, retention, and quality of educators for UME; (2) promoted innovation in education, evaluation, and research; (3) supported development of a comprehensive curriculum for medical school education; and (4) monitored the effectiveness of community-based education programs by tracking product yield and cost estimates needed to generate these programs. The model's Teaching and Learning Database contains information about more than 1,500 educational placements at 165 ambulatory teaching sites (80% in northern New England) involving 320 active preceptors. The centralized office facilitated 36 site visits, 22% of which were interdisciplinary, involving 122 preceptors. A total of 98 follow-up requests by community-based preceptors were fulfilled in 2000. The current submission-to-funding ratio for educational grants is 56%. Costs per educational activity have ranged from $811.50 to $1,938, with costs per preceptor ranging from $101.40 to $217.82. Cost per product (grants, manuscripts, presentations) in research and academic scholarship activities was $2,492. The model allows the medical school to balance institutional and departmental support for its educational programs, and to better position

  10. Improving biological understanding and complex trait prediction by integrating prior information in genomic feature models

    DEFF Research Database (Denmark)

    Edwards, Stefan McKinnon

    externally founded information, such as KEGG pathways, Gene Ontology gene sets, or genomic features, and estimate the joint contribution of the genetic variants within these sets to complex trait phenotypes. The analysis of complex trait phenotypes is hampered by the myriad of genes that control the trait......In this thesis we investigate an approach to integrate external data into the analysis of genetic variants. The goal is similar to that of gene-set enrichment tests, but relies on the robust statistical framework of linear mixed models. This approach has allowed us to integrate virtually any......, as these genes have small to moderate effects that can be difficult to detect. However, by looking at sets of genes, as in gene-set enrichment tests, it may become easier to assess an association between the set of genes and the complex trait. ---  The linear mixed models applied here are the same as used...

  11. 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 currently used for metabolic engineering and elucidating biological interactions. Here we review the history of yeast's GEMs, focusing on recent developments. We study how these models are typically evaluated, using both descriptive and predictive metrics. Additionally, we analyze the different ways...... 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....

  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. 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

  14. Genome sequencing and comparative transcriptomics of the model entomopathogenic fungi Metarhizium anisopliae and M. acridum.

    Science.gov (United States)

    Gao, Qiang; Jin, Kai; Ying, Sheng-Hua; Zhang, Yongjun; Xiao, Guohua; 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

    2011-01-06

    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 heterogeneous 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 with

  15. A model for carbohydrate metabolism in the diatom Phaeodactylum tricornutum deduced from comparative whole genome analysis.

    Directory of Open Access Journals (Sweden)

    Peter G Kroth

    Full Text Available BACKGROUND: Diatoms are unicellular algae responsible for approximately 20% of global carbon fixation. Their evolution by secondary endocytobiosis resulted in a complex cellular structure and metabolism compared to algae with primary plastids. METHODOLOGY/PRINCIPAL FINDINGS: The whole genome sequence of the diatom Phaeodactylum tricornutum has recently been completed. We identified and annotated genes for enzymes involved in carbohydrate pathways based on extensive EST support and comparison to the whole genome sequence of a second diatom, Thalassiosira pseudonana. Protein localization to mitochondria was predicted based on identified similarities to mitochondrial localization motifs in other eukaryotes, whereas protein localization to plastids was based on the presence of signal peptide motifs in combination with plastid localization motifs previously shown to be required in diatoms. We identified genes potentially involved in a C4-like photosynthesis in P. tricornutum and, on the basis of sequence-based putative localization of relevant proteins, discuss possible differences in carbon concentrating mechanisms and CO(2 fixation between the two diatoms. We also identified genes encoding enzymes involved in photorespiration with one interesting exception: glycerate kinase was not found in either P. tricornutum or T. pseudonana. Various Calvin cycle enzymes were found in up to five different isoforms, distributed between plastids, mitochondria and the cytosol. Diatoms store energy either as lipids or as chrysolaminaran (a beta-1,3-glucan outside of the plastids. We identified various beta-glucanases and large membrane-bound glucan synthases. Interestingly most of the glucanases appear to contain C-terminal anchor domains that may attach the enzymes to membranes. CONCLUSIONS/SIGNIFICANCE: Here we present a detailed synthesis of carbohydrate metabolism in diatoms based on the genome sequences of Thalassiosira pseudonana and Phaeodactylum tricornutum

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

    Science.gov (United States)

    Vital-Lopez, Francisco G; Reifman, Jaques; Wallqvist, Anders

    2015-10-01

    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 cells. Developing treatments against biofilms requires an understanding of bacterial biofilm-specific physiological traits. Research efforts have started to elucidate the intricate mechanisms underlying biofilm development. However, many aspects of these mechanisms are still poorly understood. Here, we addressed questions regarding biofilm metabolism using a genome-scale kinetic model of the P. aeruginosa metabolic network and gene expression profiles. Specifically, we computed metabolite concentration differences between known mutants with altered biofilm formation and the wild-type strain to predict drug targets against P. aeruginosa biofilms. We also simulated the altered metabolism driven by gene expression changes between biofilm and stationary growth-phase planktonic cultures. Our analysis suggests that the synthesis of important biofilm-related molecules, such as the quorum-sensing molecule Pseudomonas quinolone signal and the exopolysaccharide Psl, is regulated not only through the expression of genes in their own synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules. Finally, we investigated why mutants defective in anthranilate degradation have an impaired ability to form biofilms. Alternative to a previous hypothesis that this biofilm reduction is caused by a decrease in energy production, we proposed that the dysregulation of the synthesis of secondary metabolites derived from anthranilate and chorismate is what impaired the biofilms of these mutants. Notably, these insights generated through our kinetic model-based approach are not accessible from previous constraint-based model analyses of P. aeruginosa biofilm

  17. Understanding variation in transcription factor binding by modeling transcription factor genome-epigenome interactions.

    Directory of Open Access Journals (Sweden)

    Chieh-Chun Chen

    Full Text Available Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES cells, including DNA methylation (MeDIP-seq and MRE-seq, DNA hydroxymethylation (5-hmC-seq, and histone modifications (ChIP-seq. We discovered correlations of transcription factors (TFs for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFκB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg.

  18. Understanding variation in transcription factor binding by modeling transcription factor genome-epigenome interactions.

    Science.gov (United States)

    Chen, Chieh-Chun; Xiao, Shu; Xie, Dan; Cao, Xiaoyi; Song, Chun-Xiao; Wang, Ting; He, Chuan; Zhong, Sheng

    2013-01-01

    Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES) cells, including DNA methylation (MeDIP-seq and MRE-seq), DNA hydroxymethylation (5-hmC-seq), and histone modifications (ChIP-seq). We discovered correlations of transcription factors (TFs) for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq) and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFκB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg).

  19. Integrated genome-scale analysis of the transcriptional regulatory landscape in a blood stem/progenitor cell model.

    Science.gov (United States)

    Wilson, Nicola K; Schoenfelder, Stefan; Hannah, Rebecca; Sánchez Castillo, Manuel; Schütte, Judith; Ladopoulos, Vasileios; Mitchelmore, Joanna; Goode, Debbie K; Calero-Nieto, Fernando J; Moignard, Victoria; Wilkinson, Adam C; Jimenez-Madrid, Isabel; Kinston, Sarah; Spivakov, Mikhail; Fraser, Peter; Göttgens, Berthold

    2016-03-31

    Comprehensive study of transcriptional control processes will be required to enhance our understanding of both normal and malignant hematopoiesis. Modern sequencing technologies have revolutionized our ability to generate genome-scale expression and histone modification profiles, transcription factor (TF)-binding maps, and also comprehensive chromatin-looping information. Many of these technologies, however, require large numbers of cells, and therefore cannot be applied to rare hematopoietic stem/progenitor cell (HSPC) populations. The stem cell factor-dependent multipotent progenitor cell line HPC-7 represents a well-recognized cell line model for HSPCs. Here we report genome-wide maps for 17 TFs, 3 histone modifications, DNase I hypersensitive sites, and high-resolution promoter-enhancer interactomes in HPC-7 cells. Integrated analysis of these complementary data sets revealed TF occupancy patterns of genomic regions involved in promoter-anchored loops. Moreover, preferential associations between pairs of TFs bound at either ends of chromatin loops led to the identification of 4 previously unrecognized protein-protein interactions between key blood stem cell regulators. All HPC-7 data sets are freely available both through standard repositories and a user-friendly Web interface. Together with previously generated genome-wide data sets, this study integrates HPC-7 data into a genomic resource on par with ENCODE tier 1 cell lines and, importantly, is the only current model with comprehensive genome-scale data that is relevant to HSPC biology. © 2016 by The American Society of Hematology.

  20. redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models.

    Science.gov (United States)

    Ataman, Meric; Hernandez Gardiol, Daniel F; Fengos, Georgios; Hatzimanikatis, Vassily

    2017-07-01

    Genome-scale metabolic reconstructions have proven to be valuable resources in enhancing our understanding of metabolic networks as they encapsulate all known metabolic capabilities of the organisms from genes to proteins to their functions. However the complexity of these large metabolic networks often hinders their utility in various practical applications. Although reduced models are commonly used for modeling and in integrating experimental data, they are often inconsistent across different studies and laboratories due to different criteria and detail, which can compromise transferability of the findings and also integration of experimental data from different groups. In this study, we have developed a systematic semi-automatic approach to reduce genome-scale models into core models in a consistent and logical manner focusing on the central metabolism or subsystems of interest. The method minimizes the loss of information using an approach that combines graph-based search and optimization methods. The resulting core models are shown to be able to capture key properties of the genome-scale models and preserve consistency in terms of biomass and by-product yields, flux and concentration variability and gene essentiality. The development of these "consistently-reduced" models will help to clarify and facilitate integration of different experimental data to draw new understanding that can be directly extendable to genome-scale models.

  1. redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models.

    Directory of Open Access Journals (Sweden)

    Meric Ataman

    2017-07-01

    Full Text Available Genome-scale metabolic reconstructions have proven to be valuable resources in enhancing our understanding of metabolic networks as they encapsulate all known metabolic capabilities of the organisms from genes to proteins to their functions. However the complexity of these large metabolic networks often hinders their utility in various practical applications. Although reduced models are commonly used for modeling and in integrating experimental data, they are often inconsistent across different studies and laboratories due to different criteria and detail, which can compromise transferability of the findings and also integration of experimental data from different groups. In this study, we have developed a systematic semi-automatic approach to reduce genome-scale models into core models in a consistent and logical manner focusing on the central metabolism or subsystems of interest. The method minimizes the loss of information using an approach that combines graph-based search and optimization methods. The resulting core models are shown to be able to capture key properties of the genome-scale models and preserve consistency in terms of biomass and by-product yields, flux and concentration variability and gene essentiality. The development of these "consistently-reduced" models will help to clarify and facilitate integration of different experimental data to draw new understanding that can be directly extendable to genome-scale models.

  2. Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function

    Science.gov (United States)

    2017-01-01

    Decades of biochemical, bioinformatic, and sequencing data are currently being systematically compiled into genome-scale metabolic reconstructions (GEMs). Such reconstructions are knowledge-bases useful for engineering, modeling, and comparative analysis. Here we review the fifteen GEMs of archaeal species that have been constructed to date. They represent primarily members of the Euryarchaeota with three-quarters comprising representative of methanogens. Unlike other reviews on GEMs, we specially focus on archaea. We briefly review the GEM construction process and the genealogy of the archaeal models. The major insights gained during the construction of these models are then reviewed with specific focus on novel metabolic pathway predictions and growth characteristics. Metabolic pathway usage is discussed in the context of the composition of each organism's biomass and their specific energy and growth requirements. We show how the metabolic models can be used to study the evolution of metabolism in archaea. Conservation of particular metabolic pathways can be studied by comparing reactions using the genes associated with their enzymes. This demonstrates the utility of GEMs to evolutionary studies, far beyond their original purpose of metabolic modeling; however, much needs to be done before archaeal models are as extensively complete as those for bacteria. PMID:28133437

  3. Etiology matters - Genomic DNA Methylation Patterns in Three Rat Models of Acquired Epilepsy.

    Science.gov (United States)

    Dębski, Konrad J; Pitkanen, Asla; Puhakka, Noora; Bot, Anna M; Khurana, Ishant; Harikrishnan, K N; Ziemann, Mark; Kaspi, Antony; El-Osta, Assam; Lukasiuk, Katarzyna; Kobow, Katja

    2016-05-09

    This study tested the hypothesis that acquired epileptogenesis is accompanied by DNA methylation changes independent of etiology. We investigated DNA methylation and gene expression in the hippocampal CA3/dentate gyrus fields at 3 months following epileptogenic injury in three experimental models of epilepsy: focal amygdala stimulation, systemic pilocarpine injection, or lateral fluid-percussion induced traumatic brain injury (TBI) in rats. In the models studies, DNA methylation and gene expression profiles distinguished controls from injured animals. We observed consistent increased methylation in gene bodies and hypomethylation at non-genic regions. We did not find a common methylation signature in all three different models and few regions common to any two models. Our data provide evidence that genome-wide alteration of DNA methylation signatures is a general pathomechanism associated with epileptogenesis and epilepsy in experimental animal models, but the broad pathophysiological differences between models (i.e. pilocarpine, amygdala stimulation, and post-TBI) are reflected in distinct etiology-dependent DNA methylation patterns.

  4. Etiology matters – Genomic DNA Methylation Patterns in Three Rat Models of Acquired Epilepsy

    Science.gov (United States)

    Dębski, Konrad J.; Pitkanen, Asla; Puhakka, Noora; Bot, Anna M.; Khurana, Ishant; Harikrishnan, KN; Ziemann, Mark; Kaspi, Antony; El-Osta, Assam; Lukasiuk, Katarzyna; Kobow, Katja

    2016-01-01

    This study tested the hypothesis that acquired epileptogenesis is accompanied by DNA methylation changes independent of etiology. We investigated DNA methylation and gene expression in the hippocampal CA3/dentate gyrus fields at 3 months following epileptogenic injury in three experimental models of epilepsy: focal amygdala stimulation, systemic pilocarpine injection, or lateral fluid-percussion induced traumatic brain injury (TBI) in rats. In the models studies, DNA methylation and gene expression profiles distinguished controls from injured animals. We observed consistent increased methylation in gene bodies and hypomethylation at non-genic regions. We did not find a common methylation signature in all three different models and few regions common to any two models. Our data provide evidence that genome-wide alteration of DNA methylation signatures is a general pathomechanism associated with epileptogenesis and epilepsy in experimental animal models, but the broad pathophysiological differences between models (i.e. pilocarpine, amygdala stimulation, and post-TBI) are reflected in distinct etiology-dependent DNA methylation patterns. PMID:27157830

  5. 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.

  6. 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.

  7. A Bayesian hidden Markov model for motif discovery through joint modeling of genomic sequence and ChIP-chip data.

    Science.gov (United States)

    Gelfond, Jonathan A L; Gupta, Mayetri; Ibrahim, Joseph G

    2009-12-01

    We propose a unified framework for the analysis of chromatin (Ch) immunoprecipitation (IP) microarray (ChIP-chip) data for detecting transcription factor binding sites (TFBSs) or motifs. ChIP-chip assays are used to focus the genome-wide search for TFBSs by isolating a sample of DNA fragments with TFBSs and applying this sample to a microarray with probes corresponding to tiled segments across the genome. Present analytical methods use a two-step approach: (i) analyze array data to estimate IP-enrichment peaks then (ii) analyze the corresponding sequences independently of intensity information. The proposed model integrates peak finding and motif discovery through a unified Bayesian hidden Markov model (HMM) framework that accommodates the inherent uncertainty in both measurements. A Markov chain Monte Carlo algorithm is formulated for parameter estimation, adapting recursive techniques used for HMMs. In simulations and applications to a yeast RAP1 dataset, the proposed method has favorable TFBS discovery performance compared to currently available two-stage procedures in terms of both sensitivity and specificity.

  8. 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.

  9. Diagnosis of ulcerative colitis before onset of inflammation by multivariate modeling of genome-wide gene expression data

    DEFF Research Database (Denmark)

    Olsen, Jørgen; Gerds, Thomas A; Seidelin, Jakob B

    2009-01-01

    biopsies from 78 patients were included. A diagnostic model was derived with the random forest method based on 71 biopsies from 60 patients. The model-internal out-of-bag performance measure yielded perfect classification. Furthermore, the model was validated in independent 18 noninflamed biopsies from 18...... of random forest modeling of genome-wide gene expression data for distinguishing quiescent and active UC colonic mucosa versus control and CD colonic mucosa.(Inflamm Bowel Dis 2009)....

  10. Supplementary Educational Models in Canadian Neurosurgery Residency Programs.

    Science.gov (United States)

    Ryu, Won Hyung A; Chan, Sonny; Sutherland, Garnette R

    2017-03-01

    The proposed implementation of work hour restrictions has presented a significant challenge of maintaining the quality of resident education and ensuring adequate hands-on experience that is essential for novice surgeons. To maintain the level of resident surgical competency, revision of the apprentice model of surgical education to include supplementary educational methods, such as laboratory and virtual reality (VR) simulations, have become frequent topics of discussion. We aimed to better understand the role of supplementary educational methods in Canadian neurosurgery residency training. An online survey was sent to program directors of all 14 Canadian neurosurgical residency programs and active resident members of the Canadian Neurosurgical Society (N=85). We asked 16 questions focusing on topics of surgeon perception, current implementation and barriers to supplementary educational models. Of the 99 surveys sent, 8 out of 14 (57%) program directors and 37 out of 85 (44%) residents completed the survey. Of the 14 neurosurgery residency programs across Canada, 7 reported utilizing laboratory-based teaching within their educational plan, while only 3 programs reported using VR simulation as a supplementary teaching method. The biggest barriers to implementing supplementary educational methods were resident availability, lack of resources, and cost. Work-hour restrictions threaten to compromise the traditional apprentice model of surgical training. The potential value of supplementary educational methods for surgical education is evident, as reported by both program directors and residents across Canada. However, availability and utilization of laboratory and VR simulations are limited by numerous factors such as time constrains and lack of resources.

  11. Generation of mouse models of myeloid malignancy with combinatorial genetic lesions using CRISPR-Cas9 genome editing.

    Science.gov (United States)

    Heckl, Dirk; Kowalczyk, Monika S; Yudovich, David; Belizaire, Roger; Puram, Rishi V; McConkey, Marie E; Thielke, Anne; Aster, Jon C; Regev, Aviv; Ebert, Benjamin L

    2014-09-01

    Genome sequencing studies have shown that human malignancies often bear mutations in four or more driver genes, but it is difficult to recapitulate this degree of genetic complexity in mouse models using conventional breeding. Here we use the CRISPR-Cas9 system of genome editing to overcome this limitation. By delivering combinations of small guide RNAs (sgRNAs) and Cas9 with a lentiviral vector, we modified up to five genes in a single mouse hematopoietic stem cell (HSC), leading to clonal outgrowth and myeloid malignancy. We thereby generated models of acute myeloid leukemia (AML) with cooperating mutations in genes encoding epigenetic modifiers, transcription factors and mediators of cytokine signaling, recapitulating the combinations of mutations observed in patients. Our results suggest that lentivirus-delivered sgRNA:Cas9 genome editing should be useful to engineer a broad array of in vivo cancer models that better reflect the complexity of human disease.

  12. 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.

  13. Wavelet thresholding estimation in a Poissonian interactions model with application to genomic data

    CERN Document Server

    Sansonnet, Laure

    2011-01-01

    This paper deals with the study of dependencies between two given events modeled by point processes. In particular, we focus on the context of DNA to detect favored or avoided distances between two given motifs along a genome suggesting possible interactions at a molecular level. For this, we naturally introduce a so-called reproduction function h that allows to quantify the favored positions of the motifs and which is considered as the intensity of a Poisson process. Our first interest is the estimation of this function h assumed to be well localized. The estimator based on random thresholds achieves an oracle inequality. Then, minimax properties of the estimator on Besov balls are established. Some simulations are provided, allowing the calibration of tuning parameters from a numerical point of view and proving the good practical behavior of our procedure. Finally, our method is applied to the analysis of the influence between gene occurrences along the E. coli genome and occurrences of a motif known to be ...

  14. A one-dimensional statistical mechanics model for nucleosome positioning on genomic DNA.

    Science.gov (United States)

    Tesoro, S; Ali, I; Morozov, A N; Sulaiman, N; Marenduzzo, D

    2016-02-12

    The first level of folding of DNA in eukaryotes is provided by the so-called '10 nm chromatin fibre', where DNA wraps around histone proteins (∼10 nm in size) to form nucleosomes, which go on to create a zig-zagging bead-on-a-string structure. In this work we present a one-dimensional statistical mechanics model to study nucleosome positioning within one such 10 nm fibre. We focus on the case of genomic sheep DNA, and we start from effective potentials valid at infinite dilution and determined from high-resolution in vitro salt dialysis experiments. We study positioning within a polynucleosome chain, and compare the results for genomic DNA to that obtained in the simplest case of homogeneous DNA, where the problem can be mapped to a Tonks gas. First, we consider the simple, analytically solvable, case where nucleosomes are assumed to be point-like. Then, we perform numerical simulations to gauge the effect of their finite size on the nucleosomal distribution probabilities. Finally we compare nucleosome distributions and simulated nuclease digestion patterns for the two cases (homogeneous and sheep DNA), thereby providing testable predictions of the effect of sequence on experimentally observable quantities in experiments on polynucleosome chromatin fibres reconstituted in vitro.

  15. 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.

  16. In vivo genome editing improves muscle function in a mouse model of Duchenne muscular dystrophy.

    Science.gov (United States)

    Nelson, Christopher E; Hakim, Chady H; Ousterout, David G; Thakore, Pratiksha I; Moreb, Eirik A; Castellanos Rivera, Ruth M; Madhavan, Sarina; Pan, Xiufang; Ran, F Ann; Yan, Winston X; Asokan, Aravind; Zhang, Feng; Duan, Dongsheng; Gersbach, Charles A

    2016-01-22

    Duchenne muscular dystrophy (DMD) is a devastating disease affecting about 1 out of 5000 male births and caused by mutations in the dystrophin gene. Genome editing has the potential to restore expression of a modified dystrophin gene from the native locus to modulate disease progression. In this study, adeno-associated virus was used to deliver the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system to the mdx mouse model of DMD to remove the mutated exon 23 from the dystrophin gene. This includes local and systemic delivery to adult mice and systemic delivery to neonatal mice. Exon 23 deletion by CRISPR-Cas9 resulted in expression of the modified dystrophin gene, partial recovery of functional dystrophin protein in skeletal myofibers and cardiac muscle, improvement of muscle biochemistry, and significant enhancement of muscle force. This work establishes CRISPR-Cas9-based genome editing as a potential therapy to treat DMD. Copyright © 2016, American Association for the Advancement of Science.

  17. Examination of Self-Determination within the Sport Education Model

    Science.gov (United States)

    Perlman, Dana J.

    2011-01-01

    The purpose of this study was to examine the influence of the Sport Education Model (SEM) on students' self-determined motivation and underlying psychological need(s) in physical education. A total of 182 Year-9 students were engaged in 20 lesson units of volleyball, using either the SEM or a traditional approach. Data was collected using a…

  18. Integrating Art Education Models: Contemporary Controversies in Spain

    Science.gov (United States)

    Belver, Manuel; Ulln, Ana; Acaso, Mara

    2005-01-01

    In this article, a basic controversy for art education in Spain is analysed, and its antecedents in thought and social and artistic practices are reviewed. The controversy refers to the question whether school art education should be oriented towards the fine arts or towards the manual arts. Consequently, which should be the cultural model of…

  19. Improving Teaching and Learning: Three Models to Reshape Educational Practice

    Science.gov (United States)

    Roberson, Sam

    2014-01-01

    The work of schools is teaching and learning. However, the current educational culture is dominated by three characteristics: (1) the mechanistic view of organization and its practice based on the assembly line model where students progress along a value added conveyor; (2) the predominance of the Essentialist philosophy of education, in which the…

  20. 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…

  1. 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)…

  2. 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…

  3. 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)…

  4. In Search of the Nordic Model in Education

    Science.gov (United States)

    Antikainen, Ari

    2006-01-01

    The Nordic model of education is defined in this article as an attempt to construct a national education system on the foundation of specific local values and practices, but at the same time subject to international influences. According to the author, equity, participation, and welfare are the major goals and the publicly funded comprehensive…

  5. Implications of the Hospitalist Model for Medical Students' Education.

    Science.gov (United States)

    Hauer, Karen E.; Wachter, Robert M.

    2001-01-01

    Proposes a research agenda to investigate the educational impact for medical students of the hospitalist model, suggests strategies to mitigate the limitations in students' exposures to subspecialty faculty, and recommends professional development in teaching for hospitalists to ensure that student education thrives in this new environment of…

  6. A MODEL INFORMATION SYSTEM FOR THE ADULT EDUCATION PROFESSION.

    Science.gov (United States)

    DECROW, ROGER

    A MODEL OF INFORMATION SERVICES FOR THE ADULT EDUCATION PROFESSION PROVIDES FOR--(1) ACCESS TO THE LITERATURE THROUGH BIBLIOGRAPHIES, REVIEWS, AND MECHANIZED RETRIEVAL, (2) PHYSICAL ACCESS (MAINLY IN MICROFORM), (3) SPECIALIZED INFORMATION SERVICES LINKED WITH ONE ANOTHER AND THE ERIC CLEARINGHOUSE ON ADULT EDUCATION, (4) COORDINATION, RESEARCH,…

  7. 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

  8. Integration of Multiple Genomic Data Sources in a Bayesian Cox Model for Variable Selection and Prediction.

    Science.gov (United States)

    Treppmann, Tabea; Ickstadt, Katja; Zucknick, Manuela

    2017-01-01

    Bayesian variable selection becomes more and more important in statistical analyses, in particular when performing variable selection in high dimensions. For survival time models and in the presence of genomic data, the state of the art is still quite unexploited. One of the more recent approaches suggests a Bayesian semiparametric proportional hazards model for right censored time-to-event data. We extend this model to directly include variable selection, based on a stochastic search procedure within a Markov chain Monte Carlo sampler for inference. This equips us with an intuitive and flexible approach and provides a way for integrating additional data sources and further extensions. We make use of the possibility of implementing parallel tempering to help improve the mixing of the Markov chains. In our examples, we use this Bayesian approach to integrate copy number variation data into a gene-expression-based survival prediction model. This is achieved by formulating an informed prior based on copy number variation. We perform a simulation study to investigate the model's behavior and prediction performance in different situations before applying it to a dataset of glioblastoma patients and evaluating the biological relevance of the findings.

  9. Genome assembly and annotation ofArabidopsis halleri, a model for heavy metal hyperaccumulation and evolutionary ecology

    OpenAIRE

    Briskine, Roman V; Paape, Timothy; Shimizu-Inatsugi, Rie; Nishiyama, Tomoaki; Akama, Satoru; Sese, Jun; Kentaro K. Shimizu

    2016-01-01

    The self-incompatible species Arabidopsis halleri is a close relative of the self-compatible model plant Arabidopsis thaliana. The broad European and Asian distribution and heavy metal hyperaccumulation ability makes A. halleri a useful model for ecological genomics studies.We used long-insert mate-pair libraries to improve the genome assembly of the A. halleri ssp.gemmifera Tada mine genotype (W302) collected from a site with high contamination by heavy metals in Japan. After five rounds of ...

  10. 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.

  11. An educational model for ensemble streamflow simulation and uncertainty analysis

    National Research Council Canada - National Science Library

    AghaKouchak, A; Nakhjiri, N; Habib, E

    2013-01-01

    ...) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity...

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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…

  17. Learning to teach mathematical modelling in secondary and tertiary education

    Science.gov (United States)

    Ferri, Rita Borromeo

    2017-07-01

    Since 2003 mathematical modelling in Germany is not only a topic for scientific disciplines in university mathematics courses, but also in school starting with primary school. This paper shows what mathematical modelling means in school and how it can be taught as a basis for complex modeling problems in tertiary education.

  18. The Meaning of Role Modelling in Moral and Character Education

    Science.gov (United States)

    Sanderse, Wouter

    2013-01-01

    Character education considers teachers to be role models, but it is unclear what this means in practice. Do teachers model admirable character traits? And do they do so effectively? In this article the relevant pedagogical and psychological literature is reviewed in order to shed light on these questions. First, the use of role modelling as a…

  19. Deriving Genomic Breeding Values for Residual Feed Intake from Covariance Functions of Random Regression Models

    DEFF Research Database (Denmark)

    Strathe, Anders B; Mark, Thomas; Nielsen, Bjarne

    . Based on covariance functions, residual feed intake (RFI) was defined and derived as the conditional genetic variance in feed intake given mid-test breeding value for BW and rate of gain. The heritability of RFI over the entire period was 0.36, but more interestingly, the genetic variance of RFI was 6......Random regression models were used to estimate covariance functions between cumulated feed intake (CFI) and body weight (BW) in 8424 Danish Duroc pigs. Random regressions on second order Legendre polynomials of age were used to describe genetic and permanent environmental curves in BW and CFI......% of the genetic variance in feed intake, revealing that a minor component of feed intake was genetically independent of maintenance and growth. In conclusion, the approach derived herein led to a consistent definition of RFI, where genomic breeding values were easily obtained...

  20. A model of health education and management for osteoporosis prevention

    OpenAIRE

    Wang, Liang; Xu, Xiaowen; Hao, Hongxia; Chen, Liying; Su, Tianjiao; Zhang, Yan; Ma, Weifeng; XIE, YUANYUAN; Wang, Tiantian; Yang, Fan; He, Li; Wang, Wenjiao; Fu, Xuemei; Ma, Yuanzheng

    2016-01-01

    Osteoporosis, a chronic disease with no therapeutic cure, affects a growing number of people as the aging population in China rapidly increases. Therefore, developing an evidence-based model of health education and management for osteoporosis prevention is required. In the present study, an osteoporosis club was established, which is a novel model of health education and management for osteoporosis prevention. A unified management of membership was used based on a digitized database. A total ...

  1. Teaching Incision and Drainage: Perceived Educational Value of Abscess Models.

    Science.gov (United States)

    Adams, Cynthia M; Nigrovic, Lise E; Hayes, Gavin; Weinstock, Peter H; Nagler, Joshua

    2017-07-17

    Incision and drainage (I&D) of skin abscesses is an important procedural skill for pediatric emergency medicine providers. Practical skills training using simulation provides an opportunity to learn and gain confidence with this invasive procedure. Our objective was to assess the perceived educational value of 2 versions of an abscess model as part of an educational workshop for teaching I&D. A combined didactic and practical skills workshop was developed for use at 2 national conferences. The didactic content was created through an iterative process. To facilitate hands-on training, 2 versions of an abscess model were created: 1 constructed from a negative mold and the other using a 3-dimensional printer. Participants were surveyed regarding prior experience with I&D, procedural confidence, and perceptions of the educational utility of the models. Seventy physicians and 75 nurse practitioners participated in the study. Procedural confidence improved after training using each version of the model, with the greatest improvements noted among novice learners. Ninety-four percent of physicians, and 99% of nurse practitioners rated the respective models as either "educational" or "very educational," and 97% and 100%, respectively, would recommend the abscess models to others. A combined didactic and practical skills educational workshop using novel abscess models was effective at improving learners' confidence. Our novel models provide an effective strategy for teaching procedural skills such as I&D and demonstrate a novel use of 3-dimensional printers in medical education. Further study is needed to determine if these educational gains translate into improvement in clinical performance or patient outcomes.

  2. Implementability of Instructional Supervision as a Contemporary Educational Supervision Model in Turkish Education System

    OpenAIRE

    2012-01-01

    In this study, implementability of instructional supervision as one of contemporary educational supervision models in Turkish Education System was evaluated. Instructional supervision which aims to develop instructional processes and increase the quality of student learning based on observation of classroom activities requires collaboration among supervisors and teachers. In this literature review, significant problems have been detected due to structural organization, structural and control-...

  3. Effective civic education : an educational effectiveness model for explaining students' civic knowledge

    NARCIS (Netherlands)

    Isac, Maria Magdalena; Maslowski, Ralf; van der Werf, Greetje

    2011-01-01

    In this study, a comprehensive educational effectiveness model is tested in relation to student's civic knowledge. Multilevel analysis was applied on the dataset of the IEA Civic Education Study (CIVED; Torney-Purta, Lehmann, Oswald, & Schulz, 2001), which was conducted among junior secondary-school

  4. Educational Transformation in Upper-Division Physics: The Science Education Initiative Model, Outcomes, and Lessons Learned

    Science.gov (United States)

    Chasteen, Stephanie V.; Wilcox, Bethany; Caballero, Marcos D.; Perkins, Katherine K.; Pollock, Steven J.; Wieman, Carl E.

    2015-01-01

    In response to the need for a scalable, institutionally supported model of educational change, the Science Education Initiative (SEI) was created as an experiment in transforming course materials and faculty practices at two institutions--University of Colorado Boulder (CU) and University of British Columbia. We find that this departmentally…

  5. Effective Civic Education: An Educational Effectiveness Model for Explaining Students' Civic Knowledge

    Science.gov (United States)

    Isac, Maria Magdalena; Maslowski, Ralf; van der Werf, Greetje

    2011-01-01

    In this study, a comprehensive educational effectiveness model is tested in relation to student's civic knowledge. Multilevel analysis was applied on the dataset of the IEA Civic Education Study (CIVED; Torney-Purta, Lehmann, Oswald, & Schulz, 2001), which was conducted among junior secondary-school students (age 14), their schools, and their…

  6. The copepod Tigriopus: a promising marine model organism for ecotoxicology and environmental genomics.

    Science.gov (United States)

    Raisuddin, Sheikh; Kwok, Kevin W H; Leung, Kenneth M Y; Schlenk, Daniel; Lee, Jae-Seong

    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, 5,673 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. 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

  8. Expanding a dynamic flux balance model of yeast fermentation to genome-scale

    Directory of Open Access Journals (Sweden)

    Agosin Eduardo

    2011-05-01

    Full Text Available Abstract 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.

  9. MapMaker and PathTracer for tracking carbon in genome-scale metabolic models.

    Science.gov (United States)

    Tervo, Christopher J; Reed, Jennifer L

    2016-05-01

    Constraint-based reconstruction and analysis (COBRA) modeling results can be difficult to interpret given the large numbers of reactions in genome-scale models. While paths in metabolic networks can be found, existing methods are not easily combined with constraint-based approaches. To address this limitation, two tools (MapMaker and PathTracer) were developed to find paths (including cycles) between metabolites, where each step transfers carbon from reactant to product. MapMaker predicts carbon transfer maps (CTMs) between metabolites using only information on molecular formulae and reaction stoichiometry, effectively determining which reactants and products share carbon atoms. MapMaker correctly assigned CTMs for over 97% of the 2,251 reactions in an Escherichia coli metabolic model (iJO1366). Using CTMs as inputs, PathTracer finds paths between two metabolites. PathTracer was applied to iJO1366 to investigate the importance of using CTMs and COBRA constraints when enumerating paths, to find active and high flux paths in flux balance analysis (FBA) solutions, to identify paths for putrescine utilization, and to elucidate a potential CO2 fixation pathway in E. coli. These results illustrate how MapMaker and PathTracer can be used in combination with constraint-based models to identify feasible, active, and high flux paths between metabolites.

  10. To know or not to know? Integrating ethical aspects of genomic healthcare in the education of health professionals.

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    Eriksen, Kathrine Krageskov

    2015-01-01

    Novel possibilities for employing genetic testing as part of the diagnostic process for a wide variety of diseases and conditions are emerging almost every day. This development brings prospects of more efficient treatment and prevention of serious and often lethal conditions. However, it also raises ethical questions concerning the issue of knowing or not knowing about our genetic make-up. Thus, as techniques for genetic testing are increasingly employed, demands on health professionals are changing. Health professionals must be able to inform and guide patients, and therefore they need knowledge and competencies related to both the technical and the ethical dimensions of genetic testing. This paper explores the requirements of the general education of health professionals if this need for ethics is acknowledged. It is suggested that it is important to include both an individualised and a societal ethical perspective to the development of genomic healthcare and that a key concept in doing so is 'professional reflectivity'. Employing one concrete example of teaching, this concept of reflectivity is operationalised in the health educational setting at the bachelor's level with a special focus on biomedical laboratory science, and three key concepts are developed: Gap sensitive interaction, professional humility, and contextual awareness. Additionally, anchored ethical dialog is explored as an instructional design that may support the development of reflectivity among health professionals. © 2015 The International Union of Biochemistry and Molecular Biology.

  11. 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.

  12. 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.

  13. A 'joint venture' model of recontacting in clinical genomics: challenges for responsible implementation.

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    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.

  14. Enhancer identification in mouse embryonic stem cells using integrative modeling of chromatin and genomic features

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    Chen Chih-yu

    2012-04-01

    Full Text Available Abstract Background Epigenetic modifications, transcription factor (TF availability and differences in chromatin folding influence how the genome is interpreted by the transcriptional machinery responsible for gene expression. Enhancers buried in non-coding regions are found to be associated with significant differences in histone marks between different cell types. In contrast, gene promoters show more uniform modifications across cell types. Here we used histone modification and chromatin-associated protein ChIP-Seq data sets in mouse embryonic stem (ES cells as well as genomic features to identify functional enhancer regions. Using co-bound sites of OCT4, SOX2 and NANOG (co-OSN, validated enhancers and co-bound sites of MYC and MYCN (limited enhancer activity as enhancer positive and negative training sets, we performed multinomial logistic regression with LASSO regularization to identify key features. Results Cross validations reveal that a combination of p300, H3K4me1, MED12 and NIPBL features to be top signatures of co-OSN regions. Using a model from 10 signatures, 83% of top 1277 putative 1 kb enhancer regions (probability greater than or equal to 0.8 overlapped with at least one TF peak from 7 mouse ES cell ChIP-Seq data sets. These putative enhancers are associated with increased gene expression of neighbouring genes and significantly enriched in multiple TF bound loci in agreement with combinatorial models of TF binding. Furthermore, we identified several motifs of known TFs significantly enriched in putative enhancer regions compared to random promoter regions and background. Comparison with an active H3K27ac mark in various cell types confirmed cell type-specificity of these enhancers. Conclusions The top enhancer signatures we identified (p300, H3K4me1, MED12 and NIPBL will allow for the identification of cell type-specific enhancer regions in diverse cell types.

  15. BOLOGNA MODEL OF MEDICAL EDUCATION-UTOPIA OR REALITY.

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    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. Success stories in genomic medicine from resource-limited countries.

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    Mitropoulos, Konstantinos; Al Jaibeji, Hayat; Forero, Diego A; Laissue, Paul; Wonkam, Ambroise; Lopez-Correa, Catalina; Mohamed, Zahurin; Chantratita, Wasun; Lee, Ming Ta Michael; Llerena, Adrian; Brand, Angela; Ali, Bassam R; Patrinos, George P

    2015-06-18

    In recent years, the translation of genomic discoveries into mainstream medical practice and public health has gained momentum, facilitated by the advent of new technologies. However, there are often major discrepancies in the pace of implementation of genomic medicine between developed and developing/resource-limited countries. The main reason does not only lie in the limitation of resources but also in the slow pace of adoption of the new findings and the poor understanding of the potential that this new discipline offers to rationalize medical diagnosis and treatment. Here, we present and critically discuss examples from the successful implementation of genomic medicine in resource-limited countries, focusing on pharmacogenomics, genome informatics, and public health genomics, emphasizing in the latter case genomic education, stakeholder analysis, and economics in pharmacogenomics. These examples can be considered as model cases and be readily replicated for the wide implementation of pharmacogenomics and genomic medicine in other resource-limited environments.

  17. 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 con

  18. Modelling Mathematical Reasoning in Physics Education

    Science.gov (United States)

    Uhden, Olaf; Karam, Ricardo; Pietrocola, Mauricio; Pospiech, Gesche

    2012-01-01

    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…

  19. Alternative Models for Training Developers in Education.

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    Stowe, Richard A.

    Three steps may be taken to minimize the difficulties involved in educational development: 1) a realistic expectation should be projected in regard to the prowess of development; 2) the "state-of-the-art" should receive continuous improvement; and 3) training programs to prepare fully professional developers should be established as rapidly as…

  20. Modeling Academic Education Processes by Dynamic Storyboarding

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    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…