WorldWideScience

Sample records for premier genetic model

  1. Premier's imaging IR limb sounder

    Science.gov (United States)

    Kraft, Stefan; Bézy, Jean-Loup; Meynart, Roland; Langen, Jörg; Carnicero Dominguez, Bernardo; Bensi, Paolo; Silvestrin, Pierluigi

    2017-11-01

    The Imaging IR Limb Sounder (IRLS) is one of the two instruments planned on board of the candidate Earth Explorer Core Mission PREMIER. PREMIER stands for PRocess Exploration through Measurements of Infrared and Millimetre-wave Emitted Radiation. PREMIER went recently through the process of a feasibility study (Phase A) within the Earth Observation Envelope Program. Emerging from recent advanced instrument technologies IRLS shall, next to a millimetre-wave limb sounder (called STEAMR), explore the benefits of three-dimensional limb sounding with embedded cloud imaging capability. Such 3D imaging technology is expected to open a new era of limb sounding that will allow detailed studies of the link between atmospheric composition and climate, since it will map simultaneously fields of temperature and many trace gases in the mid/upper troposphere and stratosphere across a large vertical and horizontal field of view and with high vertical and horizontal resolution. PREMIER shall fly in a tandem formation looking backwards to METOP's swath and thereby improve meteorological and environmental analyses.

  2. Premier Wen hails sci-tech cooperation with CERN

    CERN Multimedia

    2004-01-01

    Premier Wen Jiabao met CERN's director general Dr Robert Aymar and physicist and Nobel laureate Dr Samuel Chao Chung Ting. Premier Wen emphasied the importance for China to collaborate on fundamental science (0.5 page)

  3. Premier Hospital Historical Data

    Data.gov (United States)

    U.S. Department of Health & Human Services — To provide a historical overview of the participating hospitals, before the first project report, Premier Healthcare Informatics has used data already available for...

  4. Mastering Adobe Premiere Pro CS6

    CERN Document Server

    Ekert, Paul

    2013-01-01

    Designed to be practical and engaging, Mastering Adobe Premiere Pro CS6 is a project-based book to help you truly augment your skills and become a film editing hotshot.If you're just starting out or even migrating from existing video editing software, then this book is for you. With rapid progression through practical examples constructed to be both engaging and useful, Mastering Adobe Premiere Pro CS6 is ideal for learning the sometimes complex workflows of this powerful application.

  5. Management and marketing of sporting events: Nike Premier Cup Project

    OpenAIRE

    Nedbal, Jakub

    2008-01-01

    Title: Management and marketing ofsporting events: Nike Premier Cup project Points of thesis: Publish the Nike Premier Cup promotion campaign project and point out improvement possibilities for upcoming years based on analysis ofpast and present state. Methods: Data will be obtained by interview, observation, description analysis and SWOT analysis Results: Promotion campaign, improvement possibilities, final day schedule Keywords: SWOT analysis, promotion, management, marketing, Nike Premier ...

  6. The long-term effect of premier pay for performance on patient outcomes.

    Science.gov (United States)

    Jha, Ashish K; Joynt, Karen E; Orav, E John; Epstein, Arnold M

    2012-04-26

    found no evidence that the largest hospital-based pay-for-performance program led to a decrease in 30-day mortality. Expectations of improved outcomes for programs modeled after Premier HQID should therefore remain modest.

  7. Policy Advice to Alberta’s New Premier

    Directory of Open Access Journals (Sweden)

    Jack M. Mintz

    2014-09-01

    Full Text Available On September 6th, 2014, members of the Progressive Conservative Party of Alberta elected Jim Prentice as leader of their party, and Premier of Alberta. The School of Public Policy assembled its key thinkers in economic, taxation, energy and natural resource policy to provide unsolicited but important advice to Premier Prentice on some areas of policy that matter most to Alberta, and that will demand the Premier’s attention as he takes office. These are opinion pieces, are not peer reviewed, and reflect the views of their authors alone.

  8. Rapsodie first core manufacture. 1. part: processing plant; Fabrication du premier coeur de rapsodie. Premiere partie: l'atelier de fabrication

    Energy Technology Data Exchange (ETDEWEB)

    Masselot, Y; Bataller, S; Ganivet, M; Guillet, H; Robillard, A; Stosskopf, F [Commissariat a l' Energie Atomique, Cadarache (France). Centre d' Etudes Nucleaires

    1968-07-01

    This report is the first in a series of three describing the processes, results and peculiar technical problems related to the manufacture of the first core of the fast reactor Rapsodie. A detailed study of manufacturing processes(pellets, pins, fissile sub-assemblies), the associated testings (raw materials, processed pellets and pins, sub-assemblies before delivery), manufacturing facilities and improvements for a second campaign are described. (author) [French] Ce rapport est le premier d'une serie de trois qui decrivent les procedes, les resultats et les problemes techniques particuliers de la fabrication du du premier coeur de la pile a neutrons rapides Rapsodie. Il comporte une etude detaillee des procedes de fabrication (pastilles, aiguilles, assemblages combustibles) et des methodes de controle associees (matieres premieres, pastilles et aiguilles en cours de fabrication, assemblages fissiles avant livraison), ainsi qu'une decription complete des installations de l'atelier de fabrication et les modifications apportees pour une deuxieme campagne. (auteur)

  9. High-intensity running in English FA Premier League soccer matches

    DEFF Research Database (Denmark)

    Bradley, Paul S.; Sheldon, William; Wooster, Blake

    2009-01-01

    The aims of this study were to (1) determine the activity profiles of a large sample of English FA Premier League soccer players and (2) examine high-intensity running during elite-standard soccer matches for players in various playing positions. Twenty-eight English FA Premier League games were...

  10. The Role of Internet in Marketing Premiering Movies

    OpenAIRE

    Tuohimaa, Suvi

    2010-01-01

    The objective of this thesis was to find out about the role of Internet today in premiering movie marketing and whether Internet is a good tool for it. The hope was to obtain new information provided by moviegoers and to contribute something useful to the art of marketing premiering movies. This thesis was a part of the School of Business and Information Management's Innomajakka-project but did not have an official commissioner, so the topic for the thesis came from the writer's personal and ...

  11. Market size and attendance in English Premier League football

    OpenAIRE

    Buraimo, B; Simmons, R

    2006-01-01

    This paper models the impacts of market size and team competition for fan base on matchday attendance in the English Premier League over the period 1997-2004 using a large panel data set. We construct a comprehensive set of control variables and use tobit estimation to overcome the problems caused by sell-out crowds. We also account for unobserved influences on attendance by means of random effects attached to home teams. Our treatment of market size, with its use of Geographical Information ...

  12. First experiments results about the engineering model of Rapsodie; Premiers resultats d'essais interessant le bloc pile de rapsodie

    Energy Technology Data Exchange (ETDEWEB)

    Chalot, A; Ginier, R; Sauvage, M [Association Euratom-CEA Cadarache (France). Centre d' Etudes Nucleaires

    1964-07-01

    This report deals with the first series of experiments carried out on the engineering model of Rapsodie and on an associated sodium facility set in a laboratory hall of Cadarache. It conveys more precisely: 1/ - The difficulties encountered during the erection and assembly of the engineering model and a compilation of the results of the first series of experiments and tests carried out on this installation (loading of the subassemblies preheating, thermal chocks...). 2/ - The experiments and tests carried out on the two prototypes control rod drive mechanisms which brought to the choice for the design of the definitive drive mechanism. As a whole, the results proved the validity of the general design principles adopted for Rapsodie. (authors) [French] Ce rapport traite des premiers essais realises sur la maquette du bloc pile de Rapsodie et sur une installation annexe de sodium, implantees dans un hall d'essais de Cadarache. Il fait part: 1/- Des difficultes eprouvees lors du montage de la maquette et rassemble les resultats des premiers essais effectues sur cette installation (chargement des assemblages, prechauffage, chocs thermiques...). 2/- Des essais realises sur deux prototypes de mecanisme de barre de controle qui ont conduit a la conception du mecanisme definitif. L'ensemble des resultats obtenus a permis de confirmer la validite des principes adoptes pour la pile Rapsodie. (auteurs)

  13. Echographie devant une metrorragie du premier trimestre de ...

    African Journals Online (AJOL)

    Echographie devant une metrorragie du premier trimestre de grossesse sur uterus bicorne a issue favorable. Vaginal bleeding in a pregnant woman with a bicornuate uterus, ultrasound finding and favourable outcome.

  14. QUALITY OF NURSING WORK LIFE IMPROVEMENT MODEL TO DECREASE NURSE INTENTION TO QUIT IN PREMIER SURABAYA HOSPITAL

    Directory of Open Access Journals (Sweden)

    Jany Prihastuty

    2017-04-01

    Full Text Available Introduction: Quality of Nursing Work Life (QNWL is a thing that needs attention by human resource management approach. The purpose of this research was to provide develop model to increase QNWL in order to lower nurse’s intention to quit the Premier Hospital Surabaya. Methods: Design used in the structure was explanatory research. The independent variables was Internal factors (Individual factors, social and environment conceptual factors, operational factors, administrative factors where as the dependent variable from this study was intention to quit, and moderator variables QNWL random sampling technique. Total sample was 160 nurses, taken according to inclusion criteria. The research was conducted in Premier Hospital Surabaya from October 2012 - July 2013. Data were collected by using structured questionnaire. Data were then analyzed by using multiple linear regression test with level of significance of ≤ 0.05. Result: The results showed, QNWL was influenced by relationships inter-professional part of variabel social and environment conceptual factors, supervision monitoring part of variabel operational factors, career development part of variabel administrative factors. Intention to quit influenced by relationships between nurses, inter-departmental and inter-professional part of variabel social and environment conceptual factors and salaries and benefits part of variabel administrative factors with significant value p = 0.005. Discussion: It can be concluded good inter-professional relation, supervision monitoring, and good career development affected QNWL. Good relationships between nurses, inter-departmental and inter- professional led to lower intention to quit. Low salary and benefits led nurse’s intention to quit getting stronger.

  15. How to Revise, and Revise Really Well, for Premier Academic Journals

    DEFF Research Database (Denmark)

    LaPlaca, Peter J.; Lindgreen, Adam; Vanhamme, Joelle

    2018-01-01

    Most of the premier academic journals in all fields routinely have rejection rates of 80%, 95%, or higher. All journals prefer articles that make significant contributions to the field. Revising a manuscript and responding properly to the comments of reviewers and editors often is challenging....... This article discusses how to revise effectively a manuscript according to the (minor or major) comments of reviewers and editors for premier academic journals. We provide a series of tips for helping the authors in their endeavor, making the process less arduous and improving the possibility of a positive...

  16. Scottish Premier League Reading Stars Evaluation Report

    Science.gov (United States)

    National Literacy Trust, 2009

    2009-01-01

    Scottish Premier League (SPL) Reading Stars uses the motivational power of football to attract families who need support with literacy into a positive and friendly learning environment. It ran for the first time between March and August 2009 and attracted 225 children and 190 adults to take part in a series of inspirational learning sessions in 23…

  17. Open Access Publishing in Indian Premier Research Institutions

    Science.gov (United States)

    Bhat, Mohammad Hanief

    2009-01-01

    Introduction: Publishing research findings in open access journals is a means of enhancing visibility and consequently increasing the impact of publications. This study provides an overview of open access publishing in premier research institutes of India. Method: The publication output of each institution from 2003 to 2007 was ascertained through…

  18. Logistique de transport pour le projet LHC enseignements des premiers secteurs

    CERN Document Server

    Prodon, S

    2003-01-01

    Ce papier dresse un premier bilan de la logistique de transport mise en place pour l'installation du LHC. Les moyens de planification mis en oeuvre seront tout d'abord évoqués avec notamment les réunions avec les groupes utilisateurs, l'élaboration de procédures de transport, la génération de listings d'articles à transporter ou encore l'établissement d'un planning des ressources. Cependant, les premiers travaux d'installation du LHC ont fait apparaître des divergences importantes entre le planning logistique établi et la réalité du terrain. Ces écarts seront analysés, qu'il s'agisse de différences sur le volume de matériel à acheminer, d'opérations non planifiées, de changements de plannings entraînant de longues et délicates traversées de chantiers ou de manque de planification des besoins en personnel dans certaines zones. Tous ces enseignements acquis au cours des premiers travaux devraient permettre de dégager des voies d'amélioration à mettre en place pour les prochains secteur...

  19. Physiological response of one of South Africa's premier freshwater ...

    African Journals Online (AJOL)

    Physiological response of one of South Africa's premier freshwater sport angling species, the Orange-Vaal smallmouth yellowfish Labeobarbus aeneus, ... These data suggest that catch-and-release causes physiological stress to fish, but nonetheless this practice can be a valuable fisheries management tool to ensure the ...

  20. ABOUT THE SMART SPORTS DEVELOPMENT. EVIDENCE FROM THE UK PREMIERE LEAGUE

    Directory of Open Access Journals (Sweden)

    Vlad Ionut Dumitrache

    2016-11-01

    Full Text Available Smart economy implies the development of key factors like global economy growth, competition, economic progress, economic prosperity, innovation. In the European top-level football, like the case of the British Premier League, financial indicators have demonstrated that the factors that define smart economy can be identified. The new rules of the financial fair-play policies and the ever growing revenues for television rights have created a new market in sports economy, one that identifies itself with the criteria identifies in studies regarding smart economy. This paper comparatively examines the determinants of four indicators of the football team quality in the British Premier League, in order to find out whether a common set of potential determinants could be effective in improving all four indicators of quality, without worsening any of them. This allows finding what measures undertaken at the level of football teams could raise the football team quality. Considering the subjective and multidimensional nature of the football team quality, we first propose four indicators that might be appropriate to define this latent summative measure. Then we select a number of four potentially common determinants of the football team quality, and finally discuss the empirical results, based on panel generalized least squares regression models. The television broadcasting rights are found to be the most important determinant of the football team quality.

  1. Premiere toob lavale jalgpallimeeskonna, inimkatsed ja punase tooli / Kairi Prints

    Index Scriptorium Estoniae

    Prints, Kairi, 1977-

    2012-01-01

    Premiere 2012 osalevad neli Eesti tantsukunstnikku: Svetlana Grigorjeva tantsulavastusega "sõp rus est", Kaisa Selde, Kristina-Maria Heinsalu ja Christin Lunts tantsulavastusega "fie", esmakordselt võtab osa välismaalane - sakslanna Mareike Franz tantsulavastusega "Duett". Kõik esietenduvad 9. veebruaril Kanuti gildi saalis

  2. The impact of dermatology in premier medicine journals.

    Science.gov (United States)

    Kheterpal, Meenal K; Ellis, Charles N

    2011-01-01

    In the past 15 years, research in dermatology has significantly increased. Dermatology-related contributions in premier medical journals such as The New England Journal of Medicine (NEJM) and The Journal of the American Medical Association (JAMA) are the representation of our field in the medical world. To analyze this representation, incidence of dermatology-related contributions in NEJM and JAMA during 3 separate years (during a 15-year period) was calculated.

  3. Trichoberoard gastrique : Premier cas observe en milieu bur kina be ...

    African Journals Online (AJOL)

    Le trichobezoard est une concretion de cheveux, de poils ou de fibres de tapis et de debris alimentaire, localisee habituellement dans l'estomac. Le trichobezoard est une pathologie rare qui survient habituellement chez des adolescentes presentant des troubles psychiques. La premiere observation de trichobezoard a ete ...

  4. IMPROVEMENTS FOR THE OPERATION OF CHINESE FOOTBALL LEAGUE BY ANALYSING THE SUCCESS ASSETS OF ENGLISH PREMIER LEAGUE

    OpenAIRE

    Cao, Hanxiong

    2012-01-01

    The purpose of this thesis is going to analyze the success assets of English Premier League (which is now the most successful football league in the world) and the defects of Chinese Super League by analyzing the financial statements of the Premier League, and try to make some possible improvements for Chinese Super League according to the results of the analysis.

  5. Computers for Schools Kenya se classe au premier rang | CRDI ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Cinq ans après avoir remis en service ses premiers ordinateurs recyclés et leur avoir trouvé un nouveau nid, l'organisation non gouvernementale Computers for Schools Kenya (CFSK) s'est mérité un prix convoité à l'échelle de l'Afrique pour son travail.

  6. Effectiveness of in-season manager changes in English Premier League Football

    NARCIS (Netherlands)

    Besters, Lucas; van Ours, Jan; van Tuijl, Martin

    We analyze the performance effects of in-season manager changes in English Premier League football during the seasons 2000/2001–2014/2015. We find that some managerial changes are successful, while others are counterproductive. On average, performance does not improve following a managerial

  7. What’s a Cricketer’s Worth? Predicting Bid Prices for Indian Premier League Auctions

    Directory of Open Access Journals (Sweden)

    Siddhartha K. RASTOGI

    2017-04-01

    Full Text Available Indian Premier League is a twenty-over format cricket tournament of teams representing different Indian cities. Beginning 2008, it is established now as a grand annual affair. The team franchises are auctioned on long term basis, whereas cricketers are auctioned every season under certain conditions. Despite such wealth of information, studies on IPL auctions are rare barring four cited models. The present paper studies the results of year 2011 English-style auction of cricketers and recalibrates the old yet most accurate model by Rastogi and Deodhar (2009. Both models use ordinary least square method of regression albeit with different variable. The old models lack predictive power, whereas the recalibrated model presented displays better predictive capability as compared to earlier models. It also succeeds in reducing overall predictability gap and stands significantly parsimonious vis-à-vis previous models. Further, the final model presented is applied on 2013 and 2014 auction data to show superior results.

  8. Market Segmentation, Targeting, Dan Brand Positioning Dari Winston Premier Surabaya

    OpenAIRE

    Tania, Debby

    2014-01-01

    Sejak tahun 2012 mulai terasa bahwa bisnis properti mengalami kenaikan di Indonesia. Banyak masyarakat Indonesia berinvestasi pada properti karena dianggap aman dan menguntungkan. Sehingga muncul banyak produk properti baru di Indonesia. Perkembangan properti di Indonesia menjadi peluang besar bagi Agen Properti untuk dapat menjalankan bisnisnya. Winston Premier sebagai salah satu Agen properti di Surabaya Barat yang baru berdiri memerlukan strategi pemasaran yang tepat untuk digunakan guna b...

  9. 40Ar-39Ar laser probe dating of individual clinopyroxene inclusions in Premier eclogitic diamonds

    International Nuclear Information System (INIS)

    Burgess, R.; Turner, G.; Laurenzi, M.; Harris, J.W.

    1989-01-01

    The ages of seven individual clinopyroxene inclusions in Premier diamonds of eclogitic association have been determined using the 40 Ar- 39 Ar dating technique. Syngenetic inclusions weighing between 10 and 130 μg were exposed on cleaved surfaces of the diamonds and analysed using a laser probe. The inclusion ages were found to be in the range 1111±35 to 1254±38 Ma with an average of 1185±94 Ma. The ages obtained are in good agreement with previous determinations made on aggregates of eclogitic inclusions from Premier diamonds and demonstrate the applicability of the laser probe to dating individual diamond inclusions. (orig.)

  10. Graphical models for genetic analyses

    DEFF Research Database (Denmark)

    Lauritzen, Steffen Lilholt; Sheehan, Nuala A.

    2003-01-01

    This paper introduces graphical models as a natural environment in which to formulate and solve problems in genetics and related areas. Particular emphasis is given to the relationships among various local computation algorithms which have been developed within the hitherto mostly separate areas...... of graphical models and genetics. The potential of graphical models is explored and illustrated through a number of example applications where the genetic element is substantial or dominating....

  11. 40Ar/39Ar laser-probe dating of diamond inclusions from the Premier kimberlite

    International Nuclear Information System (INIS)

    Phillips, D.; Onstott, T.C.; Harris, J.W.; Strathclyde Univ., Glasgow

    1989-01-01

    Inclusions encapsulated by diamonds at the time of their formation provide a means for determining diamond crystallization ages and the chemistry of the surrounding upper mantle at that time. Sm-Nd studies of peridotitic inclusions, from Cretaceous-age kimberlites in southern Africa, suggest that the diamonds formed 3.3 Gyr ago. By contrast, eclogite-suite inclusions generally yield younger ages, sometimes approaching the time of kimberlite eruption. Here we report the results of 40 Ar/ 39 Ar laser-probe analyses of individual eclogitic clinopyroxene inclusions from Premier diamonds, which yield a mean age of 1,198±14 Myr. This age agrees well with Sm-Nd and 40 Ar/ 39 Ar analyses on similar Premier inclusions, and is indistinguishable from the inferred time of emplacement of the host kimberlite (1,150-1,230 Myr), which implies that diamond formation was essentially synchronous with kimberlite generation. The extrapolated non-radiogenic 40 Ar/ 36 Ar ratio of 334±102 is similar to the present-day atmospheric composition. This value is inconsistent with Sr and Nd isotopic signatures from Premier eclogite inclusions, which suggest a depleted mantle source ( 40 Ar/ 36 Ar>20,000). Pre-entrapment equilibration of the inclusions with an 36 Ar-rich fluid is the most probable explanation for the low non-radiogenic ( 40 Ar/ 36 Ar) composition. (author)

  12. Predicting Football Matches Results using Bayesian Networks for English Premier League (EPL)

    Science.gov (United States)

    Razali, Nazim; Mustapha, Aida; Yatim, Faiz Ahmad; Aziz, Ruhaya Ab

    2017-08-01

    The issues of modeling asscoiation football prediction model has become increasingly popular in the last few years and many different approaches of prediction models have been proposed with the point of evaluating the attributes that lead a football team to lose, draw or win the match. There are three types of approaches has been considered for predicting football matches results which include statistical approaches, machine learning approaches and Bayesian approaches. Lately, many studies regarding football prediction models has been produced using Bayesian approaches. This paper proposes a Bayesian Networks (BNs) to predict the results of football matches in term of home win (H), away win (A) and draw (D). The English Premier League (EPL) for three seasons of 2010-2011, 2011-2012 and 2012-2013 has been selected and reviewed. K-fold cross validation has been used for testing the accuracy of prediction model. The required information about the football data is sourced from a legitimate site at http://www.football-data.co.uk. BNs achieved predictive accuracy of 75.09% in average across three seasons. It is hoped that the results could be used as the benchmark output for future research in predicting football matches results.

  13. Effectiveness of in-season manager changes in English Premier League Football

    OpenAIRE

    Besters, Lucas; van Ours, Jan; van Tuijl, Martin

    2016-01-01

    We analyze the performance effects of in-season manager changes in English Premier League football during the seasons 2000/2001–2014/2015. We find that some managerial changes are successful, while others are counterproductive. On average, performance does not improve following a managerial replacement. The successfulness of managerial turnover depends on specific highly unpredictable circumstances, as we illustrate through case-studies.

  14. RANKING THE SPECTATORS’ DIFFICULTIES IN PURCHASING ELECTRONIC TICKETS OF FOOTBALL PREMIER LEAGUE

    Directory of Open Access Journals (Sweden)

    Ahmad Narimani

    2017-04-01

    Full Text Available This study aimed to rank the spectators’ difficulties in buying electronic tickets of football premier league matches at Azadi stadium. The population consisted of all spectators of Esteghlal-Persepolis match in the fifteenth league at Azadi stadium (N= 100000. According to Morgan table and using simple random sampling method, 500 participants were selected as sample. A researcher-made questionnaire was used for collecting the data; its face validity was confirmed by 15 experts and performing a pilot study on 30 subjects, its Cronbach’s alpha was calculated to be 0.86. Using SPSS 22, the descriptive and inferential (including Friedman test statistics was applied for analyzing the data. The findings showed that there was a significant difference between rankings of difficulties in buying electronic tickets of Football premier league matches at Azadi Stadium. The difficulties were ranked as: problem in ticket systems, early selling out of electronic tickets, lack of confidence to electronic ticket sale, lack of skill to work with the internet, low speed of internet, and lack of access to the internet

  15. Un premier service mobile en Égypte qui relie les petits exploitants ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Un premier service mobile en Égypte qui relie les petits exploitants aux acheteurs. Un homme qui parle sur un téléphone mobile. Les petits exploitants agricoles dominent l'agriculture égyptienne, mais leur manque de connaissances en matière de commercialisation et de compétences techniques, ainsi qu'une mauvaise ...

  16. Examining behavioral processes through which lifestyle interventions promote weight loss: results from PREMIER.

    Science.gov (United States)

    Fitzpatrick, Stephanie L; Bandeen-Roche, Karen; Stevens, Victor J; Coughlin, Janelle W; Rubin, Richard R; Brantley, Phillip J; Funk, Kristine L; Svetkey, Laura P; Jerome, Gerald J; Dalcin, Arlene; Charleston, Jeanne; Appel, Lawrence J

    2014-04-01

    To examine the behavioral processes through which lifestyle interventions impacted weight loss. The analyses were limited to overweight and obese Black and White adults randomized to a PREMIER lifestyle intervention (N = 501). Structural equation modeling was conducted to test the direct and indirect relationships of session attendance, days of self-monitoring diet and exercise, change in diet composition and exercise, and 6-month weight change. Greater session attendance was associated with increased self-monitoring, which was in turn significantly related to reduction in percent energy from total fat consumed. Change in percent energy from fat and self-monitoring was associated with 6-month percent change in weight. Both a decrease in fat intake and increase in self-monitoring are potential mediators of the relationship between attendance and weight change. The findings provide a reasonable model that suggests regular session attendance and use of behavioral strategies like self-monitoring are associated with improved behavioral outcomes that are associated with weight loss. Copyright © 2013 The Obesity Society.

  17. Les animateurs TICE du premier degré, quelle professionnalité ?

    OpenAIRE

    Villemonteix , François

    2007-01-01

    International audience; Les animateurs TICE du premier degré, quelle professionnalité ? Congrès international AREF 2007 (Actualité de la Recherche en Education et en Formation) François VILLEMONTEIX Doctorant Laboratoire EDA (Education et apprentissages) Université Paris 5 – La Sorbonne franç RÉSUMÉ. Dans le but de favoriser le développement d'usages instrumentés dans les classes de l'école primaire française, l'institution éducative a depuis les années 80 at...

  18. Behavior genetic modeling of human fertility

    DEFF Research Database (Denmark)

    Rodgers, J L; Kohler, H P; Kyvik, K O

    2001-01-01

    Behavior genetic designs and analysis can be used to address issues of central importance to demography. We use this methodology to document genetic influence on human fertility. Our data come from Danish twin pairs born from 1953 to 1959, measured on age at first attempt to get pregnant (First......Try) and number of children (NumCh). Behavior genetic models were fitted using structural equation modeling and DF analysis. A consistent medium-level additive genetic influence was found for NumCh, equal across genders; a stronger genetic influence was identified for FirstTry, greater for females than for males....... A bivariate analysis indicated significant shared genetic variance between NumCh and FirstTry....

  19. [Sõltumatu Tantsu Ühenduse poolt korraldatud sarjast "Premiere"] / Evelin Lagle ; küsinud Tambet Kaugema

    Index Scriptorium Estoniae

    Lagle, Evelin, 1986-

    2012-01-01

    Uutele koreograafidele pühendatud sarja "Premiere" programmis osalevad tantsulavastustega neli tantsukunstnikku Eestist - Tallinna Ülikooli lõpetanud Svetlana Grigorjeva, Turu Kunstiakadeemia lõpetanud Kaisa Selde, Viljandi Kultuuriakadeemia lõpetanud Kristina-Maria Heinsalu ja Tallinna Ülikooli lõpetanud Christin Lunts

  20. ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT - PHYSICAL REMOVAL OF MICROBIAL CONTAMINATION AGENTS IN DRINKING WATER, WATTS P{REMIER ULTRA 5 REVERSE OSMOSIS DRINKING WATER TREATMENT SYSTEM (POU)

    Science.gov (United States)

    The Watts Premier Ultra 5 system was tested for removal of bacteria and viruses at NSF International's Laboratory. Watts Premier submitted ten units, which were split into two groups of five. One group received 25 days of conditioning prior to challenge testing, while the secon...

  1. Analisis Kualitas Pelayanan terhadap Kepuasan Konsumen Jasa Hotel Santika Premiere Semarang

    OpenAIRE

    Dewangga, Nandy; Hidayat, Wahyu; Widiartanto, Widiartanto

    2014-01-01

    The competition of global business today focusing on consumers is a strategic choice in business world in order to survive. For example, the tight competition of business in the company of hotel services is by improving the service quality to consumers. The problems in this research were the decreasing number of hotel service users and the increasing number of consumer complaint as the service users of Santika Premiere Hotel in Semarang from year to year. The aims of this research were to ide...

  2. Eco-genetic modeling of contemporary life-history evolution.

    Science.gov (United States)

    Dunlop, Erin S; Heino, Mikko; Dieckmann, Ulf

    2009-10-01

    We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by

  3. Analisis Pengaruh Kualitas Pelayanan Terhadap Kepuasan Pelanggan pada Hotel Santika Premiere Dyandra Medan

    OpenAIRE

    Purba, Mey Royani M.

    2013-01-01

    Quality of service is an expected level of excellence and control over the level of excellence to comply the customer wants. Satisfaction is the difference between the perceived performance with expectations. This study aimed to to identify and analyze the influence of the quality of services consisting of physical tangible, reliability, responsiveness, assurance, and empathy to customer satisfaction on Santika Premiere Dyandra Hotel. To measure service quality from the point of servic...

  4. Black Generation Y gender differences in Premier Soccer League spectator motives : sport marketing

    OpenAIRE

    T.E. Mofokeng; A.L. Bevan-Dye

    2014-01-01

    The purpose of this study was to determine whether there are gender differences concerning Premier Soccer League (PSL) spectator motives amongst black Generation Y students in South Africa. In South Africa, the black Generation Y cohort (individuals born between 1986 and 2005) represents an important but under-researched market segment in that, in 2013, they made up 32 percent of the country's population. From a PSL marketing perspective, understanding the motives that drive game spectatorshi...

  5. Genetic coding and gene expression - new Quadruplet genetic coding model

    Science.gov (United States)

    Shankar Singh, Rama

    2012-07-01

    Successful demonstration of human genome project has opened the door not only for developing personalized medicine and cure for genetic diseases, but it may also answer the complex and difficult question of the origin of life. It may lead to making 21st century, a century of Biological Sciences as well. Based on the central dogma of Biology, genetic codons in conjunction with tRNA play a key role in translating the RNA bases forming sequence of amino acids leading to a synthesized protein. This is the most critical step in synthesizing the right protein needed for personalized medicine and curing genetic diseases. So far, only triplet codons involving three bases of RNA, transcribed from DNA bases, have been used. Since this approach has several inconsistencies and limitations, even the promise of personalized medicine has not been realized. The new Quadruplet genetic coding model proposed and developed here involves all four RNA bases which in conjunction with tRNA will synthesize the right protein. The transcription and translation process used will be the same, but the Quadruplet codons will help overcome most of the inconsistencies and limitations of the triplet codes. Details of this new Quadruplet genetic coding model and its subsequent potential applications including relevance to the origin of life will be presented.

  6. Context trees for privacy-preserving modeling of genetic data

    NARCIS (Netherlands)

    Kusters, C.J.; Ignatenko, T.

    2016-01-01

    In this work, we use context trees for privacypreserving modeling of genetic sequences. The resulting estimated models are applied for functional comparison of genetic sequences in a privacy preserving way. Here we define privacy as uncertainty about the genetic source sequence given its model and

  7. Latent spatial models and sampling design for landscape genetics

    Science.gov (United States)

    Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

    2016-01-01

    We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

  8. Noise in Genetic Toggle Switch Models

    Directory of Open Access Journals (Sweden)

    Andrecut M.

    2006-06-01

    Full Text Available In this paper we study the intrinsic noise effect on the switching behavior of a simple genetic circuit corresponding to the genetic toggle switch model. The numerical results obtained from a noisy mean-field model are compared to those obtained from the stochastic Gillespie simulation of the corresponding system of chemical reactions. Our results show that by using a two step reaction approach for modeling the transcription and translation processes one can make the system to lock in one of the steady states for exponentially long times.

  9. Behavior genetics: Bees as model

    International Nuclear Information System (INIS)

    Nates Parra, Guiomar

    2011-01-01

    The honeybee Apis mellifera (Apidae) is a model widely used in behavior because of its elaborate social life requiring coordinate actions among the members of the society. Within a colony, division of labor, the performance of tasks by different individuals, follows genetically determined physiological changes that go along with aging. Modern advances in tools of molecular biology and genomics, as well as the sequentiation of A. mellifera genome, have enabled a better understanding of honeybee behavior, in particular social behavior. Numerous studies show that aspects of worker behavior are genetically determined, including defensive, hygienic, reproductive and foraging behavior. For example, genetic diversity is associated with specialization to collect water, nectar and pollen. Also, control of worker reproduction is associated with genetic differences. In this paper, I review the methods and the main results from the study of the genetic and genomic basis of some behaviors in bees.

  10. Epidemiology and history of knee injury and its impact on activity limitation among football premier league professional referees.

    Science.gov (United States)

    Mahdavi Mohtasham, Hamid; Shahrbanian, Shahnaz; Khoshroo, Fatemeh

    2018-01-01

    The purpose of this study was to determine the epidemiology and history of knee injury and its impact on activity limitation among football premier league professional referees in Iran. This was a descriptive study. 59 Football Premier League professional referees participated in the study. The knee injury related information such as injury history and mechanism was recorded. Injury related symptoms and their impacts on the activity limitation, ability to perform activities of daily living as well participation in sports and recreational activities was obtained through the Knee Outcome Survey (KOS). The results indicated that 31 out of 59 participants reported the history of knee injury. In addition, 18.6%, 22.4% and 81% of the referees reported that they had been injured during the last 6 months of the last year, and at some point in their refereeing careers, respectively. Results further indicated that 48.8% of the injuries occurred in the non-dominant leg and they occurred more frequently during training sessions (52%). Furthermore, the value of KOS was 85 ± 13 for Activities of Daily Living subscale and 90 ± 9 for Sports and Recreational Activities subscale of the KOS. Knee injury was quite common among the Football Premier League professional referees. It was also indicated that the injuries occurred mainly due to insufficient physical fitness. Therefore, it is suggested that football referees undergo the proper warm-up program to avoid knee injury.

  11. Asymmetry after hamstring injury in English Premier League: issue resolved, or perhaps not?

    Science.gov (United States)

    Barreira, P; Drust, B; Robinson, M A; Vanrenterghem, J

    2015-06-01

    Hamstring injuries constitute one of the most concerning injuries in English Premier League football, due to its high primary incidence but also its recurrence. Functional methods assessing hamstring function during high-risk performance tasks such as sprinting are vital to identify potential risk factors. The purpose of this study was to assess horizontal force deficits during maximum sprint running on a non-motorized treadmill in football players with previous history of hamstring strains as a pre-season risk-assessment in a club setting. 17 male football players from one Premier League Club were divided into 2 groups, experimental (n=6, age=24.5±2.3 years) and control (n=11, age=21.3±1.2 years), according to history of previous hamstring injury. Participants performed a protocol including a 10-s maximum sprint on a non-motorized treadmill. Force deficits during acceleration phase and steady state phases of the sprint were assessed between limbs and between groups. The main outcome measures were horizontal and vertical peak forces during the acceleration phase or steady state. There were no significant differences in peak forces between previously injured and non-injured limbs, or between groups, challenging the ideas around functional force deficits in sprint running as a diagnostic measure of hamstring re-injury risk. © Georg Thieme Verlag KG Stuttgart · New York.

  12. Testing the Structure of Hydrological Models using Genetic Programming

    Science.gov (United States)

    Selle, B.; Muttil, N.

    2009-04-01

    Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  13. Introduction to genetic algorithms as a modeling tool

    International Nuclear Information System (INIS)

    Wildberger, A.M.; Hickok, K.A.

    1990-01-01

    Genetic algorithms are search and classification techniques modeled on natural adaptive systems. This is an introduction to their use as a modeling tool with emphasis on prospects for their application in the power industry. It is intended to provide enough background information for its audience to begin to follow technical developments in genetic algorithms and to recognize those which might impact on electric power engineering. Beginning with a discussion of genetic algorithms and their origin as a model of biological adaptation, their advantages and disadvantages are described in comparison with other modeling tools such as simulation and neural networks in order to provide guidance in selecting appropriate applications. In particular, their use is described for improving expert systems from actual data and they are suggested as an aid in building mathematical models. Using the Thermal Performance Advisor as an example, it is suggested how genetic algorithms might be used to make a conventional expert system and mathematical model of a power plant adapt automatically to changes in the plant's characteristics

  14. Comparing estimates of genetic variance across different relationship models.

    Science.gov (United States)

    Legarra, Andres

    2016-02-01

    Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Testing the structure of a hydrological model using Genetic Programming

    Science.gov (United States)

    Selle, Benny; Muttil, Nitin

    2011-01-01

    SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

  16. Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

    Science.gov (United States)

    Han, Lide; Yang, Jian; Zhu, Jun

    2007-06-01

    A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

  17. Report to New England Governors and Eastern Canadian Premiers on climate change projects

    International Nuclear Information System (INIS)

    2002-08-01

    The Premiers-Governors energy discussions are aimed at promoting joint energy cooperation between provinces and states. This report outlines the major accomplishments in the implementation of the Climate Change Action Plan adopted by the Conference in 1998. The project priorities for the coming year are also outlined. In 2001, the New England Governors (NEG) and the Eastern Canadian Premiers (ECP) directed the Environment Committee and the Northeast International Committee on Energy (NICE) to implement a plan to develop a regional emissions inventory so that participating jurisdictions would have common data for measuring progress. The plan also identified specific climate actions that could be readily implemented. This report describes the results of 5 working groups which were created to focus on the following potential categories: energy, transportation, inventory and registry, adaptation, and 'lead by example'. In addition to the working groups, the Climate Change Steering Committee developed 4 proposals for consideration for implementation. These were the LED Traffic Light Proposal, the College and University Partnerships in Emissions Reductions, State/Provincial Purchasing Programs for High Efficiency-Low Emission Office Equipment, and Use of Cleaner, More Energy-Efficient Vehicles in State/Provincial Fleets. The Steering Committee will also pursue other tasks in the coming year, including the study of other proposals for cost-effective measures that could contribute to the goals of the Climate Change Action Plan, examine Internet options for coordinating internal project work, examine opportunities to pursue climate action, and identify opportunities to improve vehicle fuel efficiency

  18. Short communication: Genetic lag represents commercial herd genetic merit more accurately than the 4-path selection model.

    Science.gov (United States)

    Dechow, C D; Rogers, G W

    2018-05-01

    Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  19. Une forme urbaine du premier âge touristique: les promenades littorales

    Directory of Open Access Journals (Sweden)

    Franck DEBIÉ

    1993-03-01

    Full Text Available Les promenades maritimes caractérisent les stations de bord de mer du premier âge touristique (1850-1930. Elles traduisent dans le paysage un urbanisme spéculatif, à rapprocher de celui qui produit le square et le boulevard, et donnent lieu à une urbanisation du littoral sous forme de vastes appendices linéaires. Les pratiques sociales associées à la promenade rappellent celles du jardin de plaisir, et renvoient au même rêve d’une urbanité idéale, libérée des miasmes, des promiscuités sociales, des contraintes qui pèsent sur les amours et les jeux.

  20. Genetic and non-genetic animal models for autism spectrum disorders (ASD).

    Science.gov (United States)

    Ergaz, Zivanit; Weinstein-Fudim, Liza; Ornoy, Asher

    2016-09-01

    Autism spectrum disorder (ASD) is associated, in addition to complex genetic factors, with a variety of prenatal, perinatal and postnatal etiologies. We discuss the known animal models, mostly in mice and rats, of ASD that helps us to understand the etiology, pathogenesis and treatment of human ASD. We describe only models where behavioral testing has shown autistic like behaviors. Some genetic models mimic known human syndromes like fragile X where ASD is part of the clinical picture, and others are without defined human syndromes. Among the environmentally induced ASD models in rodents, the most common model is the one induced by valproic acid (VPA) either prenatally or early postnatally. VPA induces autism-like behaviors following single exposure during different phases of brain development, implying that the mechanism of action is via a general biological mechanism like epigenetic changes. Maternal infection and inflammation are also associated with ASD in man and animal models. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Developing robotic behavior using a genetic programming model

    International Nuclear Information System (INIS)

    Pryor, R.J.

    1998-01-01

    This report describes the methodology for using a genetic programming model to develop tracking behaviors for autonomous, microscale robotic vehicles. The use of such vehicles for surveillance and detection operations has become increasingly important in defense and humanitarian applications. Through an evolutionary process similar to that found in nature, the genetic programming model generates a computer program that when downloaded onto a robotic vehicle's on-board computer will guide the robot to successfully accomplish its task. Simulations of multiple robots engaged in problem-solving tasks have demonstrated cooperative behaviors. This report also discusses the behavior model produced by genetic programming and presents some results achieved during the study

  2. Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

    Science.gov (United States)

    Franić, Sanja; Dolan, Conor V; Borsboom, Denny; Hudziak, James J; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

    2013-09-01

    In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.

  3. CMCpy: Genetic Code-Message Coevolution Models in Python

    Science.gov (United States)

    Becich, Peter J.; Stark, Brian P.; Bhat, Harish S.; Ardell, David H.

    2013-01-01

    Code-message coevolution (CMC) models represent coevolution of a genetic code and a population of protein-coding genes (“messages”). Formally, CMC models are sets of quasispecies coupled together for fitness through a shared genetic code. Although CMC models display plausible explanations for the origin of multiple genetic code traits by natural selection, useful modern implementations of CMC models are not currently available. To meet this need we present CMCpy, an object-oriented Python API and command-line executable front-end that can reproduce all published results of CMC models. CMCpy implements multiple solvers for leading eigenpairs of quasispecies models. We also present novel analytical results that extend and generalize applications of perturbation theory to quasispecies models and pioneer the application of a homotopy method for quasispecies with non-unique maximally fit genotypes. Our results therefore facilitate the computational and analytical study of a variety of evolutionary systems. CMCpy is free open-source software available from http://pypi.python.org/pypi/CMCpy/. PMID:23532367

  4. Evolutionary genetics: the Drosophila model

    Indian Academy of Sciences (India)

    Unknown

    Evolutionary genetics straddles the two fundamental processes of life, ... of the genus Drosophila have been used extensively as model systems in experimental ... issue will prove interesting, informative and thought-provoking for both estab-.

  5. Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

    DEFF Research Database (Denmark)

    Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

    2014-01-01

    A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

  6. Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

    DEFF Research Database (Denmark)

    Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

    2013-01-01

    A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

  7. Chinese Dream——Concert in Commemoration of 115th Birth Anniversary of Premier Zhou Enlai Held

    Institute of Scientific and Technical Information of China (English)

    Our; Staff; Reporter

    2013-01-01

    <正>The theme song of the film The Founding of a Republic sung by male vocalists Dai Yuqiang and Wei Song reverberated in the Opera Hall at the National Center for the Performing Arts on the `evening of March 14. It marked the start of the concert in commemoration of the 115th anniversary of the birth of Premier Zhou Enlai, with "Chinese Dream" as the theme.

  8. [The emphases and basic procedures of genetic counseling in psychotherapeutic model].

    Science.gov (United States)

    Zhang, Yuan-Zhi; Zhong, Nanbert

    2006-11-01

    The emphases and basic procedures of genetic counseling are all different with those in old models. In the psychotherapeutic model, genetic counseling will not only focus on counselees' genetic disorders and birth defects, but also their psychological problems. "Client-centered therapy" termed by Carl Rogers plays an important role in genetic counseling process. The basic procedures of psychotherapeutic model of genetic counseling include 7 steps: initial contact, introduction, agendas, inquiry of family history, presenting information, closing the session and follow-up.

  9. MULTICRITERIA ANALYSIS OF FOOTBALL MATCH PERFORMANCES: COMPOSITION OF PROBABILISTIC PREFERENCES APPLIED TO THE ENGLISH PREMIER LEAGUE 2015/2016

    Directory of Open Access Journals (Sweden)

    Vitor Principe

    Full Text Available ABSTRACT This article aims to analyze the technical performance of football teams in the FA Premier League during the 2015/2016 season. Data of twenty clubs over 38 matches for each club are considered using 23 variables. These variables have been explored in the football literature and address different features of technical performance. The different configuration of the data for teams in detached segments motivated the multi-criteria approach, which enables identification of strong and weak sectors in each segment. The uncertainty as to the outcome of football matches and the imprecision of the measures indicated the use of Composition of Probabilistic Preferences (CPP to model the problem. “R” software was used in the modeling and computation. The CPP global scores obtained were more consistent with the final classification than those of other methods. CPP scores revealed different performances of particular groups of variables indicating aspects to be improved and explored.

  10. An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends (Open Access publication

    Directory of Open Access Journals (Sweden)

    Madsen Per

    2007-07-01

    Full Text Available Abstract In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.

  11. Population genetics of Setaria viridis, a new model system.

    Science.gov (United States)

    Huang, Pu; Feldman, Maximilian; Schroder, Stephan; Bahri, Bochra A; Diao, Xianmin; Zhi, Hui; Estep, Matt; Baxter, Ivan; Devos, Katrien M; Kellogg, Elizabeth A

    2014-10-01

    An extensive survey of the standing genetic variation in natural populations is among the priority steps in developing a species into a model system. In recent years, green foxtail (Setaria viridis), along with its domesticated form foxtail millet (S. italica), has rapidly become a promising new model system for C4 grasses and bioenergy crops, due to its rapid life cycle, large amount of seed production and small diploid genome, among other characters. However, remarkably little is known about the genetic diversity in natural populations of this species. In this study, we survey the genetic diversity of a worldwide sample of more than 200 S. viridis accessions, using the genotyping-by-sequencing technique. Two distinct genetic groups in S. viridis and a third group resembling S. italica were identified, with considerable admixture among the three groups. We find the genetic variation of North American S. viridis correlates with both geography and climate and is representative of the total genetic diversity in this species. This pattern may reflect several introduction/dispersal events of S. viridis into North America. We also modelled demographic history and show signal of recent population decline in one subgroup. Finally, we show linkage disequilibrium decay is rapid (<45 kb) in our total sample and slow in genetic subgroups. These results together provide an in-depth understanding of the pattern of genetic diversity of this new model species on a broad geographic scale. They also provide key guidelines for on-going and future work including germplasm preservation, local adaptation, crossing designs and genomewide association studies. © 2014 John Wiley & Sons Ltd.

  12. ETV REPORT: REMOVAL OF CHEMICAL CONTAMINANTS IN DRINKING WATER – WATTS PREMIER INC. WP-4V DRINKING WATER TREATMENT SYSTEM

    Science.gov (United States)

    The Watts Premier WP-4V POU drinking water treatment system was tested for removal of aldicarb, benzene, cadmium, carbofuran, cesium, chloroform, dichlorvos, dicrotophos, fenamiphos, mercury, mevinphos, oxamyl, strontium, and strychnine. The WP-4V employs a reverse osmosis (RO) m...

  13. The effect of playing formation on high-intensity running and technical profiles in English FA Premier League soccer matches

    DEFF Research Database (Denmark)

    Bradley, Paul S; Carling, Chris; Archer, Dave

    2011-01-01

    The aim of this study was to examine the effect of playing formation on high-intensity running and technical performance during elite soccer matches. Twenty English FA Premier League games were analysed using a multiple-camera computerized tracking system (n = 153 players). Overall ball possession...

  14. Disease activity, physical function, and radiographic progression after longterm therapy with adalimumab plus methotrexate: 5-year results of PREMIER

    NARCIS (Netherlands)

    van der Heijde, Désirée; Breedveld, Ferdinand C.; Kavanaugh, Arthur; Keystone, Edward C.; Landewé, Robert; Patra, Kaushik; Pangan, Aileen L.

    2010-01-01

    To evaluate the efficacy and safety of initial combination treatment with adalimumab (ADA) and methotrexate (MTX) versus monotherapy with ADA or MTX during an open-label extension of PREMIER. Patients with early rheumatoid arthritis (RA) received blinded ADA plus MTX, ADA alone, or MTX alone for 2

  15. Etat des lieux des soins de premier recours des malades mentaux à Antananarivo : étude rétrospective

    Science.gov (United States)

    Bakohariliva, Hasina Andrianarivony; Rafehivola, Imisanavalona Hanitrinihaja; Raobelle, Evah Norotiana; Raharivelo, Adeline; Rajaonarison, Bertille Hortense

    2018-01-01

    Résumé Religion et guérisseurs traditionnels occupent encore une place prépondérante dans la prise en charge des maladies mentales à Madagascar. Ainsi, nous nous sommes fixés comme objectif d'établir un état des lieux sur les soins de premier recours des malades mentaux. Nous avons mené une étude rétrospective descriptive s'étalant sur une période de 16 mois allant de janvier 2014 en avril 2015 au sein du service de psychiatrie du CHU de Befelatanana à Antananarivo. La prévalence des psychoses était de 25%. Le genre féminin (53%), l'ethnie merina (77%), les étudiants (45%), le niveau d'étude secondaire (40%), les célibataires (72%), la religion protestante (45%), ainsi que le niveau socio-économique moyen (57,5%) étaient prédominants. Dans les paramètres cliniques, le mode de début brutal (52%), le premier recours à la religion (40%), la présence d'antécédents des cas similaire (90%), étaient majoritaires. La schizophrénie était la pathologie la plus rencontrée dans la moitié des cas. Le délai d'amélioration en cas de traitement religieux et traditionnels était dans la moitié des cas de plus de 10 jours d'hospitalisation. Les patients ayant reçu une prise en charge psychiatrique en premier recours, étaient améliorés dans 75 % cas en moins de 10jours. Le retard du recours aux soins psychiatriques est une réalité à Madagascar qui aggrave le pronostic des psychoses. PMID:29632623

  16. [Pierre Chirac "premier physician" of the king and the aborted plan to create an "Académie de médecine" in Paris (1731-1732)].

    Science.gov (United States)

    Lunel, Alexandre

    2005-03-01

    After being appointed "premier physician" in 1731, Pierre Chirac, thanks to his influence with the king, tried to realize an ambitious project. Inspired by the creation of an Academie de Chirurgie by the "premier surgeon", Chirac decided to creation an Académie de Médecine in Paris. Under his guidance, it was planned to collect opinions from all doctors of the kingdom in order to enhance global knowledge of disease, symptoms and treatments. However, threatened with the loss of its secular superiority, the Paris University Medical School immediately opposed the project. Although well advanced, the project was finally abandoned on Chirac's death.

  17. Shaping asteroid models using genetic evolution (SAGE)

    Science.gov (United States)

    Bartczak, P.; Dudziński, G.

    2018-02-01

    In this work, we present SAGE (shaping asteroid models using genetic evolution), an asteroid modelling algorithm based solely on photometric lightcurve data. It produces non-convex shapes, orientations of the rotation axes and rotational periods of asteroids. The main concept behind a genetic evolution algorithm is to produce random populations of shapes and spin-axis orientations by mutating a seed shape and iterating the process until it converges to a stable global minimum. We tested SAGE on five artificial shapes. We also modelled asteroids 433 Eros and 9 Metis, since ground truth observations for them exist, allowing us to validate the models. We compared the derived shape of Eros with the NEAR Shoemaker model and that of Metis with adaptive optics and stellar occultation observations since other models from various inversion methods were available for Metis.

  18. Premier League academy soccer players' experiences of competing in a tournament bio-banded for biological maturation.

    Science.gov (United States)

    Cumming, Sean P; Brown, Daniel J; Mitchell, Siobhan; Bunce, James; Hunt, Dan; Hedges, Chris; Crane, Gregory; Gross, Aleks; Scott, Sam; Franklin, Ed; Breakspear, Dave; Dennison, Luke; White, Paul; Cain, Andrew; Eisenmann, Joey C; Malina, Robert M

    2018-04-01

    Individual differences in the growth and maturation have been shown to impact player performance and development in youth soccer. This study investigated Premier League academy players' experiences of participating in a tournament bio-banded for biological maturation. Players (N = 66) from four professional soccer clubs aged 11 and 14 years and between 85-90% of adult stature participated in a tournament. Players competed in three 11 vs 11 games on a full size pitch with 25-min halves. Sixteen players participated in four 15-min focus groups and were asked to describe their experiences of participating in the bio-banded tournament in comparison to age group competition. All players described their experience as positive and recommended the Premier League integrate bio-banding into the existing games programme. In comparison to age-group competitions, early maturing players described the bio-banded games more physically challenging, and found that they had to adapt their style of play placing a greater emphasis on technique and tactics. Late maturing players considered the games to be less physically challenging, yet appreciated the having more opportunity to use, develop and demonstrate their technical, physical, and psychological competencies. Bio-banding strategies appear to contribute positively towards the holistic development of young soccer players.

  19. Numeral eddy current sensor modelling based on genetic neural network

    International Nuclear Information System (INIS)

    Yu Along

    2008-01-01

    This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method

  20. Genetic demographic networks: Mathematical model and applications.

    Science.gov (United States)

    Kimmel, Marek; Wojdyła, Tomasz

    2016-10-01

    Recent improvement in the quality of genetic data obtained from extinct human populations and their ancestors encourages searching for answers to basic questions regarding human population history. The most common and successful are model-based approaches, in which genetic data are compared to the data obtained from the assumed demography model. Using such approach, it is possible to either validate or adjust assumed demography. Model fit to data can be obtained based on reverse-time coalescent simulations or forward-time simulations. In this paper we introduce a computational method based on mathematical equation that allows obtaining joint distributions of pairs of individuals under a specified demography model, each of them characterized by a genetic variant at a chosen locus. The two individuals are randomly sampled from either the same or two different populations. The model assumes three types of demographic events (split, merge and migration). Populations evolve according to the time-continuous Moran model with drift and Markov-process mutation. This latter process is described by the Lyapunov-type equation introduced by O'Brien and generalized in our previous works. Application of this equation constitutes an original contribution. In the result section of the paper we present sample applications of our model to both simulated and literature-based demographies. Among other we include a study of the Slavs-Balts-Finns genetic relationship, in which we model split and migrations between the Balts and Slavs. We also include another example that involves the migration rates between farmers and hunters-gatherers, based on modern and ancient DNA samples. This latter process was previously studied using coalescent simulations. Our results are in general agreement with the previous method, which provides validation of our approach. Although our model is not an alternative to simulation methods in the practical sense, it provides an algorithm to compute pairwise

  1. Hierarchical linear modeling of longitudinal pedigree data for genetic association analysis

    DEFF Research Database (Denmark)

    Tan, Qihua; B Hjelmborg, Jacob V; Thomassen, Mads

    2014-01-01

    -effect models to explicitly model the genetic relationship. These have proved to be an efficient way of dealing with sample clustering in pedigree data. Although current algorithms implemented in popular statistical packages are useful for adjusting relatedness in the mixed modeling of genetic effects...... associated with blood pressure with estimated inflation factors of 0.99, suggesting that our modeling of random effects efficiently handles the genetic relatedness in pedigrees. Application to simulated data captures important variants specified in the simulation. Our results show that the method is useful......Genetic association analysis on complex phenotypes under a longitudinal design involving pedigrees encounters the problem of correlation within pedigrees, which could affect statistical assessment of the genetic effects. Approaches have been proposed to integrate kinship correlation into the mixed...

  2. Genetic screens in Caenorhabditis elegans models for neurodegenerative diseases

    NARCIS (Netherlands)

    Alvarenga Fernandes Sin, Olga; Michels, Helen; Nollen, Ellen A. A.

    2014-01-01

    Caenorhabditis elegans comprises unique features that make it an attractive model organism in diverse fields of biology. Genetic screens are powerful to identify genes and C. elegans can be customized to forward or reverse genetic screens and to establish gene function. These genetic screens can be

  3. Animal models for human genetic diseases | Sharif | African Journal ...

    African Journals Online (AJOL)

    The study of human genetic diseases can be greatly aided by animal models because of their similarity to humans in terms of genetics. In addition to understand diverse aspects of basic biology, model organisms are extensively used in applied research in agriculture, industry, and also in medicine, where they are used to ...

  4. Monitoring evaluation of a spillway pilaster for Premiere Chute Dam

    Energy Technology Data Exchange (ETDEWEB)

    Crepeau, Louis; Kassem, Chakib [OSMOS Canada Inc., Montreal, (Canada)

    2010-07-01

    The Premiere-Chute hydroelectric power station, commissioned in 1968, has four hydraulic turbines for a total of 130 MW. One of the pilasters of the dam weir, built with pre-stressed concrete, showed a crack at the level of the post-tension cable. This paper presented an evaluation of the behaviour of the pilaster in question, No. 9. The main goal was to prevent any disruption to the gate opening through adequate monitoring for a long term data follow-up. Six long-base OSMOS type optical sensors were installed on each face of the spillway pilaster. The behaviour of the No. 9 pilaster was then compared with that of other pilasters with respect to the effects of temperature and water level fluctuation in the dam. After the pilasters had been monitored for six months, it was found that No. 9 pilaster showed the least deformation of all. It was therefore concluded that the behaviour of this pilaster was normal.

  5. REMOVAL OF CHEMICAL AND MICROBIAL CONTAMINANTS IN DRINKING WATER - WATTS PREMIER M-2400 POINT-OF-ENTRY REVERSE OSMOSIS DRINKINGWATER TREATMENT SYSTEM

    Science.gov (United States)

    The Watts Premier M-2400 POE RO Drinking Water Treatment System was tested at the NSF Drinking Water Treatment Systems Laboratory for removal of the viruses fr and MS2, the bacteria Brevundimonas diminuta, and chemicals aldicarb, benzene, cadmium, carbofuran, cesium, chl...

  6. Qualitative Impact Assessment 2010: An Independent Study Conducted by BDRC Continental, Ltd., February-July 2010. Premier League Reading Stars

    Science.gov (United States)

    National Literacy Trust, 2010

    2010-01-01

    Premier League Reading Stars (PLRS) is in its eighth year. To complement a pre-post quantitative survey, an impact evidence base was required to inform consideration of continued funding into 2011 and beyond. PLRS is very highly regarded among child participants, parents, and librarians. The structure of the scheme, its basis on football, and the…

  7. Modelling the co-evolution of indirect genetic effects and inherited variability.

    Science.gov (United States)

    Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter

    2018-03-28

    When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of

  8. Injury profile of a professional soccer team in the premier league of iran.

    Science.gov (United States)

    Hassabi, Mohammad; Mohammad-Javad Mortazavi, Seyed; Giti, Mohammad-Reza; Hassabi, Majid; Mansournia, Mohammad-Ali; Shapouran, Sara

    2010-12-01

    Despite numerous studies which have been done regarding soccer injuries worldwide, there is lack of available data considering the epidemiology of injuries in the Iranian soccer premier league, although it is the most popular sport in the country. The main goal of this research was to determine the incidence of physical injuries in the studied population, considering other characteristics such as site, type and mechanism as well. Twenty one adult male professional soccer players (age 24±3), members of a team (Tehran-Pas) participating in Iranian premier league, were followed during a 4-month period. The injury characteristics and exposure times were recorded by the team physician during all the matches and training sessions. The total exposure time was 2610 playing hours (2352 h of training versus 258 h of competition). Eighty six percent of the injuries were acute. Incidence of acute injuries was 16.5 (95% CI: 12-22) per 1000 hours of playing (11.5 per 1000 hrs of training and 62 per 1000 hrs of competition). The most common types of injuries were strains followed by contusions, each of which constituted 30% of acute injuries. More than 80% of injuries occurred in lower limbs, especially in thigh and groin regions. Nearly 60% of acute injuries occurred in dominant side of the body, and collision was the reason of about half of the acute injuries. Severity of more than 70% of the injuries was minor. On average each injury had led the player being off the field for about 10 days. The incidence of injury in this research is in range of numbers obtained in important international tournaments but the rate of injuries during training sessions is higher than comparable studies.

  9. The energy outlook in China-Minutes from the seminar organised by the Centre Geopolitique de l'Energie et des Matieres Premieres

    International Nuclear Information System (INIS)

    Keppler, J.H.; Meritet, S.

    2004-01-01

    As part of the seminars that are organised on a regular basis, the Centre de Geopolitique de l'Energie et des Matieres Premieres has devoted, on the 2. of June, a day to China, its energetics outlook and the resulting economic and geopolitical challenges. (authors)

  10. ENU mutagenesis to generate genetically modified rat models.

    Science.gov (United States)

    van Boxtel, Ruben; Gould, Michael N; Cuppen, Edwin; Smits, Bart M G

    2010-01-01

    The rat is one of the most preferred model organisms in biomedical research and has been extremely useful for linking physiology and pathology to the genome. However, approaches to genetically modify specific genes in the rat germ line remain relatively scarce. To date, the most efficient approach for generating genetically modified rats has been the target-selected N-ethyl-N-nitrosourea (ENU) mutagenesis-based technology. Here, we describe the detailed protocols for ENU mutagenesis and mutant retrieval in the rat model organism.

  11. What Happens When Employers are Free to Discriminate? Evidence from the English Barclays Premier Fantasy Football League

    OpenAIRE

    Bryson, Alex; Chevalier, Arnaud

    2014-01-01

    Research on employers' hiring discrimination is limited by the unlawfulness of such activity. Consequently, researchers have focused on the intention to hire. Instead, we rely on a virtual labour market, the Fantasy Football Premier League, where employers can freely exercise their taste for racial discrimination in terms of hiring and firing. The setting allows us to eliminate co-worker, consumer-based and statistical discrimination as potential sources of discrimination, thus isolating the ...

  12. Teaching Genetic Counseling Skills: Incorporating a Genetic Counseling Adaptation Continuum Model to Address Psychosocial Complexity.

    Science.gov (United States)

    Shugar, Andrea

    2017-04-01

    Genetic counselors are trained health care professionals who effectively integrate both psychosocial counseling and information-giving into their practice. Preparing genetic counseling students for clinical practice is a challenging task, particularly when helping them develop effective and active counseling skills. Resistance to incorporating these skills may stem from decreased confidence, fear of causing harm or a lack of clarity of psycho-social goals. The author reflects on the personal challenges experienced in teaching genetic counselling students to work with psychological and social complexity, and proposes a Genetic Counseling Adaptation Continuum model and methodology to guide students in the use of advanced counseling skills.

  13. THE ALLOMETRIC-AUTOREGRESSIVE MODEL IN GENETIC ...

    African Journals Online (AJOL)

    The application of an allometric-autoregressive model for the quantification of growth and efficiency of feed utilization for purposes of selection for ... be of value in genetic studies. ... mass) gives a fair indication of the cumulative preweaning.

  14. Animal models for human genetic diseases

    African Journals Online (AJOL)

    Sharif Sons

    The study of human genetic diseases can be greatly aided by animal models because of their similarity .... and gene targeting in embryonic stem cells) has been a powerful tool in .... endonucleases that are designed to make a doublestrand.

  15. ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT, REMOVAL OF ARSENIC IN DRINKING WATER: WATTS PREMIER M-SERIES M-15,000 REVERSE OSMOSIS TREATMENT SYSTEM

    Science.gov (United States)

    Verification testing of the Watts Premier M-Series M-15,000 RO Treatment System was conducted over a 31-day period from April 26, 2004, through May 26, 2004. This test was conducted at the Coachella Valley Water District (CVWD) Well 7802 in Thermal, California. The source water...

  16. Alternate service delivery models in cancer genetic counseling: a mini-review

    Directory of Open Access Journals (Sweden)

    Adam Hudson Buchanan

    2016-05-01

    Full Text Available Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models such as telephone counseling, telegenetics and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology.

  17. Estimation and interpretation of genetic effects with epistasis using the NOIA model.

    Science.gov (United States)

    Alvarez-Castro, José M; Carlborg, Orjan; Rönnegård, Lars

    2012-01-01

    We introduce this communication with a brief outline of the historical landmarks in genetic modeling, especially concerning epistasis. Then, we present methods for the use of genetic modeling in QTL analyses. In particular, we summarize the essential expressions of the natural and orthogonal interactions (NOIA) model of genetic effects. Our motivation for reviewing that theory here is twofold. First, this review presents a digest of the expressions for the application of the NOIA model, which are often mixed with intermediate and additional formulae in the original articles. Second, we make the required theory handy for the reader to relate the genetic concepts to the particular mathematical expressions underlying them. We illustrate those relations by providing graphical interpretations and a diagram summarizing the key features for applying genetic modeling with epistasis in comprehensive QTL analyses. Finally, we briefly review some examples of the application of NOIA to real data and the way it improves the interpretability of the results.

  18. Genetic engineering in nonhuman primates for human disease modeling.

    Science.gov (United States)

    Sato, Kenya; Sasaki, Erika

    2018-02-01

    Nonhuman primate (NHP) experimental models have contributed greatly to human health research by assessing the safety and efficacy of newly developed drugs, due to their physiological and anatomical similarities to humans. To generate NHP disease models, drug-inducible methods, and surgical treatment methods have been employed. Recent developments in genetic and developmental engineering in NHPs offer new options for producing genetically modified disease models. Moreover, in recent years, genome-editing technology has emerged to further promote this trend and the generation of disease model NHPs has entered a new era. In this review, we summarize the generation of conventional disease model NHPs and discuss new solutions to the problem of mosaicism in genome-editing technology.

  19. See you at the match: Motivation for sport consumption and intrinsic psychological reward of premier football league spectators in South Africa

    Directory of Open Access Journals (Sweden)

    Frederick W. Stander

    2016-04-01

    Full Text Available Orientation: Local football contributes significantly to the social- and economic welfare of South Africa through its spectators. Understanding the motives and experiences of football spectators could provide opportunities for capitalising on football as revenue stream feeding the South African economy. Research purpose: To investigate how motives for sport consumption predict intrinsic psychological reward of South African premier league football spectators. Motivation for the study: Sport - particularly football - is an untapped resource for stimulating economic development and growth through its consumers. Spectators, who often experience their investment in the sport as deeply rewarding and meaningful, should participate more frequently in purchasing products or services associated with the sport. Through understanding the motives for sport consumption of South African premier league football spectators and the impact of these motives on intrinsic psychological reward experiences, football clubs are able to provide a targeted experience or service to spectators in order to further stimulate economic growth. Research design, approach and method: A census sample of 806 football spectators attending various matches at a football stadium in Soweto was drawn. A cross-sectional research design was implemented. This research was exploratory and descriptive. Structural equation modelling was implemented to assess the factor structures of the constructs, to confirm composite reliability of the measures and to assess the structural paths between the variables. Main findings: A predictive model for intrinsic psychological rewards (life satisfaction and meaning through the motivation for sport consumption (individual – and game related factors was confirmed. It was further established that motivation for sport consumption is significantly positively a related to and b associated with the experience of intrinsic psychological reward by South African

  20. Modeling genetic imprinting effects of DNA sequences with multilocus polymorphism data

    Directory of Open Access Journals (Sweden)

    Staud Roland

    2009-08-01

    Full Text Available Abstract Single nucleotide polymorphisms (SNPs represent the most widespread type of DNA sequence variation in the human genome and they have recently emerged as valuable genetic markers for revealing the genetic architecture of complex traits in terms of nucleotide combination and sequence. Here, we extend an algorithmic model for the haplotype analysis of SNPs to estimate the effects of genetic imprinting expressed at the DNA sequence level. The model provides a general procedure for identifying the number and types of optimal DNA sequence variants that are expressed differently due to their parental origin. The model is used to analyze a genetic data set collected from a pain genetics project. We find that DNA haplotype GAC from three SNPs, OPRKG36T (with two alleles G and T, OPRKA843G (with alleles A and G, and OPRKC846T (with alleles C and T, at the kappa-opioid receptor, triggers a significant effect on pain sensitivity, but with expression significantly depending on the parent from which it is inherited (p = 0.008. With a tremendous advance in SNP identification and automated screening, the model founded on haplotype discovery and statistical inference may provide a useful tool for genetic analysis of any quantitative trait with complex inheritance.

  1. Sleep and Development in Genetically Tractable Model Organisms.

    Science.gov (United States)

    Kayser, Matthew S; Biron, David

    2016-05-01

    Sleep is widely recognized as essential, but without a clear singular function. Inadequate sleep impairs cognition, metabolism, immune function, and many other processes. Work in genetic model systems has greatly expanded our understanding of basic sleep neurobiology as well as introduced new concepts for why we sleep. Among these is an idea with its roots in human work nearly 50 years old: sleep in early life is crucial for normal brain maturation. Nearly all known species that sleep do so more while immature, and this increased sleep coincides with a period of exuberant synaptogenesis and massive neural circuit remodeling. Adequate sleep also appears critical for normal neurodevelopmental progression. This article describes recent findings regarding molecular and circuit mechanisms of sleep, with a focus on development and the insights garnered from models amenable to detailed genetic analyses. Copyright © 2016 by the Genetics Society of America.

  2. A simple algorithm to estimate genetic variance in an animal threshold model using Bayesian inference Genetics Selection Evolution 2010, 42:29

    DEFF Research Database (Denmark)

    Ødegård, Jørgen; Meuwissen, Theo HE; Heringstad, Bjørg

    2010-01-01

    Background In the genetic analysis of binary traits with one observation per animal, animal threshold models frequently give biased heritability estimates. In some cases, this problem can be circumvented by fitting sire- or sire-dam models. However, these models are not appropriate in cases where...... records exist for the parents). Furthermore, the new algorithm showed much faster Markov chain mixing properties for genetic parameters (similar to the sire-dam model). Conclusions The new algorithm to estimate genetic parameters via Gibbs sampling solves the bias problems typically occurring in animal...... individual records exist on parents. Therefore, the aim of our study was to develop a new Gibbs sampling algorithm for a proper estimation of genetic (co)variance components within an animal threshold model framework. Methods In the proposed algorithm, individuals are classified as either "informative...

  3. Potential uses of genetic geological modelling to identify new uranium provinces

    International Nuclear Information System (INIS)

    Finch, W.I.

    1982-01-01

    Genetic-geological modelling is the placing of the various processes of the development of a uranium province into distinct stages that are ordered chronologically and made part of a matrix with corresponding geologic evidence. The models can be applied to a given region by using one of several methods to determine a numerical favorability rating. Two of the possible methods, geologic decision analysis and an oil-and-gas type of play analysis, are briefly described. Simplified genetic models are given for environments of the quartz-pebble conglomerate, unconformity-related vein, and sandstone types of deposits. Comparison of the genetic models of these three sedimentary-related environments reveals several common attributes that may define a general uranium province environment

  4. Genetics in endocrinology: genetic variation in deiodinases: a systematic review of potential clinical effects in humans.

    Science.gov (United States)

    Verloop, Herman; Dekkers, Olaf M; Peeters, Robin P; Schoones, Jan W; Smit, Johannes W A

    2014-09-01

    Iodothyronine deiodinases represent a family of selenoproteins involved in peripheral and local homeostasis of thyroid hormone action. Deiodinases are expressed in multiple organs and thyroid hormone affects numerous biological systems, thus genetic variation in deiodinases may affect multiple clinical endpoints. Interest in clinical effects of genetic variation in deiodinases has clearly increased. We aimed to provide an overview for the role of deiodinase polymorphisms in human physiology and morbidity. In this systematic review, studies evaluating the relationship between deiodinase polymorphisms and clinical parameters in humans were eligible. No restrictions on publication date were imposed. The following databases were searched up to August 2013: Pubmed, EMBASE (OVID-version), Web of Science, COCHRANE Library, CINAHL (EbscoHOST-version), Academic Search Premier (EbscoHOST-version), and ScienceDirect. Deiodinase physiology at molecular and tissue level is described, and finally the role of these polymorphisms in pathophysiological conditions is reviewed. Deiodinase type 1 (D1) polymorphisms particularly show moderate-to-strong relationships with thyroid hormone parameters, IGF1 production, and risk for depression. D2 variants correlate with thyroid hormone levels, insulin resistance, bipolar mood disorder, psychological well-being, mental retardation, hypertension, and risk for osteoarthritis. D3 polymorphisms showed no relationship with inter-individual variation in serum thyroid hormone parameters. One D3 polymorphism was associated with risk for osteoarthritis. Genetic deiodinase profiles only explain a small proportion of inter-individual variations in serum thyroid hormone levels. Evidence suggests a role of genetic deiodinase variants in certain pathophysiological conditions. The value for determination of deiodinase polymorphism in clinical practice needs further investigation. © 2014 European Society of Endocrinology.

  5. Portfolio optimization by using linear programing models based on genetic algorithm

    Science.gov (United States)

    Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

    2018-01-01

    In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

  6. Two-level mixed modeling of longitudinal pedigree data for genetic association analysis

    DEFF Research Database (Denmark)

    Tan, Q.

    2013-01-01

    of follow-up. Approaches have been proposed to integrate kinship correlation into the mixed effect models to explicitly model the genetic relationship which have been proven as an efficient way for dealing with sample clustering in pedigree data. Although useful for adjusting relatedness in the mixed...... assess the genetic associations with the mean level and the rate of change in a phenotype both with kinship correlation integrated in the mixed effect models. We apply our method to longitudinal pedigree data to estimate the genetic effects on systolic blood pressure measured over time in large pedigrees......Genetic association analysis on complex phenotypes under a longitudinal design involving pedigrees encounters the problem of correlation within pedigrees which could affect statistical assessment of the genetic effects on both the mean level of the phenotype and its rate of change over the time...

  7. Football fans and food: a case study of a football club in the English premier league.

    Science.gov (United States)

    Ireland, Robin; Watkins, Francine

    2010-05-01

    Although there is growing awareness of the impact of diet on health, little attention has been given to the food available in our sports stadia. We used a football club (Citygrene FC) - Citygrene is a fictional name - in the English Premier League as a case study to examine the attitudes of male and female football supporters to the food and drink available at their home stadium (Citygrene Stadium). The research design used five focus groups of male and female fans. The discourse was audiotaped, transcribed, coded and analysed for themes. A football stadium in the English Premier League, England. The participants were season ticket holders drawn from two stands at Citygrene Stadium. The research showed a high level of dissatisfaction with the food and drink supplied. There were key differences in the views of the male and female participants in the focus groups, with the women more concerned about wider issues such as the lack of healthy food. Both men and women were aware of their role as consumers and felt that there was an opportunity for Citygrene to improve their catering profits, if they provided a better selection of food and drink and an improved service. The study shows that there is a demand for healthier food options (and a wider choice of food and drink in general), which may provide an economic opportunity for stadium and catering managers. In addition, a stadium may be considered a potential 'healthy setting', which can serve as a supportive environment for healthier food choices.

  8. Glycemic index and glycemic load are associated with some cardiovascular risk factors among the PREMIER study participants

    Directory of Open Access Journals (Sweden)

    Pao-Hwa Lin

    2012-06-01

    Full Text Available Background: The clinical significance of glycemic index (GI and glycemic load (GL is inconclusive. Objective : This study was conducted to examine the association of GI and GL with clinical cardiovascular disease (CVD risk factors including body weight, blood pressure (BP, serum lipids, fasting glucose, insulin and homocysteine over time among the PREMIER participants. Design: PREMIER was an 18-month randomized lifestyle intervention trial, conducted from 2000 to 2002, designed to help participants reduce BP by following the Dietary Approaches to Stop Hypertension (DASH dietary pattern, losing weight, reducing sodium and increasing physical activity. GI and GL were estimated from 24 h diet recall data at baseline, 6 and 18 months after intervention. PROC MIXED model was used to examine the association of changes in GI or GL with changes in CVD risk factors. Results: A total of 756 randomized participants, 62% females and 34% African Americans and who averaged 50.0±0.3 years old and 95.3±0.7 kg, were included in this report. Neither GI nor GL changes was associated with changes in any risk factors at 6 months. At 18 months, however, the GI change was significantly and positively associated with total cholesterol (TC change only (p<0.05, β = 23.80±12.11 mg/dL or 0.62±0.31 mmol/L with a significant age interaction. The GL change was significantly associated with TC (p=0.02, β = 0.28±0.15 mg/dL or 0.01±0.00 mmol/L positively and with low density lipoprotein cholesterol (LDL-C changes negatively (p=0.03, β = − 0.01±0.00 mg/dL or −0.00±0.00 mmol/L, and significant age interactions were observed for both. Conclusion: GI and GL was associated with TC and LDL-C after controlling for energy, fat and fiber intake and other potential confounders and the associations were modified by age. Further investigation into this relationship is important because of its potential clinical impact.

  9. Model comparisons and genetic and environmental parameter ...

    African Journals Online (AJOL)

    arc

    Model comparisons and genetic and environmental parameter estimates of growth and the ... breeding strategies and for accurate breeding value estimation. The objectives ...... Sci. 23, 72-76. Van Wyk, J.B., Fair, M.D. & Cloete, S.W.P., 2003.

  10. Simulating pattern-process relationships to validate landscape genetic models

    Science.gov (United States)

    A. J. Shirk; S. A. Cushman; E. L. Landguth

    2012-01-01

    Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all...

  11. Shirt sponsorship by gambling companies in the English and Scottish Premier Leagues: global reach and public health concerns

    OpenAIRE

    Bunn, C.; Ireland, R.; Minton, J.; Holman, D.J.; Philpott, M.; Chambers, S.

    2018-01-01

    While the nature of gambling practices is contested, a strong evidence\\ud base demonstrates that gambling can become a serious disorder and have\\ud a range of detrimental effects for individuals, communities and societies.\\ud Over the last decade, football in the UK has become visibly entwined with\\ud gambling marketing. To explore this apparent trend, we tracked shirt\\ud sponsors in both the English and Scottish Premier Leagues since 1992 and\\ud found a pronounced increase in the presence of...

  12. Pengaruh Kualitas Pelayanan, Harga Dan Lokasi Terhadap Loyalitas Melalui Kepuasan Tamu Pada Santika Premiere Dyandra Hotel & Convention Medan

    OpenAIRE

    Tambunan, Susi Marta

    2016-01-01

    Santika Premiere Dyandra Hotel & Convention, Medan, is one of movers in hotel service industry which combines products and services, including the combination of service quality, price, and location in order to attract and provide satisfaction for its guests. It also pays attention to and gives expectation and needs for the guests by giving something correctly which are in line with the guests’ need by providing good performance so that they will be satisfied and will eventually be loyal to t...

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Shiori Yabe

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

  15. PM Synchronous Motor Dynamic Modeling with Genetic Algorithm ...

    African Journals Online (AJOL)

    Adel

    This paper proposes dynamic modeling simulation for ac Surface Permanent Magnet Synchronous ... Simulations are implemented using MATLAB with its genetic algorithm toolbox. .... selection, the process that drives biological evolution.

  16. The genetic analysis of repeated measures I: Simplex models

    NARCIS (Netherlands)

    Molenaar, P.C.M.; Boomsma, D.I.

    1987-01-01

    Extends the simplex model to a model that may be used for the genetic and environmental analysis of covariance (ANCOVA) structures. This "double" simplex structure can be specified as a linear structural relationships model. It is shown that data that give rise to a simplex correlation structure,

  17. Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models.

    Science.gov (United States)

    Moran, Paula; Stokes, Jennifer; Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John; O'Tuathaigh, Colm

    2016-01-01

    The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.

  18. Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

    Science.gov (United States)

    Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John

    2016-01-01

    The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia. PMID:27725886

  19. Genetic demixing and evolution in linear stepping stone models

    Science.gov (United States)

    Korolev, K. S.; Avlund, Mikkel; Hallatschek, Oskar; Nelson, David R.

    2010-04-01

    Results for mutation, selection, genetic drift, and migration in a one-dimensional continuous population are reviewed and extended. The population is described by a continuous limit of the stepping stone model, which leads to the stochastic Fisher-Kolmogorov-Petrovsky-Piscounov equation with additional terms describing mutations. Although the stepping stone model was first proposed for population genetics, it is closely related to “voter models” of interest in nonequilibrium statistical mechanics. The stepping stone model can also be regarded as an approximation to the dynamics of a thin layer of actively growing pioneers at the frontier of a colony of micro-organisms undergoing a range expansion on a Petri dish. The population tends to segregate into monoallelic domains. This segregation slows down genetic drift and selection because these two evolutionary forces can only act at the boundaries between the domains; the effects of mutation, however, are not significantly affected by the segregation. Although fixation in the neutral well-mixed (or “zero-dimensional”) model occurs exponentially in time, it occurs only algebraically fast in the one-dimensional model. An unusual sublinear increase is also found in the variance of the spatially averaged allele frequency with time. If selection is weak, selective sweeps occur exponentially fast in both well-mixed and one-dimensional populations, but the time constants are different. The relatively unexplored problem of evolutionary dynamics at the edge of an expanding circular colony is studied as well. Also reviewed are how the observed patterns of genetic diversity can be used for statistical inference and the differences are highlighted between the well-mixed and one-dimensional models. Although the focus is on two alleles or variants, q -allele Potts-like models of gene segregation are considered as well. Most of the analytical results are checked with simulations and could be tested against recent spatial

  20. Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Wafa Abdelmalek

    2009-01-01

    Full Text Available The volatility is a crucial variable in option pricing and hedging strategies. The aim of this paper is to provide some initial evidence of the empirical relevance of genetic programming to volatility's forecasting. By using real data from S&P500 index options, the genetic programming's ability to forecast Black and Scholes-implied volatility is compared between time series samples and moneyness-time to maturity classes. Total and out-of-sample mean squared errors are used as forecasting's performance measures. Comparisons reveal that the time series model seems to be more accurate in forecasting-implied volatility than moneyness time to maturity models. Overall, results are strongly encouraging and suggest that the genetic programming approach works well in solving financial problems.

  1. Genetic Resources in the “Calabaza Pipiana” Squash (Cucurbita argyrosperma) in Mexico: Genetic Diversity, Genetic Differentiation and Distribution Models

    Science.gov (United States)

    Sánchez-de la Vega, Guillermo; Castellanos-Morales, Gabriela; Gámez, Niza; Hernández-Rosales, Helena S.; Vázquez-Lobo, Alejandra; Aguirre-Planter, Erika; Jaramillo-Correa, Juan P.; Montes-Hernández, Salvador; Lira-Saade, Rafael; Eguiarte, Luis E.

    2018-01-01

    Analyses of genetic variation allow understanding the origin, diversification and genetic resources of cultivated plants. Domesticated taxa and their wild relatives are ideal systems for studying genetic processes of plant domestication and their joint is important to evaluate the distribution of their genetic resources. Such is the case of the domesticated subspecies C. argyrosperma ssp. argyrosperma, known in Mexico as calabaza pipiana, and its wild relative C. argyrosperma ssp. sororia. The main aim of this study was to use molecular data (microsatellites) to assess the levels of genetic variation and genetic differentiation within and among populations of domesticated argyrosperma across its distribution in Mexico in comparison to its wild relative, sororia, and to identify environmental suitability in previously proposed centers of domestication. We analyzed nine unlinked nuclear microsatellite loci to assess levels of diversity and distribution of genetic variation within and among populations in 440 individuals from 19 populations of cultivated landraces of argyrosperma and from six wild populations of sororia, in order to conduct a first systematic analysis of their genetic resources. We also used species distribution models (SDMs) for sororia to identify changes in this wild subspecies’ distribution from the Holocene (∼6,000 years ago) to the present, and to assess the presence of suitable environmental conditions in previously proposed domestication sites. Genetic variation was similar among subspecies (HE = 0.428 in sororia, and HE = 0.410 in argyrosperma). Nine argyrosperma populations showed significant levels of inbreeding. Both subspecies are well differentiated, and genetic differentiation (FST) among populations within each subspecies ranged from 0.152 to 0.652. Within argyrosperma we found three genetic groups (Northern Mexico, Yucatan Peninsula, including Michoacan and Veracruz, and Pacific coast plus Durango). We detected low levels of gene

  2. Genetic Resources in the “Calabaza Pipiana” Squash (Cucurbita argyrosperma in Mexico: Genetic Diversity, Genetic Differentiation and Distribution Models

    Directory of Open Access Journals (Sweden)

    Guillermo Sánchez-de la Vega

    2018-03-01

    Full Text Available Analyses of genetic variation allow understanding the origin, diversification and genetic resources of cultivated plants. Domesticated taxa and their wild relatives are ideal systems for studying genetic processes of plant domestication and their joint is important to evaluate the distribution of their genetic resources. Such is the case of the domesticated subspecies C. argyrosperma ssp. argyrosperma, known in Mexico as calabaza pipiana, and its wild relative C. argyrosperma ssp. sororia. The main aim of this study was to use molecular data (microsatellites to assess the levels of genetic variation and genetic differentiation within and among populations of domesticated argyrosperma across its distribution in Mexico in comparison to its wild relative, sororia, and to identify environmental suitability in previously proposed centers of domestication. We analyzed nine unlinked nuclear microsatellite loci to assess levels of diversity and distribution of genetic variation within and among populations in 440 individuals from 19 populations of cultivated landraces of argyrosperma and from six wild populations of sororia, in order to conduct a first systematic analysis of their genetic resources. We also used species distribution models (SDMs for sororia to identify changes in this wild subspecies’ distribution from the Holocene (∼6,000 years ago to the present, and to assess the presence of suitable environmental conditions in previously proposed domestication sites. Genetic variation was similar among subspecies (HE = 0.428 in sororia, and HE = 0.410 in argyrosperma. Nine argyrosperma populations showed significant levels of inbreeding. Both subspecies are well differentiated, and genetic differentiation (FST among populations within each subspecies ranged from 0.152 to 0.652. Within argyrosperma we found three genetic groups (Northern Mexico, Yucatan Peninsula, including Michoacan and Veracruz, and Pacific coast plus Durango. We detected low

  3. Perceptions of the Coach–Athlete Relationship Predict the Attainment of Mastery Achievement Goals Six Months Later: A Two-Wave Longitudinal Study among F. A. Premier League Academy Soccer Players

    Directory of Open Access Journals (Sweden)

    Adam R. Nicholls

    2017-05-01

    Full Text Available All football teams that compete within the F. A. Premier League possess an academy, whose objective is to produce more and better home-grown players that are capable of playing professionally. These young players spend a large amount of time with their coach, but little is known about player’s perception of the coach–athlete relationship within F. A. Premier League Academies. The objectives of this study were to examine whether perceptions of the coach–athlete relationship changed over six months and if the coach–athlete relationship predicted self-reported goal achievement among F. A. Premier League academy players. This study included cross-sectional (n = 104 and longitudinal (n = 52 assessments, in which academy soccer players completed a measure of the coach–athlete relationship and goal achievement across either one or two time periods. The cross-sectional data were subjected to bivariate correlations, whereas the longitudinal data were analyzed using multiple regressions. Perceptions of the coach–athlete relationship remained stable over time. The coach–athlete relationship predicted the achievement of mastery goals six months later. Enhancing the quality of the coach–athlete relationship among elite adolescent athletes appears to be a suitable way of maximizing mastery achievement goals, particularly among developmental athletes who participate in team sports.

  4. An animal model of differential genetic risk for methamphetamine intake

    Directory of Open Access Journals (Sweden)

    Tamara ePhillips

    2015-09-01

    Full Text Available The question of whether genetic factors contribute to risk for methamphetamine (MA use and dependence has not been intensively investigated. Compared to human populations, genetic animal models offer the advantages of control over genetic family history and drug exposure. Using selective breeding, we created lines of mice that differ in genetic risk for voluntary MA intake and identified the chromosomal addresses of contributory genes. A quantitative trait locus was identified on chromosome 10 that accounts for more than 50% of the genetic variance in MA intake in the selected mouse lines. In addition, behavioral and physiological screening identified differences corresponding with risk for MA intake that have generated hypotheses that are testable in humans. Heightened sensitivity to aversive and certain physiological effects of MA, such as MA-induced reduction in body temperature, are hallmarks of mice bred for low MA intake. Furthermore, unlike MA-avoiding mice, MA-preferring mice are sensitive to rewarding and reinforcing MA effects, and to MA-induced increases in brain extracellular dopamine levels. Gene expression analyses implicate the importance of a network enriched in transcription factor genes, some of which regulate the mu opioid receptor gene, Oprm1, in risk for MA use. Neuroimmune factors appear to play a role in differential response to MA between the mice bred for high and low intake. In addition, chromosome 10 candidate gene studies provide strong support for a trace amine associated receptor 1 gene, Taar1, polymorphism in risk for MA intake. MA is a trace amine-associated receptor 1 (TAAR1 agonist, and a non-functional Taar1 allele segregates with high MA consumption. Thus, reduced TAAR1 function has the potential to increase risk for MA use. Overall, existing findings support the MA drinking lines as a powerful model for identifying genetic factors involved in determining risk for harmful MA use. Future directions include the

  5. Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

    Directory of Open Access Journals (Sweden)

    Paula Moran

    2016-01-01

    Full Text Available The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.

  6. A Rational Model In Theoretical Genetics

    Directory of Open Access Journals (Sweden)

    Karl Javorszky

    2008-07-01

    Full Text Available This model connects information processing in biological organisms with methods and concepts used in classical, technical information processing. The central concept shows copying and regulatory interaction between a logical sequence consisting of triplets and the amount of constituents of a set. The basic mathematical model of information processing within a biological cell has been worked out. The cell in the model copies its present state into a sequence and reads it off the sequence. The sequence comes in triplets and is not one sequence but appears in two almost identical varieties. We treat consecutive and contemporary assemblies of information carrying media as equally suited to contain information. Methods used so far utilised the consecutive property of media, while in biology one observes the concurrent existence of specific realisations of possibilities. Genetics connects the two approaches by using an interplay between consecutively (sequentially ordered logical markers (the DNA and the state of the set engulfing the DNA. Several mathematical tools have been evolved to assemble an interface between sequentially ordered carriers and the same number of carriers if they arrive contemporaneously. Using linguistic theory and formal logic one concludes that measurement(s on a cell are a (set of logical sentence(s relating to an assembly of n objects with group structures among each other. We linearise and count all possible group relations on a set of n objects and introduce the concept of multidimensional partitions hitherto left undefined. We introduce the concept of a maximally structured set by establishing an upper limit to the information carrying capacity of n objects used commutatively and sequentially at the same time (like genetics does. The copying and re-copying mechanism which is the core matter with genetics appears in the model as differing transmission efficiency coefficients of media if the media are used once sequentially

  7. Les premiers pas d’Agnon à Jaffa (1908-1912 First Steps of S.Y. Agnon in Jaffa (1908-1912 ראשית דרכו של עגנון ביפו (1908 עד 1912

    Directory of Open Access Journals (Sweden)

    Masha Itzhaki

    2012-11-01

    Full Text Available Les premiers pas du célèbre auteur S. Y. Agnon lors de son premier séjour à Jaffa (1908-1912 sont liés aux deux revues hébraïques : Ha-Omer, histoire d’un échec, et Ha-po‘el ha-tsa‘ir, histoire d’une réussite, et aux rédacteurs en chef de ces revues, les écrivains et pères spirituels du jeune Agnon, Sh. Ben Tzion, un écrivain esthétique, bourgeois, et Y. H. Brenner, un penseur tourmenté, un véritable intellectuel socialiste.The first period of the famous writer S. Y. Agnon in Jaffa (1908-1912 has a lot to do with two literary Hebrew periodicals: Ha-Omer, a story of a failure, and Ha-po‘el ha-tsa‘ir, a successful one, as well as  with two major figures in Hebrew literary milieu at that time, the editors, Sh. Ben Tzion and Y. H. Brenner.

  8. Genetics of traffic assignment models for strategic transport planning

    NARCIS (Netherlands)

    Bliemer, M.C.J.; Raadsen, M.P.H.; Brederode, L.J.N.; Bell, M.G.H.; Wismans, Luc Johannes Josephus; Smith, M.J.

    2016-01-01

    This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic

  9. Cross-validation analysis for genetic evaluation models for ranking in endurance horses.

    Science.gov (United States)

    García-Ballesteros, S; Varona, L; Valera, M; Gutiérrez, J P; Cervantes, I

    2018-01-01

    Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider-horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider-horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In

  10. Applicability of genetic algorithms to parameter estimation of economic models

    Directory of Open Access Journals (Sweden)

    Marcel Ševela

    2004-01-01

    Full Text Available The paper concentrates on capability of genetic algorithms for parameter estimation of non-linear economic models. In the paper we test the ability of genetic algorithms to estimate of parameters of demand function for durable goods and simultaneously search for parameters of genetic algorithm that lead to maximum effectiveness of the computation algorithm. The genetic algorithms connect deterministic iterative computation methods with stochastic methods. In the genteic aůgorithm approach each possible solution is represented by one individual, those life and lifes of all generations of individuals run under a few parameter of genetic algorithm. Our simulations resulted in optimal mutation rate of 15% of all bits in chromosomes, optimal elitism rate 20%. We can not set the optimal extend of generation, because it proves positive correlation with effectiveness of genetic algorithm in all range under research, but its impact is degreasing. The used genetic algorithm was sensitive to mutation rate at most, than to extend of generation. The sensitivity to elitism rate is not so strong.

  11. Associated chemical and carbon isotopic composition variations in diamonds from Finsch and Premier kimberlite, South Africa

    International Nuclear Information System (INIS)

    Deines, P.

    1984-01-01

    The carbon isotopic composition of 66 inclusion-containing diamonds from the Premier kimberlite, South Africa, 93 inclusion-containing diamonds and four diamonds of two diamond-bearing peridotite xenoliths from the Finsch kimberlite, South Africa was measured. The data suggest a relationship between the carbon isotopic composition of the diamonds and the chemical composition of the associated silicates. For both kimberlites similar trends are noted for diamonds containing peridotite-suite inclusions (P-type) and for diamonds containing eclogite-suite inclusions (E-type): Higher delta 13 C P-type diamonds tend to have inclusions lower in SiO 2 , Al 2 O 3 , Cr 2 O 3 , MgO, Mg/(Mg + Fe) and higher in FeO and CaO. Higher delta 13 C E-type diamonds tend to have inclusions lower in SiO 2 , Al 2 O 3 , MgO, Mg/(Mg + Fe), Na 2 O, K 2 O, TiO 2 and higher in CaO, Ca/(Ca + Mg). Consideration of a number of different models that have been proposed for the genesis of kimberlites, their zenoliths and diamonds shows that they are all consistent with the conclusion that in the mantle, regions exist that are characterized by different mean carbon isotopic compositions. (author)

  12. Genetic algorithms and experimental discrimination of SUSY models

    International Nuclear Information System (INIS)

    Allanach, B.C.; Quevedo, F.; Grellscheid, D.

    2004-01-01

    We introduce genetic algorithms as a means to estimate the accuracy required to discriminate among different models using experimental observables. We exemplify the technique in the context of the minimal supersymmetric standard model. If supersymmetric particles are discovered, models of supersymmetry breaking will be fit to the observed spectrum and it is beneficial to ask beforehand: what accuracy is required to always allow the discrimination of two particular models and which are the most important masses to observe? Each model predicts a bounded patch in the space of observables once unknown parameters are scanned over. The questions can be answered by minimising a 'distance' measure between the two hypersurfaces. We construct a distance measure that scales like a constant fraction of an observable, since that is how the experimental errors are expected to scale. Genetic algorithms, including concepts such as natural selection, fitness and mutations, provide a solution to the minimisation problem. We illustrate the efficiency of the method by comparing three different classes of string models for which the above questions could not be answered with previous techniques. The required accuracy is in the range accessible to the Large Hadron Collider (LHC) when combined with a future linear collider (LC) facility. The technique presented here can be applied to more general classes of models or observables. (author)

  13. Initial assessment of a model relating intratumoral genetic heterogeneity to radiological morphology

    Science.gov (United States)

    Noterdaeme, O; Kelly, M; Friend, P; Soonowalla, Z; Steers, G; Brady, M

    2010-01-01

    Tumour heterogeneity has major implications for tumour development and response to therapy. Tumour heterogeneity results from mutations in the genes responsible for mismatch repair or maintenance of chromosomal stability. Cells with different genetic properties may grow at different rates and exhibit different resistance to therapeutic interventions. To date, there exists no approach to non-invasively assess tumour heterogeneity. Here we present a biologically inspired model of tumour growth, which relates intratumoral genetic heterogeneity to gross morphology visible on radiological images. The model represents the development of a tumour as a set of expanding spheres, each sphere representing a distinct clonal centre, with the sprouting of new spheres corresponding to new clonal centres. Each clonal centre may possess different characteristics relating to genetic composition, growth rate and response to treatment. We present a clinical example for which the model accurately tracks tumour growth and shows the correspondence to genetic variation (as determined by array comparative genomic hybridisation). One clinical implication of our work is that the assessment of heterogeneous tumours using Response Evaluation Criteria In Solid Tumours (RECIST) or volume measurements may not accurately reflect tumour growth, stability or the response to treatment. We believe that this is the first model linking the macro-scale appearance of tumours to their genetic composition. We anticipate that our model will provide a more informative way to assess the response of heterogeneous tumours to treatment, which is of increasing importance with the development of novel targeted anti-cancer treatments. PMID:19690073

  14. Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

    Science.gov (United States)

    Louis, S.J.; Raines, G.L.

    2003-01-01

    We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

  15. Different concepts and models of information for family-relevant genetic findings: comparison and ethical analysis.

    Science.gov (United States)

    Lenk, Christian; Frommeld, Debora

    2015-08-01

    Genetic predispositions often concern not only individual persons, but also other family members. Advances in the development of genetic tests lead to a growing number of genetic diagnoses in medical practice and to an increasing importance of genetic counseling. In the present article, a number of ethical foundations and preconditions for this issue are discussed. Four different models for the handling of genetic information are presented and analyzed including a discussion of practical implications. The different models' ranges of content reach from a strictly autonomous position over self-governed arrangements in the practice of genetic counseling up to the involvement of official bodies and committees. The different models show a number of elements which seem to be very useful for the handling of genetic data in families from an ethical perspective. In contrast, the limitations of the standard medical attempt regarding confidentiality and personal autonomy in the context of genetic information in the family are described. Finally, recommendations for further ethical research and the development of genetic counseling in families are given.

  16. Evaluation of sports nutrition knowledge of New Zealand premier club rugby coaches.

    Science.gov (United States)

    Zinn, Caryn; Schofield, Grant; Wall, Clare

    2006-04-01

    Little is known about if and how team coaches disseminate nutrition information to athletes. In a census survey, New Zealand premier rugby coaches (n = 168) completed a psychometrically validated questionnaire, received by either Internet or standard mail (response rate, 46%), identifying their nutrition advice dissemination practices to players, their level of nutrition knowledge, and the factors determining this level of knowledge. The majority of coaches provided advice to their players (83.8%). Coaches responded correctly to 55.6% of all knowledge questions. An independent t-test showed coaches who imparted nutrition advice obtained a significantly greater score, 56.8%, than those not imparting advice, 48.4% (P = 0.008). One-way ANOVA showed significant relationships between total knowledge score of all coaches and qualifications [F(1,166) = 5.28, P = 0.001], own knowledge rating [F(3,164) = 6.88, P = 0.001] and nutrition training [F(1,166) = 9.83, P = 0.002]. We conclude that these rugby coaches were inadequately prepared to impart nutrition advice to athletes and could benefit from further nutrition training.

  17. Population genetics models of local ancestry.

    Science.gov (United States)

    Gravel, Simon

    2012-06-01

    Migrations have played an important role in shaping the genetic diversity of human populations. Understanding genomic data thus requires careful modeling of historical gene flow. Here we consider the effect of relatively recent population structure and gene flow and interpret genomes of individuals that have ancestry from multiple source populations as mosaics of segments originating from each population. This article describes general and tractable models for local ancestry patterns with a focus on the length distribution of continuous ancestry tracts and the variance in total ancestry proportions among individuals. The models offer improved agreement with Wright-Fisher simulation data when compared to the state-of-the art and can be used to infer time-dependent migration rates from multiple populations. Considering HapMap African-American (ASW) data, we find that a model with two distinct phases of "European" gene flow significantly improves the modeling of both tract lengths and ancestry variances.

  18. Parallel Genetic Algorithms for calibrating Cellular Automata models: Application to lava flows

    International Nuclear Information System (INIS)

    D'Ambrosio, D.; Spataro, W.; Di Gregorio, S.; Calabria Univ., Cosenza; Crisci, G.M.; Rongo, R.; Calabria Univ., Cosenza

    2005-01-01

    Cellular Automata are highly nonlinear dynamical systems which are suitable far simulating natural phenomena whose behaviour may be specified in terms of local interactions. The Cellular Automata model SCIARA, developed far the simulation of lava flows, demonstrated to be able to reproduce the behaviour of Etnean events. However, in order to apply the model far the prediction of future scenarios, a thorough calibrating phase is required. This work presents the application of Genetic Algorithms, general-purpose search algorithms inspired to natural selection and genetics, far the parameters optimisation of the model SCIARA. Difficulties due to the elevated computational time suggested the adoption a Master-Slave Parallel Genetic Algorithm far the calibration of the model with respect to the 2001 Mt. Etna eruption. Results demonstrated the usefulness of the approach, both in terms of computing time and quality of performed simulations

  19. Linear systems surviving the first breakdown; Systemes unbaires survivant a la premiere panne

    Energy Technology Data Exchange (ETDEWEB)

    Uberschlag, J [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1967-07-01

    Various types of linear systems are described which are not affected by the first breakdown. They make it possible to operate continuously and are thus very reliable. This is because the first breakdown which occurs affects only very slightly the operation. These components can be replaced during working. The operation, the errors, and the detection are briefly considered in the case of three different designs of linear servo systems. An attempt at comparison is made, it could be developed in a particular case. (author) [French] On decrit divers types de systemes lineaires survivant a la premiere panne. Ils permettent un fonctionnement permanent et sont donc d'une tres grande fiabilite. En effet, une panne, qui peut etre signalee, perturbe peu le fonctionnement. Ces composants peuvent etre remplaces en marche. Les considerations de fonctionnement, d'erreur, de detection des pannes sont succinctement presentees, sur trois schemas de systemes lineaires asservis. Une tentative de comparaison est faite, qui pourrait etre developpee dans des cas precis. (auteur)

  20. Towards Improving our Understanding on the Retrievals of Key Parameters Characterising Land Surface Interactions from Space: Introduction & First Results from the PREMIER-EO Project

    Science.gov (United States)

    Ireland, Gareth; North, Matthew R.; Petropoulos, George P.; Srivastava, Prashant K.; Hodges, Crona

    2015-04-01

    Acquiring accurate information on the spatio-temporal variability of soil moisture content (SM) and evapotranspiration (ET) is of key importance to extend our understanding of the Earth system's physical processes, and is also required in a wide range of multi-disciplinary research studies and applications. The utility and applicability of Earth Observation (EO) technology provides an economically feasible solution to derive continuous spatio-temporal estimates of key parameters characterising land surface interactions, including ET as well as SM. Such information is of key value to practitioners, decision makers and scientists alike. The PREMIER-EO project recently funded by High Performance Computing Wales (HPCW) is a research initiative directed towards the development of a better understanding of EO technology's present ability to derive operational estimations of surface fluxes and SM. Moreover, the project aims at addressing knowledge gaps related to the operational estimation of such parameters, and thus contribute towards current ongoing global efforts towards enhancing the accuracy of those products. In this presentation we introduce the PREMIER-EO project, providing a detailed overview of the research aims and objectives for the 1 year duration of the project's implementation. Subsequently, we make available the initial results of the work carried out herein, in particular, related to an all-inclusive and robust evaluation of the accuracy of existing operational products of ET and SM from different ecosystems globally. The research outcomes of this project, once completed, will provide an important contribution towards addressing the knowledge gaps related to the operational estimation of ET and SM. This project results will also support efforts ongoing globally towards the operational development of related products using technologically advanced EO instruments which were launched recently or planned be launched in the next 1-2 years. Key Words: PREMIER

  1. Genetic Algorithm Based Microscale Vehicle Emissions Modelling

    Directory of Open Access Journals (Sweden)

    Sicong Zhu

    2015-01-01

    Full Text Available There is a need to match emission estimations accuracy with the outputs of transport models. The overall error rate in long-term traffic forecasts resulting from strategic transport models is likely to be significant. Microsimulation models, whilst high-resolution in nature, may have similar measurement errors if they use the outputs of strategic models to obtain traffic demand predictions. At the microlevel, this paper discusses the limitations of existing emissions estimation approaches. Emission models for predicting emission pollutants other than CO2 are proposed. A genetic algorithm approach is adopted to select the predicting variables for the black box model. The approach is capable of solving combinatorial optimization problems. Overall, the emission prediction results reveal that the proposed new models outperform conventional equations in terms of accuracy and robustness.

  2. Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

    Science.gov (United States)

    Sastry, Kumara Narasimha

    2007-03-01

    Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common

  3. Model parameters estimation and sensitivity by genetic algorithms

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca

    2003-01-01

    In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The

  4. [The discussion of the infiltrative model of mathematical knowledge to genetics teaching].

    Science.gov (United States)

    Liu, Jun; Luo, Pei-Gao

    2011-11-01

    Genetics, the core course of biological field, is an importance major-basic course in curriculum of many majors related with biology. Due to strong theoretical and practical as well as abstract of genetics, it is too difficult to study on genetics for many students. At the same time, mathematics is one of the basic courses in curriculum of the major related natural science, which has close relationship with the establishment, development and modification of genetics. In this paper, to establish the intrinsic logistic relationship and construct the integral knowledge network and to help students improving the analytic, comprehensive and logistic abilities, we applied some mathematical infiltrative model genetic knowledge in genetics teaching, which could help students more deeply learn and understand genetic knowledge.

  5. Research on interactive genetic-geological models to evaluate favourability for undiscovered uranium resources

    International Nuclear Information System (INIS)

    Finch, W.I.; Granger, H.C.; Lupe, R.; McCammon, R.B.

    1980-01-01

    Current methods of evaluating favourability for undiscovered uranium resources are unduly subjective, quite possibly inconsistent and, as a consequence, of questionable reliability. This research is aimed at reducing the subjectivity and increasing the reliability by designing an improved method that depends largely on geological data and their statistical frequency of occurrence. This progress report outlines a genetic approach to modelling the geological factors that controlled uranium mineralization in order to evaluate the favourability for the occurrence of undiscovered uranium deposits of the type modelled. A genetic model is constructed from all the factors that describe the processes, in chronological sequence, that formed uranium deposits thought to have a common origin. The field and laboratory evidence for the processes constitute a geologic-occurrence base that parallels the chronological sequence of events. The genetic model and the geologic-occurrence base are portrayed as two columns of an interactive matrix called the ''genetic-geologic model''. For each column, eight chronological stages are used to describe the overall formation of the uranium deposits. These stages consist of (1) precursor processes; (2) host-rock formation; (3) preparation of host-rock; (4) uranium-source development; (5) transport of uranium; (6) primary uranium deposition; (7) post-deposition modification; and (8) preservation. To apply the genetic-geological model to evaluate favourability, a question is posed that determines the presence or absence of each attribute listed under the geologic-occurrence base. By building a logic circuit of the attributes according to either their essential or non-essential nature, the resultant match between a well-documented control area and the test area may be determined. The degree of match is a measure of favourability for uranium occurrence as hypothesized in the genetic model

  6. Genetic Process Mining: Alignment-based Process Model Mutation

    NARCIS (Netherlands)

    Eck, van M.L.; Buijs, J.C.A.M.; Dongen, van B.F.; Fournier, F.; Mendling, J.

    2015-01-01

    The Evolutionary Tree Miner (ETM) is a genetic process discovery algorithm that enables the user to guide the discovery process based on preferences with respect to four process model quality dimensions: replay fitness, precision, generalization and simplicity. Traditionally, the ETM algorithm uses

  7. Estimation in a multiplicative mixed model involving a genetic relationship matrix

    Directory of Open Access Journals (Sweden)

    Eccleston John A

    2009-04-01

    Full Text Available Abstract Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

  8. Genetic search feature selection for affective modeling

    DEFF Research Database (Denmark)

    Martínez, Héctor P.; Yannakakis, Georgios N.

    2010-01-01

    Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

  9. Emerging technologies to create inducible and genetically defined porcine cancer models

    Directory of Open Access Journals (Sweden)

    Lawrence B Schook

    2016-02-01

    Full Text Available There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research.

  10. Emerging Technologies to Create Inducible and Genetically Defined Porcine Cancer Models.

    Science.gov (United States)

    Schook, Lawrence B; Rund, Laurie; Begnini, Karine R; Remião, Mariana H; Seixas, Fabiana K; Collares, Tiago

    2016-01-01

    There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic, and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research.

  11. Quantitative genetics of Taura syndrome resistance in Pacific (Penaeus vannamei): A cure model approach

    DEFF Research Database (Denmark)

    Ødegård, Jørgen; Gitterle, Thomas; Madsen, Per

    2011-01-01

    cure survival model using Gibbs sampling, treating susceptibility and endurance as separate genetic traits. Results: Overall mortality at the end of test was 28%, while 38% of the population was considered susceptible to the disease. The estimated underlying heritability was high for susceptibility (0....... However, genetic evaluation of susceptibility based on the cure model showed clear associations with standard genetic evaluations that ignore the cure fraction for these data. Using the current testing design, genetic variation in observed survival time and absolute survival at the end of test were most...

  12. Genetic hotels for the standard genetic code: evolutionary analysis based upon novel three-dimensional algebraic models.

    Science.gov (United States)

    José, Marco V; Morgado, Eberto R; Govezensky, Tzipe

    2011-07-01

    Herein, we rigorously develop novel 3-dimensional algebraic models called Genetic Hotels of the Standard Genetic Code (SGC). We start by considering the primeval RNA genetic code which consists of the 16 codons of type RNY (purine-any base-pyrimidine). Using simple algebraic operations, we show how the RNA code could have evolved toward the current SGC via two different intermediate evolutionary stages called Extended RNA code type I and II. By rotations or translations of the subset RNY, we arrive at the SGC via the former (type I) or via the latter (type II), respectively. Biologically, the Extended RNA code type I, consists of all codons of the type RNY plus codons obtained by considering the RNA code but in the second (NYR type) and third (YRN type) reading frames. The Extended RNA code type II, comprises all codons of the type RNY plus codons that arise from transversions of the RNA code in the first (YNY type) and third (RNR) nucleotide bases. Since the dimensions of remarkable subsets of the Genetic Hotels are not necessarily integer numbers, we also introduce the concept of algebraic fractal dimension. A general decoding function which maps each codon to its corresponding amino acid or the stop signals is also derived. The Phenotypic Hotel of amino acids is also illustrated. The proposed evolutionary paths are discussed in terms of the existing theories of the evolution of the SGC. The adoption of 3-dimensional models of the Genetic and Phenotypic Hotels will facilitate the understanding of the biological properties of the SGC.

  13. Medulloblastoma: Molecular Genetics and Animal Models

    Directory of Open Access Journals (Sweden)

    Corey Raffel

    2004-07-01

    Full Text Available Medulloblastoma is a primary brain tumor found in the cerebellum of children. The tumor occurs in association with two inherited cancer syndromes: Turcot syndrome and Gorlin syndrome. Insights into the molecular biology of the tumor have come from looking at alterations in the genes altered in these syndromes, PTC and APC, respectively. Murine models of medulloblastoma have been constructed based on these alterations. Additional murine models that, while mimicking the appearance of the human tumor, seem unrelated to the human tumor's molecular alterations have been made. In this review, the clinical picture, origin, molecular biology, murine models of medulloblastoma are discussed. Although a great deal has been discovered about this tumor, the genetic alterations responsible for tumor development in a majority of patients have yet to be described.

  14. Structurations formelle et conceptuelle des articles de dictionnaires : le premier modèle de codification des articles dans l’histoire des dictionnaires Larousse

    Directory of Open Access Journals (Sweden)

    Corbin Pierre

    2014-07-01

    Nous nous proposons d’examiner, dans l’histoire des dictionnaires généraux monolingues Larousse des origines à nos jours, une sélection de jalons de l’articulation entre structure conceptuelle et structure formelle des articles. Au regard de l’ampleur des données à couvrir, il ne pourra bien entendu s’agir que d’un survol, mais celui-ci permettra (1 de présenter le premier des trois modèles majeurs de codification des articles dans l’histoire des dictionnaires Larousse, celui qui trouve son origine dans le Nouveau dictionnaire de la langue française de 1856 ou ses éditions révisées, (2 de prendre en compte les dictionnaires proposés par cet éditeur en un siècle et demi qui ont repris le modèle de 1856 ou sa forme révisée, et (3 de présenter contrastivement au premier les deux autres modèles majeurs, qui trouvent leur ancrage chronologique respectivement dans le Grand dictionnaire universel du XIXe siècle de 1866-1876 et le Dictionnaire du français contemporain de 1966.

  15. Technical and tactical training team «Helios» Kharkiv in the first round of 23 Ukrainian football championship in the premier league 2013–2014

    Directory of Open Access Journals (Sweden)

    Rebaz Sleman

    2014-10-01

    Full Text Available Purpose: to define the characteristics of the model command of technical and tactical training team participating in the Ukrainian Premier League First League. Material and Methods: the research was conducted using the method of peer review. The experts were involved 5 specialists football. Results: the mean values for the analyzed variables in 10 games. The various technical and tactical actions and their percentage in the overall structure of the game team statistics for 20 games, as well as some indicators of team play "Helios" Kharkov. Conclusions: the obtained quantitative and qualitative indicators (coefficient of marriage as a team on the technical and tactical actions, as well as separately for each technical and tactical reception. The performances allow you to make adjustments to the training process this command to improve sportsmanship.

  16. Genetic models of absence epilepsy: New concepts and insights

    NARCIS (Netherlands)

    Luijtelaar, E.L.J.M. van; Coenen, A.M.L.; Schwartzkroin, P.A.

    2009-01-01

    The discovery, development, and use of genetic rodent models of absence epilepsy have led to a new theory about the origin of absence seizures. A focal zone has been identified in the peri-oral region of the somatosensory cortex in WAG/Rij and GAERS – the two most commonly used models – from which

  17. Dynamic modeling of genetic networks using genetic algorithm and S-system.

    Science.gov (United States)

    Kikuchi, Shinichi; Tominaga, Daisuke; Arita, Masanori; Takahashi, Katsutoshi; Tomita, Masaru

    2003-03-22

    The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters; (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability; and (3) a gradual optimization strategy to increase the number of predictable parameters. The proposed method is implemented as a C program called PEACE1 (Predictor by Evolutionary Algorithms and Canonical Equations 1). Its performance was compared with the basic method. The comparison showed that: (1) the convergence rate increased about 5-fold; (2) the optimization speed was raised about 1.5-fold; and (3) the number of predictable parameters was increased about 5-fold. Moreover, we successfully inferred the dynamics of a small genetic network constructed with 60 parameters for 5 network variables and feedback loops using only time-course data of gene expression.

  18. Genetic mouse models relevant to schizophrenia: taking stock and looking forward.

    Science.gov (United States)

    Harrison, Paul J; Pritchett, David; Stumpenhorst, Katharina; Betts, Jill F; Nissen, Wiebke; Schweimer, Judith; Lane, Tracy; Burnet, Philip W J; Lamsa, Karri P; Sharp, Trevor; Bannerman, David M; Tunbridge, Elizabeth M

    2012-03-01

    Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene-gene and gene-environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue. Copyright © 2011 Elsevier Ltd. All rights reserved.

  19. Models for Estimating Genetic Parameters of Milk Production Traits Using Random Regression Models in Korean Holstein Cattle

    Directory of Open Access Journals (Sweden)

    C. I. Cho

    2016-05-01

    Full Text Available The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs, and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK, fat yield (FAT, protein yield (PROT, and solids-not-fat yield (SNF. The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP of the third to fifth order (L3–L5, fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order. The residual variances in the models were either homogeneous (HOM or heterogeneous (15 classes, HET15; 60 classes, HET60. A total of nine models (3 orders of polynomials×3 types of residual variance including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC and/or Schwarz Bayesian information criteria (BIC statistics to identify the model(s of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF and L4-HET15 (FAT, which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first

  20. ENU mutagenesis to generate genetically modified rat models

    NARCIS (Netherlands)

    van Boxtel, R.; Gould, M.; Cuppen, E.; Smits, B.M.

    2010-01-01

    The rat is one of the most preferred model organisms in biomedical research and has been extremely useful for linking physiology and pathology to the genome. However, approaches to genetically modify specific genes in the rat germ line remain relatively scarce. To date, the most efficient approach

  1. A review of animal models used to evaluate potential allergenicity of genetically modified organisms (GMOs)

    DEFF Research Database (Denmark)

    Marsteller, Nathan; Bøgh, Katrine Lindholm; Goodman, Richard E.

    2017-01-01

    Food safety regulators request prediction of allergenicity for newly expressed proteins in genetically modified (GM) crops and in novel foods. Some have suggested using animal models to assess potential allergenicity. A variety of animal models have been used in research to evaluate sensitisation...... of genetically modified organisms (GMOs).......Food safety regulators request prediction of allergenicity for newly expressed proteins in genetically modified (GM) crops and in novel foods. Some have suggested using animal models to assess potential allergenicity. A variety of animal models have been used in research to evaluate sensitisation...

  2. Applications of Systems Genetics and Biology for Obesity Using Pig Models

    DEFF Research Database (Denmark)

    Kogelman, Lisette; Kadarmideen, Haja N.

    2016-01-01

    approach, a branch of systems biology. In this chapter, we will describe the state of the art of genetic studies on human obesity, using pig populations. We will describe the features of using the pig as a model for human obesity and briefly discuss the genetics of obesity, and we will focus on systems...

  3. Genetic Modeling of Radiation Injury in Prostate Cancer Patients Treated with Radiotherapy

    Science.gov (United States)

    2017-10-01

    AWARD NUMBER: W81XWH-15-1-0681 TITLE: Genetic Modeling of Radiation Injury in Prostate Cancer Patients Treated with Radiotherapy PRINCIPAL...TITLE AND SUBTITLE 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-15-1-0681Genetic Modeling of Radiation Injury in Prostate Cancer Patients Treated...effects, urinary morbidity, rectal injury, sexual dysfunction 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF

  4. Energy Intake and Expenditure of Professional Soccer Players of the English Premier League: Evidence of Carbohydrate Periodization.

    Science.gov (United States)

    Anderson, Liam; Orme, Patrick; Naughton, Robert J; Close, Graeme L; Milsom, Jordan; Rydings, David; O'Boyle, Andy; Di Michele, Rocco; Louis, Julien; Hambly, Catherine; Speakman, John Roger; Morgans, Ryland; Drust, Barry; Morton, James P

    2017-06-01

    In an attempt to better identify and inform the energy requirements of elite soccer players, we quantified the energy expenditure (EE) of players from the English Premier League (n = 6) via the doubly labeled water method (DLW) over a 7-day in-season period. Energy intake (EI) was also assessed using food diaries, supported by the remote food photographic method and 24 hr recalls. The 7-day period consisted of 5 training days (TD) and 2 match days (MD). Although mean daily EI (3186 ± 367 kcals) was not different from (p > .05) daily EE (3566 ± 585 kcals), EI was greater (p recovery from match play was not in accordance with guidelines to promote muscle glycogen storage.

  5. Equilibrium and non-equilibrium concepts in forest genetic modelling: population- and individually-based approaches

    OpenAIRE

    Kramer, Koen; van der Werf, D. C.

    2010-01-01

    The environment is changing and so are forests, in their functioning, in species composition, and in the species’ genetic composition. Many empirical and process-based models exist to support forest management. However, most of these models do not consider the impact of environmental changes and forest management on genetic diversity nor on the rate of adaptation of critical plant processes. How genetic diversity and rates of adaptation depend on management actions is a crucial next step in m...

  6. Model-based problem solving through symbolic regression via pareto genetic programming

    NARCIS (Netherlands)

    Vladislavleva, E.

    2008-01-01

    Pareto genetic programming methodology is extended by additional generic model selection and generation strategies that (1) drive the modeling engine to creation of models of reduced non-linearity and increased generalization capabilities, and (2) improve the effectiveness of the search for robust

  7. Genetics on the Fly: A Primer on the Drosophila Model System

    Science.gov (United States)

    Hales, Karen G.; Korey, Christopher A.; Larracuente, Amanda M.; Roberts, David M.

    2015-01-01

    Fruit flies of the genus Drosophila have been an attractive and effective genetic model organism since Thomas Hunt Morgan and colleagues made seminal discoveries with them a century ago. Work with Drosophila has enabled dramatic advances in cell and developmental biology, neurobiology and behavior, molecular biology, evolutionary and population genetics, and other fields. With more tissue types and observable behaviors than in other short-generation model organisms, and with vast genome data available for many species within the genus, the fly’s tractable complexity will continue to enable exciting opportunities to explore mechanisms of complex developmental programs, behaviors, and broader evolutionary questions. This primer describes the organism’s natural history, the features of sequenced genomes within the genus, the wide range of available genetic tools and online resources, the types of biological questions Drosophila can help address, and historical milestones. PMID:26564900

  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

    2017-01-01

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

  9. Estimation of genetic parameters related to eggshell strength using random regression models.

    Science.gov (United States)

    Guo, J; Ma, M; Qu, L; Shen, M; Dou, T; Wang, K

    2015-01-01

    This study examined the changes in eggshell strength and the genetic parameters related to this trait throughout a hen's laying life using random regression. The data were collected from a crossbred population between 2011 and 2014, where the eggshell strength was determined repeatedly for 2260 hens. Using random regression models (RRMs), several Legendre polynomials were employed to estimate the fixed, direct genetic and permanent environment effects. The residual effects were treated as independently distributed with heterogeneous variance for each test week. The direct genetic variance was included with second-order Legendre polynomials and the permanent environment with third-order Legendre polynomials. The heritability of eggshell strength ranged from 0.26 to 0.43, the repeatability ranged between 0.47 and 0.69, and the estimated genetic correlations between test weeks was high at > 0.67. The first eigenvalue of the genetic covariance matrix accounted for about 97% of the sum of all the eigenvalues. The flexibility and statistical power of RRM suggest that this model could be an effective method to improve eggshell quality and to reduce losses due to cracked eggs in a breeding plan.

  10. The evolution of menstruation: A new model for genetic assimilation

    Science.gov (United States)

    Emera, D.; Romero, R.; Wagner, G.

    2012-01-01

    Why do humans menstruate while most mammals do not? Here, we present our answer to this long-debated question, arguing that (i) menstruation occurs as a mechanistic consequence of hormone-induced differentiation of the endometrium (referred to as spontaneous decidualization, or SD); (ii) SD evolved because of maternal-fetal conflict; and (iii) SD evolved by genetic assimilation of the decidualization reaction, which is induced by the fetus in non-menstruating species. The idea that menstruation occurs as a consequence of SD has been proposed in the past, but here we present a novel hypothesis on how SD evolved. We argue that decidualization became genetically stabilized in menstruating lineages, allowing females to prepare for pregnancy without any signal from the fetus. We present three models for the evolution of SD by genetic assimilation, based on recent advances in our understanding of the mechanisms of endometrial differentiation and implantation. Testing these models will ultimately shed light on the evolutionary significance of menstruation, as well as on the etiology of human reproductive disorders like endometriosis and recurrent pregnancy loss. PMID:22057551

  11. Application of the genetic algorithm to blume-emery-griffiths model: Test Cases

    International Nuclear Information System (INIS)

    Erdinc, A.

    2004-01-01

    The equilibrium properties of the Blume-Emery-Griffiths (BEO) model Hamiltonian with the arbitrary bilinear (1), biquadratic (K) and crystal field interaction (D) are studied using the genetic algorithm technique. Results are compared with lowest approximation of the cluster variation method (CVM), which is identical to the mean field approximation. We found that the genetic algorithm to be very efficient for fast search at the average fraction of the spins, especially in the early stages as the system is far from the equilibrium state. A combination of the genetic algorithm followed by one of the well-tested simulation techniques seems to be an optimal approach. The curvature of the inverse magnetic susceptibility is also presented for the stable state of the BEG model

  12. Modeling the Isentropic Head Value of Centrifugal Gas Compressor using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Safiyullah Ferozkhan

    2016-01-01

    Full Text Available Gas compressor performance is vital in oil and gas industry because of the equipment criticality which requires continuous operations. Plant operators often face difficulties in predicting appropriate time for maintenance and would usually rely on time based predictive maintenance intervals as recommended by original equipment manufacturer (OEM. The objective of this work is to develop the computational model to find the isentropic head value using genetic programming. The isentropic head value is calculated from the OEM performance chart. Inlet mass flow rate and speed of the compressor are taken as the input value. The obtained results from the GP computational models show good agreement with experimental and target data with the average prediction error of 1.318%. The genetic programming computational model will assist machinery engineers to quantify performance deterioration of gas compressor and the results from this study will be then utilized to estimate future maintenance requirements based on the historical data. In general, this genetic programming modelling provides a powerful solution for gas compressor operators to realize predictive maintenance approach in their operations.

  13. Evolutionary model with genetics, aging, and knowledge

    Science.gov (United States)

    Bustillos, Armando Ticona; de Oliveira, Paulo Murilo

    2004-02-01

    We represent a process of learning by using bit strings, where 1 bits represent the knowledge acquired by individuals. Two ways of learning are considered: individual learning by trial and error, and social learning by copying knowledge from other individuals or from parents in the case of species with parental care. The age-structured bit string allows us to study how knowledge is accumulated during life and its influence over the genetic pool of a population after many generations. We use the Penna model to represent the genetic inheritance of each individual. In order to study how the accumulated knowledge influences the survival process, we include it to help individuals to avoid the various death situations. Modifications in the Verhulst factor do not show any special feature due to its random nature. However, by adding years to life as a function of the accumulated knowledge, we observe an improvement of the survival rates while the genetic fitness of the population becomes worse. In this latter case, knowledge becomes more important in the last years of life where individuals are threatened by diseases. Effects of offspring overprotection and differences between individual and social learning can also be observed. Sexual selection as a function of knowledge shows some effects when fidelity is imposed.

  14. PRELIMINARY RESEARCHES REGARDING THE GENETIC AND MORPHOMETRIC CHARACTERIZATION OF HONEYBEES (A. MELLIFERA L. FROM ROMANIA

    Directory of Open Access Journals (Sweden)

    ELIZA CAUIA

    2008-10-01

    Full Text Available The international investigations regarding the honeybees’ diversity carried out until now have revealed a certain degree of genetic pollution in different countries from Europe, because of the import of more productive honeybees’ races or of some interracial honeybees’ hybrids. This fact might have a negative impact on the success adaptability of honeybees at the ecosystem. Although, the Romanian honeybees (Apis mellifera carpathica are well adapted to the local conditions and express a good resistance to diseases, the introgression (genetic pollution of different honeybees’ races could be an imminent event. So that, starting from 2007, by a cooperation between the Institute for Beekeeping Research and Development from Bucharest and the Institute of Genetics of the University of Bucharest, we have initiated different investigations in order to obtain a more accurate state of the Romanian honeybees’ diversity. We have performed specific molecular analyses, using mtDNA (the COI-COII test extracted from 32 different honeybees samples collected from several regions from Romania. For a better and detailed characterization of the collected honeybee’s samples we have also carried out some morphometric measurements of their wings. Our data have shown that the Romanian population of honeybees is almost homogenous from the genetic and the morphometric points of views. These types of investigations represent a premiere for Romania.

  15. A Genetic Animal Model of Alcoholism for Screening Medications to Treat Addiction

    Science.gov (United States)

    Bell, Richard L.; Hauser, Sheketha; Rodd, Zachary A.; Liang, Tiebing; Sari, Youssef; McClintick, Jeanette; Rahman, Shafiqur; Engleman, Eric A.

    2016-01-01

    The purpose of this review is to present up-to-date pharmacological, genetic and behavioral findings from the alcohol-preferring P rat and summarize similar past work. Behaviorally, the focus will be on how the P rat meets criteria put forth for a valid animal model of alcoholism with a highlight on its use as an animal model of polysubstance abuse, including alcohol, nicotine and psychostimulants. Pharmacologically and genetically, the focus will be on the neurotransmitter and neuropeptide systems that have received the most attention: cholinergic, dopaminergic, GABAergic, glutamatergic, serotonergic, noradrenergic, corticotrophin releasing hormone, opioid, and neuropeptide Y. Herein we sought to place the P rat’s behavioral and neurochemical phenotypes, and to some extent its genotype, in the context of the clinical literature. After reviewing the findings thus far, this paper discusses future directions for expanding the use of this genetic animal model of alcoholism to identify molecular targets for treating drug addiction in general. PMID:27055615

  16. Genetic enhancement of macroautophagy in vertebrate models of neurodegenerative diseases.

    Science.gov (United States)

    Ejlerskov, Patrick; Ashkenazi, Avraham; Rubinsztein, David C

    2018-04-03

    Most of the neurodegenerative diseases that afflict humans manifest with the intraneuronal accumulation of toxic proteins that are aggregate-prone. Extensive data in cell and neuronal models support the concept that such proteins, like mutant huntingtin or alpha-synuclein, are substrates for macroautophagy (hereafter autophagy). Furthermore, autophagy-inducing compounds lower the levels of such proteins and ameliorate their toxicity in diverse animal models of neurodegenerative diseases. However, most of these compounds also have autophagy-independent effects and it is important to understand if similar benefits are seen with genetic strategies that upregulate autophagy, as this strengthens the validity of this strategy in such diseases. Here we review studies in vertebrate models using genetic manipulations of core autophagy genes and describe how these improve pathology and neurodegeneration, supporting the validity of autophagy upregulation as a target for certain neurodegenerative diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

  17. Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study.

    Science.gov (United States)

    Rijsdijk, Frühling V; Vernon, P A; Boomsma, Dorret I

    2002-05-01

    Hierarchical models of intelligence are highly informative and widely accepted. Application of these models to twin data, however, is sparse. This paper addresses the question of how a genetic hierarchical model fits the Wechsler Adult Intelligence Scale (WAIS) subtests and the Raven Standard Progressive test score, collected in 194 18-year-old Dutch twin pairs. We investigated whether first-order group factors possess genetic and environmental variance independent of the higher-order general factor and whether the hierarchical structure is significant for all sources of variance. A hierarchical model with the 3 Cohen group-factors (verbal comprehension, perceptual organisation and freedom-from-distractibility) and a higher-order g factor showed the best fit to the phenotypic data and to additive genetic influences (A), whereas the unique environmental source of variance (E) could be modeled by a single general factor and specifics. There was no evidence for common environmental influences. The covariation among the WAIS group factors and the covariation between the group factors and the Raven is predominantly influenced by a second-order genetic factor and strongly support the notion of a biological basis of g.

  18. Linear Mixed Models in Statistical Genetics

    NARCIS (Netherlands)

    R. de Vlaming (Ronald)

    2017-01-01

    markdownabstractOne of the goals of statistical genetics is to elucidate the genetic architecture of phenotypes (i.e., observable individual characteristics) that are affected by many genetic variants (e.g., single-nucleotide polymorphisms; SNPs). A particular aim is to identify specific SNPs that

  19. Models for genetic evaluations of claw health traits in Spanish dairy cattle.

    Science.gov (United States)

    Pérez-Cabal, M A; Charfeddine, N

    2015-11-01

    Genetic parameters of 7 claw health traits from Spanish dairy cattle were estimated and the predictive ability of linear and ordinal threshold models were compared and assessed. This study included data on interdigital and digital dermatitis (DE), sole ulcer (SU), white line disease (WL), interdigital hyperplasia (IH), interdigital phlegmon (IP), and chronic laminitis (CL) collected between July 2012 and June 2013 from 834 dairy herds visited by 21 trained trimmers. An overall claw disorder (OCD) was also considered an indicator the absence or the presence of at least 1 of the 6 disorders. Claw health traits were scored as categorical traits with 3 degrees of severity (nonaffected, mild, and severe disorder). Genetic parameters were estimated by fitting both a standard linear model and an ordinal threshold animal model. Around 21% of cows had at least 1 claw disorder, and the most frequent disorders were SU, DE, WL, and CL. Heritabilities of claw disorders estimated with a linear model ranged from 0.01 (IP) to 0.05 (OCD), whereas estimates from the ordinal threshold models ranged from 0.06 to 0.39 (for IP and IH, respectively). Repeatabilities of claw health estimated with the linear model varied from 0.03 to 0.18 and estimates with the ordinal threshold model ranged from 0.33 to 0.69. The global trait OCD was correlated with all disorders, except for IH and IP when the linear model was fitted. Two different genetic backgrounds of claw disorders were found. Digital dermatitis showed positive correlations with IH and IP, whereas SU was positively correlated with WL and CL. The predictive ability of the models was assessed using mean squared error and Pearson correlation between the real observation and the corresponding prediction using cross-validation. Regardless of the claw health status, the linear model led to smaller mean squared error. However, differences in predictive ability were found when predicting nonaffected and affected animals. For most traits

  20. Setaria viridis as a model system to advance millet genetics and genomics

    Directory of Open Access Journals (Sweden)

    Pu Huang

    2016-11-01

    Full Text Available Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crop.

  1. Setaria viridis as a Model System to Advance Millet Genetics and Genomics.

    Science.gov (United States)

    Huang, Pu; Shyu, Christine; Coelho, Carla P; Cao, Yingying; Brutnell, Thomas P

    2016-01-01

    Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail ( Setaria viridis ) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica . These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.

  2. Setaria viridis as a Model System to Advance Millet Genetics and Genomics

    Science.gov (United States)

    Huang, Pu; Shyu, Christine; Coelho, Carla P.; Cao, Yingying; Brutnell, Thomas P.

    2016-01-01

    Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops. PMID:27965689

  3. Recent developments in computer modeling add ecological realism to landscape genetics

    Science.gov (United States)

    Background / Question / Methods A factor limiting the rate of progress in landscape genetics has been the shortage of spatial models capable of linking life history attributes such as dispersal behavior to complex dynamic landscape features. The recent development of new models...

  4. A Unifying Model for the Analysis of Phenotypic, Genetic and Geographic Data

    DEFF Research Database (Denmark)

    Guillot, Gilles; Rena, Sabrina; Ledevin, Ronan

    2012-01-01

    Recognition of evolutionary units (species, populations) requires integrating several kinds of data such as genetic or phenotypic markers or spatial information, in order to get a comprehensive view concerning the dierentiation of the units. We propose a statistical model with a double original...... advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography; and (ii) it allows one to analyze genetic and phenotypic data within a unied model and inference framework, thus...... an intricate case of inter- and intra-species dierentiation based on an original data-set of georeferenced genetic and morphometric markers obtained on Myodes voles from Sweden. A computer program is made available as an extension of the R package Geneland....

  5. Genetic Algorithms for a Parameter Estimation of a Fermentation Process Model: A Comparison

    Directory of Open Access Journals (Sweden)

    Olympia Roeva

    2005-12-01

    Full Text Available In this paper the problem of a parameter estimation using genetic algorithms is examined. A case study considering the estimation of 6 parameters of a nonlinear dynamic model of E. coli fermentation is presented as a test problem. The parameter estimation problem is stated as a nonlinear programming problem subject to nonlinear differential-algebraic constraints. This problem is known to be frequently ill-conditioned and multimodal. Thus, traditional (gradient-based local optimization methods fail to arrive satisfied solutions. To overcome their limitations, the use of different genetic algorithms as stochastic global optimization methods is explored. These algorithms are proved to be very suitable for the optimization of highly non-linear problems with many variables. Genetic algorithms can guarantee global optimality and robustness. These facts make them advantageous in use for parameter identification of fermentation models. A comparison between simple, modified and multi-population genetic algorithms is presented. The best result is obtained using the modified genetic algorithm. The considered algorithms converged very closely to the cost value but the modified algorithm is in times faster than other two.

  6. Amniotic Fluid Stem Cells: A Novel Source for Modeling of Human Genetic Diseases

    Directory of Open Access Journals (Sweden)

    Ivana Antonucci

    2016-04-01

    Full Text Available In recent years, great interest has been devoted to the use of Induced Pluripotent Stem cells (iPS for modeling of human genetic diseases, due to the possibility of reprogramming somatic cells of affected patients into pluripotent cells, enabling differentiation into several cell types, and allowing investigations into the molecular mechanisms of the disease. However, the protocol of iPS generation still suffers from technical limitations, showing low efficiency, being expensive and time consuming. Amniotic Fluid Stem cells (AFS represent a potential alternative novel source of stem cells for modeling of human genetic diseases. In fact, by means of prenatal diagnosis, a number of fetuses affected by chromosomal or Mendelian diseases can be identified, and the amniotic fluid collected for genetic testing can be used, after diagnosis, for the isolation, culture and differentiation of AFS cells. This can provide a useful stem cell model for the investigation of the molecular basis of the diagnosed disease without the necessity of producing iPS, since AFS cells show some features of pluripotency and are able to differentiate in cells derived from all three germ layers “in vitro”. In this article, we describe the potential benefits provided by using AFS cells in the modeling of human genetic diseases.

  7. Genetic mouse models of brain ageing and Alzheimer's disease.

    Science.gov (United States)

    Bilkei-Gorzo, Andras

    2014-05-01

    Progression of brain ageing is influenced by a complex interaction of genetic and environmental factors. Analysis of genetically modified animals with uniform genetic backgrounds in a standardised, controlled environment enables the dissection of critical determinants of brain ageing on a molecular level. Human and animal studies suggest that increased load of damaged macromolecules, efficacy of DNA maintenance, mitochondrial activity, and cellular stress defences are critical determinants of brain ageing. Surprisingly, mouse lines with genetic impairment of anti-oxidative capacity generally did not show enhanced cognitive ageing but rather an increased sensitivity to oxidative challenge. Mouse lines with impaired mitochondrial activity had critically short life spans or severe and rapidly progressing neurodegeneration. Strains with impaired clearance in damaged macromolecules or defects in the regulation of cellular stress defences showed alterations in the onset and progression of cognitive decline. Importantly, reduced insulin/insulin-like growth factor signalling generally increased life span but impaired cognitive functions revealing a complex interaction between ageing of the brain and of the body. Brain ageing is accompanied by an increased risk of developing Alzheimer's disease. Transgenic mouse models expressing high levels of mutant human amyloid precursor protein showed a number of symptoms and pathophysiological processes typical for early phase of Alzheimer's disease. Generally, therapeutic strategies effective against Alzheimer's disease in humans were also active in the Tg2576, APP23, APP/PS1 and 5xFAD lines, but a large number of false positive findings were also reported. The 3xtg AD model likely has the highest face and construct validity but further studies are needed. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

    DEFF Research Database (Denmark)

    Bothwell, H.; Bisbing, S.; Therkildsen, Nina Overgaard

    2013-01-01

    It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental...... loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi...... variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major...

  9. Application of genetic algorithm in radio ecological models parameter determination

    Energy Technology Data Exchange (ETDEWEB)

    Pantelic, G. [Institute of Occupatioanl Health and Radiological Protection ' Dr Dragomir Karajovic' , Belgrade (Serbia)

    2006-07-01

    The method of genetic algorithms was used to determine the biological half-life of 137 Cs in cow milk after the accident in Chernobyl. Methodologically genetic algorithms are based on the fact that natural processes tend to optimize themselves and therefore this method should be more efficient in providing optimal solutions in the modeling of radio ecological and environmental events. The calculated biological half-life of 137 Cs in milk is (32 {+-} 3) days and transfer coefficient from grass to milk is (0.019 {+-} 0.005). (authors)

  10. Simulated evolution applied to study the genetic code optimality using a model of codon reassignments.

    Science.gov (United States)

    Santos, José; Monteagudo, Angel

    2011-02-21

    As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical genetic code was measured taking into account the harmful consequences resulting from point mutations leading to the replacement of one amino acid for another. There are two basic theories to measure the level of optimization: the statistical approach, which compares the canonical genetic code with many randomly generated alternative ones, and the engineering approach, which compares the canonical code with the best possible alternative. Here we used a genetic algorithm to search for better adapted hypothetical codes and as a method to guess the difficulty in finding such alternative codes, allowing to clearly situate the canonical code in the fitness landscape. This novel proposal of the use of evolutionary computing provides a new perspective in the open debate between the use of the statistical approach, which postulates that the genetic code conserves amino acid properties far better than expected from a random code, and the engineering approach, which tends to indicate that the canonical genetic code is still far from optimal. We used two models of hypothetical codes: one that reflects the known examples of codon reassignment and the model most used in the two approaches which reflects the current genetic code translation table. Although the standard code is far from a possible optimum considering both models, when the more realistic model of the codon reassignments was used, the evolutionary algorithm had more difficulty to overcome the efficiency of the canonical genetic code. Simulated evolution clearly reveals that the canonical genetic code is far from optimal regarding its optimization. Nevertheless, the efficiency of the canonical code increases when mistranslations are taken into account with the two models, as indicated by the fact that the best possible codes show the patterns of the

  11. Simulated evolution applied to study the genetic code optimality using a model of codon reassignments

    Directory of Open Access Journals (Sweden)

    Monteagudo Ángel

    2011-02-01

    Full Text Available Abstract Background As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical genetic code was measured taking into account the harmful consequences resulting from point mutations leading to the replacement of one amino acid for another. There are two basic theories to measure the level of optimization: the statistical approach, which compares the canonical genetic code with many randomly generated alternative ones, and the engineering approach, which compares the canonical code with the best possible alternative. Results Here we used a genetic algorithm to search for better adapted hypothetical codes and as a method to guess the difficulty in finding such alternative codes, allowing to clearly situate the canonical code in the fitness landscape. This novel proposal of the use of evolutionary computing provides a new perspective in the open debate between the use of the statistical approach, which postulates that the genetic code conserves amino acid properties far better than expected from a random code, and the engineering approach, which tends to indicate that the canonical genetic code is still far from optimal. We used two models of hypothetical codes: one that reflects the known examples of codon reassignment and the model most used in the two approaches which reflects the current genetic code translation table. Although the standard code is far from a possible optimum considering both models, when the more realistic model of the codon reassignments was used, the evolutionary algorithm had more difficulty to overcome the efficiency of the canonical genetic code. Conclusions Simulated evolution clearly reveals that the canonical genetic code is far from optimal regarding its optimization. Nevertheless, the efficiency of the canonical code increases when mistranslations are taken into account with the two models, as indicated by the

  12. A Model for Understanding the Genetic Basis for Disparity in Prostate Cancer Risk

    Science.gov (United States)

    2017-10-01

    AWARD NUMBER: W81XWH-15-1-0529 TITLE: A Model for Understanding the Genetic Basis for Disparity in Prostate Cancer Risk PRINCIPAL INVESTIGATOR...AND SUBTITLE A Model for Understanding the Genetic Basis for Disparity in Prostate Cancer Risk 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-15-1...STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Prostate cancer is the most commonly diagnosed cancer in

  13. A genetic algorithm for optimizing multi-pole Debye models of tissue dielectric properties

    International Nuclear Information System (INIS)

    Clegg, J; Robinson, M P

    2012-01-01

    Models of tissue dielectric properties (permittivity and conductivity) enable the interactions of tissues and electromagnetic fields to be simulated, which has many useful applications in microwave imaging, radio propagation, and non-ionizing radiation dosimetry. Parametric formulae are available, based on a multi-pole model of tissue dispersions, but although they give the dielectric properties over a wide frequency range, they do not convert easily to the time domain. An alternative is the multi-pole Debye model which works well in both time and frequency domains. Genetic algorithms are an evolutionary approach to optimization, and we found that this technique was effective at finding the best values of the multi-Debye parameters. Our genetic algorithm optimized these parameters to fit to either a Cole–Cole model or to measured data, and worked well over wide or narrow frequency ranges. Over 10 Hz–10 GHz the best fits for muscle, fat or bone were each found for ten dispersions or poles in the multi-Debye model. The genetic algorithm is a fast and effective method of developing tissue models that compares favourably with alternatives such as the rational polynomial fit. (paper)

  14. Genetic Evaluation and Ranking of Different Animal Models Using ...

    African Journals Online (AJOL)

    An animal model utilizes all relationships available in a given data set. Estimates for variance components for additive direct, additive maternal, maternal environmental and direct environmental effects, and their covariances between direct and maternal genetic effects for post weaning growth traits have been obtained with ...

  15. Genetic modelling in schizophrenia according to HLA typing.

    Science.gov (United States)

    Smeraldi, E; Macciardi, F; Gasperini, M; Orsini, A; Bellodi, L; Fabio, G; Morabito, A

    1986-09-01

    Studying families of schizophrenic patients, we observed that the risk of developing the overt form of the illness could be enhanced by some factors. Among these various factors we focused our attention on a biological variable, namely the presence or the absence of particular HLA antigens: partitioning our schizophrenic patients according to their HLA structure (i.e. those with HLA-A1 or CRAG-A1 antigens and those with HLA-non-CRAG-A1 antigens, respectively), revealed different illness distribution in the two groups. From a genetic point of view, this finding suggests the presence of heterogeneity in the hypothetical liability system related to schizophrenia and we evaluated the heterogeneity hypothesis by applying alternative genetic models to our data, trying to detect more biologically homogeneous subgroups of the disease.

  16. Genetic algorithm based optimization of advanced solar cell designs modeled in Silvaco AtlasTM

    OpenAIRE

    Utsler, James

    2006-01-01

    A genetic algorithm was used to optimize the power output of multi-junction solar cells. Solar cell operation was modeled using the Silvaco ATLASTM software. The output of the ATLASTM simulation runs served as the input to the genetic algorithm. The genetic algorithm was run as a diffusing computation on a network of eighteen dual processor nodes. Results showed that the genetic algorithm produced better power output optimizations when compared with the results obtained using the hill cli...

  17. Forecasting Shaharchay River Flow in Lake Urmia Basin using Genetic Programming and M5 Model Tree

    Directory of Open Access Journals (Sweden)

    S. Samadianfard

    2017-01-01

    Full Text Available Introduction: Precise prediction of river flows is the key factor for proper planning and management of water resources. Thus, obtaining the reliable methods for predicting river flows has great importance in water resource engineering. In the recent years, applications of intelligent methods such as artificial neural networks, fuzzy systems and genetic programming in water science and engineering have been grown extensively. These mentioned methods are able to model nonlinear process of river flows without any need to geometric properties. A huge number of studies have been reported in the field of using intelligent methods in water resource engineering. For example, Noorani and Salehi (23 presented a model for predicting runoff in Lighvan basin using adaptive neuro-fuzzy network and compared the performance of it with neural network and fuzzy inference methods in east Azerbaijan, Iran. Nabizadeh et al. (21 used fuzzy inference system and adaptive neuro-fuzzy inference system in order to predict river flow in Lighvan river. Khalili et al. (13 proposed a BL-ARCH method for prediction of flows in Shaharchay River in Urmia. Khu et al. (16 used genetic programming for runoff prediction in Orgeval catchment in France. Firat and Gungor (11 evaluated the fuzzy-neural model for predicting Mendes river flow in Turkey. The goal of present study is comparing the performance of genetic programming and M5 model trees for prediction of Shaharchay river flow in the basin of Lake Urmia and obtaining a comprehensive insight of their abilities. Materials and Methods: Shaharchay river as a main source of providing drinking water of Urmia city and agricultural needs of surrounding lands and finally one of the main input sources of Lake Urmia is quite important in the region. For obtaining the predetermined goals of present study, average monthly flows of Shaharchay River in Band hydrometric station has been gathered from 1951 to 2011. Then, two third of mentioned

  18. Application of genetic algorithm in radio ecological models parameter determination

    International Nuclear Information System (INIS)

    Pantelic, G.

    2006-01-01

    The method of genetic algorithms was used to determine the biological half-life of 137 Cs in cow milk after the accident in Chernobyl. Methodologically genetic algorithms are based on the fact that natural processes tend to optimize themselves and therefore this method should be more efficient in providing optimal solutions in the modeling of radio ecological and environmental events. The calculated biological half-life of 137 Cs in milk is (32 ± 3) days and transfer coefficient from grass to milk is (0.019 ± 0.005). (authors)

  19. The Mouse Lemur, a Genetic Model Organism for Primate Biology, Behavior, and Health.

    Science.gov (United States)

    Ezran, Camille; Karanewsky, Caitlin J; Pendleton, Jozeph L; Sholtz, Alex; Krasnow, Maya R; Willick, Jason; Razafindrakoto, Andriamahery; Zohdy, Sarah; Albertelli, Megan A; Krasnow, Mark A

    2017-06-01

    Systematic genetic studies of a handful of diverse organisms over the past 50 years have transformed our understanding of biology. However, many aspects of primate biology, behavior, and disease are absent or poorly modeled in any of the current genetic model organisms including mice. We surveyed the animal kingdom to find other animals with advantages similar to mice that might better exemplify primate biology, and identified mouse lemurs ( Microcebus spp.) as the outstanding candidate. Mouse lemurs are prosimian primates, roughly half the genetic distance between mice and humans. They are the smallest, fastest developing, and among the most prolific and abundant primates in the world, distributed throughout the island of Madagascar, many in separate breeding populations due to habitat destruction. Their physiology, behavior, and phylogeny have been studied for decades in laboratory colonies in Europe and in field studies in Malagasy rainforests, and a high quality reference genome sequence has recently been completed. To initiate a classical genetic approach, we developed a deep phenotyping protocol and have screened hundreds of laboratory and wild mouse lemurs for interesting phenotypes and begun mapping the underlying mutations, in collaboration with leading mouse lemur biologists. We also seek to establish a mouse lemur gene "knockout" library by sequencing the genomes of thousands of mouse lemurs to identify null alleles in most genes from the large pool of natural genetic variants. As part of this effort, we have begun a citizen science project in which students across Madagascar explore the remarkable biology around their schools, including longitudinal studies of the local mouse lemurs. We hope this work spawns a new model organism and cultivates a deep genetic understanding of primate biology and health. We also hope it establishes a new and ethical method of genetics that bridges biological, behavioral, medical, and conservation disciplines, while

  20. Genetic parameters for racing records in trotters using linear and generalized linear models.

    Science.gov (United States)

    Suontama, M; van der Werf, J H J; Juga, J; Ojala, M

    2012-09-01

    Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.

  1. Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction.

    Directory of Open Access Journals (Sweden)

    Yiming Hu

    2017-06-01

    Full Text Available Accurate prediction of disease risk based on genetic factors is an important goal in human genetics research and precision medicine. Advanced prediction models will lead to more effective disease prevention and treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome-wide association studies (GWAS in the past decade, accuracy of genetic risk prediction remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes. In this work, we introduce PleioPred, a principled framework that leverages pleiotropy and functional annotations in genetic risk prediction for complex diseases. PleioPred uses GWAS summary statistics as its input, and jointly models multiple genetically correlated diseases and a variety of external information including linkage disequilibrium and diverse functional annotations to increase the accuracy of risk prediction. Through comprehensive simulations and real data analyses on Crohn's disease, celiac disease and type-II diabetes, we demonstrate that our approach can substantially increase the accuracy of polygenic risk prediction and risk population stratification, i.e. PleioPred can significantly better separate type-II diabetes patients with early and late onset ages, illustrating its potential clinical application. Furthermore, we show that the increment in prediction accuracy is significantly correlated with the genetic correlation between the predicted and jointly modeled diseases.

  2. Genetic models of absence epilepsy: New concepts and insights

    NARCIS (Netherlands)

    Luijtelaar, E.L.J.M. van; Stein, J.

    2017-01-01

    The discovery, development and use of genetic rodent models of absence epilepsy have led to a new theory about the origin of absence seizures, which has gained impact within the international epilepsy community. A focal zone has been identified in the perioral region of the somatosensory cortex in

  3. Revised models and genetic parameter estimates for production and ...

    African Journals Online (AJOL)

    Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the ...

  4. Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

    Science.gov (United States)

    Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

    2017-09-21

    Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

  5. Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

    Science.gov (United States)

    Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

    2015-03-01

    A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Trace elements in diamonds from the Premier, Finsch, and Jagersfontein mines, and their petrogenetic significance

    International Nuclear Information System (INIS)

    Fesq, H.W.; Bibby, D.M.; Erasmus, C.S.; Kable, E.J.D.

    1975-01-01

    Neutron-activation studies of the impurity chemistry of more than 1500 natural diamonds from three South African kimberlite sources, Premier, Finsch, and Jagersfontein, provide evidence for the presence of submicroscopic inclusions of a quenched (or temperature re-equilibrated) melt from which these diamonds crystallized. These microscopic inclusions of parental magma contain variable amounts of fluids rich in water and carbon dioxide, as well as iron-nickelcopper-cobalt sulphides, and a major silicate phase, which is remarkably constant in composition irrespective of the source of the diamonds and the age of emplacement of their host kimberlite. These microscopic inclusions are present in varying amounts in all the diamonds that were analysed, and may even dominate the impurity chemistry of diamonds having observable mineral inclusions. An estimate of the composition of the major elements in the silicate melt indicates that the diamonds that were investigated crystallized from picritic magma rich in water and carbon dioxide in the presence of immiscible iron-nickel-copper-cobalt sulphides [af

  7. Modelling the genetic risk in age-related macular degeneration.

    Directory of Open Access Journals (Sweden)

    Felix Grassmann

    Full Text Available Late-stage age-related macular degeneration (AMD is a common sight-threatening disease of the central retina affecting approximately 1 in 30 Caucasians. Besides age and smoking, genetic variants from several gene loci have reproducibly been associated with this condition and likely explain a large proportion of disease. Here, we developed a genetic risk score (GRS for AMD based on 13 risk variants from eight gene loci. The model exhibited good discriminative accuracy, area-under-curve (AUC of the receiver-operating characteristic of 0.820, which was confirmed in a cross-validation approach. Noteworthy, younger AMD patients aged below 75 had a significantly higher mean GRS (1.87, 95% CI: 1.69-2.05 than patients aged 75 and above (1.45, 95% CI: 1.36-1.54. Based on five equally sized GRS intervals, we present a risk classification with a relative AMD risk of 64.0 (95% CI: 14.11-1131.96 for individuals in the highest category (GRS 3.44-5.18, 0.5% of the general population compared to subjects with the most common genetic background (GRS -0.05-1.70, 40.2% of general population. The highest GRS category identifies AMD patients with a sensitivity of 7.9% and a specificity of 99.9% when compared to the four lower categories. Modeling a general population around 85 years of age, 87.4% of individuals in the highest GRS category would be expected to develop AMD by that age. In contrast, only 2.2% of individuals in the two lowest GRS categories which represent almost 50% of the general population are expected to manifest AMD. Our findings underscore the large proportion of AMD cases explained by genetics particularly for younger AMD patients. The five-category risk classification could be useful for therapeutic stratification or for diagnostic testing purposes once preventive treatment is available.

  8. Genetic Diseases and Genetic Determinism Models in French Secondary School Biology Textbooks

    Science.gov (United States)

    Castera, Jeremy; Bruguiere, Catherine; Clement, Pierre

    2008-01-01

    The presentation of genetic diseases in French secondary school biology textbooks is analysed to determine the major conceptions taught in the field of human genetics. References to genetic diseases, and the processes by which they are explained (monogeny, polygeny, chromosomal anomaly and environmental influence) are studied in recent French…

  9. Behavioral phenotypes of genetic mouse models of autism.

    Science.gov (United States)

    Kazdoba, T M; Leach, P T; Crawley, J N

    2016-01-01

    More than a hundred de novo single gene mutations and copy-number variants have been implicated in autism, each occurring in a small subset of cases. Mutant mouse models with syntenic mutations offer research tools to gain an understanding of the role of each gene in modulating biological and behavioral phenotypes relevant to autism. Knockout, knockin and transgenic mice incorporating risk gene mutations detected in autism spectrum disorder and comorbid neurodevelopmental disorders are now widely available. At present, autism spectrum disorder is diagnosed solely by behavioral criteria. We developed a constellation of mouse behavioral assays designed to maximize face validity to the types of social deficits and repetitive behaviors that are central to an autism diagnosis. Mouse behavioral assays for associated symptoms of autism, which include cognitive inflexibility, anxiety, hyperactivity, and unusual reactivity to sensory stimuli, are frequently included in the phenotypic analyses. Over the past 10 years, we and many other laboratories around the world have employed these and additional behavioral tests to phenotype a large number of mutant mouse models of autism. In this review, we highlight mouse models with mutations in genes that have been identified as risk genes for autism, which work through synaptic mechanisms and through the mTOR signaling pathway. Robust, replicated autism-relevant behavioral outcomes in a genetic mouse model lend credence to a causal role for specific gene contributions and downstream biological mechanisms in the etiology of autism. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

  10. Teaching genetics using hands-on models, problem solving, and inquiry-based methods

    Science.gov (United States)

    Hoppe, Stephanie Ann

    Teaching genetics can be challenging because of the difficulty of the content and misconceptions students might hold. This thesis focused on using hands-on model activities, problem solving, and inquiry-based teaching/learning methods in order to increase student understanding in an introductory biology class in the area of genetics. Various activities using these three methods were implemented into the classes to address any misconceptions and increase student learning of the difficult concepts. The activities that were implemented were shown to be successful based on pre-post assessment score comparison. The students were assessed on the subjects of inheritance patterns, meiosis, and protein synthesis and demonstrated growth in all of the areas. It was found that hands-on models, problem solving, and inquiry-based activities were more successful in learning concepts in genetics and the students were more engaged than tradition styles of lecture.

  11. Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

    Science.gov (United States)

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

    2011-02-01

    Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

  12. New insights into the endophenotypic status of cognition in bipolar disorder: genetic modelling study of twins and siblings.

    Science.gov (United States)

    Georgiades, Anna; Rijsdijk, Fruhling; Kane, Fergus; Rebollo-Mesa, Irene; Kalidindi, Sridevi; Schulze, Katja K; Stahl, Daniel; Walshe, Muriel; Sahakian, Barbara J; McDonald, Colm; Hall, Mei-Hua; Murray, Robin M; Kravariti, Eugenia

    2016-06-01

    Twin studies have lacked statistical power to apply advanced genetic modelling techniques to the search for cognitive endophenotypes for bipolar disorder. To quantify the shared genetic variability between bipolar disorder and cognitive measures. Structural equation modelling was performed on cognitive data collected from 331 twins/siblings of varying genetic relatedness, disease status and concordance for bipolar disorder. Using a parsimonious AE model, verbal episodic and spatial working memory showed statistically significant genetic correlations with bipolar disorder (rg = |0.23|-|0.27|), which lost statistical significance after covarying for affective symptoms. Using an ACE model, IQ and visual-spatial learning showed statistically significant genetic correlations with bipolar disorder (rg = |0.51|-|1.00|), which remained significant after covarying for affective symptoms. Verbal episodic and spatial working memory capture a modest fraction of the bipolar diathesis. IQ and visual-spatial learning may tap into genetic substrates of non-affective symptomatology in bipolar disorder. © The Royal College of Psychiatrists 2016.

  13. Genetic parameters for direct and maternal calving ease in Walloon dairy cattle based on linear and threshold models.

    Science.gov (United States)

    Vanderick, S; Troch, T; Gillon, A; Glorieux, G; Gengler, N

    2014-12-01

    Calving ease scores from Holstein dairy cattle in the Walloon Region of Belgium were analysed using univariate linear and threshold animal models. Variance components and derived genetic parameters were estimated from a data set including 33,155 calving records. Included in the models were season, herd and sex of calf × age of dam classes × group of calvings interaction as fixed effects, herd × year of calving, maternal permanent environment and animal direct and maternal additive genetic as random effects. Models were fitted with the genetic correlation between direct and maternal additive genetic effects either estimated or constrained to zero. Direct heritability for calving ease was approximately 8% with linear models and approximately 12% with threshold models. Maternal heritabilities were approximately 2 and 4%, respectively. Genetic correlation between direct and maternal additive effects was found to be not significantly different from zero. Models were compared in terms of goodness of fit and predictive ability. Criteria of comparison such as mean squared error, correlation between observed and predicted calving ease scores as well as between estimated breeding values were estimated from 85,118 calving records. The results provided few differences between linear and threshold models even though correlations between estimated breeding values from subsets of data for sires with progeny from linear model were 17 and 23% greater for direct and maternal genetic effects, respectively, than from threshold model. For the purpose of genetic evaluation for calving ease in Walloon Holstein dairy cattle, the linear animal model without covariance between direct and maternal additive effects was found to be the best choice. © 2014 Blackwell Verlag GmbH.

  14. Genetic evaluation of calf and heifer survival in Iranian Holstein cattle using linear and threshold models.

    Science.gov (United States)

    Forutan, M; Ansari Mahyari, S; Sargolzaei, M

    2015-02-01

    Calf and heifer survival are important traits in dairy cattle affecting profitability. This study was carried out to estimate genetic parameters of survival traits in female calves at different age periods, until nearly the first calving. Records of 49,583 female calves born during 1998 and 2009 were considered in five age periods as days 1-30, 31-180, 181-365, 366-760 and full period (day 1-760). Genetic components were estimated based on linear and threshold sire models and linear animal models. The models included both fixed effects (month of birth, dam's parity number, calving ease and twin/single) and random effects (herd-year, genetic effect of sire or animal and residual). Rates of death were 2.21, 3.37, 1.97, 4.14 and 12.4% for the above periods, respectively. Heritability estimates were very low ranging from 0.48 to 3.04, 0.62 to 3.51 and 0.50 to 4.24% for linear sire model, animal model and threshold sire model, respectively. Rank correlations between random effects of sires obtained with linear and threshold sire models and with linear animal and sire models were 0.82-0.95 and 0.61-0.83, respectively. The estimated genetic correlations between the five different periods were moderate and only significant for 31-180 and 181-365 (r(g) = 0.59), 31-180 and 366-760 (r(g) = 0.52), and 181-365 and 366-760 (r(g) = 0.42). The low genetic correlations in current study would suggest that survival at different periods may be affected by the same genes with different expression or by different genes. Even though the additive genetic variations of survival traits were small, it might be possible to improve these traits by traditional or genomic selection. © 2014 Blackwell Verlag GmbH.

  15. Genetic Aspects of Autism Spectrum Disorders: Insights from Animal Models

    Directory of Open Access Journals (Sweden)

    Swati eBanerjee

    2014-02-01

    Full Text Available Autism spectrum disorders (ASD are a complex neurodevelopmental disorder that display a triad of core behavioral deficits including restricted interests, often accompanied by repetitive behavior, deficits in language and communication, and an inability to engage in reciprocal social interactions. ASD is among the most heritable disorders but is not a simple disorder with a singular pathology and has a rather complex etiology. It is interesting to note that perturbations in synaptic growth, development and stability underlie a variety of neuropsychiatric disorders, including ASD, schizophrenia, epilepsy and intellectual disability. Biological characterization of an increasing repertoire of synaptic mutants in various model organisms indicates synaptic dysfunction as causal in the pathophysiology of ASD. Our understanding of the genes and genetic pathways that contribute towards the formation, stabilization and maintenance of functional synapses coupled with an in-depth phenotypic analysis of the cellular and behavioral characteristics is therefore essential to unraveling the pathogenesis of these disorders. In this review, we discuss the genetic aspects of ASD emphasizing on the well conserved set of genes and genetic pathways implicated in this disorder, many of which contribute to synapse assembly and maintenance across species. We also review how fundamental research using animal models is providing key insights into the various facets of human ASD.

  16. Budding yeast for budding geneticists: a primer on the Saccharomyces cerevisiae model system.

    Science.gov (United States)

    Duina, Andrea A; Miller, Mary E; Keeney, Jill B

    2014-05-01

    The budding yeast Saccharomyces cerevisiae is a powerful model organism for studying fundamental aspects of eukaryotic cell biology. This Primer article presents a brief historical perspective on the emergence of this organism as a premier experimental system over the course of the past century. An overview of the central features of the S. cerevisiae genome, including the nature of its genetic elements and general organization, is also provided. Some of the most common experimental tools and resources available to yeast geneticists are presented in a way designed to engage and challenge undergraduate and graduate students eager to learn more about the experimental amenability of budding yeast. Finally, a discussion of several major discoveries derived from yeast studies highlights the far-reaching impact that the yeast system has had and will continue to have on our understanding of a variety of cellular processes relevant to all eukaryotes, including humans.

  17. Use of Genetic Models to Study the Urinary Concentrating Mechanism

    DEFF Research Database (Denmark)

    Olesen, Emma Tina Bisgaard; Kortenoeven, Marleen L.A.; Fenton, Robert A.

    2015-01-01

    technology is providing critical new information about urinary concentrating processes and thus mechanisms for maintaining body water homeostasis. In this chapter we provide a brief overview of genetic mouse model generation, and then summarize findings in transgenic and knockout mice pertinent to our...

  18. Application of genetic algorithm in modeling on-wafer inductors for up to 110 Ghz

    Science.gov (United States)

    Liu, Nianhong; Fu, Jun; Liu, Hui; Cui, Wenpu; Liu, Zhihong; Liu, Linlin; Zhou, Wei; Wang, Quan; Guo, Ao

    2018-05-01

    In this work, the genetic algorithm has been introducted into parameter extraction for on-wafer inductors for up to 110 GHz millimeter-wave operations, and nine independent parameters of the equivalent circuit model are optimized together. With the genetic algorithm, the model with the optimized parameters gives a better fitting accuracy than the preliminary parameters without optimization. Especially, the fitting accuracy of the Q value achieves a significant improvement after the optimization.

  19. Analysis of conditional genetic effects and variance components in developmental genetics.

    Science.gov (United States)

    Zhu, J

    1995-12-01

    A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

  20. Advanced technologies for genetically manipulating the silkworm Bombyx mori, a model Lepidopteran insect

    Science.gov (United States)

    Xu, Hanfu; O'Brochta, David A.

    2015-01-01

    Genetic technologies based on transposon-mediated transgenesis along with several recently developed genome-editing technologies have become the preferred methods of choice for genetically manipulating many organisms. The silkworm, Bombyx mori, is a Lepidopteran insect of great economic importance because of its use in silk production and because it is a valuable model insect that has greatly enhanced our understanding of the biology of insects, including many agricultural pests. In the past 10 years, great advances have been achieved in the development of genetic technologies in B. mori, including transposon-based technologies that rely on piggyBac-mediated transgenesis and genome-editing technologies that rely on protein- or RNA-guided modification of chromosomes. The successful development and application of these technologies has not only facilitated a better understanding of B. mori and its use as a silk production system, but also provided valuable experiences that have contributed to the development of similar technologies in non-model insects. This review summarizes the technologies currently available for use in B. mori, their application to the study of gene function and their use in genetically modifying B. mori for biotechnology applications. The challenges, solutions and future prospects associated with the development and application of genetic technologies in B. mori are also discussed. PMID:26108630

  1. Mapping of the stochastic Lotka-Volterra model to models of population genetics and game theory

    Science.gov (United States)

    Constable, George W. A.; McKane, Alan J.

    2017-08-01

    The relationship between the M -species stochastic Lotka-Volterra competition (SLVC) model and the M -allele Moran model of population genetics is explored via timescale separation arguments. When selection for species is weak and the population size is large but finite, precise conditions are determined for the stochastic dynamics of the SLVC model to be mappable to the neutral Moran model, the Moran model with frequency-independent selection, and the Moran model with frequency-dependent selection (equivalently a game-theoretic formulation of the Moran model). We demonstrate how these mappings can be used to calculate extinction probabilities and the times until a species' extinction in the SLVC model.

  2. Genetic Algorithms Principles Towards Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Nabil M. Hewahi

    2011-10-01

    Full Text Available In this paper we propose a general approach based on Genetic Algorithms (GAs to evolve Hidden Markov Models (HMM. The problem appears when experts assign probability values for HMM, they use only some limited inputs. The assigned probability values might not be accurate to serve in other cases related to the same domain. We introduce an approach based on GAs to find
    out the suitable probability values for the HMM to be mostly correct in more cases than what have been used to assign the probability values.

  3. Chemical event chain model of coupled genetic oscillators.

    Science.gov (United States)

    Jörg, David J; Morelli, Luis G; Jülicher, Frank

    2018-03-01

    We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

  4. Chemical event chain model of coupled genetic oscillators

    Science.gov (United States)

    Jörg, David J.; Morelli, Luis G.; Jülicher, Frank

    2018-03-01

    We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

  5. Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

    Science.gov (United States)

    Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C

    2013-01-01

    In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377

  6. An enhanced dynamic model of battery using genetic algorithm suitable for photovoltaic applications

    International Nuclear Information System (INIS)

    Blaifi, S.; Moulahoum, S.; Colak, I.; Merrouche, W.

    2016-01-01

    Highlights: • We proposed a developed dynamic battery model suitable for photovoltaic systems. • We used genetic algorithm optimization method to find parameters that gives minimized error. • The validation was carried out with real measurements from stand-alone photovoltaic string. - Abstract: Modeling of batteries in photovoltaic systems has been a major issue related to the random dynamic regime imposed by the changes of solar irradiation and ambient temperature added to the complexity of battery electrochemical and electrical behaviors. However, various approaches have been proposed to model the battery behavior by predicting from detailed electrochemical, electrical or analytical models to high-level stochastic models. In this paper, an improvement of dynamic electrical battery model is proposed by automatic parameter extraction using genetic algorithm in order to give usefulness and future implementation for practical application. It is highlighted that the enhancement of 21 values of the parameters of CEIMAT model presents a good agreement with real measurements for different modes like charge or discharge and various conditions.

  7. Panel 4: Recent Advances in Otitis Media in Molecular Biology, Biochemistry, Genetics, and Animal Models

    Science.gov (United States)

    Li, Jian-Dong; Hermansson, Ann; Ryan, Allen F.; Bakaletz, Lauren O.; Brown, Steve D.; Cheeseman, Michael T.; Juhn, Steven K.; Jung, Timothy T. K.; Lim, David J.; Lim, Jae Hyang; Lin, Jizhen; Moon, Sung-Kyun; Post, J. Christopher

    2014-01-01

    Background Otitis media (OM) is the most common childhood bacterial infection and also the leading cause of conductive hearing loss in children. Currently, there is an urgent need for developing novel therapeutic agents for treating OM based on full understanding of molecular pathogenesis in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Objective To provide a state-of-the-art review concerning recent advances in OM in the areas of molecular biology, biochemistry, genetics, and animal model studies and to discuss the future directions of OM studies in these areas. Data Sources and Review Methods A structured search of the current literature (since June 2007). The authors searched PubMed for published literature in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Results Over the past 4 years, significant progress has been made in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. These studies brought new insights into our understanding of the molecular and biochemical mechanisms underlying the molecular pathogenesis of OM and helped identify novel therapeutic targets for OM. Conclusions and Implications for Practice Our understanding of the molecular pathogenesis of OM has been significantly advanced, particularly in the areas of inflammation, innate immunity, mucus overproduction, mucosal hyperplasia, middle ear and inner ear interaction, genetics, genome sequencing, and animal model studies. Although these studies are still in their experimental stages, they help identify new potential therapeutic targets. Future preclinical and clinical studies will help to translate these exciting experimental research findings into clinical applications. PMID:23536532

  8. Genetic evaluation of European quails by random regression models

    Directory of Open Access Journals (Sweden)

    Flaviana Miranda Gonçalves

    2012-09-01

    Full Text Available The objective of this study was to compare different random regression models, defined from different classes of heterogeneity of variance combined with different Legendre polynomial orders for the estimate of (covariance of quails. The data came from 28,076 observations of 4,507 female meat quails of the LF1 lineage. Quail body weights were determined at birth and 1, 14, 21, 28, 35 and 42 days of age. Six different classes of residual variance were fitted to Legendre polynomial functions (orders ranging from 2 to 6 to determine which model had the best fit to describe the (covariance structures as a function of time. According to the evaluated criteria (AIC, BIC and LRT, the model with six classes of residual variances and of sixth-order Legendre polynomial was the best fit. The estimated additive genetic variance increased from birth to 28 days of age, and dropped slightly from 35 to 42 days. The heritability estimates decreased along the growth curve and changed from 0.51 (1 day to 0.16 (42 days. Animal genetic and permanent environmental correlation estimates between weights and age classes were always high and positive, except for birth weight. The sixth order Legendre polynomial, along with the residual variance divided into six classes was the best fit for the growth rate curve of meat quails; therefore, they should be considered for breeding evaluation processes by random regression models.

  9. Genetic Programming for Automatic Hydrological Modelling

    Science.gov (United States)

    Chadalawada, Jayashree; Babovic, Vladan

    2017-04-01

    One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

  10. Phonologie et morphosyntaxe de l’anglais dans un produit SIC : le premier module de MACAO Phonologie et morphosyntaxe de l’anglais dans un produit SIC : le premier module de MACAO

    Directory of Open Access Journals (Sweden)

    Laurence Vincent-Durroux

    2002-12-01

    Full Text Available La préoccupation fréquente, chez les étudiants spécialistes d’autres disciplines que l’anglais, d’améliorer leur compréhension de l’anglais oral a motivé notre démarche de création d’un produit SIC (Systèmes d’Information et de Communication : MACAO (Modules d’Aide à la Compréhension de l’Anglais Oral. Le premier module, "S’entraîner à la reconnaissance", est réalisé et l’outil informatique s’est révélé particulièrement utile pour notre projet. Dans cet article, nous faisons état des difficultés récurrentes en compréhension de l’anglais oral : elles peuvent être dues à des attentes erronées fondées sur la dissymétrie entre la langue écrite et la langue orale, mais aussi à une reconnaissance difficile de certains morphèmes par l’existence de variantes phonologiques en fonction du contexte et par la proximité phonologique de certains morphèmes. Nous présentons également comment le contenu du premier module tente d’apporter des solutions à ces difficultés : en amenant les apprenants à prendre conscience du phénomène de réduction vocalique et d’inaccentuation qui touche certaines syllabes des mots aussi bien que certains éléments monosyllabiques de l’énoncé et en proposant un entraînement à la reconnaissance de ces éléments. Le module est en cours de validation avec une phase d’évaluation.French students who have English as part of their curriculum often express the wish to improve their comprehension of oral English. This led us to envisage the creation of a CALL product: MACAO (Modules to help in the comprehension of oral English. The first module has been created: "Training oneself for recognition". The computer was particularly adequate in this prospect. In this paper we present the most frequent difficulties in the comprehension of oral English: they can be related either to erroneous expectations based on the dissymmetry between the written form and the oral

  11. Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

    Science.gov (United States)

    Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

    2017-06-01

    The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

  12. Nature and nurture: environmental influences on a genetic rat model of depression.

    Science.gov (United States)

    Mehta-Raghavan, N S; Wert, S L; Morley, C; Graf, E N; Redei, E E

    2016-03-29

    In this study, we sought to learn whether adverse events such as chronic restraint stress (CRS), or 'nurture' in the form of environmental enrichment (EE), could modify depression-like behavior and blood biomarker transcript levels in a genetic rat model of depression. The Wistar Kyoto More Immobile (WMI) is a genetic model of depression that aided in the identification of blood transcriptomic markers, which successfully distinguished adolescent and adult subjects with major depressive disorders from their matched no-disorder controls. Here, we followed the effects of CRS and EE in adult male WMIs and their genetically similar control strain, the Wistar Kyoto Less Immobile (WLI), that does not show depression-like behavior, by measuring the levels of these transcripts in the blood and hippocampus. In WLIs, increased depression-like behavior and transcriptomic changes were present in response to CRS, but in WMIs no behavioral or additive transcriptomic changes occurred. Environmental enrichment decreased both the inherent depression-like behavior in the WMIs and the behavioral difference between WMIs and WLIs, but did not reverse basal transcript level differences between the strains. The inverse behavioral change induced by CRS and EE in the WLIs did not result in parallel inverse expression changes of the transcriptomic markers, suggesting that these behavioral responses to the environment work via separate molecular pathways. In contrast, 'trait' transcriptomic markers with expression differences inherent and unchanging between the strains regardless of the environment suggest that in our model, environmental and genetic etiologies of depression work through independent molecular mechanisms.

  13. Toward a comprehensive, theoretical model of compassion fatigue: An integrative literature review.

    Science.gov (United States)

    Coetzee, Siedine K; Laschinger, Heather K S

    2018-03-01

    This study was an integrative literature review in relation to compassion fatigue models, appraising these models, and developing a comprehensive theoretical model of compassion fatigue. A systematic search on PubMed, EbscoHost (Academic Search Premier, E-Journals, Medline, PsycINFO, Health Source Nursing/Academic Edition, CINAHL, MasterFILE Premier and Health Source Consumer Edition), gray literature, and manual searches of included reference lists was conducted in 2016. The studies (n = 11) were analyzed, and the strengths and limitations of the compassion fatigue models identified. We further built on these models through the application of the conservation of resources theory and the social neuroscience of empathy. The compassion fatigue model shows that it is not empathy that puts nurses at risk of developing compassion fatigue, but rather a lack of resources, inadequate positive feedback, and the nurse's response to personal distress. By acting on these three aspects, the risk of developing compassion fatigue can be addressed, which could improve the retention of a compassionate and committed nurse workforce. © 2017 John Wiley & Sons Australia, Ltd.

  14. Developing genetic epidemiological models to predict risk for nasopharyngeal carcinoma in high-risk population of China.

    Directory of Open Access Journals (Sweden)

    Hong-Lian Ruan

    Full Text Available To date, the only established model for assessing risk for nasopharyngeal carcinoma (NPC relies on the sero-status of the Epstein-Barr virus (EBV. By contrast, the risk assessment models proposed here include environmental risk factors, family history of NPC, and information on genetic variants. The models were developed using epidemiological and genetic data from a large case-control study, which included 1,387 subjects with NPC and 1,459 controls of Cantonese origin. The predictive accuracy of the models were then assessed by calculating the area under the receiver-operating characteristic curves (AUC. To compare the discriminatory improvement of models with and without genetic information, we estimated the net reclassification improvement (NRI and integrated discrimination index (IDI. Well-established environmental risk factors for NPC include consumption of salted fish and preserved vegetables and cigarette smoking (in pack years. The environmental model alone shows modest discriminatory ability (AUC = 0.68; 95% CI: 0.66, 0.70, which is only slightly increased by the addition of data on family history of NPC (AUC = 0.70; 95% CI: 0.68, 0.72. With the addition of data on genetic variants, however, our model's discriminatory ability rises to 0.74 (95% CI: 0.72, 0.76. The improvements in NRI and IDI also suggest the potential usefulness of considering genetic variants when screening for NPC in endemic areas. If these findings are confirmed in larger cohort and population-based case-control studies, use of the new models to analyse data from NPC-endemic areas could well lead to earlier detection of NPC.

  15. A genetic algorithm for solving supply chain network design model

    Science.gov (United States)

    Firoozi, Z.; Ismail, N.; Ariafar, S. H.; Tang, S. H.; Ariffin, M. K. M. A.

    2013-09-01

    Network design is by nature costly and optimization models play significant role in reducing the unnecessary cost components of a distribution network. This study proposes a genetic algorithm to solve a distribution network design model. The structure of the chromosome in the proposed algorithm is defined in a novel way that in addition to producing feasible solutions, it also reduces the computational complexity of the algorithm. Computational results are presented to show the algorithm performance.

  16. Estimating the actual subject-specific genetic correlations in behavior genetics.

    Science.gov (United States)

    Molenaar, Peter C M

    2012-10-01

    Generalization of the standard behavior longitudinal genetic factor model for the analysis of interindividual phenotypic variation to a genetic state space model for the analysis of intraindividual variation enables the possibility to estimate subject-specific heritabilities.

  17. A Tri-Part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning about Authentic Genetics Dilemmas

    Science.gov (United States)

    Shea, Nicole A.; Duncan, Ravit Golan; Stephenson, Celeste

    2015-01-01

    Genetics literacy is becoming increasingly important as advancements in our application of genetic technologies such as stem cell research, cloning, and genetic screening become more prevalent. Very few studies examine how genetics literacy is applied when reasoning about authentic genetic dilemmas. However, there is evidence that situational…

  18. Daily Distribution of Macronutrient Intakes of Professional Soccer Players From the English Premier League.

    Science.gov (United States)

    Anderson, Liam; Naughton, Robert J; Close, Graeme L; Di Michele, Rocco; Morgans, Ryland; Drust, Barry; Morton, James P

    2017-12-01

    The daily distribution of macronutrient intake can modulate aspects of training adaptations, performance and recovery. We therefore assessed the daily distribution of macronutrient intake (as assessed using food diaries supported by the remote food photographic method and 24-hr recalls) of professional soccer players (n = 6) of the English Premier League during a 7-day period consisting of two match days and five training days. On match days, average carbohydrate (CHO) content of the prematch (recovery from an evening kick-off) were similar (p > .05) though such intakes were lower than contemporary guidelines considered optimal for prematch CHO intake and postmatch recovery. On training days, we observed a skewed and hierarchical approach (p lunch (0.6 g·kg -1 )>breakfast (0.3 g·kg -1 )>evening snacks (0.1 g·kg -1 ). We conclude players may benefit from consuming greater amounts of CHO in both the prematch and postmatch meals so as to increase CHO availability and maximize rates of muscle glycogen resynthesis, respectively. Furthermore, attention should also be given to ensuring even daily distribution of protein intake so as to potentially promote components of training adaptation.

  19. [Analysis of genetic models and gene effects on main agronomy characters in rapeseed].

    Science.gov (United States)

    Li, J; Qiu, J; Tang, Z; Shen, L

    1992-01-01

    According to four different genetic models, the genetic patterns of 8 agronomy traits were analysed by using the data of 24 generations which included positive and negative cross of 81008 x Tower, both of the varieties are of good quality. The results showed that none of 8 characters could fit in with additive-dominance models. Epistasis was found in all of these characters, and it has significant effect on generation means. Seed weight/plant and some other main yield characters are controlled by duplicate interaction genes. The interaction between triple genes or multiple genes needs to be utilized in yield heterosis.

  20. 76 FR 37684 - Airworthiness Directives; Diamond Aircraft Industries GmbH Model (Diamond) DA 40 Airplanes...

    Science.gov (United States)

    2011-06-28

    ... Industries GmbH Model (Diamond) DA 40 Airplanes Equipped With Certain Cabin Air Conditioning Systems AGENCY... inspections of the Diamond Model DA 40 airplanes equipped with a VCS installed per Premier Aircraft Service... GmbH Model (Diamond) DA 40 Airplanes Equipped With Certain Cabin Air Conditioning Systems: Docket No...

  1. Evaluating the APEX model for simulating streamflow and water quality on ten agricultural watersheds in the U.S.

    Science.gov (United States)

    Simulation models are increasingly used to assess water quality constituent losses from agricultural systems. Mis-use often gives irrelevant or erroneous answers. The Agricultural Policy Environmental Extender (APEX) model is emerging as one of the premier modeling tools for fields, farms, and agr...

  2. Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

    Directory of Open Access Journals (Sweden)

    Maria Gabriela Campolina Diniz Peixoto

    2014-05-01

    Full Text Available The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524 of test-day milk yield (TDMY from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects, whereas the contemporary group, calving age (linear and quadratic effects and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

  3. Genetic algorithms used for PWRs refuel management automatic optimization: a new modelling

    International Nuclear Information System (INIS)

    Chapot, Jorge Luiz C.; Schirru, Roberto; Silva, Fernando Carvalho da

    1996-01-01

    A Genetic Algorithms-based system, linking the computer codes GENESIS 5.0 and ANC through the interface ALGER, has been developed aiming the PWRs fuel management optimization. An innovative codification, the Lists Model, has been incorporated to the genetic system, which avoids the use of variants of the standard crossover operator and generates only valid loading patterns in the core. The GENESIS/ALGER/ANC system has been successfully tested in an optimization study for Angra-1 second cycle. (author)

  4. Les marqueurs d'aspect de dicto : 'à première vue', 'au premier abord', 'de prime abord'

    Directory of Open Access Journals (Sweden)

    Lenepveu Véronique

    2012-07-01

    Full Text Available On se propose d’étudier les locutions adverbiales "à première vue", "au premier abord", "de prime abord", trois locutions qui comportent une forme numérale ordinale et qui entretiennent des relations de proximité sémantique. Nous nous intéressons précisément au fonctionnement sémantique et pragmatique de ces locutions à valeur paradigmatisante (Nølke 1983, quand elles introduisent un point de vue (Anscombre & Ducrot 1983, Ducrot 1984, Nølke 1994. Dans cette perspective, nous faisons l’hypothèse d’un procès énonciatif, qui consiste à prendre en considération une situation, et qui vise à constituer un jugement stabilisé. Nous admettons alors que les locutions adverbiales 'à première vue', 'au premier abord', 'de prime abord', servent à sélectionner la phase initiale de ce procès énonciatif, ce qu’attestent les mises en corrélation possibles des trois marqueurs de point de vue avec des expressions qui signalent une évolution dans le temps du jugement du locuteur concernant une situation ('à mieux regarder', 'à y regarder de plus près', 'tout compte fait', 'tout bien considéré', .... L’étude de ces enchaînements, qui vont parfois au-delà du paragraphe, fait apparaître la capacité des trois locutions à initier un cadre (Charolles 1997, et à appeler un autre cadre dans lequel le jugement va être réévalué. En présentant le point de vue qu’elle introduit comme provisoire et en attente de confirmation, chacune de ces locutions anticipe ainsi sur la suite du texte, et s’inscrit dans une structure aspectuelle de dicto qui est celle d’un procès énonciatif de constitution d’un jugement stabilisé. Nous nous appuyons sur des énoncés attestés au XXème, sélectionnés sur "Frantext intégral", ou bien choisis dans Le Monde sur cederom (1995-96, 1999-2002.

  5. Genetic analyses of partial egg production in Japanese quail using multi-trait random regression models.

    Science.gov (United States)

    Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E

    2017-12-01

    1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.

  6. Cost optimization model and its heuristic genetic algorithms

    International Nuclear Information System (INIS)

    Liu Wei; Wang Yongqing; Guo Jilin

    1999-01-01

    Interest and escalation are large quantity in proportion to the cost of nuclear power plant construction. In order to optimize the cost, the mathematics model of cost optimization for nuclear power plant construction was proposed, which takes the maximum net present value as the optimization goal. The model is based on the activity networks of the project and is an NP problem. A heuristic genetic algorithms (HGAs) for the model was introduced. In the algorithms, a solution is represented with a string of numbers each of which denotes the priority of each activity for assigned resources. The HGAs with this encoding method can overcome the difficulty which is harder to get feasible solutions when using the traditional GAs to solve the model. The critical path of the activity networks is figured out with the concept of predecessor matrix. An example was computed with the HGAP programmed in C language. The results indicate that the model is suitable for the objectiveness, the algorithms is effective to solve the model

  7. A genetic model of progressively partial melting for uranium-bearing granites in south China

    International Nuclear Information System (INIS)

    Zhai Jianping.

    1989-01-01

    A genetic model of progressively partial and enrichment mechanism of uranium during partial melting of the sources of material studied and the significance of the genetic model in search of uranium deposits is elaborated. This model accounts better for some geological and geochemical features of uranium-bearing granties and suspects the traditional idea that igneous uranium-bearing granites were formed by fusion of U-rich strata surrounding these granites. Finally this paper points out that the infuence of U-rich strata of wall rocks of granites over uranium-bearing granites depends on variation of water solubility in the magma and assimilation of magma to wall rocks during its ascending and crystallization

  8. Genetic complexity in a Drosophila model of diabetes-associated misfolded human proinsulin.

    Science.gov (United States)

    Park, Soo-Young; Ludwig, Michael Z; Tamarina, Natalia A; He, Bin Z; Carl, Sarah H; Dickerson, Desiree A; Barse, Levi; Arun, Bharath; Williams, Calvin L; Miles, Cecelia M; Philipson, Louis H; Steiner, Donald F; Bell, Graeme I; Kreitman, Martin

    2014-02-01

    Drosophila melanogaster has been widely used as a model of human Mendelian disease, but its value in modeling complex disease has received little attention. Fly models of complex disease would enable high-resolution mapping of disease-modifying loci and the identification of novel targets for therapeutic intervention. Here, we describe a fly model of permanent neonatal diabetes mellitus and explore the complexity of this model. The approach involves the transgenic expression of a misfolded mutant of human preproinsulin, hINS(C96Y), which is a cause of permanent neonatal diabetes. When expressed in fly imaginal discs, hINS(C96Y) causes a reduction of adult structures, including the eye, wing, and notum. Eye imaginal discs exhibit defects in both the structure and the arrangement of ommatidia. In the wing, expression of hINS(C96Y) leads to ectopic expression of veins and mechano-sensory organs, indicating disruption of wild-type signaling processes regulating cell fates. These readily measurable "disease" phenotypes are sensitive to temperature, gene dose, and sex. Mutant (but not wild-type) proinsulin expression in the eye imaginal disc induces IRE1-mediated XBP1 alternative splicing, a signal for endoplasmic reticulum stress response activation, and produces global change in gene expression. Mutant hINS transgene tester strains, when crossed to stocks from the Drosophila Genetic Reference Panel, produce F1 adults with a continuous range of disease phenotypes and large broad-sense heritability. Surprisingly, the severity of mutant hINS-induced disease in the eye is not correlated with that in the notum in these crosses, nor with eye reduction phenotypes caused by the expression of two dominant eye mutants acting in two different eye development pathways, Drop (Dr) or Lobe (L), when crossed into the same genetic backgrounds. The tissue specificity of genetic variability for mutant hINS-induced disease has, therefore, its own distinct signature. The genetic dominance

  9. Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model.

    Science.gov (United States)

    Tufto, Jarle

    2015-08-01

    Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

  10. Human Urine-Derived Renal Progenitors for Personalized Modeling of Genetic Kidney Disorders.

    Science.gov (United States)

    Lazzeri, Elena; Ronconi, Elisa; Angelotti, Maria Lucia; Peired, Anna; Mazzinghi, Benedetta; Becherucci, Francesca; Conti, Sara; Sansavini, Giulia; Sisti, Alessandro; Ravaglia, Fiammetta; Lombardi, Duccio; Provenzano, Aldesia; Manonelles, Anna; Cruzado, Josep M; Giglio, Sabrina; Roperto, Rosa Maria; Materassi, Marco; Lasagni, Laura; Romagnani, Paola

    2015-08-01

    The critical role of genetic and epigenetic factors in the pathogenesis of kidney disorders is gradually becoming clear, and the need for disease models that recapitulate human kidney disorders in a personalized manner is paramount. In this study, we describe a method to select and amplify renal progenitor cultures from the urine of patients with kidney disorders. Urine-derived human renal progenitors exhibited phenotype and functional properties identical to those purified from kidney tissue, including the capacity to differentiate into tubular cells and podocytes, as demonstrated by confocal microscopy, Western blot analysis of podocyte-specific proteins, and scanning electron microscopy. Lineage tracing studies performed with conditional transgenic mice, in which podocytes are irreversibly tagged upon tamoxifen treatment (NPHS2.iCreER;mT/mG), that were subjected to doxorubicin nephropathy demonstrated that renal progenitors are the only urinary cell population that can be amplified in long-term culture. To validate the use of these cells for personalized modeling of kidney disorders, renal progenitors were obtained from (1) the urine of children with nephrotic syndrome and carrying potentially pathogenic mutations in genes encoding for podocyte proteins and (2) the urine of children without genetic alterations, as validated by next-generation sequencing. Renal progenitors obtained from patients carrying pathogenic mutations generated podocytes that exhibited an abnormal cytoskeleton structure and functional abnormalities compared with those obtained from patients with proteinuria but without genetic mutations. The results of this study demonstrate that urine-derived patient-specific renal progenitor cultures may be an innovative research tool for modeling of genetic kidney disorders. Copyright © 2015 by the American Society of Nephrology.

  11. Genetic Programming and Standardization in Water Temperature Modelling

    Directory of Open Access Journals (Sweden)

    Maritza Arganis

    2009-01-01

    Full Text Available An application of Genetic Programming (an evolutionary computational tool without and with standardization data is presented with the aim of modeling the behavior of the water temperature in a river in terms of meteorological variables that are easily measured, to explore their explanatory power and to emphasize the utility of the standardization of variables in order to reduce the effect of those with large variance. Recorded data corresponding to the water temperature behavior at the Ebro River, Spain, are used as analysis case, showing a performance improvement on the developed model when data are standardized. This improvement is reflected in a reduction of the mean square error. Finally, the models obtained in this document were applied to estimate the water temperature in 2004, in order to provide evidence about their applicability to forecasting purposes.

  12. Consequences of the genetic threshold model for observing partial migration under climate change scenarios.

    Science.gov (United States)

    Cobben, Marleen M P; van Noordwijk, Arie J

    2017-10-01

    Migration is a widespread phenomenon across the animal kingdom as a response to seasonality in environmental conditions. Partially migratory populations are populations that consist of both migratory and residential individuals. Such populations are very common, yet their stability has long been debated. The inheritance of migratory activity is currently best described by the threshold model of quantitative genetics. The inclusion of such a genetic threshold model for migratory behavior leads to a stable zone in time and space of partially migratory populations under a wide range of demographic parameter values, when assuming stable environmental conditions and unlimited genetic diversity. Migratory species are expected to be particularly sensitive to global warming, as arrival at the breeding grounds might be increasingly mistimed as a result of the uncoupling of long-used cues and actual environmental conditions, with decreasing reproduction as a consequence. Here, we investigate the consequences for migratory behavior and the stability of partially migratory populations under five climate change scenarios and the assumption of a genetic threshold value for migratory behavior in an individual-based model. The results show a spatially and temporally stable zone of partially migratory populations after different lengths of time in all scenarios. In the scenarios in which the species expands its range from a particular set of starting populations, the genetic diversity and location at initialization determine the species' colonization speed across the zone of partial migration and therefore across the entire landscape. Abruptly changing environmental conditions after model initialization never caused a qualitative change in phenotype distributions, or complete extinction. This suggests that climate change-induced shifts in species' ranges as well as changes in survival probabilities and reproductive success can be met with flexibility in migratory behavior at the

  13. Efficient multiple-trait association and estimation of genetic correlation using the matrix-variate linear mixed model.

    Science.gov (United States)

    Furlotte, Nicholas A; Eskin, Eleazar

    2015-05-01

    Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. An implementation of this method is available at http://genetics.cs.ucla.edu/mvLMM. Copyright © 2015 by the Genetics Society of America.

  14. System Response Analysis and Model Order Reduction, Using Conventional Method, Bond Graph Technique and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lubna Moin

    2009-04-01

    Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and

  15. Genetic human prion disease modelled in PrP transgenic Drosophila.

    Science.gov (United States)

    Thackray, Alana M; Cardova, Alzbeta; Wolf, Hanna; Pradl, Lydia; Vorberg, Ina; Jackson, Walker S; Bujdoso, Raymond

    2017-09-20

    Inherited human prion diseases, such as fatal familial insomnia (FFI) and familial Creutzfeldt-Jakob disease (fCJD), are associated with autosomal dominant mutations in the human prion protein gene PRNP and accumulation of PrP Sc , an abnormal isomer of the normal host protein PrP C , in the brain of affected individuals. PrP Sc is the principal component of the transmissible neurotoxic prion agent. It is important to identify molecular pathways and cellular processes that regulate prion formation and prion-induced neurotoxicity. This will allow identification of possible therapeutic interventions for individuals with, or at risk from, genetic human prion disease. Increasingly, Drosophila has been used to model human neurodegenerative disease. An important unanswered question is whether genetic prion disease with concomitant spontaneous prion formation can be modelled in Drosophila We have used pUAST/PhiC31-mediated site-directed mutagenesis to generate Drosophila transgenic for murine or hamster PrP (prion protein) that carry single-codon mutations associated with genetic human prion disease. Mouse or hamster PrP harbouring an FFI (D178N) or fCJD (E200K) mutation showed mild Proteinase K resistance when expressed in Drosophila Adult Drosophila transgenic for FFI or fCJD variants of mouse or hamster PrP displayed a spontaneous decline in locomotor ability that increased in severity as the flies aged. Significantly, this mutant PrP-mediated neurotoxic fly phenotype was transferable to recipient Drosophila that expressed the wild-type form of the transgene. Collectively, our novel data are indicative of the spontaneous formation of a PrP-dependent neurotoxic phenotype in FFI- or CJD-PrP transgenic Drosophila and show that inherited human prion disease can be modelled in this invertebrate host. © 2017 The Author(s).

  16. Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study

    NARCIS (Netherlands)

    Rijsdijk, F.V.; Vernon, P.A.; Boomsma, D.I.

    2002-01-01

    Hierarchical models of intelligence are highly informative and widely accepted. Application of these models to twin data, however, is sparse. This paper addresses the question of how a genetic hierarchical model fits the Wechsler Adult Intelligence Scale (WAIS) subtests and the Raven Standard

  17. Modeling Self-Healing of Concrete Using Hybrid Genetic Algorithm-Artificial Neural Network.

    Science.gov (United States)

    Ramadan Suleiman, Ahmed; Nehdi, Moncef L

    2017-02-07

    This paper presents an approach to predicting the intrinsic self-healing in concrete using a hybrid genetic algorithm-artificial neural network (GA-ANN). A genetic algorithm was implemented in the network as a stochastic optimizing tool for the initial optimal weights and biases. This approach can assist the network in achieving a global optimum and avoid the possibility of the network getting trapped at local optima. The proposed model was trained and validated using an especially built database using various experimental studies retrieved from the open literature. The model inputs include the cement content, water-to-cement ratio (w/c), type and dosage of supplementary cementitious materials, bio-healing materials, and both expansive and crystalline additives. Self-healing indicated by means of crack width is the model output. The results showed that the proposed GA-ANN model is capable of capturing the complex effects of various self-healing agents (e.g., biochemical material, silica-based additive, expansive and crystalline components) on the self-healing performance in cement-based materials.

  18. Modeling AEC—New Approaches to Study Rare Genetic Disorders

    Science.gov (United States)

    Koch, Peter J.; Dinella, Jason; Fete, Mary; Siegfried, Elaine C.; Koster, Maranke I.

    2015-01-01

    Ankyloblepharon-ectodermal defects-cleft lip/palate (AEC) syndrome is a rare monogenetic disorder that is characterized by severe abnormalities in ectoderm-derived tissues, such as skin and its appendages. A major cause of morbidity among affected infants is severe and chronic skin erosions. Currently, supportive care is the only available treatment option for AEC patients. Mutations in TP63, a gene that encodes key regulators of epidermal development, are the genetic cause of AEC. However, it is currently not clear how mutations in TP63 lead to the various defects seen in the patients’ skin. In this review, we will discuss current knowledge of the AEC disease mechanism obtained by studying patient tissue and genetically engineered mouse models designed to mimic aspects of the disorder. We will then focus on new approaches to model AEC, including the use of patient cells and stem cell technology to replicate the disease in a human tissue culture model. The latter approach will advance our understanding of the disease and will allow for the development of new in vitro systems to identify drugs for the treatment of skin erosions in AEC patients. Further, the use of stem cell technology, in particular induced pluripotent stem cells (iPSC), will enable researchers to develop new therapeutic approaches to treat the disease using the patient’s own cells (autologous keratinocyte transplantation) after correction of the disease-causing mutations. PMID:24665072

  19. Conception et réalisation de l'unité de décision du système de déclenchement de premier niveau du détecteur LHCb au LHC

    CERN Document Server

    Laubser, Julien

    2007-01-01

    Le detecteur LHCb est l'une des quatre experiences de physique des particules installees sur la nouvelle chaine d'acceleration LHC (Large Hadron Collider) du CERN a Geneve. Afin de reduire la quantite de donnees destinees au stockage pour les analyses hors ligne, un dispositif de selection en ligne des collisions interessantes selon la physique a etudier est mis en place en parallele de la chaine d'acquisition des donnees. Ce dispositif est compose d'un premier niveau(niveau 0) realise par un systeme electronique complexe et d'un second niveau de selection realise par informatique HLT (High Level Trigger). L'unite de decision de niveau 0 (L0DU) est le systeme central du niveau 0 de declenchement. L0DU prend la decision d'accepter ou de rejeter la collision pour ce premier niveau a partir d'une fraction d'informations issues des sous-detecteurs les plus rapides (432 bits a 80 MHz). L'unite de decision est un circuit imprime 16 couches integrant des composants de haute technologie de type FPGA (Field Programmab...

  20. Study of the first collective levels of the even-even nuclei between masses 182 and 206; Etude des premiers niveaux collectifs des noyaux pairs-pairs entre les masses 182 et 206

    Energy Technology Data Exchange (ETDEWEB)

    Barloutaud, R; Leveque, A; Lehmann, P; Quidort, J [Commissariat a l' Energie Atomique, Saclay (France).Centre d' Etudes Nucleaires

    1959-07-01

    The reduced probabilities of deexcitation of the first two 2 + levels of {sup 184}W, {sup 186}W, {sup 188}Os, {sup 190}Os, {sup 192}Os and {sup 194}Pt have been deduced from coulombic excitation experiments on these nuclei.The results are included in a chart of the properties of the first two 2 + levels of even-even nuclei situated between masses 182 and 206. The variation of these properties as a function of nuclear distortion is compared with the various theoretical predictions concerning vibration levels. (author) [French] Les probabilites reduites de desexcitation des deux premiers niveaux 2 + de {sup 184}W, {sup 186}W, {sup 188}Os, {sup 190}Os, {sup 192}Os and {sup 194}Pt ont ete deduites des experiences d'excitation coulombienne de ces noyaux. Les resultats sont inseres dans une systematique des proprietes des deux premiers niveaux 2 + des noyaux pairs-pairs situes entre les masses 182 et 206. La variation de ces proprietes en fonction de la deformation nucleaire est comparee aux diverses predictions theoriques concernant les niveaux de vibration. (auteur)

  1. Molecular genetics of cancer and tumorigenesis: Drosophila models

    Institute of Scientific and Technical Information of China (English)

    Wu-Min Deng

    2011-01-01

    Why do some cells not respond to normal control of cell division and become tumorous? Which signals trigger some tumor cells to migrate and colonize other tissues? What genetic factors are responsible for tumorigenesis and cancer development? What environmental factors play a role in cancer formation and progression? In how many ways can our bodies prevent and restrict the growth of cancerous cells?How can we identify and deliver effective drugs to fight cancer? In the fight against cancer,which kills more people than any other disease,these and other questions have long interested researchers from a diverse range of fields.To answer these questions and to fight cancer more effectively,we must increase our understanding of basic cancer biology.Model organisms,including the fruit fly Drosophila melanogaster,have played instrumental roles in our understanding of this devastating disease and the search for effective cures.Drosophila and its highly effective,easy-touse,and ever-expanding genetic tools have contributed toand enriched our knowledge of cancer and tumor formation tremendously.

  2. Experiencing the genetic body: parents' encounters with pediatric clinical genetics.

    Science.gov (United States)

    Raspberry, Kelly; Skinner, Debra

    2007-01-01

    Because of advancements in genetic research and technologies, the clinical practice of genetics is becoming a prevalent component of biomedicine. As the genetic basis for more and more diseases are found, it is possible that ways of experiencing health, illness, identity, kin relations, and the body are becoming geneticized, or understood within a genetic model of disease. Yet, other models and relations that go beyond genetic explanations also shape interpretations of health and disease. This article explores how one group of individuals for whom genetic disorder is highly relevant formulates their views of the body in light of genetic knowledge. Using data from an ethnographic study of 106 parents or potential parents of children with known or suspected genetic disorders who were referred to a pediatric genetic counseling and evaluation clinic in the southeastern United States, we find that these parents do, to some degree, perceive of their children's disorders in terms of a genetic body that encompasses two principal qualities: a sense of predetermined health and illness and an awareness of a profound historicity that reaches into the past and extends into the present and future. They experience this genetic body as both fixed and historical, but they also express ideas of a genetic body made less deterministic by their own efforts and future possibilities. This account of parents' experiences with genetics and clinical practice contributes to a growing body of work on the ways in which genetic information and technologies are transforming popular and medical notions of the body, and with it, health, illness, kinship relations, and personal and social identities.

  3. Evaluating the Genetics of Common Variable Immunodeficiency: Monogenetic Model and Beyond

    Directory of Open Access Journals (Sweden)

    Guillem de Valles-Ibáñez

    2018-05-01

    Full Text Available Common variable immunodeficiency (CVID is the most frequent symptomatic primary immunodeficiency characterized by recurrent infections, hypogammaglobulinemia and poor response to vaccines. Its diagnosis is made based on clinical and immunological criteria, after exclusion of other diseases that can cause similar phenotypes. Currently, less than 20% of cases of CVID have a known underlying genetic cause. We have analyzed whole-exome sequencing and copy number variants data of 36 children and adolescents diagnosed with CVID and healthy relatives to estimate the proportion of monogenic cases. We have replicated an association of CVID to p.C104R in TNFRSF13B and reported the second case of homozygous patient to date. Our results also identify five causative genetic variants in LRBA, CTLA4, NFKB1, and PIK3R1, as well as other very likely causative variants in PRKCD, MAPK8, or DOCK8 among others. We experimentally validate the effect of the LRBA stop-gain mutation which abolishes protein production and downregulates the expression of CTLA4, and of the frameshift indel in CTLA4 producing expression downregulation of the protein. Our results indicate a monogenic origin of at least 15–24% of the CVID cases included in the study. The proportion of monogenic patients seems to be lower in CVID than in other PID that have also been analyzed by whole exome or targeted gene panels sequencing. Regardless of the exact proportion of CVID monogenic cases, other genetic models have to be considered for CVID. We propose that because of its prevalence and other features as intermediate penetrancies and phenotypic variation within families, CVID could fit with other more complex genetic scenarios. In particular, in this work, we explore the possibility of CVID being originated by an oligogenic model with the presence of heterozygous mutations in interacting proteins or by the accumulation of detrimental variants in particular immunological pathways, as well as

  4. Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models.

    Science.gov (United States)

    Berry, D P; Buckley, F; Dillon, P; Evans, R D; Rath, M; Veerkamp, R F

    2003-11-01

    Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.

  5. Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models.

    Science.gov (United States)

    De Haas, Y; Janss, L L G; Kadarmideen, H N

    2007-10-01

    Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

  6. Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

    Science.gov (United States)

    Bellucci, Michael A; Coker, David F

    2011-07-28

    We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. © 2011 American Institute of Physics

  7. Parameters Calculation of ZnO Surge Arrester Models by Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    A. Bayadi

    2006-09-01

    Full Text Available This paper proposes to provide a new technique based on the genetic algorithm to obtain the best possible series of values of the parameters of the ZnO surge arresters models. The validity of the predicted parameters is then checked by comparing the results predicted with the experimental results available in the literature. Using the ATP-EMTP package an application of the arrester model on network system studies is presented and discussed.

  8. Comparing ESC and iPSC?Based Models for Human Genetic Disorders

    OpenAIRE

    Halevy, Tomer; Urbach, Achia

    2014-01-01

    Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients’ somatic cells, and the ne...

  9. Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

    Science.gov (United States)

    Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

    2009-07-01

    Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

  10. Poisson versus threshold models for genetic analysis of clinical mastitis in US Holsteins.

    Science.gov (United States)

    Vazquez, A I; Weigel, K A; Gianola, D; Bates, D M; Perez-Cabal, M A; Rosa, G J M; Chang, Y M

    2009-10-01

    Typically, clinical mastitis is coded as the presence or absence of disease in a given lactation, and records are analyzed with either linear models or binary threshold models. Because the presence of mastitis may include cows with multiple episodes, there is a loss of information when counts are treated as binary responses. Poisson models are appropriated for random variables measured as the number of events, and although these models are used extensively in studying the epidemiology of mastitis, they have rarely been used for studying the genetic aspects of mastitis. Ordinal threshold models are pertinent for ordered categorical responses; although one can hypothesize that the number of clinical mastitis episodes per animal reflects a continuous underlying increase in mastitis susceptibility, these models have rarely been used in genetic analysis of mastitis. The objective of this study was to compare probit, Poisson, and ordinal threshold models for the genetic evaluation of US Holstein sires for clinical mastitis. Mastitis was measured as a binary trait or as the number of mastitis cases. Data from 44,908 first-parity cows recorded in on-farm herd management software were gathered, edited, and processed for the present study. The cows were daughters of 1,861 sires, distributed over 94 herds. Predictive ability was assessed via a 5-fold cross-validation using 2 loss functions: mean squared error of prediction (MSEP) as the end point and a cost difference function. The heritability estimates were 0.061 for mastitis measured as a binary trait in the probit model and 0.085 and 0.132 for the number of mastitis cases in the ordinal threshold and Poisson models, respectively; because of scale differences, only the probit and ordinal threshold models are directly comparable. Among healthy animals, MSEP was smallest for the probit model, and the cost function was smallest for the ordinal threshold model. Among diseased animals, MSEP and the cost function were smallest

  11. An Adaptive Agent-Based Model of Homing Pigeons: A Genetic Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Francis Oloo

    2017-01-01

    Full Text Available Conventionally, agent-based modelling approaches start from a conceptual model capturing the theoretical understanding of the systems of interest. Simulation outcomes are then used “at the end” to validate the conceptual understanding. In today’s data rich era, there are suggestions that models should be data-driven. Data-driven workflows are common in mathematical models. However, their application to agent-based models is still in its infancy. Integration of real-time sensor data into modelling workflows opens up the possibility of comparing simulations against real data during the model run. Calibration and validation procedures thus become automated processes that are iteratively executed during the simulation. We hypothesize that incorporation of real-time sensor data into agent-based models improves the predictive ability of such models. In particular, that such integration results in increasingly well calibrated model parameters and rule sets. In this contribution, we explore this question by implementing a flocking model that evolves in real-time. Specifically, we use genetic algorithms approach to simulate representative parameters to describe flight routes of homing pigeons. The navigation parameters of pigeons are simulated and dynamically evaluated against emulated GPS sensor data streams and optimised based on the fitness of candidate parameters. As a result, the model was able to accurately simulate the relative-turn angles and step-distance of homing pigeons. Further, the optimised parameters could replicate loops, which are common patterns in flight tracks of homing pigeons. Finally, the use of genetic algorithms in this study allowed for a simultaneous data-driven optimization and sensitivity analysis.

  12. A Comparison of Telephone Genetic Counseling and In-Person Genetic Counseling from the Genetic Counselor's Perspective.

    Science.gov (United States)

    Burgess, Kelly R; Carmany, Erin P; Trepanier, Angela M

    2016-02-01

    Growing demand for and limited geographic access to genetic counseling services is increasing the need for alternative service delivery models (SDM) like telephone genetic counseling (TGC). Little research has been done on genetic counselors' perspectives of the practice of TGC. We created an anonymous online survey to assess whether telephone genetic counselors believed the tasks identified in the ABGC (American Board of Genetic Counseling) Practice Analysis were performed similarly or differently in TGC compared to in person genetic counseling (IPGC). If there were differences noted, we sought to determine the nature of the differences and if additional training might be needed to address them. Eighty eight genetic counselors with experience in TGC completed some or all of the survey. Respondents identified differences in 13 (14.8%) of the 88 tasks studied. The tasks identified as most different in TGC were: "establishing rapport through verbal and nonverbal interactions" (60.2%; 50/83 respondents identified the task as different), "recognizing factors affecting the counseling interaction" (47.8%; 32/67), "assessing client/family emotions, support, etc." (40.1%; 27/66) and "educating clients about basic genetic concepts" (35.6%; 26/73). A slight majority (53.8%; 35/65) felt additional training was needed to communicate information without visual aids and more effectively perform psychosocial assessments. In summary, although a majority of genetic counseling tasks are performed similarly between TGC and IPGC, TGC counselors recognize that specific training in the TGC model may be needed to address the key differences.

  13. Genetic coding and united-hypercomplex systems in the models of algebraic biology.

    Science.gov (United States)

    Petoukhov, Sergey V

    2017-08-01

    Structured alphabets of DNA and RNA in their matrix form of representations are connected with Walsh functions and a new type of systems of multidimensional numbers. This type generalizes systems of complex numbers and hypercomplex numbers, which serve as the basis of mathematical natural sciences and many technologies. The new systems of multi-dimensional numbers have interesting mathematical properties and are called in a general case as "systems of united-hypercomplex numbers" (or briefly "U-hypercomplex numbers"). They can be widely used in models of multi-parametrical systems in the field of algebraic biology, artificial life, devices of biological inspired artificial intelligence, etc. In particular, an application of U-hypercomplex numbers reveals hidden properties of genetic alphabets under cyclic permutations in their doublets and triplets. A special attention is devoted to the author's hypothesis about a multi-linguistic in DNA-sequences in a relation with an ensemble of U-numerical sub-alphabets. Genetic multi-linguistic is considered as an important factor to provide noise-immunity properties of the multi-channel genetic coding. Our results attest to the conformity of the algebraic properties of the U-numerical systems with phenomenological properties of the DNA-alphabets and with the complementary device of the double DNA-helix. It seems that in the modeling field of algebraic biology the genetic-informational organization of living bodies can be considered as a set of united-hypercomplex numbers in some association with the famous slogan of Pythagoras "the numbers rule the world". Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Deficits in fine motor skills in a genetic animal model of ADHD

    Directory of Open Access Journals (Sweden)

    Qian Yu

    2010-09-01

    Full Text Available Abstract Background In an attempt to model some behavioral aspects of Attention Deficit/Hyperactivity Disorder (ADHD, we examined whether an existing genetic animal model of ADHD is valid for investigating not only locomotor hyperactivity, but also more complex motor coordination problems displayed by the majority of children with ADHD. Methods We subjected young adolescent Spontaneously Hypertensive Rats (SHRs, the most commonly used genetic animal model of ADHD, to a battery of tests for motor activity, gross motor coordination, and skilled reaching. Wistar (WIS rats were used as controls. Results Similar to children with ADHD, young adolescent SHRs displayed locomotor hyperactivity in a familiar, but not in a novel environment. They also had lower performance scores in a complex skilled reaching task when compared to WIS rats, especially in the most sensitive measure of skilled performance (i.e., single attempt success. In contrast, their gross motor performance on a Rota-Rod test was similar to that of WIS rats. Conclusion The results support the notion that the SHR strain is a useful animal model system to investigate potential molecular mechanisms underlying fine motor skill problems in children with ADHD.

  15. PENGARUH PEMBAGIAN KERJA TERHADAP PENINGKATAN EFISIENSI KERJA KARYAWAN PASTRY DI HOTEL SANTIKA PREMIERE MALANG

    Directory of Open Access Journals (Sweden)

    Estikowati Estikowati

    2017-12-01

    Full Text Available The study was conducted to determine the effect of the division of labor on the work efficiency of pastry employees at Hotel Santika Premiere Malang. Work efficiency relates to the product produced with the resources used. While the division of labor is a separator type of work done by individuals. Researchers used the Simple Linear Regression Analyze method to predict how far the value of the dependent variable will be changed if the independent variable is changed. From result of research of independent variable (X that is Division of labor and dependent variable (Y Work efficiency have significant relation. This is evidenced from the data processing is known significant value sebersar 0.003 <0.05, with the conclusion Ho rejected and Ha accepted that there is influence between the Division of labor (X on Efficiency of work. From the questionnaire data the authors conclude that the existing division of labor is not appropriate for employees so that the level of efficiency of employees decreased. Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-ansi-language:IN;} The study was conducted to determine the effect of the division of labor on the work efficiency of pastry employees at Hotel Santika Premiere Malang. Work efficiency relates to the product produced with the resources used. While the division of labor is

  16. OPTIMIZATION OF LAND USE SUITABILITY FOR AGRICULTURE USING INTEGRATED GEOSPATIAL MODEL AND GENETIC ALGORITHMS

    Directory of Open Access Journals (Sweden)

    S. B. Mansor

    2012-08-01

    Full Text Available In this study, a geospatial model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the infrastructural preference. The model was developed based on multi-agent genetic algorithm. The model was customized to accommodate the constraint set for the study area, namely the resource saving and environmental-friendly. The model was then applied to solve the practical multi-objective spatial optimization allocation problems of land use in the core region of Menderjan Basin in Iran. The first task was to study the dominant crops and economic suitability evaluation of land. Second task was to determine the fitness function for the genetic algorithms. The third objective was to optimize the land use map using economical benefits. The results has indicated that the proposed model has much better performance for solving complex multi-objective spatial optimization allocation problems and it is a promising method for generating land use alternatives for further consideration in spatial decision-making.

  17. Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

    Directory of Open Access Journals (Sweden)

    Guosheng Su

    Full Text Available Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1 a simple additive genetic model (MA, 2 a model including both additive and additive by additive epistatic genetic effects (MAE, 3 a model including both additive and dominance genetic effects (MAD, and 4 a full model including all three genetic components (MAED. Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.

  18. Using Genetically Engineered Animal Models in the Postgenomic Era to Understand Gene Function in Alcoholism

    Science.gov (United States)

    Reilly, Matthew T.; Harris, R. Adron; Noronha, Antonio

    2012-01-01

    Over the last 50 years, researchers have made substantial progress in identifying genetic variations that underlie the complex phenotype of alcoholism. Not much is known, however, about how this genetic variation translates into altered biological function. Genetic animal models recapitulating specific characteristics of the human condition have helped elucidate gene function and the genetic basis of disease. In particular, major advances have come from the ability to manipulate genes through a variety of genetic technologies that provide an unprecedented capacity to determine gene function in the living organism and in alcohol-related behaviors. Even newer genetic-engineering technologies have given researchers the ability to control when and where a specific gene or mutation is activated or deleted, allowing investigators to narrow the role of the gene’s function to circumscribed neural pathways and across development. These technologies are important for all areas of neuroscience, and several public and private initiatives are making a new generation of genetic-engineering tools available to the scientific community at large. Finally, high-throughput “next-generation sequencing” technologies are set to rapidly increase knowledge of the genome, epigenome, and transcriptome, which, combined with genetically engineered mouse mutants, will enhance insight into biological function. All of these resources will provide deeper insight into the genetic basis of alcoholism. PMID:23134044

  19. Descriptive epidemiology of injuries in a Brazilian premier league soccer team

    Directory of Open Access Journals (Sweden)

    Fachina RJ

    2013-06-01

    Full Text Available Rafael Júlio de Freitas Guina Fachina,1,2 Marília dos Santos Andrade,3 Fernando Roberto Silva,4 Silas Waszczuk-Junior,4 Paulo César Montagner,1 João Paulo Borin,1 Claudio Andre Barbosa de Lira5 1Departamento de Ciência do Esporte, Faculdade de Educação Física, Universidade Estadual de Campinas (UNICAMP, Campinas, Brazil; 2Confederação Brasileira de Basketball (CBB, Rio de Janeiro, Brazil; 3Departamento de Fisiologia, Universidade Federal de São Paulo, São Paulo, Brazil; 4Grêmio Barueri Futebol LTDA, Barueri, Brazil; 5Setor de Fisiologia Humana e do Exercício, Universidade Federal de Goiás, Câmpus Jataí, Jataí, Brazil Abstract: Soccer, which has a large number of participants, has a high injury incidence that causes both financial and time burdens. Therefore, knowledge about the epidemiology of soccer injuries could allow sports-medicine professionals, such as physicians and physiotherapists, to direct their work in specific preventive programs. Thus, our aim was to conduct an epidemiological survey of injuries sustained by professional soccer players from the same team who participated in the Brazilian championship premier league in 2009. To this end, we evaluated retrospectively player medical records from the team, which included name, date of birth, position, date of injury, mechanism of injury, and type of injury. In the period of study, 95 injuries were recorded: 42 (44.2% were recorded during matches, and 53 (55.8% during the training period. Injuries occurred more frequently in midfielders and strikers. All injuries happened in the lower limb, most of the injuries were muscular, and most occurred as the result of collisions with other athletes. In summary, this study demonstrates that there is a need for greater safety awareness in the training environment. Keywords: injuries, epidemiology, soccer players

  20. Mobil positioning itself to become Canada's premier oil and gas company

    International Nuclear Information System (INIS)

    Thomas, A.

    1994-01-01

    To achieve its goal of becoming Canada's premier oil and gas company by the year 2000, Mobil Oil Canada is empowering its employees and applying appropriate technology to unlock resources and create value. Mobil produces 4.1 million m 3 of oil and natural gas liquids, 5.6 million m 3 /y of natural gas and 438,000 tonnes/y of sulfur. It also operates over 3,000 wells in western Canada and eleven gas processing plants, manages 1,700 km of pipeline, and has 33% interest in the Hibernia project on the Grand Banks. Oil lifting costs have decreased over the past three years from $3.40/bbl to $2.80/bbl and development costs are under $2/bbl. Innovative technology used to achieve high production and low costs include the use of three dimensional seismic surveys and horizontal drilling. Other techniques used at particular sites include installation of downhole injection regulators to control problems of segregation and metering between different water injection zones at the Carson Creek field, use of artificial lifts in gas wells, and a dual gas lift at the Rainbow Lake oil field. At the Lone Pine gas plant, the first Superclaus-99 sulfur recovery process was installed, reducing sulfur emissions by 60% and increasing recovery efficiency from 95% to 98%. Mobil has operated in Canada since 1940 and has made significant discoveries, including Canada's largest producing oil field, the Pembina. In 1971, Mobil discovered gas of commercial significance off the east coast and helped discover the Hibernia and Venture fields. The Hibernia project is scheduled to come on stream in 1997 and Mobil expects the economics of the project to be favorable, with a $12-13/bbl oil price needed to break even. 7 figs

  1. Comparison of whole-genome prediction models for traits with contrasting genetic architecture in a diversity panel of maize inbred lines

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    Riedelsheimer Christian

    2012-09-01

    Full Text Available Abstract Background There is increasing empirical evidence that whole-genome prediction (WGP is a powerful tool for predicting line and hybrid performance in maize. However, there is a lack of knowledge about the sensitivity of WGP models towards the genetic architecture of the trait. Whereas previous studies exclusively focused on highly polygenic traits, important agronomic traits such as disease resistances, nutrifunctional or climate adaptational traits have a genetic architecture which is either much less complex or unknown. For such cases, information about model robustness and guidelines for model selection are lacking. Here, we compared five WGP models with different assumptions about the distribution of the underlying genetic effects. As contrasting model traits, we chose three highly polygenic agronomic traits and three metabolites each with a major QTL explaining 22 to 30% of the genetic variance in a panel of 289 diverse maize inbred lines genotyped with 56,110 SNPs. Results We found the five WGP models to be remarkable robust towards trait architecture with the largest differences in prediction accuracies ranging between 0.05 and 0.14 for the same trait, most likely as the result of the high level of linkage disequilibrium prevailing in elite maize germplasm. Whereas RR-BLUP performed best for the agronomic traits, it was inferior to LASSO or elastic net for the three metabolites. We found the approach of genome partitioning of genetic variance, first applied in human genetics, as useful in guiding the breeder which model to choose, if prior knowledge of the trait architecture is lacking. Conclusions Our results suggest that in diverse germplasm of elite maize inbred lines with a high level of LD, WGP models differ only slightly in their accuracies, irrespective of the number and effects of QTL found in previous linkage or association mapping studies. However, small gains in prediction accuracies can be achieved if the WGP model is

  2. Molecular Population Genetics.

    Science.gov (United States)

    Casillas, Sònia; Barbadilla, Antonio

    2017-03-01

    Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data. Copyright © 2017 Casillas and Barbadilla.

  3. Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

    Science.gov (United States)

    Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

    2017-01-01

    This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

  4. Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops

    Science.gov (United States)

    Ru, Sushan; Hardner, Craig; Carter, Patrick A; Evans, Kate; Main, Dorrie; Peace, Cameron

    2016-01-01

    Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations—known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available. PMID:27148453

  5. Automated Test Assembly for Cognitive Diagnosis Models Using a Genetic Algorithm

    Science.gov (United States)

    Finkelman, Matthew; Kim, Wonsuk; Roussos, Louis A.

    2009-01-01

    Much recent psychometric literature has focused on cognitive diagnosis models (CDMs), a promising class of instruments used to measure the strengths and weaknesses of examinees. This article introduces a genetic algorithm to perform automated test assembly alongside CDMs. The algorithm is flexible in that it can be applied whether the goal is to…

  6. Les premiers tours du monde à forfait. L’exemple de la Société des Voyages d’Etudes Autour du Monde (1878)

    OpenAIRE

    Gauthier, Lionel

    2012-01-01

    Dans la seconde moitié du XIXe siècle, avec le développement du bateau à vapeur et du chemin de fer, et l’ouverture de nouveaux axes de transport comme le Canal de Suez, le voyage autour du monde devient envisageable pour les touristes. Ainsi, dès 1872 des tours du monde à forfait sont organisés, ce qui témoigne de l’entrée du voyage autour du monde dans l’industrie touristique naissante. Cet article étudie ces premiers voyages d’un nouveau genre à travers l’exemple de la Société des Voyages ...

  7. Strategies for MCMC computation in quantitative genetics

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Ibanez, Noelia; Sorensen, Daniel

    2006-01-01

    Given observations of a trait and a pedigree for a group of animals, the basic model in quantitative genetics is a linear mixed model with genetic random effects. The correlation matrix of the genetic random effects is determined by the pedigree and is typically very highdimensional but with a sp......Given observations of a trait and a pedigree for a group of animals, the basic model in quantitative genetics is a linear mixed model with genetic random effects. The correlation matrix of the genetic random effects is determined by the pedigree and is typically very highdimensional...

  8. Les premiers temps de l'architecture en briques au nord des Alpes : la question de l'origine cistercienne vue des Pays-Bas

    OpenAIRE

    Lehouck, Alexander

    2017-01-01

    L'argile est l'une des plus vieilles matières premières pour la fabrication de matériaux de construction. La chute de l'Empire romain a marqué la fin de l'utilisation de la brique au nord des Alpes. La brique ne ressurgit véritablement qu' à partir de la deuxième moitié du XIIe s. et de la première moitié du XIIe s.; dans la deuxième moitié du XIIIe s., la brique était devenue le matériau de construction le plus utilisé. Dans cet article, nous discutons les données concernant les premiers ...

  9. Genetic analysis of partial egg production records in Japanese quail using random regression models.

    Science.gov (United States)

    Abou Khadiga, G; Mahmoud, B Y F; Farahat, G S; Emam, A M; El-Full, E A

    2017-08-01

    The main objectives of this study were to detect the most appropriate random regression model (RRM) to fit the data of monthly egg production in 2 lines (selected and control) of Japanese quail and to test the consistency of different criteria of model choice. Data from 1,200 female Japanese quails for the first 5 months of egg production from 4 consecutive generations of an egg line selected for egg production in the first month (EP1) was analyzed. Eight RRMs with different orders of Legendre polynomials were compared to determine the proper model for analysis. All criteria of model choice suggested that the adequate model included the second-order Legendre polynomials for fixed effects, and the third-order for additive genetic effects and permanent environmental effects. Predictive ability of the best model was the highest among all models (ρ = 0.987). According to the best model fitted to the data, estimates of heritability were relatively low to moderate (0.10 to 0.17) showed a descending pattern from the first to the fifth month of production. A similar pattern was observed for permanent environmental effects with greater estimates in the first (0.36) and second (0.23) months of production than heritability estimates. Genetic correlations between separate production periods were higher (0.18 to 0.93) than their phenotypic counterparts (0.15 to 0.87). The superiority of the selected line over the control was observed through significant (P egg production in earlier ages (first and second months) than later ones. A methodology based on random regression animal models can be recommended for genetic evaluation of egg production in Japanese quail. © 2017 Poultry Science Association Inc.

  10. Genetic correlations among body condition score, yield and fertility in multiparous cows using random regression models

    OpenAIRE

    Bastin, Catherine; Gillon, Alain; Massart, Xavier; Bertozzi, Carlo; Vanderick, Sylvie; Gengler, Nicolas

    2010-01-01

    Genetic correlations between body condition score (BCS) in lactation 1 to 3 and four economically important traits (days open, 305-days milk, fat, and protein yields recorded in the first 3 lactations) were estimated on about 12,500 Walloon Holstein cows using 4-trait random regression models. Results indicated moderate favorable genetic correlations between BCS and days open (from -0.46 to -0.62) and suggested the use of BCS for indirect selection on fertility. However, unfavorable genetic c...

  11. Technical Performance Analysis of Iran Premier League Soccer Players in 2012-2013 Season

    Directory of Open Access Journals (Sweden)

    Javani Mohsen

    2015-10-01

    Full Text Available Background and purpose of study : analysis of IRAN premier league soccer players’ technical performance in season 2012-2013, using a computerized match analysis system (Borhan Mobin Development Management Co, IRAN. Material and methods: in this study, data were obtained from 120 players, who performed in competitions 90 minutes. The players were classified into 3 positional roles: defenders, midfielders and forwards. Technical performance variables analysis included: total passes, total successful passes, pass accuracy, total shots; total shots to target, shot accuracy, ball interception and ball losses. The data were statistically analyzed by one-way ANOVA, Kruskal-Wallis, Mann-Whitney U and Tukey post hoc test. Results : The findings of this study showed that players performed about 45 passes per competition. Midfielders and defenders had significantly higher number of passes than forwards. Pass accuracy was about 67% and there were no significant differences between positional roles. Also, the players performed about 0.8 shots per competition, forwards and midfielders had significantly higher number of shots than defenders. Shot accuracy was about 31%; midfielders and forwards had significantly higher shot accuracy than defenders. Forwards showed significantly lower ball interception and higher ball losses than other positions. Conclusion : The result of this study showed that there were significant differences between some technical actions in positional roles. Therefore, coaches can use this information for individualization of training according to playing positions and for optimization of training in the amateur game.

  12. Estimation de la survie des alevins de carpe (C. carpio au cours de leur premier mois d'existence

    Directory of Open Access Journals (Sweden)

    MOREAU J.

    1979-10-01

    Full Text Available Des observations réalisées sur deux stations piscicoles de Madagascar, dans des étangs ne recevant ni engrais ni nourriture, révèlent qu'au cours de leur premier mois les alevins de carpe (C. carpio subissent des mortalités voi-sines de 50 %. Ces dernières sont encore plus élevées en début et en fin de saison de reproduction. Au début, les fortes mortalités sont dues à la température trop basse et aux disponibilités alimentaires insuffisantes ; en fin de saison de reproduction, la température trop élevée et la mauvaise qualité des œufs sont sans doute en cause. Une fumure adéquate des étangs de grossissement des alevins et une alimentation correcte des géniteurs permettront peut-être de diminuer ces mortalités.

  13. Genetic basis of hindlimb loss in a naturally occurring vertebrate model

    Directory of Open Access Journals (Sweden)

    Emily K. Don

    2016-03-01

    Full Text Available Here we genetically characterise pelvic finless, a naturally occurring model of hindlimb loss in zebrafish that lacks pelvic fin structures, which are homologous to tetrapod hindlimbs, but displays no other abnormalities. Using a hybrid positional cloning and next generation sequencing approach, we identified mutations in the nuclear localisation signal (NLS of T-box transcription factor 4 (Tbx4 that impair nuclear localisation of the protein, resulting in altered gene expression patterns during pelvic fin development and the failure of pelvic fin development. Using a TALEN-induced tbx4 knockout allele we confirm that mutations within the Tbx4 NLS (A78V; G79A are sufficient to disrupt pelvic fin development. By combining histological, genetic, and cellular approaches we show that the hindlimb initiation gene tbx4 has an evolutionarily conserved, essential role in pelvic fin development. In addition, our novel viable model of hindlimb deficiency is likely to facilitate the elucidation of the detailed molecular mechanisms through which Tbx4 functions during pelvic fin and hindlimb development.

  14. A software tool to model genetic regulatory networks. Applications to the modeling of threshold phenomena and of spatial patterning in Drosophila.

    Directory of Open Access Journals (Sweden)

    Rui Dilão

    Full Text Available We present a general methodology in order to build mathematical models of genetic regulatory networks. This approach is based on the mass action law and on the Jacob and Monod operon model. The mathematical models are built symbolically by the Mathematica software package GeneticNetworks. This package accepts as input the interaction graphs of the transcriptional activators and repressors of a biological process and, as output, gives the mathematical model in the form of a system of ordinary differential equations. All the relevant biological parameters are chosen automatically by the software. Within this framework, we show that concentration dependent threshold effects in biology emerge from the catalytic properties of genes and its associated conservation laws. We apply this methodology to the segment patterning in Drosophila early development and we calibrate the genetic transcriptional network responsible for the patterning of the gap gene proteins Hunchback and Knirps, along the antero-posterior axis of the Drosophila embryo. In this approach, the zygotically produced proteins Hunchback and Knirps do not diffuse along the antero-posterior axis of the embryo of Drosophila, developing a spatial pattern due to concentration dependent thresholds. This shows that patterning at the gap genes stage can be explained by the concentration gradients along the embryo of the transcriptional regulators.

  15. The true meaning of 'exotic species' as a model for genetically engineered organisms.

    Science.gov (United States)

    Regal, P J

    1993-03-15

    The exotic or non-indigenous species model for deliberately introduced genetically engineered organisms (GEOs) has often been misunderstood or misrepresented. Yet proper comparisons of of ecologically competent GEOs to the patterns of adaptation of introduced species have been highly useful among scientists in attempting to determine how to apply biological theory to specific GEO risk issues, and in attempting to define the probabilities and scale of ecological risks with GEOs. In truth, the model predicts that most projects may be environmentally safe, but a significant minority may be very risky. The model includes a history of institutional follies that also should remind workers of the danger of oversimplifying biological issues, and warn against repeating the sorts of professional misjudgements that have too often been made in introducing organisms to new settings. We once expected that the non-indigenous species model would be refined by more analysis of species eruptions, ecological genetics, and the biology of select GEOs themselves, as outlined. But there has been political resistance to the effective regulation of GEOs, and a bureaucratic tendency to focus research agendas on narrow data collection. Thus there has been too little promotion by responsible agencies of studies to provide the broad conceptual base for truly science-based regulation. In its presently unrefined state, the non-indigenous species comparison would overestimate the risks of GEOs if it were (mis)applied to genetically disrupted, ecologically crippled GEOs, but in some cases of wild-type organisms with novel engineered traits, it could greatly underestimate the risks. Further analysis is urgently needed.

  16. Ripple-Spreading Network Model Optimization by Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Xiao-Bing Hu

    2013-01-01

    Full Text Available Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.

  17. Risk adjustment model of credit life insurance using a genetic algorithm

    Science.gov (United States)

    Saputra, A.; Sukono; Rusyaman, E.

    2018-03-01

    In managing the risk of credit life insurance, insurance company should acknowledge the character of the risks to predict future losses. Risk characteristics can be learned in a claim distribution model. There are two standard approaches in designing the distribution model of claims over the insurance period i.e, collective risk model and individual risk model. In the collective risk model, the claim arises when risk occurs is called individual claim, accumulation of individual claim during a period of insurance is called an aggregate claim. The aggregate claim model may be formed by large model and a number of individual claims. How the measurement of insurance risk with the premium model approach and whether this approach is appropriate for estimating the potential losses occur in the future. In order to solve the problem Genetic Algorithm with Roulette Wheel Selection is used.

  18. Bayesian Modeling for Genetic Anticipation in Presence of Mutational Heterogeneity: A Case Study in Lynch Syndrome

    DEFF Research Database (Denmark)

    Boonstra, Philip S; Mukherjee, Bhramar; Taylor, Jeremy M G

    2011-01-01

    Summary Genetic anticipation, described by earlier age of onset (AOO) and more aggressive symptoms in successive generations, is a phenomenon noted in certain hereditary diseases. Its extent may vary between families and/or between mutation subtypes known to be associated with the disease phenotype....... In this article, we posit a Bayesian approach to infer genetic anticipation under flexible random effects models for censored data that capture the effect of successive generations on AOO. Primary interest lies in the random effects. Misspecifying the distribution of random effects may result in incorrect...... to cause hereditary nonpolyposis colorectal cancer, also called Lynch syndrome (LS). We find evidence for a decrease in AOO between generations in this article. Our model predicts family-level anticipation effects that are potentially useful in genetic counseling clinics for high-risk families....

  19. A genetic-algorithm-aided stochastic optimization model for regional air quality management under uncertainty.

    Science.gov (United States)

    Qin, Xiaosheng; Huang, Guohe; Liu, Lei

    2010-01-01

    A genetic-algorithm-aided stochastic optimization (GASO) model was developed in this study for supporting regional air quality management under uncertainty. The model incorporated genetic algorithm (GA) and Monte Carlo simulation techniques into a general stochastic chance-constrained programming (CCP) framework and allowed uncertainties in simulation and optimization model parameters to be considered explicitly in the design of least-cost strategies. GA was used to seek the optimal solution of the management model by progressively evaluating the performances of individual solutions. Monte Carlo simulation was used to check the feasibility of each solution. A management problem in terms of regional air pollution control was studied to demonstrate the applicability of the proposed method. Results of the case study indicated the proposed model could effectively communicate uncertainties into the optimization process and generate solutions that contained a spectrum of potential air pollutant treatment options with risk and cost information. Decision alternatives could be obtained by analyzing tradeoffs between the overall pollutant treatment cost and the system-failure risk due to inherent uncertainties.

  20. Genetic analysis of body weights of individually fed beef bulls in South Africa using random regression models.

    Science.gov (United States)

    Selapa, N W; Nephawe, K A; Maiwashe, A; Norris, D

    2012-02-08

    The aim of this study was to estimate genetic parameters for body weights of individually fed beef bulls measured at centralized testing stations in South Africa using random regression models. Weekly body weights of Bonsmara bulls (N = 2919) tested between 1999 and 2003 were available for the analyses. The model included a fixed regression of the body weights on fourth-order orthogonal Legendre polynomials of the actual days on test (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, and 84) for starting age and contemporary group effects. Random regressions on fourth-order orthogonal Legendre polynomials of the actual days on test were included for additive genetic effects and additional uncorrelated random effects of the weaning-herd-year and the permanent environment of the animal. Residual effects were assumed to be independently distributed with heterogeneous variance for each test day. Variance ratios for additive genetic, permanent environment and weaning-herd-year for weekly body weights at different test days ranged from 0.26 to 0.29, 0.37 to 0.44 and 0.26 to 0.34, respectively. The weaning-herd-year was found to have a significant effect on the variation of body weights of bulls despite a 28-day adjustment period. Genetic correlations amongst body weights at different test days were high, ranging from 0.89 to 1.00. Heritability estimates were comparable to literature using multivariate models. Therefore, random regression model could be applied in the genetic evaluation of body weight of individually fed beef bulls in South Africa.

  1. Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation.

    Science.gov (United States)

    Chao, Lin; Rang, Camilla Ulla; Proenca, Audrey Menegaz; Chao, Jasper Ubirajara

    2016-01-01

    Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother's old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother's old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington's genetic assimilation

  2. Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation.

    Directory of Open Access Journals (Sweden)

    Lin Chao

    2016-01-01

    Full Text Available Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother's old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother's old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington

  3. Genetic GIScience

    DEFF Research Database (Denmark)

    Jacquez, Geoffrey; Sabel, Clive E; Shi, Chen

    2015-01-01

    The exposome, defined as the totality of an individual's exposures over the life course, is a seminal concept in the environmental health sciences. Although inherently geographic, the exposome as yet is unfamiliar to many geographers. This article proposes a place-based synthesis, genetic...... geographic information science (genetic GIScience), that is founded on the exposome, genome+, and behavome. It provides an improved understanding of human health in relation to biology (the genome+), environmental exposures (the exposome), and their social, societal, and behavioral determinants (the behavome......). Genetic GIScience poses three key needs: first, a mathematical foundation for emergent theory; second, process-based models that bridge biological and geographic scales; third, biologically plausible estimates of space?time disease lags. Compartmental models are a possible solution; this article develops...

  4. Genetic fuzzy system modeling and simulation of vascular behaviour

    DEFF Research Database (Denmark)

    Tang, Jiaowei; Boonen, Harrie C.M.

    Background: The purpose of our project is to identify the rule sets and their interaction within the framework of cardiovascular function. By an iterative process of computational simulation and experimental work, we strive to mimic the physiological basis for cardiovascular adaptive changes in c...... the pressure change of different blood vessels. Conclusion: Genetic fuzzy system is one of potential modeling methods in modeling and simulation of vascular behavior.......Background: The purpose of our project is to identify the rule sets and their interaction within the framework of cardiovascular function. By an iterative process of computational simulation and experimental work, we strive to mimic the physiological basis for cardiovascular adaptive changes...... in cardiovascular disease and ultimately improve pharmacotherapy. For this purpose, novel computational approaches incorporating adaptive properties, auto-regulatory control and rule sets will be assessed, properties that are commonly lacking in deterministic models based on differential equations. We hypothesize...

  5. Addition of host genetic variants in a prediction rule for post meningitis hearing loss in childhood: a model updating study.

    Science.gov (United States)

    Sanders, Marieke S; de Jonge, Rogier C J; Terwee, Caroline B; Heymans, Martijn W; Koomen, Irene; Ouburg, Sander; Spanjaard, Lodewijk; Morré, Servaas A; van Furth, A Marceline

    2013-07-23

    Sensorineural hearing loss is the most common sequela in survivors of bacterial meningitis (BM). In the past we developed a validated prediction model to identify children at risk for post-meningitis hearing loss. It is known that host genetic variations, besides clinical factors, contribute to severity and outcome of BM. In this study it was determined whether host genetic risk factors improve the predictive abilities of an existing model regarding hearing loss after childhood BM. Four hundred and seventy-one Dutch Caucasian childhood BM were genotyped for 11 single nucleotide polymorphisms (SNPs) in seven different genes involved in pathogen recognition. Genetic data were added to the original clinical prediction model and performance of new models was compared to the original model by likelihood ratio tests and the area under the curve (AUC) of the receiver operating characteristic curves. Addition of TLR9-1237 SNPs and the combination of TLR2 + 2477 and TLR4 + 896 SNPs improved the clinical prediction model, but not significantly (increase of AUC's from 0.856 to 0.861 and from 0.856 to 0.875 (p = 0.570 and 0.335, respectively). Other SNPs analysed were not linked to hearing loss. Although addition of genetic risk factors did not significantly improve the clinical prediction model for post-meningitis hearing loss, AUC's of the pre-existing model remain high after addition of genetic factors. Future studies should evaluate whether more combinations of SNPs in larger cohorts has an additional value to the existing prediction model for post meningitis hearing loss.

  6. Genetic analysis of somatic cell score in Danish dairy cattle using ramdom regression test-day model

    DEFF Research Database (Denmark)

    Elsaid, Reda; Sabry, Ayman; Lund, Mogens Sandø

    2011-01-01

    ,233 Danish Holstein cows, were extracted from the national milk recording database. Each data set was analyzed with random regression models using AI-REML. Fixed effects in all models were age at first calving, herd test day, days carrying calf, effects of germ plasm importation (e.g. additive breed effects......) and low between the beginning and the end of lactation. The estimated environmental correlations were lower than the genetic correlations, but the trends were similar. Based on test-day records, the accuracy of genetic evaluations for SCC should be improved when the variation in heritabilities...

  7. Genetic Algorithms for Agent-Based Infrastructure Interdependency Modeling and Analysis

    Energy Technology Data Exchange (ETDEWEB)

    May Permann

    2007-03-01

    Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, electric power, telecommunication, and financial networks. This paper describes initial research combining agent-based infrastructure modeling software and genetic algorithms (GAs) to help optimize infrastructure protection and restoration decisions. This research proposes to apply GAs to the problem of infrastructure modeling and analysis in order to determine the optimum assets to restore or protect from attack or other disaster. This research is just commencing and therefore the focus of this paper is the integration of a GA optimization method with a simulation through the simulation’s agents.

  8. Genetic Learning of Fuzzy Parameters in Predictive and Decision Support Modelling

    Directory of Open Access Journals (Sweden)

    Nebot

    2012-04-01

    Full Text Available In this research a genetic fuzzy system (GFS is proposed that performs discretization parameter learning in the context of the Fuzzy Inductive Reasoning (FIR methodology and the Linguistic Rule FIR (LR-FIR algorithm. The main goal of the GFS is to take advantage of the potentialities of GAs to learn the fuzzification parameters of the FIR and LR-FIR approaches in order to obtain reliable and useful predictive (FIR models and decision support (LR-FIR models. The GFS is evaluated in an e-learning context.

  9. Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation

    DEFF Research Database (Denmark)

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

    2011-01-01

    of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box–Cox transformations. Litter size data in rabbits and pigs that had previously been analysed...... in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box–Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis...... in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected...

  10. Native South American genetic structure and prehistory inferred from hierarchical modeling of mtDNA.

    Science.gov (United States)

    Lewis, Cecil M; Long, Jeffrey C

    2008-03-01

    Genetic diversity in Native South Americans forms a complex pattern at both the continental and local levels. In comparing the West to the East, there is more variation within groups and smaller genetic distances between groups. From this pattern, researchers have proposed that there is more variation in the West and that a larger, more genetically diverse, founding population entered the West than the East. Here, we question this characterization of South American genetic variation and its interpretation. Our concern arises because others have inferred regional variation from the mean variation within local populations without taking into account the variation among local populations within the same region. This failure produces a biased view of the actual variation in the East. In this study, we analyze the mitochondrial DNA sequence between positions 16040 and 16322 of the Cambridge reference sequence. Our sample represents a total of 886 people from 27 indigenous populations from South (22), Central (3), and North America (2). The basic unit of our analyses is nucleotide identity by descent, which is easily modeled and proportional to nucleotide diversity. We use a forward modeling strategy to fit a series of nested models to identity by descent within and between all pairs of local populations. This method provides estimates of identity by descent at different levels of population hierarchy without assuming homogeneity within populations, regions, or continents. Our main discovery is that Eastern South America harbors more genetic variation than has been recognized. We find no evidence that there is increased identity by descent in the East relative to the total for South America. By contrast, we discovered that populations in the Western region, as a group, harbor more identity by descent than has been previously recognized, despite the fact that average identity by descent within groups is lower. In this light, there is no need to postulate separate founding

  11. Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

    DEFF Research Database (Denmark)

    Su, Guosheng; Christensen, Ole Fredslund; Ostersen, Tage

    2012-01-01

    of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects...

  12. Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

    Science.gov (United States)

    Baskaran, Subbiah; Noever, D.

    1999-01-01

    Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

  13. Le premier élément du patrimoine maritime de Saint-Pierre-et-Miquelon protégé au titre des monuments historiques

    Directory of Open Access Journals (Sweden)

    Herveline Delhumeau

    2009-05-01

    Full Text Available Ymac a été classé par arrêté du 14 février 2008 au titre des monuments historiques en raison de l’intérêt ethnologique lié à sa fonction de bateau-pilote. (fig. n° 1Figure 1Ymac, ex-Radar III. Photographie après 2003. © Yannick Lafourcade.Construit en 1965 à Mavilette (Nouvelle-Ecosse, Canada par le chantier Alfred Boudreau, ce bateau traditionnel de pêche à coque en bois avait été initialement armé pour la pêche aux poissons plats par Alex Doucet, d’où son premier nom Alex D. Après avoir p...

  14. The five-factor model of personality and borderline personality disorder: a genetic analysis of comorbidity.

    Science.gov (United States)

    Distel, Marijn A; Trull, Timothy J; Willemsen, Gonneke; Vink, Jacqueline M; Derom, Catherine A; Lynskey, Michael; Martin, Nicholas G; Boomsma, Dorret I

    2009-12-15

    Recently, the nature of personality disorders and their relationship with normal personality traits has received extensive attention. The five-factor model (FFM) of personality, consisting of the personality traits neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, is one of the proposed models to conceptualize personality disorders as maladaptive variants of continuously distributed personality traits. The present study examined the phenotypic and genetic association between borderline personality and FFM personality traits. Data were available for 4403 monozygotic twins, 4425 dizygotic twins, and 1661 siblings from 6140 Dutch, Belgian, and Australian families. Broad-sense heritability estimates for neuroticism, agreeableness, conscientiousness, extraversion, openness to experience, and borderline personality were 43%, 36%, 43%, 47%, 54%, and 45%, respectively. Phenotypic correlations between borderline personality and the FFM personality traits ranged from .06 for openness to experience to .68 for neuroticism. Multiple regression analyses showed that a combination of high neuroticism and low agreeableness best predicted borderline personality. Multivariate genetic analyses showed the genetic factors that influence individual differences in neuroticism, agreeableness, conscientiousness, and extraversion account for all genetic liability to borderline personality. Unique environmental effects on borderline personality, however, were not completely shared with those for the FFM traits (33% is unique to borderline personality). Borderline personality shares all genetic variation with neuroticism, agreeableness, conscientiousness, and extraversion. The unique environmental influences specific to borderline personality may cause individuals with a specific pattern of personality traits to cross a threshold and develop borderline personality.

  15. Modeling solar radiation of Mediterranean region in Turkey by using fuzzy genetic approach

    International Nuclear Information System (INIS)

    Kisi, Ozgur

    2014-01-01

    The study investigates the ability of FG (fuzzy genetic) approach in modeling solar radiation of seven cities from Mediterranean region of Anatolia, Turkey. Latitude, longitude, altitude and month of the year data from the Adana, K. Maras, Mersin, Antalya, Isparta, Burdur and Antakya cities are used as inputs to the FG model to estimate one month ahead solar radiation. FG model is compared with ANNs (artificial neural networks) and ANFIS (adaptive neruro fuzzzy inference system) models with respect to RMSE (root mean square errors), MAE (mean absolute errors) and determination coefficient (R 2 ) statistics. Comparison results indicate that the FG model performs better than the ANN and ANFIS models. It is found that the FG model can be successfully used for estimating solar radiation by using latitude, longitude, altitude and month of the year information. FG model with RMSE = 6.29 MJ/m 2 , MAE = 4.69 MJ/m 2 and R 2 = 0.905 in the test stage was found to be superior to the optimal ANN model with RMSE = 7.17 MJ/m 2 , MAE = 5.29 MJ/m 2 and R 2 = 0.876 and ANFIS model with RMSE = 6.75 MJ/m 2 , MAE = 5.10 MJ/m 2 and R 2 = 0.892 in estimating solar radiation. - Highlights: • SR (Solar radiation) of seven cities from Mediterranean region of Turkey is predicted. • FG (Fuzzy genetic) models are developed for accurately estimation of SR. • The ability of the FG models used in the study is found to be satisfactory. • FG models are compared with commonly used ANNs (artificial neural networks). • FG models are found to perform better than the ANNs models

  16. On coding genotypes for genetic markers with multiple alleles in genetic association study of quantitative traits

    Directory of Open Access Journals (Sweden)

    Wang Tao

    2011-09-01

    Full Text Available Abstract Background In genetic association study of quantitative traits using F∞ models, how to code the marker genotypes and interpret the model parameters appropriately is important for constructing hypothesis tests and making statistical inferences. Currently, the coding of marker genotypes in building F∞ models has mainly focused on the biallelic case. A thorough work on the coding of marker genotypes and interpretation of model parameters for F∞ models is needed especially for genetic markers with multiple alleles. Results In this study, we will formulate F∞ genetic models under various regression model frameworks and introduce three genotype coding schemes for genetic markers with multiple alleles. Starting from an allele-based modeling strategy, we first describe a regression framework to model the expected genotypic values at given markers. Then, as extension from the biallelic case, we introduce three coding schemes for constructing fully parameterized one-locus F∞ models and discuss the relationships between the model parameters and the expected genotypic values. Next, under a simplified modeling framework for the expected genotypic values, we consider several reduced one-locus F∞ models from the three coding schemes on the estimability and interpretation of their model parameters. Finally, we explore some extensions of the one-locus F∞ models to two loci. Several fully parameterized as well as reduced two-locus F∞ models are addressed. Conclusions The genotype coding schemes provide different ways to construct F∞ models for association testing of multi-allele genetic markers with quantitative traits. Which coding scheme should be applied depends on how convenient it can provide the statistical inferences on the parameters of our research interests. Based on these F∞ models, the standard regression model fitting tools can be used to estimate and test for various genetic effects through statistical contrasts with the

  17. Applying ecological models to communities of genetic elements: the case of neutral theory.

    Science.gov (United States)

    Linquist, Stefan; Cottenie, Karl; Elliott, Tyler A; Saylor, Brent; Kremer, Stefan C; Gregory, T Ryan

    2015-07-01

    A promising recent development in molecular biology involves viewing the genome as a mini-ecosystem, where genetic elements are compared to organisms and the surrounding cellular and genomic structures are regarded as the local environment. Here, we critically evaluate the prospects of ecological neutral theory (ENT), a popular model in ecology, as it applies at the genomic level. This assessment requires an overview of the controversy surrounding neutral models in community ecology. In particular, we discuss the limitations of using ENT both as an explanation of community dynamics and as a null hypothesis. We then analyse a case study in which ENT has been applied to genomic data. Our central finding is that genetic elements do not conform to the requirements of ENT once its assumptions and limitations are made explicit. We further compare this genome-level application of ENT to two other, more familiar approaches in genomics that rely on neutral mechanisms: Kimura's molecular neutral theory and Lynch's mutational-hazard model. Interestingly, this comparison reveals that there are two distinct concepts of neutrality associated with these models, which we dub 'fitness neutrality' and 'competitive neutrality'. This distinction helps to clarify the various roles for neutral models in genomics, for example in explaining the evolution of genome size. © 2015 John Wiley & Sons Ltd.

  18. Helicobacter pylori genetic diversification in the Mongolian gerbil model.

    Science.gov (United States)

    Beckett, Amber C; Loh, John T; Chopra, Abha; Leary, Shay; Lin, Aung Soe; McDonnell, Wyatt J; Dixon, Beverly R E A; Noto, Jennifer M; Israel, Dawn A; Peek, Richard M; Mallal, Simon; Algood, Holly M Scott; Cover, Timothy L

    2018-01-01

    Helicobacter pylori requires genetic agility to infect new hosts and establish long-term colonization of changing gastric environments. In this study, we analyzed H. pylori genetic adaptation in the Mongolian gerbil model. This model is of particular interest because H. pylori -infected gerbils develop a high level of gastric inflammation and often develop gastric adenocarcinoma or gastric ulceration. We analyzed the whole genome sequences of H. pylori strains cultured from experimentally infected gerbils, in comparison to the genome sequence of the input strain. The mean annualized single nucleotide polymorphism (SNP) rate per site was 1.5e -5 , which is similar to the rates detected previously in H. pylori- infected humans. Many of the mutations occurred within or upstream of genes associated with iron-related functions ( fur , tonB1 , fecA2 , fecA3 , and frpB3 ) or encoding outer membrane proteins ( alpA, oipA, fecA2, fecA3, frpB3 and cagY ). Most of the SNPs within coding regions (86%) were non-synonymous mutations. Several deletion or insertion mutations led to disruption of open reading frames, suggesting that the corresponding gene products are not required or are deleterious during chronic H. pylori colonization of the gerbil stomach. Five variants (three SNPs and two deletions) were detected in isolates from multiple animals, which suggests that these mutations conferred a selective advantage. One of the mutations (FurR88H) detected in isolates from multiple animals was previously shown to confer increased resistance to oxidative stress, and we now show that this SNP also confers a survival advantage when H. pylori is co-cultured with neutrophils. Collectively, these analyses allow the identification of mutations that are positively selected during H. pylori colonization of the gerbil model.

  19. Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle.

    Science.gov (United States)

    Ayres, D R; Pereira, R J; Boligon, A A; Silva, F F; Schenkel, F S; Roso, V M; Albuquerque, L G

    2013-12-01

    Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

  20. The Potential of Zebrafish as a Model Organism for Improving the Translation of Genetic Anticancer Nanomedicines

    Directory of Open Access Journals (Sweden)

    C Gutiérrez-Lovera

    2017-11-01

    Full Text Available In the last few decades, the field of nanomedicine applied to cancer has revolutionized cancer treatment: several nanoformulations have already reached the market and are routinely being used in the clinical practice. In the case of genetic nanomedicines, i.e., designed to deliver gene therapies to cancer cells for therapeutic purposes, advances have been less impressive. This is because of the many barriers that limit the access of the therapeutic nucleic acids to their target site, and the lack of models that would allow for an improvement in the understanding of how nanocarriers can be tailored to overcome them. Zebrafish has important advantages as a model species for the study of anticancer therapies, and have a lot to offer regarding the rational development of efficient delivery of genetic nanomedicines, and hence increasing the chances of their successful translation. This review aims to provide an overview of the recent advances in the development of genetic anticancer nanomedicines, and of the zebrafish models that stand as promising tools to shed light on their mechanisms of action and overall potential in oncology.

  1. Radio-over-fiber linearization with optimized genetic algorithm CPWL model.

    Science.gov (United States)

    Mateo, Carlos; Carro, Pedro L; García-Dúcar, Paloma; De Mingo, Jesús; Salinas, Íñigo

    2017-02-20

    This article proposes an optimized version of a canonical piece-wise-linear (CPWL) digital predistorter in order to enhance the linearity of a radio-over-fiber (RoF) LTE mobile fronthaul. In this work, we propose a threshold allocation optimization process carried out by a genetic algorithm (GA) in order to optimize the CPWL model (GA-CPWL). Firstly, experiments show how the CPWL model outperforms the classical memory polynomial DPD in an intensity modulation/direct detection (IM/DD) RoF link. Then, the GA-CPWL predistorter is compared with the CPWL model in several scenarios, in order to verify that the proposed DPD offers better performance in different optical transmission conditions. Experimental results reveal that with a proper threshold allocation, the GA-CPWL predistorter offers very promising outcomes.

  2. A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan

    2017-06-01

    Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

  3. Behavioral phenotypes in schizophrenic animal models with multiple combinations of genetic and environmental factors.

    Science.gov (United States)

    Hida, Hirotake; Mouri, Akihiro; Noda, Yukihiro

    2013-01-01

    Schizophrenia is a multifactorial psychiatric disorder in which both genetic and environmental factors play a role. Genetic [e.g., Disrupted-in-schizophrenia 1 (DISC1), Neuregulin-1 (NRG1)] and environmental factors (e.g., maternal viral infection, obstetric complications, social stress) may act during the developmental period to increase the incidence of schizophrenia. In animal models, interactions between susceptibility genes and the environment can be controlled in ways not possible in humans; therefore, such models are useful for investigating interactions between or within factors in the pathogenesis and pathophysiology of schizophrenia. We provide an overview of schizophrenic animal models investigating interactions between or within factors. First, we reviewed gene-environment interaction animal models, in which schizophrenic candidate gene mutant mice were subjected to perinatal immune activation or adolescent stress. Next, environment-environment interaction animal models, in which mice were subjected to a combination of perinatal immune activation and adolescent administration of drugs, were described. These animal models showed interaction between or within factors; behavioral changes, which were obscured by each factor, were marked by interaction of factors and vice versa. Appropriate behavioral approaches with such models will be invaluable for translational research on novel compounds, and also for providing insight into the pathogenesis and pathophysiology of schizophrenia.

  4. Genetic Analysis of Somatic Cell Score in Danish Holsteins Using a Liability-Normal Mixture Model

    DEFF Research Database (Denmark)

    Madsen, P; Shariati, M M; Ødegård, J

    2008-01-01

    Mixture models are appealing for identifying hidden structures affecting somatic cell score (SCS) data, such as unrecorded cases of subclinical mastitis. Thus, liability-normal mixture (LNM) models were used for genetic analysis of SCS data, with the aim of predicting breeding values for such cas...

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

    Science.gov (United States)

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

    2015-09-01

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

  6. Genetic structure and bio-climatic modeling support allopatric over parapatric speciation along a latitudinal gradient.

    Science.gov (United States)

    Rossetto, Maurizio; Allen, Chris B; Thurlby, Katie A G; Weston, Peter H; Milner, Melita L

    2012-08-20

    Four of the five species of Telopea (Proteaceae) are distributed in a latitudinal replacement pattern on the south-eastern Australian mainland. In similar circumstances, a simple allopatric speciation model that identifies the origins of genetic isolation within temporal geographic separation is considered as the default model. However, secondary contact between differentiated lineages can result in similar distributional patterns to those arising from a process of parapatric speciation (where gene flow between lineages remains uninterrupted during differentiation). Our aim was to use the characteristic distributional patterns in Telopea to test whether it reflected the evolutionary models of allopatric or parapatric speciation. Using a combination of genetic evidence and environmental niche modelling, we focused on three main questions: do currently described geographic borders coincide with genetic and environmental boundaries; are there hybrid zones in areas of secondary contact between closely related species; did species distributions contract during the last glacial maximum resulting in distributional gaps even where overlap and hybridisation currently occur? Total genomic DNA was extracted from 619 individuals sampled from 36 populations representing the four species. Seven nuclear microsatellites (nSSR) and six chloroplast microsatellites (cpSSR) were amplified across all populations. Genetic structure and the signature of admixture in overlap zones was described using the Bayesian clustering methods implemented in STUCTURE and NewHybrids respectively. Relationships between chlorotypes were reconstructed as a median-joining network. Environmental niche models were produced for all species using environmental parameters from both the present day and the last glacial maximum (LGM).The nSSR loci amplified a total of 154 alleles, while data for the cpSSR loci produced a network of six chlorotypes. STRUCTURE revealed an optimum number of five clusters

  7. Developments in statistical analysis in quantitative genetics

    DEFF Research Database (Denmark)

    Sorensen, Daniel

    2009-01-01

    of genetic means and variances, models for the analysis of categorical and count data, the statistical genetics of a model postulating that environmental variance is partly under genetic control, and a short discussion of models that incorporate massive genetic marker information. We provide an overview......A remarkable research impetus has taken place in statistical genetics since the last World Conference. This has been stimulated by breakthroughs in molecular genetics, automated data-recording devices and computer-intensive statistical methods. The latter were revolutionized by the bootstrap...... and by Markov chain Monte Carlo (McMC). In this overview a number of specific areas are chosen to illustrate the enormous flexibility that McMC has provided for fitting models and exploring features of data that were previously inaccessible. The selected areas are inferences of the trajectories over time...

  8. Present, past and future of the European rock fern Asplenium fontanum: combining distribution modelling and population genetics to study the effect of climate change on geographic range and genetic diversity.

    Science.gov (United States)

    Bystriakova, Nadia; Ansell, Stephen W; Russell, Stephen J; Grundmann, Michael; Vogel, Johannes C; Schneider, Harald

    2014-02-01

    Climate change is expected to alter the geographic range of many plant species dramatically. Predicting this response will be critical to managing the conservation of plant resources and the effects of invasive species. The aim of this study was to predict the response of temperate homosporous ferns to climate change. Genetic diversity and changes in distribution range were inferred for the diploid rock fern Asplenium fontanum along a South-North transect, extending from its putative last glacial maximum (LGM) refugia in southern France towards southern Germany and eastern-central France. This study reconciles observations from distribution models and phylogeographic analyses derived from plastid and nuclear diversity. Genetic diversity distribution and niche modelling propose that genetic diversity accumulates in the LGM climate refugium in southern France with the formation of a diversity gradient reflecting a slow, post-LGM range expansion towards the current distribution range. Evidence supports the fern's preference for outcrossing, contradicting the expectation that homosporous ferns would populate new sites by single-spore colonization. Prediction of climate and distribution range change suggests that a dramatic loss of range and genetic diversity in this fern is possible. The observed migration is best described by the phalanx expansion model. The results suggest that homosporous ferns reproducing preferentially by outcrossing accumulate genetic diversity primarily in LGM climate refugia and may be threatened if these areas disappear due to global climate change.

  9. The first metallurgical tests on plutonium; Premiers essais metallurgiques sur le plutonium

    Energy Technology Data Exchange (ETDEWEB)

    Grison, E; Abramson, R; Anselin, F; Monti, H [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1958-07-01

    Metallic plutonium was first prepared in France in January 1956, as soon as we had access to quantities of the order of several grams of plutonium, which had been extracted from the rods of the pile EL2 at Saclay. Since up to the present this reactor, of thermal power 2 000 kW, has been our only source of plutonium, we have so far only worked on experimental quantities sufficient for the basic tests but not for tests on a scale of possible applications. It is this work, carried out during this phase of preliminary research, which is described below. With the starting up of the plutonium extraction plant at Marcoule, where the reactor G1 has been operating at power for more than a year, we shall go on next to a another order of magnitude which will allow the manufacture and experimentation of prototype fuel elements. (author) [French] La premiere elaboration de plutonium metallique en France fut faite en janvier 1956, des que nous pumes disposer de quantites de plutonium de l'ordre de quelques grammes, qui avaient ete retires des barreaux de la pile EL2 de Saclay. Ce reacteur, d'une puissance thermique de 2 000 kW, ayant ete jusqu'a present notre seule source de plutonium, nous n'avons encore travaille que sur des quantites experimentales suffisantes pour les essais de base, mais non pour des essais a l'echelle d'applications possibles. Ce sont les travaux effectues pendant cette phase de recherches preliminaires qui seront evoques ci-dessous. Avec la mise eu route de l'usine d'extraction de plutonium de Marcoule, ou le reacteur G1 fonctionne en puissance depuis plus d'un an, nous allons passer prochainement a un autre ordre de grandeur, qui nous permettra la fabrication et l'experimentation d'elements combustibles prototypes. (auteur)

  10. Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure

    Science.gov (United States)

    Cheng, Chun-Tian; Zhao, Ming-Yan; Chau, K. W.; Wu, Xin-Yu

    2006-01-01

    Genetic Algorithm (GA) is globally oriented in searching and thus useful in optimizing multiobjective problems, especially where the objective functions are ill-defined. Conceptual rainfall-runoff models that aim at predicting streamflow from the knowledge of precipitation over a catchment have become a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the multiple criteria for judging the performances of observed data. However, it is often difficult to derive all objective functions for the parameter calibration problem of a conceptual model. Thus, a new method to the multiple criteria parameter calibration problem, which combines GA with TOPSIS (technique for order performance by similarity to ideal solution) for Xinanjiang model, is presented. This study is an immediate further development of authors' previous research (Cheng, C.T., Ou, C.P., Chau, K.W., 2002. Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. Journal of Hydrology, 268, 72-86), whose obvious disadvantages are to split the whole procedure into two parts and to become difficult to integrally grasp the best behaviors of model during the calibration procedure. The current method integrates the two parts of Xinanjiang rainfall-runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity. Comparison of results with two-step procedure shows that the current methodology gives similar results to the previous method, is also feasible and robust, but simpler and easier to apply in practice.

  11. Genetics of human hydrocephalus

    Science.gov (United States)

    Williams, Michael A.; Rigamonti, Daniele

    2006-01-01

    Human hydrocephalus is a common medical condition that is characterized by abnormalities in the flow or resorption of cerebrospinal fluid (CSF), resulting in ventricular dilatation. Human hydrocephalus can be classified into two clinical forms, congenital and acquired. Hydrocephalus is one of the complex and multifactorial neurological disorders. A growing body of evidence indicates that genetic factors play a major role in the pathogenesis of hydrocephalus. An understanding of the genetic components and mechanism of this complex disorder may offer us significant insights into the molecular etiology of impaired brain development and an accumulation of the cerebrospinal fluid in cerebral compartments during the pathogenesis of hydrocephalus. Genetic studies in animal models have started to open the way for understanding the underlying pathology of hydrocephalus. At least 43 mutants/loci linked to hereditary hydrocephalus have been identified in animal models and humans. Up to date, 9 genes associated with hydrocephalus have been identified in animal models. In contrast, only one such gene has been identified in humans. Most of known hydrocephalus gene products are the important cytokines, growth factors or related molecules in the cellular signal pathways during early brain development. The current molecular genetic evidence from animal models indicate that in the early development stage, impaired and abnormal brain development caused by abnormal cellular signaling and functioning, all these cellular and developmental events would eventually lead to the congenital hydrocephalus. Owing to our very primitive knowledge of the genetics and molecular pathogenesis of human hydrocephalus, it is difficult to evaluate whether data gained from animal models can be extrapolated to humans. Initiation of a large population genetics study in humans will certainly provide invaluable information about the molecular and cellular etiology and the developmental mechanisms of human

  12. Experimental Population Genetics in the Introductory Genetics Laboratory Using "Drosophila" as a Model Organism

    Science.gov (United States)

    Johnson, Ronald; Kennon, Tillman

    2009-01-01

    Hypotheses of population genetics are derived and tested by students in the introductory genetics laboratory classroom as they explore the effects of biotic variables (physical traits of fruit flies) and abiotic variables (island size and distance) on fruit fly populations. In addition to this hypothesis-driven experiment, the development of…

  13. Find the weakest link. A comparison between demographic, genetic and demo-genetic metapopulation extinction times

    Directory of Open Access Journals (Sweden)

    Robert Alexandre

    2011-09-01

    Full Text Available Abstract Background While the ultimate causes of most species extinctions are environmental, environmental constraints have various secondary consequences on evolutionary and ecological processes. The roles of demographic, genetic mechanisms and their interactions in limiting the viabilities of species or populations have stirred much debate and remain difficult to evaluate in the absence of demography-genetics conceptual and technical framework. Here, I computed projected times to metapopulation extinction using (1 a model focusing on the effects of species properties, habitat quality, quantity and temporal variability on the time to demographic extinction; (2 a genetic model focusing on the dynamics of the drift and inbreeding loads under the same species and habitat constraints; (3 a demo-genetic model accounting for demographic-genetic processes and feedbacks. Results Results indicate that a given population may have a high demographic, but low genetic viability or vice versa; and whether genetic or demographic aspects will be the most limiting to overall viability depends on the constraints faced by the species (e.g., reduction of habitat quantity or quality. As a consequence, depending on metapopulation or species characteristics, incorporating genetic considerations to demographically-based viability assessments may either moderately or severely reduce the persistence time. On the other hand, purely genetically-based estimates of species viability may either underestimate (by neglecting demo-genetic interactions or overestimate (by neglecting the demographic resilience true viability. Conclusion Unbiased assessments of the viabilities of species may only be obtained by identifying and considering the most limiting processes (i.e., demography or genetics, or, preferentially, by integrating them.

  14. On the Reliability of Nonlinear Modeling using Enhanced Genetic Programming Techniques

    Science.gov (United States)

    Winkler, S. M.; Affenzeller, M.; Wagner, S.

    The use of genetic programming (GP) in nonlinear system identification enables the automated search for mathematical models that are evolved by an evolutionary process using the principles of selection, crossover and mutation. Due to the stochastic element that is intrinsic to any evolutionary process, GP cannot guarantee the generation of similar or even equal models in each GP process execution; still, if there is a physical model underlying to the data that are analyzed, then GP is expected to find these structures and produce somehow similar results. In this paper we define a function for measuring the syntactic similarity of mathematical models represented as structure trees; using this similarity function we compare the results produced by GP techniques for a data set representing measurement data of a BMW Diesel engine.

  15. Modeling of genetic algorithms with a finite population

    NARCIS (Netherlands)

    C.H.M. van Kemenade

    1997-01-01

    textabstractCross-competition between non-overlapping building blocks can strongly influence the performance of evolutionary algorithms. The choice of the selection scheme can have a strong influence on the performance of a genetic algorithm. This paper describes a number of different genetic

  16. Probability Model of Allele Frequency of Alzheimer’s Disease Genetic Risk Factor

    Directory of Open Access Journals (Sweden)

    Afshin Fayyaz-Movaghar

    2016-06-01

    Full Text Available Background and Purpose: The identification of genetics risk factors of human diseases is very important. This study is conducted to model the allele frequencies (AFs of Alzheimer’s disease. Materials and Methods: In this study, several candidate probability distributions are fitted on a data set of Alzheimer’s disease genetic risk factor. Unknown parameters of the considered distributions are estimated, and some criterions of goodness-of-fit are calculated for the sake of comparison. Results: Based on some statistical criterions, the beta distribution gives the best fit on AFs. However, the estimate values of the parameters of beta distribution lead us to the standard uniform distribution. Conclusion: The AFs of Alzheimer’s disease follow the standard uniform distribution.

  17. Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association studies

    NARCIS (Netherlands)

    van der Net, Jeroen B.; Janssens, A. Cecile J. W.; Eijkemans, Marinus J. C.; Kastelein, John J. P.; Sijbrands, Eric J. G.; Steyerberg, Ewout W.

    2008-01-01

    Cross-sectional genetic association studies can be analyzed using Cox proportional hazards models with age as time scale, if age at onset of disease is known for the cases and age at data collection is known for the controls. We assessed to what degree and under what conditions Cox proportional

  18. Cumulative t-link threshold models for the genetic analysis of calving ease scores

    Directory of Open Access Journals (Sweden)

    Tempelman Robert J

    2003-09-01

    Full Text Available Abstract In this study, a hierarchical threshold mixed model based on a cumulative t-link specification for the analysis of ordinal data or more, specifically, calving ease scores, was developed. The validation of this model and the Markov chain Monte Carlo (MCMC algorithm was carried out on simulated data from normally and t4 (i.e. a t-distribution with four degrees of freedom distributed populations using the deviance information criterion (DIC and a pseudo Bayes factor (PBF measure to validate recently proposed model choice criteria. The simulation study indicated that although inference on the degrees of freedom parameter is possible, MCMC mixing was problematic. Nevertheless, the DIC and PBF were validated to be satisfactory measures of model fit to data. A sire and maternal grandsire cumulative t-link model was applied to a calving ease dataset from 8847 Italian Piemontese first parity dams. The cumulative t-link model was shown to lead to posterior means of direct and maternal heritabilities (0.40 ± 0.06, 0.11 ± 0.04 and a direct maternal genetic correlation (-0.58 ± 0.15 that were not different from the corresponding posterior means of the heritabilities (0.42 ± 0.07, 0.14 ± 0.04 and the genetic correlation (-0.55 ± 0.14 inferred under the conventional cumulative probit link threshold model. Furthermore, the correlation (> 0.99 between posterior means of sire progeny merit from the two models suggested no meaningful rerankings. Nevertheless, the cumulative t-link model was decisively chosen as the better fitting model for this calving ease data using DIC and PBF.

  19. A Multi-Marker Genetic Association Test Based on the Rasch Model Applied to Alzheimer's Disease.

    Directory of Open Access Journals (Sweden)

    Wenjia Wang

    Full Text Available Results from Genome-Wide Association Studies (GWAS have shown that the genetic basis of complex traits often include many genetic variants with small to moderate effects whose identification remains a challenging problem. In this context multi-marker analysis at the gene and pathway level can complement traditional point-wise approaches that treat the genetic markers individually. In this paper we propose a novel statistical approach for multi-marker analysis based on the Rasch model. The method summarizes the categorical genotypes of SNPs by a generalized logistic function into a genetic score that can be used for association analysis. Through different sets of simulations, the false-positive rate and power of the proposed approach are compared to a set of existing methods, and shows good performances. The application of the Rasch model on Alzheimer's Disease (AD ADNI GWAS dataset also allows a coherent interpretation of the results. Our analysis supports the idea that APOE is a major susceptibility gene for AD. In the top genes selected by proposed method, several could be functionally linked to AD. In particular, a pathway analysis of these genes also highlights the metabolism of cholesterol, that is known to play a key role in AD pathogenesis. Interestingly, many of these top genes can be integrated in a hypothetic signalling network.

  20. Inferring genetic parameters of lactation in Tropical Milking Criollo cattle with random regression test-day models.

    Science.gov (United States)

    Santellano-Estrada, E; Becerril-Pérez, C M; de Alba, J; Chang, Y M; Gianola, D; Torres-Hernández, G; Ramírez-Valverde, R

    2008-11-01

    This study inferred genetic and permanent environmental variation of milk yield in Tropical Milking Criollo cattle and compared 5 random regression test-day models using Wilmink's function and Legendre polynomials. Data consisted of 15,377 test-day records from 467 Tropical Milking Criollo cows that calved between 1974 and 2006 in the tropical lowlands of the Gulf Coast of Mexico and in southern Nicaragua. Estimated heritabilities of test-day milk yields ranged from 0.18 to 0.45, and repeatabilities ranged from 0.35 to 0.68 for the period spanning from 6 to 400 d in milk. Genetic correlation between days in milk 10 and 400 was around 0.50 but greater than 0.90 for most pairs of test days. The model that used first-order Legendre polynomials for additive genetic effects and second-order Legendre polynomials for permanent environmental effects gave the smallest residual variance and was also favored by the Akaike information criterion and likelihood ratio tests.

  1. Optimizing models for production and inventory control using a genetic algorithm

    Directory of Open Access Journals (Sweden)

    Dragan S. Pamučar

    2012-01-01

    Full Text Available In order to make the Economic Production Quantity (EPQ model more applicable to real-world production and inventory control problems, in this paper we expand this model by assuming that some imperfect items of different product types being produced such as reworks are allowed. In addition, we may have more than one product and supplier along with warehouse space and budget limitation. We show that the model of the problem is a constrained non-linear integer program and propose a genetic algorithm to solve it. Moreover, a design of experiments is employed to calibrate the parameters of the algorithm for different problem sizes. In the end, a numerical example is presented to demonstrate the application of the proposed methodology.

  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

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

  3. Fatal Prion Disease in a Mouse Model of Genetic E200K Creutzfeldt-Jakob Disease

    Science.gov (United States)

    Friedman-Levi, Yael; Meiner, Zeev; Canello, Tamar; Frid, Kati; Kovacs, Gabor G.; Budka, Herbert; Avrahami, Dana; Gabizon, Ruth

    2011-01-01

    Genetic prion diseases are late onset fatal neurodegenerative disorders linked to pathogenic mutations in the prion protein-encoding gene, PRNP. The most prevalent of these is the substitution of Glutamate for Lysine at codon 200 (E200K), causing genetic Creutzfeldt-Jakob disease (gCJD) in several clusters, including Jews of Libyan origin. Investigating the pathogenesis of genetic CJD, as well as developing prophylactic treatments for young asymptomatic carriers of this and other PrP mutations, may well depend upon the availability of appropriate animal models in which long term treatments can be evaluated for efficacy and toxicity. Here we present the first effective mouse model for E200KCJD, which expresses chimeric mouse/human (TgMHu2M) E199KPrP on both a null and a wt PrP background, as is the case for heterozygous patients and carriers. Mice from both lines suffered from distinct neurological symptoms as early as 5–6 month of age and deteriorated to death several months thereafter. Histopathological examination of the brain and spinal cord revealed early gliosis and age-related intraneuronal deposition of disease-associated PrP similarly to human E200K gCJD. Concomitantly we detected aggregated, proteinase K resistant, truncated and oxidized PrP forms on immunoblots. Inoculation of brain extracts from TgMHu2ME199K mice readily induced, the first time for any mutant prion transgenic model, a distinct fatal prion disease in wt mice. We believe that these mice may serve as an ideal platform for the investigation of the pathogenesis of genetic prion disease and thus for the monitoring of anti-prion treatments. PMID:22072968

  4. Fatal prion disease in a mouse model of genetic E200K Creutzfeldt-Jakob disease.

    Directory of Open Access Journals (Sweden)

    Yael Friedman-Levi

    2011-11-01

    Full Text Available Genetic prion diseases are late onset fatal neurodegenerative disorders linked to pathogenic mutations in the prion protein-encoding gene, PRNP. The most prevalent of these is the substitution of Glutamate for Lysine at codon 200 (E200K, causing genetic Creutzfeldt-Jakob disease (gCJD in several clusters, including Jews of Libyan origin. Investigating the pathogenesis of genetic CJD, as well as developing prophylactic treatments for young asymptomatic carriers of this and other PrP mutations, may well depend upon the availability of appropriate animal models in which long term treatments can be evaluated for efficacy and toxicity. Here we present the first effective mouse model for E200KCJD, which expresses chimeric mouse/human (TgMHu2M E199KPrP on both a null and a wt PrP background, as is the case for heterozygous patients and carriers. Mice from both lines suffered from distinct neurological symptoms as early as 5-6 month of age and deteriorated to death several months thereafter. Histopathological examination of the brain and spinal cord revealed early gliosis and age-related intraneuronal deposition of disease-associated PrP similarly to human E200K gCJD. Concomitantly we detected aggregated, proteinase K resistant, truncated and oxidized PrP forms on immunoblots. Inoculation of brain extracts from TgMHu2ME199K mice readily induced, the first time for any mutant prion transgenic model, a distinct fatal prion disease in wt mice. We believe that these mice may serve as an ideal platform for the investigation of the pathogenesis of genetic prion disease and thus for the monitoring of anti-prion treatments.

  5. MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.

    Science.gov (United States)

    Wang, Julia; Al-Ouran, Rami; Hu, Yanhui; Kim, Seon-Young; Wan, Ying-Wooi; Wangler, Michael F; Yamamoto, Shinya; Chao, Hsiao-Tuan; Comjean, Aram; Mohr, Stephanie E; Perrimon, Norbert; Liu, Zhandong; Bellen, Hugo J

    2017-06-01

    One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid user-friendly format. To this end, we created MARRVEL (model organism aggregated resources for rare variant exploration). MARRVEL is a publicly available website that integrates information from six human genetic databases and seven model organism databases. For any given variant or gene, MARRVEL displays information from OMIM, ExAC, ClinVar, Geno2MP, DGV, and DECIPHER. Importantly, it curates model organism-specific databases to concurrently display a concise summary regarding the human gene homologs in budding and fission yeast, worm, fly, fish, mouse, and rat on a single webpage. Experiment-based information on tissue expression, protein subcellular localization, biological process, and molecular function for the human gene and homologs in the seven model organisms are arranged into a concise output. Hence, rather than visiting multiple separate databases for variant and gene analysis, users can obtain important information by searching once through MARRVEL. Altogether, MARRVEL dramatically improves efficiency and accessibility to data collection and facilitates analysis of human genes and variants by cross-disciplinary integration of 18 million records available in public databases to facilitate clinical diagnosis and basic research. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

  6. Elaboration of the Reciprocal-Engagement Model of Genetic Counseling Practice: a Qualitative Investigation of Goals and Strategies.

    Science.gov (United States)

    Redlinger-Grosse, Krista; Veach, Patricia McCarthy; LeRoy, Bonnie S; Zierhut, Heather

    2017-12-01

    As the genetic counseling field evolves, a comprehensive model of practice is critical. The Reciprocal-Engagement Model (REM) consists of 5 tenets and 17 goals. Lacking in the REM, however, are well-articulated counselor strategies and behaviors. The purpose of the present study was to further elaborate and provide supporting evidence for the REM by identifying and mapping genetic counseling strategies to the REM goals. A secondary, qualitative analysis was conducted on data from two prior studies: 1) focus group results of genetic counseling outcomes (Redlinger-Grosse et al., Journal of Genetic Counseling, 2015); and 2) genetic counselors' examples of successful and unsuccessful genetic counseling sessions (Geiser et al. 2009). Using directed content analysis, 337 unique strategies were extracted from focus group data. A Q-sort of the 337 strategies yielded 15 broader strategy domains that were then mapped to the successful and unsuccessful session examples. Differing prevalence of strategy domains identified in successful sessions versus the prevalence of domains identified as lacking in unsuccessful sessions provide further support for the REM goals. The most prevalent domains for successful sessions were Information Giving and Use Psychosocial Skills and Strategies; and for unsuccessful sessions, Information Giving and Establish Working Alliance. Identified strategies support the REM's reciprocal nature, especially with regard to addressing patients' informational and psychosocial needs. Patients' contributions to success (or lack thereof) of sessions was also noted, supporting a REM tenet that individual characteristics and the counselor-patient relationship are central to processes and outcomes. The elaborated REM could be used as a framework for certain graduate curricular objectives, and REM components could also inform process and outcomes research studies to document and further characterize genetic counselor strategies.

  7. Multilocus genetic models of handedness closely resemble single-locus models in explaining family data and are compatible with genome-wide association studies.

    Science.gov (United States)

    McManus, I C; Davison, Angus; Armour, John A L

    2013-06-01

    Right- and left-handedness run in families, show greater concordance in monozygotic than dizygotic twins, and are well described by single-locus Mendelian models. Here we summarize a large genome-wide association study (GWAS) that finds no significant associations with handedness and is consistent with a meta-analysis of GWASs. The GWAS had 99% power to detect a single locus using the conventional criterion of P < 5 × 10(-8) for the single locus models of McManus and Annett. The strong conclusion is that handedness is not controlled by a single genetic locus. A consideration of the genetic architecture of height, primary ciliary dyskinesia, and intelligence suggests that handedness inheritance can be explained by a multilocus variant of the McManus DC model, classical effects on family and twins being barely distinguishable from the single locus model. Based on the ENGAGE meta-analysis of GWASs, we estimate at least 40 loci are involved in determining handedness. © 2013 New York Academy of Sciences.

  8. Genetic structure and bio-climatic modeling support allopatric over parapatric speciation along a latitudinal gradient

    Directory of Open Access Journals (Sweden)

    Rossetto Maurizio

    2012-08-01

    Full Text Available Abstract Background Four of the five species of Telopea (Proteaceae are distributed in a latitudinal replacement pattern on the south-eastern Australian mainland. In similar circumstances, a simple allopatric speciation model that identifies the origins of genetic isolation within temporal geographic separation is considered as the default model. However, secondary contact between differentiated lineages can result in similar distributional patterns to those arising from a process of parapatric speciation (where gene flow between lineages remains uninterrupted during differentiation. Our aim was to use the characteristic distributional patterns in Telopea to test whether it reflected the evolutionary models of allopatric or parapatric speciation. Using a combination of genetic evidence and environmental niche modelling, we focused on three main questions: do currently described geographic borders coincide with genetic and environmental boundaries; are there hybrid zones in areas of secondary contact between closely related species; did species distributions contract during the last glacial maximum resulting in distributional gaps even where overlap and hybridisation currently occur? Results Total genomic DNA was extracted from 619 individuals sampled from 36 populations representing the four species. Seven nuclear microsatellites (nSSR and six chloroplast microsatellites (cpSSR were amplified across all populations. Genetic structure and the signature of admixture in overlap zones was described using the Bayesian clustering methods implemented in STUCTURE and NewHybrids respectively. Relationships between chlorotypes were reconstructed as a median-joining network. Environmental niche models were produced for all species using environmental parameters from both the present day and the last glacial maximum (LGM. The nSSR loci amplified a total of 154 alleles, while data for the cpSSR loci produced a network of six chlorotypes. STRUCTURE revealed

  9. Using probability modelling and genetic parentage assignment to test the role of local mate availability in mating system variation.

    Science.gov (United States)

    Blyton, Michaela D J; Banks, Sam C; Peakall, Rod; Lindenmayer, David B

    2012-02-01

    The formal testing of mating system theories with empirical data is important for evaluating the relative importance of different processes in shaping mating systems in wild populations. Here, we present a generally applicable probability modelling framework to test the role of local mate availability in determining a population's level of genetic monogamy. We provide a significance test for detecting departures in observed mating patterns from model expectations based on mate availability alone, allowing the presence and direction of behavioural effects to be inferred. The assessment of mate availability can be flexible and in this study it was based on population density, sex ratio and spatial arrangement. This approach provides a useful tool for (1) isolating the effect of mate availability in variable mating systems and (2) in combination with genetic parentage analyses, gaining insights into the nature of mating behaviours in elusive species. To illustrate this modelling approach, we have applied it to investigate the variable mating system of the mountain brushtail possum (Trichosurus cunninghami) and compared the model expectations with the outcomes of genetic parentage analysis over an 18-year study. The observed level of monogamy was higher than predicted under the model. Thus, behavioural traits, such as mate guarding or selective mate choice, may increase the population level of monogamy. We show that combining genetic parentage data with probability modelling can facilitate an improved understanding of the complex interactions between behavioural adaptations and demographic dynamics in driving mating system variation. © 2011 Blackwell Publishing Ltd.

  10. Broad Bandwidth or High Fidelity? Evidence from the Structure of Genetic and Environmental Effects on the Facets of the Five Factor Model

    Science.gov (United States)

    Briley, Daniel A.; Tucker-Drob, Elliot M.

    2017-01-01

    The Five Factor Model (FFM) of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. Models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets for three of the Big Five domains. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality. PMID:22695681

  11. A genetic algorithm-based job scheduling model for big data analytics.

    Science.gov (United States)

    Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

    Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

  12. Genetic technologies for extremely thermophilic microorganisms of Sulfolobus, the only genetically tractable genus of crenarchaea.

    Science.gov (United States)

    Peng, Nan; Han, Wenyuan; Li, Yingjun; Liang, Yunxiang; She, Qunxin

    2017-04-01

    Archaea represents the third domain of life, with the information-processing machineries more closely resembling those of eukaryotes than the machineries of the bacterial counterparts but sharing metabolic pathways with organisms of Bacteria, the sister prokaryotic phylum. Archaeal organisms also possess unique features as revealed by genomics and genome comparisons and by biochemical characterization of prominent enzymes. Nevertheless, diverse genetic tools are required for in vivo experiments to verify these interesting discoveries. Considerable efforts have been devoted to the development of genetic tools for archaea ever since their discovery, and great progress has been made in the creation of archaeal genetic tools in the past decade. Versatile genetic toolboxes are now available for several archaeal models, among which Sulfolobus microorganisms are the only genus representing Crenarchaeota because all the remaining genera are from Euryarchaeota. Nevertheless, genetic tools developed for Sulfolobus are probably the most versatile among all archaeal models, and these include viral and plasmid shuttle vectors, conventional and novel genetic manipulation methods, CRISPR-based gene deletion and mutagenesis, and gene silencing, among which CRISPR tools have been reported only for Sulfolobus thus far. In this review, we summarize recent developments in all these useful genetic tools and discuss their possible application to research into archaeal biology by means of Sulfolobus models.

  13. Using genetic algorithms to calibrate a water quality model.

    Science.gov (United States)

    Liu, Shuming; Butler, David; Brazier, Richard; Heathwaite, Louise; Khu, Soon-Thiam

    2007-03-15

    With the increasing concern over the impact of diffuse pollution on water bodies, many diffuse pollution models have been developed in the last two decades. A common obstacle in using such models is how to determine the values of the model parameters. This is especially true when a model has a large number of parameters, which makes a full range of calibration expensive in terms of computing time. Compared with conventional optimisation approaches, soft computing techniques often have a faster convergence speed and are more efficient for global optimum searches. This paper presents an attempt to calibrate a diffuse pollution model using a genetic algorithm (GA). Designed to simulate the export of phosphorus from diffuse sources (agricultural land) and point sources (human), the Phosphorus Indicators Tool (PIT) version 1.1, on which this paper is based, consisted of 78 parameters. Previous studies have indicated the difficulty of full range model calibration due to the number of parameters involved. In this paper, a GA was employed to carry out the model calibration in which all parameters were involved. A sensitivity analysis was also performed to investigate the impact of operators in the GA on its effectiveness in optimum searching. The calibration yielded satisfactory results and required reasonable computing time. The application of the PIT model to the Windrush catchment with optimum parameter values was demonstrated. The annual P loss was predicted as 4.4 kg P/ha/yr, which showed a good fitness to the observed value.

  14. Comparing ESC and iPSC—Based Models for Human Genetic Disorders

    Directory of Open Access Journals (Sweden)

    Tomer Halevy

    2014-10-01

    Full Text Available Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs from patients’ somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn’t be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

  15. Comparing ESC and iPSC-Based Models for Human Genetic Disorders.

    Science.gov (United States)

    Halevy, Tomer; Urbach, Achia

    2014-10-24

    Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients' somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn't be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

  16. Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico; Canetta, Raffaele

    2004-01-01

    In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved

  17. Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Marseguerra, Marzio E-mail: marzio.marseguerra@polimi.it; Zio, Enrico E-mail: enrico.zio@polimi.it; Canetta, Raffaele

    2004-07-01

    In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved.

  18. Integrating the landscape epidemiology and genetics of RNA viruses: rabies in domestic dogs as a model.

    Science.gov (United States)

    Brunker, K; Hampson, K; Horton, D L; Biek, R

    2012-12-01

    Landscape epidemiology and landscape genetics combine advances in molecular techniques, spatial analyses and epidemiological models to generate a more real-world understanding of infectious disease dynamics and provide powerful new tools for the study of RNA viruses. Using dog rabies as a model we have identified how key questions regarding viral spread and persistence can be addressed using a combination of these techniques. In contrast to wildlife rabies, investigations into the landscape epidemiology of domestic dog rabies requires more detailed assessment of the role of humans in disease spread, including the incorporation of anthropogenic landscape features, human movements and socio-cultural factors into spatial models. In particular, identifying and quantifying the influence of anthropogenic features on pathogen spread and measuring the permeability of dispersal barriers are important considerations for planning control strategies, and may differ according to cultural, social and geographical variation across countries or continents. Challenges for dog rabies research include the development of metapopulation models and transmission networks using genetic information to uncover potential source/sink dynamics and identify the main routes of viral dissemination. Information generated from a landscape genetics approach will facilitate spatially strategic control programmes that accommodate for heterogeneities in the landscape and therefore utilise resources in the most cost-effective way. This can include the efficient placement of vaccine barriers, surveillance points and adaptive management for large-scale control programmes.

  19. Parameter identification of ZnO surge arrester models based on genetic algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Bayadi, Abdelhafid [Laboratoire d' Automatique de Setif, Departement d' Electrotechnique, Faculte des Sciences de l' Ingenieur, Universite Ferhat ABBAS de Setif, Route de Bejaia Setif 19000 (Algeria)

    2008-07-15

    The correct and adequate modelling of ZnO surge arresters characteristics is very important for insulation coordination studies and systems reliability. In this context many researchers addressed considerable efforts to the development of surge arresters models to reproduce the dynamic characteristics observed in their behaviour when subjected to fast front impulse currents. The difficulties with these models reside essentially in the calculation and the adjustment of their parameters. This paper proposes a new technique based on genetic algorithm to obtain the best possible series of parameter values of ZnO surge arresters models. The validity of the predicted parameters is then checked by comparing the predicted results with the experimental results available in the literature. Using the ATP-EMTP package, an application of the arrester model on network system studies is presented and discussed. (author)

  20. Theory and Practice in Quantitative Genetics

    DEFF Research Database (Denmark)

    Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C

    2003-01-01

    With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative...... geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships......) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each...

  1. Development of a tiered and binned genetic counseling model for informed consent in the era of multiplex testing for cancer susceptibility.

    Science.gov (United States)

    Bradbury, Angela R; Patrick-Miller, Linda; Long, Jessica; Powers, Jacquelyn; Stopfer, Jill; Forman, Andrea; Rybak, Christina; Mattie, Kristin; Brandt, Amanda; Chambers, Rachelle; Chung, Wendy K; Churpek, Jane; Daly, Mary B; Digiovanni, Laura; Farengo-Clark, Dana; Fetzer, Dominique; Ganschow, Pamela; Grana, Generosa; Gulden, Cassandra; Hall, Michael; Kohler, Lynne; Maxwell, Kara; Merrill, Shana; Montgomery, Susan; Mueller, Rebecca; Nielsen, Sarah; Olopade, Olufunmilayo; Rainey, Kimberly; Seelaus, Christina; Nathanson, Katherine L; Domchek, Susan M

    2015-06-01

    Multiplex genetic testing, including both moderate- and high-penetrance genes for cancer susceptibility, is associated with greater uncertainty than traditional testing, presenting challenges to informed consent and genetic counseling. We sought to develop a new model for informed consent and genetic counseling for four ongoing studies. Drawing from professional guidelines, literature, conceptual frameworks, and clinical experience, a multidisciplinary group developed a tiered-binned genetic counseling approach proposed to facilitate informed consent and improve outcomes of cancer susceptibility multiplex testing. In this model, tier 1 "indispensable" information is presented to all patients. More specific tier 2 information is provided to support variable informational needs among diverse patient populations. Clinically relevant information is "binned" into groups to minimize information overload, support informed decision making, and facilitate adaptive responses to testing. Seven essential elements of informed consent are provided to address the unique limitations, risks, and uncertainties of multiplex testing. A tiered-binned model for informed consent and genetic counseling has the potential to address the challenges of multiplex testing for cancer susceptibility and to support informed decision making and adaptive responses to testing. Future prospective studies including patient-reported outcomes are needed to inform how to best incorporate multiplex testing for cancer susceptibility into clinical practice.Genet Med 17 6, 485-492.

  2. MOESHA: A genetic algorithm for automatic calibration and estimation of parameter uncertainty and sensitivity of hydrologic models

    Science.gov (United States)

    Characterization of uncertainty and sensitivity of model parameters is an essential and often overlooked facet of hydrological modeling. This paper introduces an algorithm called MOESHA that combines input parameter sensitivity analyses with a genetic algorithm calibration routin...

  3. A general framework for the evaluation of genetic association studies using multiple marginal models

    DEFF Research Database (Denmark)

    Kitsche, Andreas; Ritz, Christian; Hothorn, Ludwig A.

    2016-01-01

    OBJECTIVE: In this study, we present a simultaneous inference procedure as a unified analysis framework for genetic association studies. METHODS: The method is based on the formulation of multiple marginal models that reflect different modes of inheritance. The basic advantage of this methodology...

  4. Olfaction in three genetic and two MPTP-induced Parkinson's disease mouse models.

    Directory of Open Access Journals (Sweden)

    Stefan Kurtenbach

    Full Text Available Various genetic or toxin-induced mouse models are frequently used for investigation of early PD pathology. Although olfactory impairment is known to precede motor symptoms by years, it is not known whether it is caused by impairments in the brain, the olfactory epithelium, or both. In this study, we investigated the olfactory function in three genetic Parkinson's disease (PD mouse models and mice treated with MPTP intraperitoneally and intranasally. To investigate olfactory function, we performed electro-olfactogram recordings (EOGs and an olfactory behavior test (cookie-finding test. We show that neither a parkin knockout mouse strain, nor intraperitoneal MPTP treated animals display any olfactory impairment in EOG recordings and the applied behavior test. We also found no difference in the responses of the olfactory epithelium to odorants in a mouse strain over-expressing doubly mutated α-synuclein, while this mouse strain was not suitable to test olfaction in a cookie-finding test as it displays a mobility impairment. A transgenic mouse expressing mutated α-synuclein in dopaminergic neurons performed equal to control animals in the cookie-finding test. Further we show that intranasal MPTP application can cause functional damage of the olfactory epithelium.

  5. A model based on soil structural aspects describing the fate of genetically modified bacteria in soil

    NARCIS (Netherlands)

    Hoeven, van der N.; Elsas, van J.D.; Heijnen, C.E.

    1996-01-01

    A computer simulation model was developed which describes growth and competition of bacteria in the soil environment. In the model, soil was assumed to contain millions of pores of a few different size classes. An introduced bacterial strain, e.g. a genetically modified micro-organism (GEMMO), was

  6. Strategies for MCMC computation in quantitative genetics

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Ibánez, N.; Sorensen, Daniel

    2006-01-01

    Given observations of a trait and a pedigree for a group of animals, the basic model in quantitative genetics is a linear mixed model with genetic random effects. The correlation matrix of the genetic random effects is determined by the pedigree and is typically very highdimensional but with a sp...

  7. A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations.

    Science.gov (United States)

    Gompert, Zachariah

    2016-01-01

    Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20) SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in structure), particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur) and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among chromosomes in the Uyghur

  8. Genetic screening and testing in an episode-based payment model: preserving patient autonomy.

    Science.gov (United States)

    Sutherland, Sharon; Farrell, Ruth M; Lockwood, Charles

    2014-11-01

    The State of Ohio is implementing an episode-based payment model for perinatal care. All costs of care will be tabulated for each live birth and assigned to the delivering provider, creating a three-tiered model for reimbursement for care. Providers will be reimbursed as usual for care that is average in cost and quality, while instituting rewards or penalties for those outside the expected range in either domain. There are few exclusions, and all methods of genetic screening and diagnostic testing are included in the episode cost calculation as proposed. Prenatal ultrasonography, genetic screening, and diagnostic testing are critical components of the delivery of high-quality, evidence-based prenatal care. These tests provide pregnant women with key information about the pregnancy, which, in turn, allows them to work closely with their health care provider to determine optimal prenatal care. The concepts of informed consent and decision-making, cornerstones of the ethical practice of medicine, are founded on the principles of autonomy and respect for persons. These principles recognize that patients' rights to make choices and take actions are based on their personal beliefs and values. Given the personal nature of such decisions, it is critical that patients have unbarred access to prenatal genetic tests if they elect to use them as part of their prenatal care. The proposed restructuring of reimbursement creates a clear conflict between patient autonomy and physician financial incentives.

  9. Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

    International Nuclear Information System (INIS)

    Chung, K K; Do, D Q

    2010-01-01

    In order to model relationships between chemical structures and biological effects in quantitative structure–activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data

  10. The filamentous fungus Sordaria macrospora as a genetic model to study fruiting body development.

    Science.gov (United States)

    Teichert, Ines; Nowrousian, Minou; Pöggeler, Stefanie; Kück, Ulrich

    2014-01-01

    Filamentous fungi are excellent experimental systems due to their short life cycles as well as easy and safe manipulation in the laboratory. They form three-dimensional structures with numerous different cell types and have a long tradition as genetic model organisms used to unravel basic mechanisms underlying eukaryotic cell differentiation. The filamentous ascomycete Sordaria macrospora is a model system for sexual fruiting body (perithecia) formation. S. macrospora is homothallic, i.e., self-fertile, easily genetically tractable, and well suited for large-scale genomics, transcriptomics, and proteomics studies. Specific features of its life cycle and the availability of a developmental mutant library make it an excellent system for studying cellular differentiation at the molecular level. In this review, we focus on recent developments in identifying gene and protein regulatory networks governing perithecia formation. A number of tools have been developed to genetically analyze developmental mutants and dissect transcriptional profiles at different developmental stages. Protein interaction studies allowed us to identify a highly conserved eukaryotic multisubunit protein complex, the striatin-interacting phosphatase and kinase complex and its role in sexual development. We have further identified a number of proteins involved in chromatin remodeling and transcriptional regulation of fruiting body development. Furthermore, we review the involvement of metabolic processes from both primary and secondary metabolism, and the role of nutrient recycling by autophagy in perithecia formation. Our research has uncovered numerous players regulating multicellular development in S. macrospora. Future research will focus on mechanistically understanding how these players are orchestrated in this fungal model system. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. Mathematical programming models for solving in equal-sized facilities layout problems. A genetic search method

    International Nuclear Information System (INIS)

    Tavakkoli-Moghaddam, R.

    1999-01-01

    This paper present unequal-sized facilities layout solutions generated by a genetic search program. named Layout Design using a Genetic Algorithm) 9. The generalized quadratic assignment problem requiring pre-determined distance and material flow matrices as the input data and the continuous plane model employing a dynamic distance measure and a material flow matrix are discussed. Computational results on test problems are reported as compared with layout solutions generated by the branch - and bound algorithm a hybrid method merging simulated annealing and local search techniques, and an optimization process of an enveloped block

  12. Near infrared spectrometric technique for testing fruit quality: optimisation of regression models using genetic algorithms

    Science.gov (United States)

    Isingizwe Nturambirwe, J. Frédéric; Perold, Willem J.; Opara, Umezuruike L.

    2016-02-01

    Near infrared (NIR) spectroscopy has gained extensive use in quality evaluation. It is arguably one of the most advanced spectroscopic tools in non-destructive quality testing of food stuff, from measurement to data analysis and interpretation. NIR spectral data are interpreted through means often involving multivariate statistical analysis, sometimes associated with optimisation techniques for model improvement. The objective of this research was to explore the extent to which genetic algorithms (GA) can be used to enhance model development, for predicting fruit quality. Apple fruits were used, and NIR spectra in the range from 12000 to 4000 cm-1 were acquired on both bruised and healthy tissues, with different degrees of mechanical damage. GAs were used in combination with partial least squares regression methods to develop bruise severity prediction models, and compared to PLS models developed using the full NIR spectrum. A classification model was developed, which clearly separated bruised from unbruised apple tissue. GAs helped improve prediction models by over 10%, in comparison with full spectrum-based models, as evaluated in terms of error of prediction (Root Mean Square Error of Cross-validation). PLS models to predict internal quality, such as sugar content and acidity were developed and compared to the versions optimized by genetic algorithm. Overall, the results highlighted the potential use of GA method to improve speed and accuracy of fruit quality prediction.

  13. lme4qtl: linear mixed models with flexible covariance structure for genetic studies of related individuals.

    Science.gov (United States)

    Ziyatdinov, Andrey; Vázquez-Santiago, Miquel; Brunel, Helena; Martinez-Perez, Angel; Aschard, Hugues; Soria, Jose Manuel

    2018-02-27

    Quantitative trait locus (QTL) mapping in genetic data often involves analysis of correlated observations, which need to be accounted for to avoid false association signals. This is commonly performed by modeling such correlations as random effects in linear mixed models (LMMs). The R package lme4 is a well-established tool that implements major LMM features using sparse matrix methods; however, it is not fully adapted for QTL mapping association and linkage studies. In particular, two LMM features are lacking in the base version of lme4: the definition of random effects by custom covariance matrices; and parameter constraints, which are essential in advanced QTL models. Apart from applications in linkage studies of related individuals, such functionalities are of high interest for association studies in situations where multiple covariance matrices need to be modeled, a scenario not covered by many genome-wide association study (GWAS) software. To address the aforementioned limitations, we developed a new R package lme4qtl as an extension of lme4. First, lme4qtl contributes new models for genetic studies within a single tool integrated with lme4 and its companion packages. Second, lme4qtl offers a flexible framework for scenarios with multiple levels of relatedness and becomes efficient when covariance matrices are sparse. We showed the value of our package using real family-based data in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT2) project. Our software lme4qtl enables QTL mapping models with a versatile structure of random effects and efficient computation for sparse covariances. lme4qtl is available at https://github.com/variani/lme4qtl .

  14. An Intelligent Model for Pairs Trading Using Genetic Algorithms.

    Science.gov (United States)

    Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

    2015-01-01

    Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

  15. Effect of Keishibukuryogan on Genetic and Dietary Obesity Models

    Directory of Open Access Journals (Sweden)

    Fengying Gao

    2015-01-01

    Full Text Available Obesity has been recognized as one of the most important risk factors for a variety of chronic diseases, such as diabetes, hypertension/cardiovascular diseases, steatosis/hepatitis, and cancer. Keishibukuryogan (KBG, Gui Zhi Fu Ling Wan in Chinese is a traditional Chinese/Japanese (Kampo medicine that has been known to improve blood circulation and is also known for its anti-inflammatory or scavenging effect. In this study, we evaluated the effect of KBG in two distinct rodent models of obesity driven by either a genetic (SHR/NDmcr-cp rat model or dietary (high-fat diet-induced mouse obesity model mechanism. Although there was no significant effect on the body composition in either the SHR rat or the DIO mouse models, KBG treatment significantly decreased the serum level of leptin and liver TG level in the DIO mouse, but not in the SHR rat model. Furthermore, a lower fat deposition in liver and a smaller size of adipocytes in white adipose tissue were observed in the DIO mice treated with KBG. Importantly, we further found downregulation of genes involved in lipid metabolism in the KBG-treated liver, along with decreased liver TG and cholesterol level. Our present data experimentally support in fact that KBG can be an attractive Kampo medicine to improve obese status through a regulation of systemic leptin level and/or lipid metabolism.

  16. General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

    Science.gov (United States)

    de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

    2016-11-01

    Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

  17. GSEVM v.2: MCMC software to analyse genetically structured environmental variance models

    DEFF Research Database (Denmark)

    Ibáñez-Escriche, N; Garcia, M; Sorensen, D

    2010-01-01

    This note provides a description of software that allows to fit Bayesian genetically structured variance models using Markov chain Monte Carlo (MCMC). The gsevm v.2 program was written in Fortran 90. The DOS and Unix executable programs, the user's guide, and some example files are freely available...... for research purposes at http://www.bdporc.irta.es/estudis.jsp. The main feature of the program is to compute Monte Carlo estimates of marginal posterior distributions of parameters of interest. The program is quite flexible, allowing the user to fit a variety of linear models at the level of the mean...

  18. Drag reduction of a car model by linear genetic programming control

    Science.gov (United States)

    Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien

    2017-08-01

    We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.

  19. Genetic determinants of cardiometabolic risk: a proposed model for phenotype association and interaction.

    Science.gov (United States)

    Blackett, Piers R; Sanghera, Dharambir K

    2013-01-01

    This review provides a translational and unifying summary of metabolic syndrome genetics and highlights evidence that genetic studies are starting to unravel and untangle origins of the complex and challenging cluster of disease phenotypes. The associated genes effectively express in the brain, liver, kidney, arterial endothelium, adipocytes, myocytes, and β cells. Progression of syndrome traits has been associated with ectopic lipid accumulation in the arterial wall, visceral adipocytes, myocytes, and liver. Thus, it follows that the genetics of dyslipidemia, obesity, and nonalcoholic fatty liver disease are central in triggering progression of the syndrome to overt expression of disease traits and have become a key focus of interest for early detection and for designing prevention and treatments. To support the "birds' eye view" approach, we provide a road-map depicting commonality and interrelationships between the traits and their genetic and environmental determinants based on known risk factors, metabolic pathways, pharmacologic targets, treatment responses, gene networks, pleiotropy, and association with circadian rhythm. Although only a small portion of the known heritability is accounted for and there is insufficient support for clinical application of gene-based prediction models, there is direction and encouraging progress in a rapidly moving field that is beginning to show clinical relevance. Copyright © 2013 National Lipid Association. Published by Elsevier Inc. All rights reserved.

  20. Network clustering analysis using mixture exponential-family random graph models and its application in genetic interaction data.

    Science.gov (United States)

    Wang, Yishu; Zhao, Hongyu; Deng, Minghua; Fang, Huaying; Yang, Dejie

    2017-08-24

    Epistatic miniarrary profile (EMAP) studies have enabled the mapping of large-scale genetic interaction networks and generated large amounts of data in model organisms. It provides an incredible set of molecular tools and advanced technologies that should be efficiently understanding the relationship between the genotypes and phenotypes of individuals. However, the network information gained from EMAP cannot be fully exploited using the traditional statistical network models. Because the genetic network is always heterogeneous, for example, the network structure features for one subset of nodes are different from those of the left nodes. Exponentialfamily random graph models (ERGMs) are a family of statistical models, which provide a principled and flexible way to describe the structural features (e.g. the density, centrality and assortativity) of an observed network. However, the single ERGM is not enough to capture this heterogeneity of networks. In this paper, we consider a mixture ERGM (MixtureEGRM) networks, which model a network with several communities, where each community is described by a single EGRM.

  1. A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction

    Directory of Open Access Journals (Sweden)

    Daqing Zhang

    2015-01-01

    Full Text Available Blood-brain barrier (BBB is a highly complex physical barrier determining what substances are allowed to enter the brain. Support vector machine (SVM is a kernel-based machine learning method that is widely used in QSAR study. For a successful SVM model, the kernel parameters for SVM and feature subset selection are the most important factors affecting prediction accuracy. In most studies, they are treated as two independent problems, but it has been proven that they could affect each other. We designed and implemented genetic algorithm (GA to optimize kernel parameters and feature subset selection for SVM regression and applied it to the BBB penetration prediction. The results show that our GA/SVM model is more accurate than other currently available log BB models. Therefore, to optimize both SVM parameters and feature subset simultaneously with genetic algorithm is a better approach than other methods that treat the two problems separately. Analysis of our log BB model suggests that carboxylic acid group, polar surface area (PSA/hydrogen-bonding ability, lipophilicity, and molecular charge play important role in BBB penetration. Among those properties relevant to BBB penetration, lipophilicity could enhance the BBB penetration while all the others are negatively correlated with BBB penetration.

  2. Genetic Analysis of Milk Yield Using Random Regression Test Day Model in Tehran Province Holstein Dairy Cow

    Directory of Open Access Journals (Sweden)

    A. Seyeddokht

    2012-09-01

    Full Text Available In this research a random regression test day model was used to estimate heritability values and calculation genetic correlations between test day milk records. a total of 140357 monthly test day milk records belonging to 28292 first lactation Holstein cattle(trice time a day milking distributed in 165 herd and calved from 2001 to 2010 belonging to the herds of Tehran province were used. The fixed effects of herd-year-month of calving as contemporary group and age at calving and Holstein gene percentage as covariate were fitted. Orthogonal legendre polynomial with a 4th-order was implemented to take account of genetic and environmental aspects of milk production over the course of lactation. RRM using Legendre polynomials as base functions appears to be the most adequate to describe the covariance structure of the data. The results showed that the average of heritability for the second half of lactation period was higher than that of the first half. The heritability value for the first month was lowest (0.117 and for the eighth month of the lactation was highest (0.230 compared to the other months of lactation. Because of genetic variation was increased gradually, and residual variance was high in the first months of lactation, heritabilities were different over the course of lactation. The RRMs with a higher number of parameters were more useful to describe the genetic variation of test-day milk yield throughout the lactation. In this research estimation of genetic parameters, and calculation genetic correlations were implemented by random regression test day model, therefore using this method is the exact way to take account of parameters rather than the other ways.

  3. Design science research for decision support systems development: recent publication trends in the premier IS journals

    Directory of Open Access Journals (Sweden)

    Shah J Miah

    2016-11-01

    Full Text Available This paper presents a contemporary literature review of design science research (DSR studies in the domain of decision support systems (DSS development. The latest studies in the DSS design domain claim that DSR methodologies are the most popular design approach, but many details are still yet to be revealed for supporting this claim. In particular, it is important to thoroughly investigate the trends in either the form or deeper insights in use of DSR in this field. The aim of this study is to analyse the existing DSS design science studies to reveal insights into the use of DSR, so that we can outline research agenda for a special issue, based on findings of analysis. We selected articles (from 2005 to 2014 that were published in seven selected premier IS journals (ranked as A* in the ABDC journal ranking. The selected 57 sample articles are representative of DSS design studies that used DSR in theorising, designing, implementing, and evaluating DSS solutions. We discuss the theoretical positions of DSR for DSS development through six categories: DSS artefacts, DSR methods, DSR views, user involvement, DSS design innovations and problem domains. The findings indicate that new studies are needed to fill the knowledge gap in DSS design science, for more solid theoretical basis in near future.

  4. Exploring Middle School Students' Understanding of Three Conceptual Models in Genetics

    Science.gov (United States)

    Freidenreich, Hava Bresler; Duncan, Ravit Golan; Shea, Nicole

    2011-01-01

    Genetics is the cornerstone of modern biology and a critical aspect of scientific literacy. Research has shown, however, that many high school graduates lack fundamental understandings in genetics necessary to make informed decisions about issues and emerging technologies in this domain, such as genetic screening, genetically modified foods, etc.…

  5. Premature hippocampus-dependent memory decline in middle-aged females of a genetic rat model of depression.

    Science.gov (United States)

    Lim, Patrick H; Wert, Stephanie L; Tunc-Ozcan, Elif; Marr, Robert; Ferreira, Adriana; Redei, Eva E

    2018-02-25

    Aging and major depressive disorder are risk factors for dementia, including Alzheimer's Disease (AD), but the mechanism(s) linking depression and dementia are not known. Both AD and depression show greater prevalence in women. We began to investigate this connection using females of the genetic model of depression, the inbred Wistar Kyoto More Immobile (WMI) rat. These rats consistently display depression-like behavior compared to the genetically close control, the Wistar Kyoto Less Immobile (WLI) strain. Hippocampus-dependent contextual fear memory did not differ between young WLI and WMI females, but, by middle-age, female WMIs showed memory deficits compared to same age WLIs. This deficit, measured as duration of freezing in the fear provoking-context was not related to activity differences between the strains prior to fear conditioning. Hippocampal expression of AD-related genes, such as amyloid precursor protein, amyloid beta 42, beta secretase, synucleins, total and dephosphorylated tau, and synaptophysin, did not differ between WLIs and WMIs in either age group. However, hippocampal transcript levels of catalase (Cat) and hippocampal and frontal cortex expression of insulin-like growth factor 2 (Igf2) and Igf2 receptor (Igf2r) paralleled fear memory differences between middle-aged WLIs and WMIs. This data suggests that chronic depression-like behavior that is present in this genetic model is a risk factor for early spatial memory decline in females. The molecular mechanisms of this early memory decline likely involve the interaction of aging processes with the genetic components responsible for the depression-like behavior in this model. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification

    Directory of Open Access Journals (Sweden)

    C. Fernandez-Lozano

    2013-01-01

    Full Text Available Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM. Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA, the most representative variables for a specific classification problem can be selected.

  7. PDE Modeling of a Microfluidic Thermal Process for Genetic Analysis Application

    Directory of Open Access Journals (Sweden)

    Reza Banaei Khosroushahi

    2013-01-01

    Full Text Available This paper details the infinite dimensional dynamics of a prototype microfluidic thermal process that is used for genetic analysis purposes. Highly effective infinite dimensional dynamics, in addition to collocated sensor and actuator architecture, require the development of a precise control framework to meet the very tight performance requirements of this system, which are not fully attainable through conventional lumped modeling and controller design approaches. The general partial differential equations describing the dynamics of the system are separated into steady-state and transient parts which are derived for a carefully chosen three-dimensional axisymmetric model. These equations are solved analytically, and the results are verified using an experimentally verified precise finite element method (FEM model. The final combined result is a framework for designing a precise tracking controller applicable to the selected lab-on-a-chip device.

  8. Genetic and environmental influence on asthma

    DEFF Research Database (Denmark)

    Skadhauge, L.R.; Christensen, Kaare; Kyvik, Kirsten Ohm

    1999-01-01

    The aim of this study was to estimate the relative influence of genetic and environmental factors on the aetiology of asthma. The classic twin study design was used to analyse data on self-reported asthma obtained by a questionnaire mailed to 34,076 individuals, aged 12-41 yrs and originating from...... in the monozygotic than in the dizygotic twins. Using biometric modelling, a model including additive genetic and nonshared environmental effects provided the best overall fit to the data. According to this model, 73% of the variation in liability to asthma was explained by genetic factors. No sex difference or age......-dependency in the magnitude of genetic effects was observed. The biometric analysis emphasized a major influence of genetic factors in the aetiology of asthma. However, a substantial part of the variation in liability to asthma is due to the impact of environmental factors specific to the individual. There is no evidence...

  9. Stocking the genetic supermarket: reproductive genetic technologies and collective action problems.

    Science.gov (United States)

    Gyngell, Chris; Douglas, Thomas

    2015-05-01

    Reproductive genetic technologies (RGTs) allow parents to decide whether their future children will have or lack certain genetic predispositions. A popular model that has been proposed for regulating access to RGTs is the 'genetic supermarket'. In the genetic supermarket, parents are free to make decisions about which genes to select for their children with little state interference. One possible consequence of the genetic supermarket is that collective action problems will arise: if rational individuals use the genetic supermarket in isolation from one another, this may have a negative effect on society as a whole, including future generations. In this article we argue that RGTs targeting height, innate immunity, and certain cognitive traits could lead to collective action problems. We then discuss whether this risk could in principle justify state intervention in the genetic supermarket. We argue that there is a plausible prima facie case for the view that such state intervention would be justified and respond to a number of arguments that might be adduced against that view. © 2014 The Authors. Bioethics published by John Wiley & Sons Ltd.

  10. The synthesis paradigm in genetics.

    Science.gov (United States)

    Rice, William R

    2014-02-01

    Experimental genetics with model organisms and mathematically explicit genetic theory are generally considered to be the major paradigms by which progress in genetics is achieved. Here I argue that this view is incomplete and that pivotal advances in genetics--and other fields of biology--are also made by synthesizing disparate threads of extant information rather than generating new information from experiments or formal theory. Because of the explosive expansion of information in numerous "-omics" data banks, and the fragmentation of genetics into numerous subdisciplines, the importance of the synthesis paradigm will likely expand with time.

  11. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yudong Zhang

    2013-01-01

    Full Text Available In this paper, we proposed a hybrid system to predict corporate bankruptcy. The whole procedure consists of the following four stages: first, sequential forward selection was used to extract the most important features; second, a rule-based model was chosen to fit the given dataset since it can present physical meaning; third, a genetic ant colony algorithm (GACA was introduced; the fitness scaling strategy and the chaotic operator were incorporated with GACA, forming a new algorithm—fitness-scaling chaotic GACA (FSCGACA, which was used to seek the optimal parameters of the rule-based model; and finally, the stratified K-fold cross-validation technique was used to enhance the generalization of the model. Simulation experiments of 1000 corporations’ data collected from 2006 to 2009 demonstrated that the proposed model was effective. It selected the 5 most important factors as “net income to stock broker’s equality,” “quick ratio,” “retained earnings to total assets,” “stockholders’ equity to total assets,” and “financial expenses to sales.” The total misclassification error of the proposed FSCGACA was only 7.9%, exceeding the results of genetic algorithm (GA, ant colony algorithm (ACA, and GACA. The average computation time of the model is 2.02 s.

  12. Genetic Determinants of Cardio-Metabolic Risk: A Proposed Model for Phenotype Association and Interaction

    Science.gov (United States)

    Blackett, Piers R; Sanghera, Dharambir K

    2012-01-01

    This review provides a translational and unifying summary of metabolic syndrome genetics and highlights evidence that genetic studies are starting to unravel and untangle origins of the complex and challenging cluster of disease phenotypes. The associated genes effectively express in the brain, liver, kidney, arterial endothelium, adipocytes, myocytes and β cells. Progression of syndrome traits has been associated with ectopic lipid accumulation in the arterial wall, visceral adipocytes, myocytes, and liver. Thus it follows that the genetics of dyslipidemia, obesity, and non-alcoholic fatty liver (NAFLD) disease are central in triggering progression of the syndrome to overt expression of disease traits, and have become a key focus of interest for early detection and for designing prevention and treatments. To support the “birds’ eye view” approach we provide a road-map depicting commonality and interrelationships between the traits and their genetic and environmental determinants based on known risk factors, metabolic pathways, pharmacological targets, treatment responses, gene networks, pleiotropy, and association with circadian rhythm. Although only a small portion of the known heritability is accounted for and there is insufficient support for clinical application of gene-based prediction models, there is direction and encouraging progress in a rapidly moving field that is beginning to show clinical relevance. PMID:23351585

  13. Effect of genetic variation in a Drosophila model of diabetes-associated misfolded human proinsulin.

    Science.gov (United States)

    He, Bin Z; Ludwig, Michael Z; Dickerson, Desiree A; Barse, Levi; Arun, Bharath; Vilhjálmsson, Bjarni J; Jiang, Pengyao; Park, Soo-Young; Tamarina, Natalia A; Selleck, Scott B; Wittkopp, Patricia J; Bell, Graeme I; Kreitman, Martin

    2014-02-01

    The identification and validation of gene-gene interactions is a major challenge in human studies. Here, we explore an approach for studying epistasis in humans using a Drosophila melanogaster model of neonatal diabetes mellitus. Expression of the mutant preproinsulin (hINS(C96Y)) in the eye imaginal disc mimics the human disease: it activates conserved stress-response pathways and leads to cell death (reduction in eye area). Dominant-acting variants in wild-derived inbred lines from the Drosophila Genetics Reference Panel produce a continuous, highly heritable distribution of eye-degeneration phenotypes in a hINS(C96Y) background. A genome-wide association study (GWAS) in 154 sequenced lines identified a sharp peak on chromosome 3L, which mapped to a 400-bp linkage block within an intron of the gene sulfateless (sfl). RNAi knockdown of sfl enhanced the eye-degeneration phenotype in a mutant-hINS-dependent manner. RNAi against two additional genes in the heparan sulfate (HS) biosynthetic pathway (ttv and botv), in which sfl acts, also modified the eye phenotype in a hINS(C96Y)-dependent manner, strongly suggesting a novel link between HS-modified proteins and cellular responses to misfolded proteins. Finally, we evaluated allele-specific expression difference between the two major sfl-intronic haplotypes in heterozygtes. The results showed significant heterogeneity in marker-associated gene expression, thereby leaving the causal mutation(s) and its mechanism unidentified. In conclusion, the ability to create a model of human genetic disease, map a QTL by GWAS to a specific gene, and validate its contribution to disease with available genetic resources and the potential to experimentally link the variant to a molecular mechanism demonstrate the many advantages Drosophila holds in determining the genetic underpinnings of human disease.

  14. Modelling Autistic Features in Mice Using Quantitative Genetic Approaches

    NARCIS (Netherlands)

    Molenhuis, Remco T; Bruining, Hilgo; Kas, Martien J

    2017-01-01

    Animal studies provide a unique opportunity to study the consequences of genetic variants at the behavioural level. Human studies have identified hundreds of risk genes for autism spectrum disorder (ASD) that can lead to understanding on how genetic variation contributes to individual differences in

  15. A service-oriented architecture for integrating the modeling and formal verification of genetic regulatory networks

    Directory of Open Access Journals (Sweden)

    Page Michel

    2009-12-01

    Full Text Available Abstract Background The study of biological networks has led to the development of increasingly large and detailed models. Computer tools are essential for the simulation of the dynamical behavior of the networks from the model. However, as the size of the models grows, it becomes infeasible to manually verify the predictions against experimental data or identify interesting features in a large number of simulation traces. Formal verification based on temporal logic and model checking provides promising methods to automate and scale the analysis of the models. However, a framework that tightly integrates modeling and simulation tools with model checkers is currently missing, on both the conceptual and the implementational level. Results We have developed a generic and modular web service, based on a service-oriented architecture, for integrating the modeling and formal verification of genetic regulatory networks. The architecture has been implemented in the context of the qualitative modeling and simulation tool GNA and the model checkers NUSMV and CADP. GNA has been extended with a verification module for the specification and checking of biological properties. The verification module also allows the display and visual inspection of the verification results. Conclusions The practical use of the proposed web service is illustrated by means of a scenario involving the analysis of a qualitative model of the carbon starvation response in E. coli. The service-oriented architecture allows modelers to define the model and proceed with the specification and formal verification of the biological properties by means of a unified graphical user interface. This guarantees a transparent access to formal verification technology for modelers of genetic regulatory networks.

  16. Simulating natural selection in landscape genetics

    Science.gov (United States)

    E. L. Landguth; S. A. Cushman; N. Johnson

    2012-01-01

    Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially- explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal...

  17. Corporate social responsibility and mental health: the Premier League football Imagine Your Goals programme.

    Science.gov (United States)

    Henderson, Claire; O'Hara, Stefanie; Thornicroft, Graham; Webber, Martin

    2014-08-01

    Football is increasingly used to facilitate recovery in mental health services, often in partnership with football clubs. However, few clubs have made mental health part of their corporate social responsibility programmes until recently. We report the impact on participants of the 'Imagine Your Goals' programme, run by 16 Premier League football clubs in conjunction with England's Time to Change programme to reduce mental health-related stigma and discrimination. Mixed methods evaluation used pre/post measures of well-being, access to social capital, focus groups held early on and towards the end of the two-year programmes, and questionnaires for coaching staff. There were no significant changes to participants' mental well-being scores between baseline and follow-up, nor to the total number of social resources accessible through their networks. However, there was a statistically significant increase at follow-up in the mean score of the personal skills subscale of the Resource Generator-UK. Participants' individual skills were also higher at follow-up. Qualitative data showed programmes had largely met participants' expectations in terms of socializing, providing structure and improving fitness levels, exceeded expectations in relationships with coaching staff and additional activities, but did not always meet them in improving football skills. Participants varied in their knowledge of exit opportunities, depending on which club's programme they attended. A minority of clubs reported difficulties in recruitment and concerns about planning for the future of the projects. Football clubs and the charitable foundations they set up can successfully deliver programmes to people with mental health problems which improve access to personal skills social capital and have other potential benefits.

  18. The Protective Effect of Minocycline in a Paraquat-Induced Parkinson's Disease Model in Drosophila is Modified in Altered Genetic Backgrounds

    Directory of Open Access Journals (Sweden)

    Arati A. Inamdar

    2012-01-01

    Full Text Available Epidemiological studies link the herbicide paraquat to increased incidence of Parkinson's disease (PD. We previously reported that Drosophila exposed to paraquat recapitulate PD symptoms, including region-specific degeneration of dopaminergic neurons. Minocycline, a tetracycline derivative, exerts ameliorative effects in neurodegenerative disease models, including Drosophila. We investigated whether our environmental toxin-based PD model could contribute to an understanding of cellular and genetic mechanisms of minocycline action and whether we could assess potential interference with these drug effects in altered genetic backgrounds. Cofeeding of minocycline with paraquat prolonged survival, rescued mobility defects, blocked generation of reactive oxygen species, and extended dopaminergic neuron survival, as has been reported previously for a genetic model of PD in Drosophila. We then extended this study to identify potential interactions of minocycline with genes regulating dopamine homeostasis that might modify protection against paraquat and found that deficits in GTP cyclohydrolase adversely affect minocycline rescue. We further performed genetic studies to identify signaling pathways that are necessary for minocycline protection against paraquat toxicity and found that mutations in the Drosophila genes that encode c-Jun N-terminal kinase (JNK and Akt/Protein kinase B block minocycline rescue.

  19. Model for fitting longitudinal traits subject to threshold response applied to genetic evaluation for heat tolerance

    Directory of Open Access Journals (Sweden)

    Misztal Ignacy

    2009-01-01

    Full Text Available Abstract A semi-parametric non-linear longitudinal hierarchical model is presented. The model assumes that individual variation exists both in the degree of the linear change of performance (slope beyond a particular threshold of the independent variable scale and in the magnitude of the threshold itself; these individual variations are attributed to genetic and environmental components. During implementation via a Bayesian MCMC approach, threshold levels were sampled using a Metropolis step because their fully conditional posterior distributions do not have a closed form. The model was tested by simulation following designs similar to previous studies on genetics of heat stress. Posterior means of parameters of interest, under all simulation scenarios, were close to their true values with the latter always being included in the uncertain regions, indicating an absence of bias. The proposed models provide flexible tools for studying genotype by environmental interaction as well as for fitting other longitudinal traits subject to abrupt changes in the performance at particular points on the independent variable scale.

  20. Comparative evaluation of fuzzy logic and genetic algorithms models for portfolio optimization

    Directory of Open Access Journals (Sweden)

    Heidar Masoumi Soureh

    2017-03-01

    Full Text Available Selection of optimum methods which have appropriate speed and precision for planning and de-cision-making has always been a challenge for investors and managers. One the most important concerns for them is investment planning and optimization for acquisition of desirable wealth under controlled risk with the best return. This paper proposes a model based on Markowitz the-orem by considering the aforementioned limitations in order to help effective decisions-making for portfolio selection. Then, the model is investigated by fuzzy logic and genetic algorithms, for the optimization of the portfolio in selected active companies listed in Tehran Stock Exchange over the period 2012-2016 and the results of the above models are discussed. The results show that the two studied models had functional differences in portfolio optimization, its tools and the possibility of supplementing each other and their selection.

  1. Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma.

    Science.gov (United States)

    McFadden, David G; Politi, Katerina; Bhutkar, Arjun; Chen, Frances K; Song, Xiaoling; Pirun, Mono; Santiago, Philip M; Kim-Kiselak, Caroline; Platt, James T; Lee, Emily; Hodges, Emily; Rosebrock, Adam P; Bronson, Roderick T; Socci, Nicholas D; Hannon, Gregory J; Jacks, Tyler; Varmus, Harold

    2016-10-18

    Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity.

  2. Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma

    Science.gov (United States)

    McFadden, David G.; Politi, Katerina; Bhutkar, Arjun; Chen, Frances K.; Song, Xiaoling; Pirun, Mono; Santiago, Philip M.; Kim-Kiselak, Caroline; Platt, James T.; Lee, Emily; Hodges, Emily; Rosebrock, Adam P.; Bronson, Roderick T.; Socci, Nicholas D.; Hannon, Gregory J.; Jacks, Tyler; Varmus, Harold

    2016-01-01

    Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity. PMID:27702896

  3. 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

  4. Reporting on a Talk I Gave Some Months Ago, the Headline in "La Opinion," Los Angeles' Premier Spanish Language Newspaper, Declared the City's School System "en crisis permanente." No One Wrote in to Disagree. The Claremont Letter. Volume 3, Issue 1

    Science.gov (United States)

    Kerchner, Charles T.

    2008-01-01

    Reporting on a talk the author gave some months ago, the headline in "La Opinion," Los Angeles' premier Spanish language newspaper, declared the city's school system "en crisis permanente." No one wrote in to disagree. Indeed, at the end of "Learning from L.A.: Institutional Change in American Public Education" (Harvard Education Press) the author…

  5. Genetic diversity in a crop metapopulation

    NARCIS (Netherlands)

    Heerwaarden, van J.; Eeuwijk, van F.A.; Ross-Ibarra, J.

    2010-01-01

    The need to protect crop genetic resources has sparked a growing interest in the genetic diversity maintained in traditional farming systems worldwide. Although traditional seed management has been proposed as an important determinant of genetic diversity and structure in crops, no models exist that

  6. Genetic instability model for cancer risk in A-bomb survivors

    International Nuclear Information System (INIS)

    Niwa, Ohtsura

    1998-01-01

    This review was written rather against Mendelsohn's reductionist model for cancer risk in A-bomb survivors in following chapters. Assumptions for carcinogenic process: mutation of a cell to the cancer cell and its proliferation. Multi-step theory for carcinogenesis and age of crisis: induction of cancer by accumulation of cancer-related gene mutations which being linear to time (age). Effect of exogenous hit in the multi-step theory: radiation as an exogenous hit to damage DNA. Dose-effect relationship for cancer risk in the survivors and the problem for the latent period: for solid tumors, dose-effect relationship is linear and shortening of the latent period is not observed. Considerations on cancer data in adulthood exposure/Indirect effect model in radiation carcinogenesis: solid cancer data supporting the indirect effect model. Possible mechanism for radiation-induced long-term increase of natural mutation frequency: genetic instability remaining in the irradiated cells which being a basis of the indirect effect model. Notes for considerations of carcinogenicity in exposed people/Difference in carcinogenic mechanisms due to age. The author concluded that the radiation-induced carcinogenesis is deeply related with the natural carcinogenesis and particularly for solid cancers, it can not be explained by the classic reductionist model. (K.H.)

  7. Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

    Science.gov (United States)

    Veerkamp, R F; Koenen, E P; De Jong, G

    2001-10-01

    Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.

  8. Dominance genetic and maternal effects for genetic evaluation of egg production traits in dual-purpose chickens.

    Science.gov (United States)

    Jasouri, M; Zamani, P; Alijani, S

    2017-10-01

    1. A study was conducted to study direct dominance genetic and maternal effects on genetic evaluation of production traits in dual-purpose chickens. The data set consisted of records of body weight and egg production of 49 749 Mazandaran fowls from 19 consecutive generations. Based on combinations of different random effects, including direct additive and dominance genetic and maternal additive genetic and environmental effects, 8 different models were compared. 2. Inclusion of a maternal genetic effect in the models noticeably improved goodness of fit for all traits. Direct dominance genetic effect did not have noticeable effects on goodness of fit but simultaneous inclusion of both direct dominance and maternal additive genetic effects improved fitting criteria and accuracies of genetic parameter estimates for hatching body weight and egg production traits. 3. Estimates of heritability (h 2 ) for body weights at hatch, 8 weeks and 12 weeks of age (BW0, BW8 and BW12, respectively), age at sexual maturity (ASM), average egg weights at 28-32 weeks of laying period (AEW), egg number (EN) and egg production intensity (EI) were 0.08, 0.21, 0.22, 0.22, 0.21, 0.09 and 0.10, respectively. For BW0, BW8, BW12, ASM, AEW, EN and EI, proportion of dominance genetic to total phenotypic variance (d 2 ) were 0.06, 0.08, 0.01, 0.06, 0.06, 0.08 and 0.07 and maternal heritability estimates (m 2 ) were 0.05, 0.04, 0.03, 0.13, 0.21, 0.07 and 0.03, respectively. Negligible coefficients of maternal environmental effect (c 2 ) from 0.01 to 0.08 were estimated for all traits, other than BW0, which had an estimate of 0.30. 4. Breeding values (BVs) estimated for body weights at early ages (BW0 and BW8) were considerably affected by components of the models, but almost similar BVs were estimated by different models for higher age body weight (BW12) and egg production traits (ASM, AEW, EN and EI). Generally, it could be concluded that inclusion of maternal effects (both genetic and

  9. A Continuous Correlated Beta Process Model for Genetic Ancestry in Admixed Populations.

    Directory of Open Access Journals (Sweden)

    Zachariah Gompert

    Full Text Available Admixture and recombination create populations and genomes with genetic ancestry from multiple source populations. Analyses of genetic ancestry in admixed populations are relevant for trait and disease mapping, studies of speciation, and conservation efforts. Consequently, many methods have been developed to infer genome-average ancestry and to deconvolute ancestry into continuous local ancestry blocks or tracts within individuals. Current methods for local ancestry inference perform well when admixture occurred recently or hybridization is ongoing, or when admixture occurred in the distant past such that local ancestry blocks have fixed in the admixed population. However, methods to infer local ancestry frequencies in isolated admixed populations still segregating for ancestry do not exist. In the current paper, I develop and test a continuous correlated beta process model to fill this analytical gap. The method explicitly models autocorrelations in ancestry frequencies at the population-level and uses discriminant analysis of SNP windows to take advantage of ancestry blocks within individuals. Analyses of simulated data sets show that the method is generally accurate such that ancestry frequency estimates exhibited low root-mean-square error and were highly correlated with the true values, particularly when large (±10 or ±20 SNP windows were used. Along these lines, the proposed method outperformed post hoc inference of ancestry frequencies from a traditional hidden Markov model (i.e., the linkage model in structure, particularly when admixture occurred more distantly in the past with little on-going gene flow or was followed by natural selection. The reliability and utility of the method was further assessed by analyzing genetic ancestry in an admixed human population (Uyghur and three populations from a hybrid zone between Mus domesticus and M. musculus. Considerable variation in ancestry frequencies was detected within and among

  10. Genetic and linguistic coevolution in Northern Island Melanesia.

    Science.gov (United States)

    Hunley, Keith; Dunn, Michael; Lindström, Eva; Reesink, Ger; Terrill, Angela; Healy, Meghan E; Koki, George; Friedlaender, Françoise R; Friedlaender, Jonathan S

    2008-10-01

    Recent studies have detailed a remarkable degree of genetic and linguistic diversity in Northern Island Melanesia. Here we utilize that diversity to examine two models of genetic and linguistic coevolution. The first model predicts that genetic and linguistic correspondences formed following population splits and isolation at the time of early range expansions into the region. The second is analogous to the genetic model of isolation by distance, and it predicts that genetic and linguistic correspondences formed through continuing genetic and linguistic exchange between neighboring populations. We tested the predictions of the two models by comparing observed and simulated patterns of genetic variation, genetic and linguistic trees, and matrices of genetic, linguistic, and geographic distances. The data consist of 751 autosomal microsatellites and 108 structural linguistic features collected from 33 Northern Island Melanesian populations. The results of the tests indicate that linguistic and genetic exchange have erased any evidence of a splitting and isolation process that might have occurred early in the settlement history of the region. The correlation patterns are also inconsistent with the predictions of the isolation by distance coevolutionary process in the larger Northern Island Melanesian region, but there is strong evidence for the process in the rugged interior of the largest island in the region (New Britain). There we found some of the strongest recorded correlations between genetic, linguistic, and geographic distances. We also found that, throughout the region, linguistic features have generally been less likely to diffuse across population boundaries than genes. The results from our study, based on exceptionally fine-grained data, show that local genetic and linguistic exchange are likely to obscure evidence of the early history of a region, and that language barriers do not particularly hinder genetic exchange. In contrast, global patterns may

  11. Genetic and linguistic coevolution in Northern Island Melanesia.

    Directory of Open Access Journals (Sweden)

    Keith Hunley

    2008-10-01

    Full Text Available Recent studies have detailed a remarkable degree of genetic and linguistic diversity in Northern Island Melanesia. Here we utilize that diversity to examine two models of genetic and linguistic coevolution. The first model predicts that genetic and linguistic correspondences formed following population splits and isolation at the time of early range expansions into the region. The second is analogous to the genetic model of isolation by distance, and it predicts that genetic and linguistic correspondences formed through continuing genetic and linguistic exchange between neighboring populations. We tested the predictions of the two models by comparing observed and simulated patterns of genetic variation, genetic and linguistic trees, and matrices of genetic, linguistic, and geographic distances. The data consist of 751 autosomal microsatellites and 108 structural linguistic features collected from 33 Northern Island Melanesian populations. The results of the tests indicate that linguistic and genetic exchange have erased any evidence of a splitting and isolation process that might have occurred early in the settlement history of the region. The correlation patterns are also inconsistent with the predictions of the isolation by distance coevolutionary process in the larger Northern Island Melanesian region, but there is strong evidence for the process in the rugged interior of the largest island in the region (New Britain. There we found some of the strongest recorded correlations between genetic, linguistic, and geographic distances. We also found that, throughout the region, linguistic features have generally been less likely to diffuse across population boundaries than genes. The results from our study, based on exceptionally fine-grained data, show that local genetic and linguistic exchange are likely to obscure evidence of the early history of a region, and that language barriers do not particularly hinder genetic exchange. In contrast

  12. Genetic effects of ionising radiation

    International Nuclear Information System (INIS)

    Saunders, P.

    1981-01-01

    The mutagenic effects of ionising radiation on germ cells with resulting genetic abnormalities in subsequent generations, are considered. Having examined a simple model to explain the interaction of ionising radiation with genetic material and discussed its limitations, the methods whereby mutations are transmitted are discussed. Methods of estimating genetic risks and the results of such studies are examined. (U.K.)

  13. Energy sorghum--a genetic model for the design of C4 grass bioenergy crops.

    Science.gov (United States)

    Mullet, John; Morishige, Daryl; McCormick, Ryan; Truong, Sandra; Hilley, Josie; McKinley, Brian; Anderson, Robert; Olson, Sara N; Rooney, William

    2014-07-01

    Sorghum is emerging as an excellent genetic model for the design of C4 grass bioenergy crops. Annual energy Sorghum hybrids also serve as a source of biomass for bioenergy production. Elucidation of Sorghum's flowering time gene regulatory network, and identification of complementary alleles for photoperiod sensitivity, enabled large-scale generation of energy Sorghum hybrids for testing and commercial use. Energy Sorghum hybrids with long vegetative growth phases were found to accumulate more than twice as much biomass as grain Sorghum, owing to extended growing seasons, greater light interception, and higher radiation use efficiency. High biomass yield, efficient nitrogen recycling, and preferential accumulation of stem biomass with low nitrogen content contributed to energy Sorghum's elevated nitrogen use efficiency. Sorghum's integrated genetics-genomics-breeding platform, diverse germplasm, and the opportunity for annual testing of new genetic designs in controlled environments and in multiple field locations is aiding fundamental discovery, and accelerating the improvement of biomass yield and optimization of composition for biofuels production. Recent advances in wide hybridization between Sorghum and other C4 grasses could allow the deployment of improved genetic designs of annual energy Sorghums in the form of wide-hybrid perennial crops. The current trajectory of energy Sorghum genetic improvement indicates that it will be possible to sustainably produce biofuels from C4 grass bioenergy crops that are cost competitive with petroleum-based transportation fuels. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  14. Genetic design of pigs as experimental models in the combat between chronic diseases and healthy aging

    DEFF Research Database (Denmark)

    Bolund, Lars

    2012-01-01

    with and without intervention. The genome of different pig breeds have been sequenced, revealing that the pig is genetically more similar to man than conventional laboratory animals - in agreement with the similarities in organ development, physiology and metabolism. Genetically designed minipigs (Göttingen...... pigs. We can also produce clones of pigs, some disease prone and some fluorescing, to perform experiments in regenerative medicine where the fate of healthy fluorescent cells can be followed in the, basically identical, disease prone animals. It is also our hope that our pig models can contribute...

  15. Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics

    Science.gov (United States)

    Welch, Stephen M.; White, Jeffrey W.; Thorp, Kelly R.; Bello, Nora M.

    2018-01-01

    Ecophysiological crop models encode intra-species behaviors using parameters that are presumed to summarize genotypic properties of individual lines or cultivars. These genotype-specific parameters (GSP’s) can be interpreted as quantitative traits that can be mapped or otherwise analyzed, as are more conventional traits. The goal of this study was to investigate the estimation of parameters controlling maize anthesis date with the CERES-Maize model, based on 5,266 maize lines from 11 plantings at locations across the eastern United States. High performance computing was used to develop a database of 356 million simulated anthesis dates in response to four CERES-Maize model parameters. Although the resulting estimates showed high predictive value (R2 = 0.94), three issues presented serious challenges for use of GSP’s as traits. First (expressivity), the model was unable to express the observed data for 168 to 3,339 lines (depending on the combination of site-years), many of which ended up sharing the same parameter value irrespective of genetics. Second, for 2,254 lines, the model reproduced the data, but multiple parameter sets were equally effective (equifinality). Third, parameter values were highly dependent (p<10−6919) on the sets of environments used to estimate them (instability), calling in to question the assumption that they represent fundamental genetic traits. The issues of expressivity, equifinality and instability must be addressed before the genetic mapping of GSP’s becomes a robust means to help solve the genotype-to-phenotype problem in crops. PMID:29672629

  16. Mathematical modeling of continuous ethanol fermentation in a membrane bioreactor by pervaporation compared to conventional system: Genetic algorithm.

    Science.gov (United States)

    Esfahanian, Mehri; Shokuhi Rad, Ali; Khoshhal, Saeed; Najafpour, Ghasem; Asghari, Behnam

    2016-07-01

    In this paper, genetic algorithm was used to investigate mathematical modeling of ethanol fermentation in a continuous conventional bioreactor (CCBR) and a continuous membrane bioreactor (CMBR) by ethanol permselective polydimethylsiloxane (PDMS) membrane. A lab scale CMBR with medium glucose concentration of 100gL(-1) and Saccharomyces cerevisiae microorganism was designed and fabricated. At dilution rate of 0.14h(-1), maximum specific cell growth rate and productivity of 0.27h(-1) and 6.49gL(-1)h(-1) were respectively found in CMBR. However, at very high dilution rate, the performance of CMBR was quite similar to conventional fermentation on account of insufficient incubation time. In both systems, genetic algorithm modeling of cell growth, ethanol production and glucose concentration were conducted based on Monod and Moser kinetic models during each retention time at unsteady condition. The results showed that Moser kinetic model was more satisfactory and desirable than Monod model. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Comparison between a sire model and an animal model for genetic evaluation of fertility traits in Danish Holstein population

    DEFF Research Database (Denmark)

    Sun, C; Madsen, P; Nielsen, U S

    2009-01-01

    Comparisons between a sire model, a sire-dam model, and an animal model were carried out to evaluate the ability of the models to predict breeding values of fertility traits, based on data including 471,742 records from the first lactation of Danish Holstein cows, covering insemination years from...... the results suggest that the animal model, rather than the sire model, should be used for genetic evaluation of fertility traits......Comparisons between a sire model, a sire-dam model, and an animal model were carried out to evaluate the ability of the models to predict breeding values of fertility traits, based on data including 471,742 records from the first lactation of Danish Holstein cows, covering insemination years from...... 1995 to 2004. The traits in the analysis were days from calving to first insemination, calving interval, days open, days from first to last insemination, number of inseminations per conception, and nonreturn rate within 56 d after first service. The correlations between sire estimated breeding value...

  18. [Genetics of congenital heart diseases].

    Science.gov (United States)

    Bonnet, Damien

    2017-06-01

    Developmental genetics of congenital heart diseases has evolved from analysis of serial slices in embryos towards molecular genetics of cardiac morphogenesis with a dynamic view of cardiac development. Genetics of congenital heart diseases has also changed from formal genetic analysis of familial recurrences or population-based analysis to screening for mutations in candidates genes identified in animal models. Close cooperation between molecular embryologists, pathologists involved in heart development and pediatric cardiologists is crucial for further increase of knowledge in the field of cardiac morphogenesis and genetics of cardiac defects. The genetic model for congenital heart disease has to be revised to favor a polygenic origin rather than a monogenic one. The main mechanism is altered genic dosage that can account for heart diseases in chromosomal anomalies as well as in point mutations in syndromic and isolated congenital heart diseases. The use of big data grouping information from cardiac development, interactions between genes and proteins, epigenetic factors such as chromatin remodeling or DNA methylation is the current source for improving our knowledge in the field and to give clues for future therapies. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  19. A new cell culture model to genetically dissect the complete human papillomavirus life cycle.

    Science.gov (United States)

    Bienkowska-Haba, Malgorzata; Luszczek, Wioleta; Myers, Julia E; Keiffer, Timothy R; DiGiuseppe, Stephen; Polk, Paula; Bodily, Jason M; Scott, Rona S; Sapp, Martin

    2018-03-01

    Herein, we describe a novel infection model that achieves highly efficient infection of primary keratinocytes with human papillomavirus type 16 (HPV16). This cell culture model does not depend on immortalization and is amenable to extensive genetic analyses. In monolayer cell culture, the early but not late promoter was active and yielded a spliced viral transcript pattern similar to HPV16-immortalized keratinocytes. However, relative levels of the E8^E2 transcript increased over time post infection suggesting the expression of this viral repressor is regulated independently of other early proteins and that it may be important for the shift from the establishment to the maintenance phase of the viral life cycle. Both the early and the late promoter were strongly activated when infected cells were subjected to differentiation by growth in methylcellulose. When grown as organotypic raft cultures, HPV16-infected cells expressed late E1^E4 and L1 proteins and replication foci were detected, suggesting that they supported the completion of the viral life cycle. As a proof of principle that the infection system may be used for genetic dissection of viral factors, we analyzed E1, E6 and E7 translation termination linker mutant virus for establishment of infection and genome maintenance. E1 but not E6 and E7 was essential to establish infection. Furthermore, E6 but not E7 was required for episomal genome maintenance. Primary keratinocytes infected with wild type HPV16 immortalized, whereas keratinocytes infected with E6 and E7 knockout virus began to senesce 25 to 35 days post infection. The novel infection model provides a powerful genetic tool to study the role of viral proteins throughout the viral life cycle but especially for immediate early events and enables us to compare low- and high-risk HPV types in the context of infection.

  20. A new cell culture model to genetically dissect the complete human papillomavirus life cycle.

    Directory of Open Access Journals (Sweden)

    Malgorzata Bienkowska-Haba

    2018-03-01

    Full Text Available Herein, we describe a novel infection model that achieves highly efficient infection of primary keratinocytes with human papillomavirus type 16 (HPV16. This cell culture model does not depend on immortalization and is amenable to extensive genetic analyses. In monolayer cell culture, the early but not late promoter was active and yielded a spliced viral transcript pattern similar to HPV16-immortalized keratinocytes. However, relative levels of the E8^E2 transcript increased over time post infection suggesting the expression of this viral repressor is regulated independently of other early proteins and that it may be important for the shift from the establishment to the maintenance phase of the viral life cycle. Both the early and the late promoter were strongly activated when infected cells were subjected to differentiation by growth in methylcellulose. When grown as organotypic raft cultures, HPV16-infected cells expressed late E1^E4 and L1 proteins and replication foci were detected, suggesting that they supported the completion of the viral life cycle. As a proof of principle that the infection system may be used for genetic dissection of viral factors, we analyzed E1, E6 and E7 translation termination linker mutant virus for establishment of infection and genome maintenance. E1 but not E6 and E7 was essential to establish infection. Furthermore, E6 but not E7 was required for episomal genome maintenance. Primary keratinocytes infected with wild type HPV16 immortalized, whereas keratinocytes infected with E6 and E7 knockout virus began to senesce 25 to 35 days post infection. The novel infection model provides a powerful genetic tool to study the role of viral proteins throughout the viral life cycle but especially for immediate early events and enables us to compare low- and high-risk HPV types in the context of infection.

  1. The genetic architecture of fitness in a seed beetle: assessing the potential for indirect genetic benefits of female choice

    Directory of Open Access Journals (Sweden)

    Maklakov AA

    2008-10-01

    Full Text Available Abstract Background Quantifying the amount of standing genetic variation in fitness represents an empirical challenge. Unfortunately, the shortage of detailed studies of the genetic architecture of fitness has hampered progress in several domains of evolutionary biology. One such area is the study of sexual selection. In particular, the evolution of adaptive female choice by indirect genetic benefits relies on the presence of genetic variation for fitness. Female choice by genetic benefits fall broadly into good genes (additive models and compatibility (non-additive models where the strength of selection is dictated by the genetic architecture of fitness. To characterize the genetic architecture of fitness, we employed a quantitative genetic design (the diallel cross in a population of the seed beetle Callosobruchus maculatus, which is known to exhibit post-copulatory female choice. From reciprocal crosses of inbred lines, we assayed egg production, egg-to-adult survival, and lifetime offspring production of the outbred F1 daughters (F1 productivity. Results We used the bio model to estimate six components of genetic and environmental variance in fitness. We found sizeable additive and non-additive genetic variance in F1 productivity, but lower genetic variance in egg-to-adult survival, which was strongly influenced by maternal and paternal effects. Conclusion Our results show that, in order to gain a relevant understanding of the genetic architecture of fitness, measures of offspring fitness should be inclusive and should include quantifications of offspring reproductive success. We note that our estimate of additive genetic variance in F1 productivity (CVA = 14% is sufficient to generate indirect selection on female choice. However, our results also show that the major determinant of offspring fitness is the genetic interaction between parental genomes, as indicated by large amounts of non-additive genetic variance (dominance and/or epistasis

  2. Genetic algorithms and supernovae type Ia analysis

    International Nuclear Information System (INIS)

    Bogdanos, Charalampos; Nesseris, Savvas

    2009-01-01

    We introduce genetic algorithms as a means to analyze supernovae type Ia data and extract model-independent constraints on the evolution of the Dark Energy equation of state w(z) ≡ P DE /ρ DE . Specifically, we will give a brief introduction to the genetic algorithms along with some simple examples to illustrate their advantages and finally we will apply them to the supernovae type Ia data. We find that genetic algorithms can lead to results in line with already established parametric and non-parametric reconstruction methods and could be used as a complementary way of treating SNIa data. As a non-parametric method, genetic algorithms provide a model-independent way to analyze data and can minimize bias due to premature choice of a dark energy model

  3. Sex-specific genetic effects in physical activity: results from a quantitative genetic analysis.

    Science.gov (United States)

    Diego, Vincent P; de Chaves, Raquel Nichele; Blangero, John; de Souza, Michele Caroline; Santos, Daniel; Gomes, Thayse Natacha; dos Santos, Fernanda Karina; Garganta, Rui; Katzmarzyk, Peter T; Maia, José A R

    2015-08-01

    The objective of this study is to present a model to estimate sex-specific genetic effects on physical activity (PA) levels and sedentary behaviour (SB) using three generation families. The sample consisted of 100 families covering three generations from Portugal. PA and SB were assessed via the International Physical Activity Questionnaire short form (IPAQ-SF). Sex-specific effects were assessed by genotype-by-sex interaction (GSI) models and sex-specific heritabilities. GSI effects and heterogeneity were tested in the residual environmental variance. SPSS 17 and SOLAR v. 4.1 were used in all computations. The genetic component for PA and SB domains varied from low to moderate (11% to 46%), when analyzing both genders combined. We found GSI effects for vigorous PA (p = 0.02) and time spent watching television (WT) (p < 0.001) that showed significantly higher additive genetic variance estimates in males. The heterogeneity in the residual environmental variance was significant for moderate PA (p = 0.02), vigorous PA (p = 0.006) and total PA (p = 0.001). Sex-specific heritability estimates were significantly higher in males only for WT, with a male-to-female difference in heritability of 42.5 (95% confidence interval: 6.4, 70.4). Low to moderate genetic effects on PA and SB traits were found. Results from the GSI model show that there are sex-specific effects in two phenotypes, VPA and WT with a stronger genetic influence in males.

  4. Modeling misidentification errors that result from use of genetic tags in capture-recapture studies

    Science.gov (United States)

    Yoshizaki, J.; Brownie, C.; Pollock, K.H.; Link, W.A.

    2011-01-01

    Misidentification of animals is potentially important when naturally existing features (natural tags) such as DNA fingerprints (genetic tags) are used to identify individual animals. For example, when misidentification leads to multiple identities being assigned to an animal, traditional estimators tend to overestimate population size. Accounting for misidentification in capture-recapture models requires detailed understanding of the mechanism. Using genetic tags as an example, we outline a framework for modeling the effect of misidentification in closed population studies when individual identification is based on natural tags that are consistent over time (non-evolving natural tags). We first assume a single sample is obtained per animal for each capture event, and then generalize to the case where multiple samples (such as hair or scat samples) are collected per animal per capture occasion. We introduce methods for estimating population size and, using a simulation study, we show that our new estimators perform well for cases with moderately high capture probabilities or high misidentification rates. In contrast, conventional estimators can seriously overestimate population size when errors due to misidentification are ignored. ?? 2009 Springer Science+Business Media, LLC.

  5. Estimating genetic effect sizes under joint disease-endophenotype models in presence of gene-environment interactions

    Directory of Open Access Journals (Sweden)

    Alexandre eBureau

    2015-07-01

    Full Text Available Effects of genetic variants on the risk of complex diseases estimated from association studies are typically small. Nonetheless, variants may have important effects in presence of specific levels of environmental exposures, and when a trait related to the disease (endophenotype is either normal or impaired. We propose polytomous and transition models to represent the relationship between disease, endophenotype, genotype and environmental exposure in family studies. Model coefficients were estimated using generalized estimating equations and were used to derive gene-environment interaction effects and genotype effects at specific levels of exposure. In a simulation study, estimates of the effect of a genetic variant were substantially higher when both an endophenotype and an environmental exposure modifying the variant effect were taken into account, particularly under transition models, compared to the alternative of ignoring the endophenotype. Illustration of the proposed modeling with the metabolic syndrome, abdominal obesity, physical activity and polymorphisms in the NOX3 gene in the Quebec Family Study revealed that the positive association of the A allele of rs1375713 with the metabolic syndrome at high levels of physical activity was only detectable in subjects without abdominal obesity, illustrating the importance of taking into account the abdominal obesity endophenotype in this analysis.

  6. Le premier partenariat public-privé pour l’irrigation au Maroc : durable pour tous ?

    Directory of Open Access Journals (Sweden)

    Houdret Annabelle

    2016-03-01

    Full Text Available Les partenariats public-privé (PPP sont un phénomène relativement récent dans le secteur de l’irrigation ; le projet El Guerdane au Maroc est ainsi le premier de son genre. Inauguré en 2008, le projet alimente en eau 10 000 ha de plantations d’agrumes. Les banques internationales de développement le présentent comme un succès, mais l’impact sur le développement local est, au mieux, mitigé. Alors que certains agriculteurs ont bénéficié de cette initiative, d’autres ont été marginalisés, en termes d’accès à l’eau, aux terres fertiles et au développement. Fondé sur des recherches de terrain extensives conduites entre 2005 et 2013, l’article révèle trois problèmes cruciaux du projet PPP : des effets souvent négatifs sur les revenus des acteurs et sur le développement ; un partage inégal des coûts, des bénéfices et des risques entre les secteurs public et privé ; un impact environnemental incertain. Sur la base de ces résultats, l’étude situe le projet dans le contexte plus large de l’évolution des rapports de force politico-économiques au Maroc.

  7. Arthropod Genetics.

    Science.gov (United States)

    Zumwalde, Sharon

    2000-01-01

    Introduces an activity on arthropod genetics that involves phenotype and genotype identification of the creature and the construction process. Includes a list of required materials and directions to build a model arthropod. (YDS)

  8. Networking in autism: leveraging genetic, biomarker and model system findings in the search for new treatments.

    Science.gov (United States)

    Veenstra-VanderWeele, Jeremy; Blakely, Randy D

    2012-01-01

    Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder affecting approximately 1% of children. ASD is defined by core symptoms in two domains: negative symptoms of impairment in social and communication function, and positive symptoms of restricted and repetitive behaviors. Available treatments are inadequate for treating both core symptoms and associated conditions. Twin studies indicate that ASD susceptibility has a large heritable component. Genetic studies have identified promising leads, with converging insights emerging from single-gene disorders that bear ASD features, with particular interest in mammalian target of rapamycin (mTOR)-linked synaptic plasticity mechanisms. Mouse models of these disorders are revealing not only opportunities to model behavioral perturbations across species, but also evidence of postnatal rescue of brain and behavioral phenotypes. An intense search for ASD biomarkers has consistently pointed to elevated platelet serotonin (5-HT) levels and a surge in brain growth in the first 2 years of life. Following a review of the diversity of ASD phenotypes and its genetic origins and biomarkers, we discuss opportunities for translation of these findings into novel ASD treatments, focusing on mTor- and 5-HT-signaling pathways, and their possible intersection. Paralleling the progress made in understanding the root causes of rare genetic syndromes that affect cognitive development, we anticipate progress in models systems using bona fide ASD-associated molecular changes that have the potential to accelerate the development of ASD diagnostics and therapeutics.

  9. Hybrid Modeling KMeans – Genetic Algorithms in the Health Care Data

    Directory of Open Access Journals (Sweden)

    Tessy Badriyah

    2013-06-01

    Full Text Available K-Means is one of the major algorithms widely used in clustering due to its good computational performance. However, K-Means is very sensitive to the initially selected points which randomly selected, and therefore it does not always generate optimum solutions. Genetic algorithm approach can be applied to solve this problem. In this research we examine the potential of applying hybrid GA- KMeans with focus on the area of health care data. We proposed a new technique using hybrid method combining KMeans Clustering and Genetic Algorithms, called the “Hybrid K-Means Genetic Algorithms” (HKGA. HKGA combines the power of Genetic Algorithms and the efficiency of K-Means Clustering. We compare our results with other conventional algorithms and also with other published research as well. Our results demonstrate that the HKGA achieves very good results and in some cases superior to other methods. Keywords: Machine Learning, K-Means, Genetic Algorithms, Hybrid KMeans Genetic Algorithm (HGKA.

  10. Mixing Energy Models in Genetic Algorithms for On-Lattice Protein Structure Prediction

    Directory of Open Access Journals (Sweden)

    Mahmood A. Rashid

    2013-01-01

    Full Text Available Protein structure prediction (PSP is computationally a very challenging problem. The challenge largely comes from the fact that the energy function that needs to be minimised in order to obtain the native structure of a given protein is not clearly known. A high resolution 20×20 energy model could better capture the behaviour of the actual energy function than a low resolution energy model such as hydrophobic polar. However, the fine grained details of the high resolution interaction energy matrix are often not very informative for guiding the search. In contrast, a low resolution energy model could effectively bias the search towards certain promising directions. In this paper, we develop a genetic algorithm that mainly uses a high resolution energy model for protein structure evaluation but uses a low resolution HP energy model in focussing the search towards exploring structures that have hydrophobic cores. We experimentally show that this mixing of energy models leads to significant lower energy structures compared to the state-of-the-art results.

  11. A Drosophila model for toxicogenomics: Genetic variation in susceptibility to heavy metal exposure.

    Directory of Open Access Journals (Sweden)

    Shanshan Zhou

    2017-07-01

    Full Text Available The genetic factors that give rise to variation in susceptibility to environmental toxins remain largely unexplored. Studies on genetic variation in susceptibility to environmental toxins are challenging in human populations, due to the variety of clinical symptoms and difficulty in determining which symptoms causally result from toxic exposure; uncontrolled environments, often with exposure to multiple toxicants; and difficulty in relating phenotypic effect size to toxic dose, especially when symptoms become manifest with a substantial time lag. Drosophila melanogaster is a powerful model that enables genome-wide studies for the identification of allelic variants that contribute to variation in susceptibility to environmental toxins, since the genetic background, environmental rearing conditions and toxic exposure can be precisely controlled. Here, we used extreme QTL mapping in an outbred population derived from the D. melanogaster Genetic Reference Panel to identify alleles associated with resistance to lead and/or cadmium, two ubiquitous environmental toxins that present serious health risks. We identified single nucleotide polymorphisms (SNPs associated with variation in resistance to both heavy metals as well as SNPs associated with resistance specific to each of them. The effects of these SNPs were largely sex-specific. We applied mutational and RNAi analyses to 33 candidate genes and functionally validated 28 of them. We constructed networks of candidate genes as blueprints for orthologous networks of human genes. The latter not only provided functional contexts for known human targets of heavy metal toxicity, but also implicated novel candidate susceptibility genes. These studies validate Drosophila as a translational toxicogenomics gene discovery system.

  12. The use of genetic algorithms to model protoplanetary discs

    Science.gov (United States)

    Hetem, Annibal; Gregorio-Hetem, Jane

    2007-12-01

    The protoplanetary discs of T Tauri and Herbig Ae/Be stars have previously been studied using geometric disc models to fit their spectral energy distribution (SED). The simulations provide a means to reproduce the signatures of various circumstellar structures, which are related to different levels of infrared excess. With the aim of improving our previous model, which assumed a simple flat-disc configuration, we adopt here a reprocessing flared-disc model that assumes hydrostatic, radiative equilibrium. We have developed a method to optimize the parameter estimation based on genetic algorithms (GAs). This paper describes the implementation of the new code, which has been applied to Herbig stars from the Pico dos Dias Survey catalogue, in order to illustrate the quality of the fitting for a variety of SED shapes. The star AB Aur was used as a test of the GA parameter estimation, and demonstrates that the new code reproduces successfully a canonical example of the flared-disc model. The GA method gives a good quality of fit, but the range of input parameters must be chosen with caution, as unrealistic disc parameters can be derived. It is confirmed that the flared-disc model fits the flattened SEDs typical of Herbig stars; however, embedded objects (increasing SED slope) and debris discs (steeply decreasing SED slope) are not well fitted with this configuration. Even considering the limitation of the derived parameters, the automatic process of SED fitting provides an interesting tool for the statistical analysis of the circumstellar luminosity of large samples of young stars.

  13. Comparison on models for genetic evaluation of non-return rate and success in first insemination of the Danish Holstein cow

    DEFF Research Database (Denmark)

    Sun, C; Su, G

    2010-01-01

    The aim of is study was to compare a linear Gaussian model with logit model and probit model for genetic evaluation of non-return rate within 56 d after first-insemination (NRR56) and success in first insemination (SFI). The whole dataset used in the analysis contained 471,742 records from...... the EBV of proven bulls, obtained from the whole dataset and from a reduced dataset which only contains the first-crop daughters of sires; 2) χ2 statistic for the expected and observed frequency in a cross validation. Heritabilities estimated using linear, probit and logit models were 0.011, 0.014 and 0....... Model validation showed that there was no difference between probit model and logit model, but the two models were better than linear model in stability and predictive ability for genetic evaluation of NRR56 and SFI. However, based on the whole dataset, the correlations between EBV estimated using...

  14. Histidine decarboxylase knockout mice, a genetic model of Tourette syndrome, show repetitive grooming after induced fear.

    Science.gov (United States)

    Xu, Meiyu; Li, Lina; Ohtsu, Hiroshi; Pittenger, Christopher

    2015-05-19

    Tics, such as are seen in Tourette syndrome (TS), are common and can cause profound morbidity, but they are poorly understood. Tics are potentiated by psychostimulants, stress, and sleep deprivation. Mutations in the gene histidine decarboxylase (Hdc) have been implicated as a rare genetic cause of TS, and Hdc knockout mice have been validated as a genetic model that recapitulates phenomenological and pathophysiological aspects of the disorder. Tic-like stereotypies in this model have not been observed at baseline but emerge after acute challenge with the psychostimulant d-amphetamine. We tested the ability of an acute stressor to stimulate stereotypies in this model, using tone fear conditioning. Hdc knockout mice acquired conditioned fear normally, as manifested by freezing during the presentation of a tone 48h after it had been paired with a shock. During the 30min following tone presentation, knockout mice showed increased grooming. Heterozygotes exhibited normal freezing and intermediate grooming. These data validate a new paradigm for the examination of tic-like stereotypies in animals without pharmacological challenge and enhance the face validity of the Hdc knockout mouse as a pathophysiologically grounded model of tic disorders. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. Quantitative genetic models of sexual selection by male choice.

    Science.gov (United States)

    Nakahashi, Wataru

    2008-09-01

    There are many examples of male mate choice for female traits that tend to be associated with high fertility. I develop quantitative genetic models of a female trait and a male preference to show when such a male preference can evolve. I find that a disagreement between the fertility maximum and the viability maximum of the female trait is necessary for directional male preference (preference for extreme female trait values) to evolve. Moreover, when there is a shortage of available male partners or variance in male nongenetic quality, strong male preference can evolve. Furthermore, I also show that males evolve to exhibit a stronger preference for females that are more feminine (less resemblance to males) than the average female when there is a sexual dimorphism caused by fertility selection which acts only on females.

  16. Consumer attitudes and decision-making with regard to genetically engineered food products: A review of the literature and a presentation of models for future research

    DEFF Research Database (Denmark)

    Bredahl, Lone; Grunert, Klaus G.; Frewer, Lynn

    Executive summary 1. Few studies have to date explained consumer attitudes and purchase decisions with regard to genetically engineered food products. However, the increased marketing of genetically engineered food products and the considerable concern that consumers seem to express with regard t...... Likelihood Model and Social Judgment Theory. The model specifically takes into account the impact of credibility and various informational factors, such as persuasive content of the information provided, on attitudes.......Executive summary 1. Few studies have to date explained consumer attitudes and purchase decisions with regard to genetically engineered food products. However, the increased marketing of genetically engineered food products and the considerable concern that consumers seem to express with regard...... engineering in food production in general as additional determinants of behavioural intentions. 5. How consumers' attitudes towards genetically engineered food products are affected by various information strategies is explained in an attitude change model, which integrates aspects of the Elaboration...

  17. Consumer attitudes and decision-making with regard to genetically engineered food products: A review of the literature and a presentation of models for future research

    DEFF Research Database (Denmark)

    Bredahl, Lone; Grunert, Klaus G.; Frewer, Lynn

    1998-01-01

    Executive summary 1. Few studies have to date explained consumer attitudes and purchase decisions with regard to genetically engineered food products. However, the increased marketing of genetically engineered food products and the considerable concern that consumers seem to express with regard t...... Likelihood Model and Social Judgment Theory. The model specifically takes into account the impact of credibility and various informational factors, such as persuasive content of the information provided, on attitudes.......Executive summary 1. Few studies have to date explained consumer attitudes and purchase decisions with regard to genetically engineered food products. However, the increased marketing of genetically engineered food products and the considerable concern that consumers seem to express with regard...... engineering in food production in general as additional determinants of behavioural intentions. 5. How consumers' attitudes towards genetically engineered food products are affected by various information strategies is explained in an attitude change model, which integrates aspects of the Elaboration...

  18. Variable selection in Logistic regression model with genetic algorithm.

    Science.gov (United States)

    Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

    2018-02-01

    Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

  19. Generating Improved Experimental Designs with Spatially and Genetically Correlated Observations Using Mixed Models

    Directory of Open Access Journals (Sweden)

    Lazarus K. Mramba

    2018-03-01

    Full Text Available The aim of this study was to generate and evaluate the efficiency of improved field experiments while simultaneously accounting for spatial correlations and different levels of genetic relatedness using a mixed models framework for orthogonal and non-orthogonal designs. Optimality criteria and a search algorithm were implemented to generate randomized complete block (RCB, incomplete block (IB, augmented block (AB and unequally replicated (UR designs. Several conditions were evaluated including size of the experiment, levels of heritability, and optimality criteria. For RCB designs with half-sib or full-sib families, the optimization procedure yielded important improvements under the presence of mild to strong spatial correlation levels and relatively low heritability values. Also, for these designs, improvements in terms of overall design efficiency (ODE% reached values of up to 8.7%, but these gains varied depending on the evaluated conditions. In general, for all evaluated designs, higher ODE% values were achieved from genetically unrelated individuals compared to experiments with half-sib and full-sib families. As expected, accuracy of prediction of genetic values improved as levels of heritability and spatial correlations increased. This study has demonstrated that important improvements in design efficiency and prediction accuracies can be achieved by optimizing how the levels of a treatment are assigned to the experimental units.

  20. From animal models to human disease: a genetic approach for personalized medicine in ALS.

    Science.gov (United States)

    Picher-Martel, Vincent; Valdmanis, Paul N; Gould, Peter V; Julien, Jean-Pierre; Dupré, Nicolas

    2016-07-11

    Amyotrophic Lateral Sclerosis (ALS) is the most frequent motor neuron disease in adults. Classical ALS is characterized by the death of upper and lower motor neurons leading to progressive paralysis. Approximately 10 % of ALS patients have familial form of the disease. Numerous different gene mutations have been found in familial cases of ALS, such as mutations in superoxide dismutase 1 (SOD1), TAR DNA-binding protein 43 (TDP-43), fused in sarcoma (FUS), C9ORF72, ubiquilin-2 (UBQLN2), optineurin (OPTN) and others. Multiple animal models were generated to mimic the disease and to test future treatments. However, no animal model fully replicates the spectrum of phenotypes in the human disease and it is difficult to assess how a therapeutic effect in disease models can predict efficacy in humans. Importantly, the genetic and phenotypic heterogeneity of ALS leads to a variety of responses to similar treatment regimens. From this has emerged the concept of personalized medicine (PM), which is a medical scheme that combines study of genetic, environmental and clinical diagnostic testing, including biomarkers, to individualized patient care. In this perspective, we used subgroups of specific ALS-linked gene mutations to go through existing animal models and to provide a comprehensive profile of the differences and similarities between animal models of disease and human disease. Finally, we reviewed application of biomarkers and gene therapies relevant in personalized medicine approach. For instance, this includes viral delivering of antisense oligonucleotide and small interfering RNA in SOD1, TDP-43 and C9orf72 mice models. Promising gene therapies raised possibilities for treating differently the major mutations in familial ALS cases.

  1. Genetic parameters of calving ease using sire-maternal grandsire model in Korean Holsteins

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    Mahboob Alam

    2017-09-01

    Full Text Available Objective Calving ease (CE is a complex reproductive trait of economic importance in dairy cattle. This study was aimed to investigate the genetic merits of CE for Holsteins in Korea. Methods A total of 297,614 field records of CE, from 2000 to 2015, from first parity Holstein heifers were recorded initially. After necessary data pruning such as age at first calving (18 to 42 mo, gestation length, and presence of sire information, final datasets for CE consisted of 147,526 and 132,080 records for service sire calving ease (SCE and daughter calving ease (DCE evaluations, respectively. The CE categories were ordered and scores ranged from CE1 to CE5 (CE1, easy; CE2, slight assistance; CE3, moderate assistance; CE4, difficult calving; CE5, extreme difficulty calving. A linear transformation of CE score was obtained on each category using Snell procedure, and a scaling factor was applied to attain the spread between 0 (CE5 and 100% (CE1. A sire-maternal grandsire model analysis was performed using ASREML 3.0 software package. Results The estimated direct heritability (h2 from SCE and DCE evaluations were 0.11±0.01 and 0.08±0.01, respectively. Maternal h2 estimates were 0.05±0.02 and 0.04±0.01 from SCE and DCE approaches, respectively. Estimates of genetic correlations between direct and maternal genetic components were −0.68±0.09 (SCE and −0.71±0.09 (DCE. The average direct genetic effect increased over time, whereas average maternal effect was low and consistent. The estimated direct predicted transmitting ability (PTA was desirable and increasing over time, but the maternal PTA was undesirable and decreasing. Conclusion The evidence on sufficient genetic variances in this study could reflect a possible selection improvement over time regarding ease of calving. It is expected that the estimated genetic parameters could be a valuable resource to formulate sire selection and breeding plans which would be directed towards the reduction of

  2. Genetic controls balancing excitatory and inhibitory synaptogenesis in neurodevelopmental disorder models

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    Cheryl L Gatto

    2010-06-01

    Full Text Available Proper brain function requires stringent balance of excitatory and inhibitory synapse formation during neural circuit assembly. Mutation of genes that normally sculpt and maintain this balance results in severe dysfunction, causing neurodevelopmental disorders including autism, epilepsy and Rett syndrome. Such mutations may result in defective architectural structuring of synaptic connections, molecular assembly of synapses and/or functional synaptogenesis. The affected genes often encode synaptic components directly, but also include regulators that secondarily mediate the synthesis or assembly of synaptic proteins. The prime example is Fragile X syndrome (FXS, the leading heritable cause of both intellectual disability and autism spectrum disorders. FXS results from loss of mRNA-binding FMRP, which regulates synaptic transcript trafficking, stability and translation in activity-dependent synaptogenesis and plasticity mechanisms. Genetic models of FXS exhibit striking excitatory and inhibitory synapse imbalance, associated with impaired cognitive and social interaction behaviors. Downstream of translation control, a number of specific synaptic proteins regulate excitatory versus inhibitory synaptogenesis, independently or combinatorially, and loss of these proteins is also linked to disrupted neurodevelopment. The current effort is to define the cascade of events linking transcription, translation and the role of specific synaptic proteins in the maintenance of excitatory versus inhibitory synapses during neural circuit formation. This focus includes mechanisms that fine-tune excitation and inhibition during the refinement of functional synaptic circuits, and later modulate this balance throughout life. The use of powerful new genetic models has begun to shed light on the mechanistic bases of excitation/inhibition imbalance for a range of neurodevelopmental disease states.

  3. Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

    Science.gov (United States)

    Steiner, Christopher F.

    2012-01-01

    The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934

  4. Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty.

    Science.gov (United States)

    Du, Lei; Liu, Kefei; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L; Han, Junwei; Guo, Lei; Saykin, Andrew J; Shen, Li

    2017-10-25

    Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose [Formula: see text]-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the [Formula: see text]-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce the estimation bias in regression tasks. But using them in SCCA remains largely unexplored. In this paper, we design a unified non-convex SCCA model, based on seven non-convex functions, for unbiased estimation and stable feature selection simultaneously. We also propose an efficient optimization algorithm. The proposed method obtains both higher correlation coefficients and better canonical loading patterns. Specifically, these SCCA methods with non-convex penalties discover a strong association between the APOE e4 rs429358 SNP and the hippocampus region of the brain. They both are Alzheimer's disease related biomarkers, indicating the potential and power of the non-convex methods in brain imaging genetics.

  5. Fischer 344 and Lewis rat strains as a model of genetic vulnerability to drug addiction

    Directory of Open Access Journals (Sweden)

    Cristina eCadoni

    2016-02-01

    Full Text Available Today it is well acknowledged that both nature and nurture play important roles in the genesis of psychopathologies, including drug addiction. Increasing evidence suggests that genetic factors contribute for at least 40-60 % of the variation in liability to drug dependence. Human genetic studies suggest that multiple genes of small effect, rather than single genes, contribute to the genesis of behavioral psychopathologies. Therefore the use of inbred rat strains might provide a valuable tool to identify differences, linked to genotype, important in liability to addiction and related disorders. In this regard, Lewis and Fischer 344 inbred rats have been proposed as a model of genetic vulnerability to drug addiction, given their innate differences in sensitivity to the reinforcing and rewarding effects of drugs of abuse, as well their different responsiveness to stressful stimuli. This review will provide evidence in support of this model for the study of the genetic influence on addiction vulnerability, with particular emphasis to differences in mesolimbic dopamine (DA transmission, rewarding and emotional function. It will be highlighted that Lewis and Fischer 344 rats differ not only in several indices of DA transmission and adaptive changes following repeated drug exposure, but also in hypothalamic-pituitary-adrenal (HPA axis responsiveness, influencing not only the ability of the individual to cope with stressful events, but also interfering with rewarding and motivational processes, given the influence of corticosteroids on dopamine neurons functionality.Further differences between the two strains, as impulsivity or anxiousness, might contribute to their different proneness to addiction, and likely these features might be linked to their different DA neurotransmission plasticity. Although differences in other neurotransmitter systems might deserve further investigations, results from the reviewed studies might open new vistas in

  6. Fischer 344 and Lewis Rat Strains as a Model of Genetic Vulnerability to Drug Addiction.

    Science.gov (United States)

    Cadoni, Cristina

    2016-01-01

    Today it is well acknowledged that both nature and nurture play important roles in the genesis of psychopathologies, including drug addiction. Increasing evidence suggests that genetic factors contribute for at least 40-60% of the variation in liability to drug dependence. Human genetic studies suggest that multiple genes of small effect, rather than single genes, contribute to the genesis of behavioral psychopathologies. Therefore, the use of inbred rat strains might provide a valuable tool to identify differences, linked to genotype, important in liability to addiction and related disorders. In this regard, Lewis and Fischer 344 inbred rats have been proposed as a model of genetic vulnerability to drug addiction, given their innate differences in sensitivity to the reinforcing and rewarding effects of drugs of abuse, as well their different responsiveness to stressful stimuli. This review will provide evidence in support of this model for the study of the genetic influence on addiction vulnerability, with particular emphasis on differences in mesolimbic dopamine (DA) transmission, rewarding and emotional function. It will be highlighted that Lewis and Fischer 344 rats differ not only in several indices of DA transmission and adaptive changes following repeated drug exposure, but also in hypothalamic-pituitary-adrenal (HPA) axis responsiveness, influencing not only the ability of the individual to cope with stressful events, but also interfering with rewarding and motivational processes, given the influence of corticosteroids on dopamine neuron functionality. Further differences between the two strains, as impulsivity or anxiousness, might contribute to their different proneness to addiction, and likely these features might be linked to their different DA neurotransmission plasticity. Although differences in other neurotransmitter systems might deserve further investigation, results from the reviewed studies might open new vistas in understanding aberrant

  7. Assessment of Poisson, logit, and linear models for genetic analysis of clinical mastitis in Norwegian Red cows.

    Science.gov (United States)

    Vazquez, A I; Gianola, D; Bates, D; Weigel, K A; Heringstad, B

    2009-02-01

    Clinical mastitis is typically coded as presence/absence during some period of exposure, and records are analyzed with linear or binary data models. Because presence includes cows with multiple episodes, there is loss of information when a count is treated as a binary response. The Poisson model is designed for counting random variables, and although it is used extensively in epidemiology of mastitis, it has rarely been used for studying the genetics of mastitis. Many models have been proposed for genetic analysis of mastitis, but they have not been formally compared. The main goal of this study was to compare linear (Gaussian), Bernoulli (with logit link), and Poisson models for the purpose of genetic evaluation of sires for mastitis in dairy cattle. The response variables were clinical mastitis (CM; 0, 1) and number of CM cases (NCM; 0, 1, 2, ..). Data consisted of records on 36,178 first-lactation daughters of 245 Norwegian Red sires distributed over 5,286 herds. Predictive ability of models was assessed via a 3-fold cross-validation using mean squared error of prediction (MSEP) as the end-point. Between-sire variance estimates for NCM were 0.065 in Poisson and 0.007 in the linear model. For CM the between-sire variance was 0.093 in logit and 0.003 in the linear model. The ratio between herd and sire variances for the models with NCM response was 4.6 and 3.5 for Poisson and linear, respectively, and for model for CM was 3.7 in both logit and linear models. The MSEP for all cows was similar. However, within healthy animals, MSEP was 0.085 (Poisson), 0.090 (linear for NCM), 0.053 (logit), and 0.056 (linear for CM). For mastitic animals the MSEP values were 1.206 (Poisson), 1.185 (linear for NCM response), 1.333 (logit), and 1.319 (linear for CM response). The models for count variables had a better performance when predicting diseased animals and also had a similar performance between them. Logit and linear models for CM had better predictive ability for healthy

  8. BAD knockout provides metabolic seizure resistance in a genetic model of epilepsy with sudden unexplained death in epilepsy.

    Science.gov (United States)

    Foley, Jeannine; Burnham, Veronica; Tedoldi, Meghan; Danial, Nika N; Yellen, Gary

    2018-01-01

    Metabolic alteration, either through the ketogenic diet (KD) or by genetic alteration of the BAD protein, can produce seizure protection in acute chemoconvulsant models of epilepsy. To assess the seizure-protective role of knocking out (KO) the Bad gene in a chronic epilepsy model, we used the Kcna1 -/- model of epilepsy, which displays progressively increased seizure severity and recapitulates the early death seen in sudden unexplained death in epilepsy (SUDEP). Beginning on postnatal day 24 (P24), we continuously video monitored Kcna1 -/- and Kcna1 -/- Bad -/- double knockout mice to assess survival and seizure severity. We found that Kcna1 -/- Bad -/- mice outlived Kcna1 -/- mice by approximately 2 weeks. Kcna1 -/- Bad -/- mice also spent significantly less time in seizure than Kcna1 -/- mice on P24 and the day of death, showing that BadKO provides seizure resistance in a genetic model of chronic epilepsy. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

  9. On theoretical models of gene expression evolution with random genetic drift and natural selection.

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    Osamu Ogasawara

    2009-11-01

    Full Text Available The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference.In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1 our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2 cytological constraints can be explicitly formulated to describe long-term evolution; (3 the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances.The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.

  10. Information geometry and population genetics the mathematical structure of the Wright-Fisher model

    CERN Document Server

    Hofrichter, Julian; Tran, Tat Dat

    2017-01-01

    The present monograph develops a versatile and profound mathematical perspective of the Wright--Fisher model of population genetics. This well-known and intensively studied model carries a rich and beautiful mathematical structure, which is uncovered here in a systematic manner. In addition to approaches by means of analysis, combinatorics and PDE, a geometric perspective is brought in through Amari's and Chentsov's information geometry. This concept allows us to calculate many quantities of interest systematically; likewise, the employed global perspective elucidates the stratification of the model in an unprecedented manner. Furthermore, the links to statistical mechanics and large deviation theory are explored and developed into powerful tools. Altogether, the manuscript provides a solid and broad working basis for graduate students and researchers interested in this field.

  11. Genetic Dissection of Cardiac Remodeling in an Isoproterenol-Induced Heart Failure Mouse Model.

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    Jessica Jen-Chu Wang

    2016-07-01

    Full Text Available We aimed to understand the genetic control of cardiac remodeling using an isoproterenol-induced heart failure model in mice, which allowed control of confounding factors in an experimental setting. We characterized the changes in cardiac structure and function in response to chronic isoproterenol infusion using echocardiography in a panel of 104 inbred mouse strains. We showed that cardiac structure and function, whether under normal or stress conditions, has a strong genetic component, with heritability estimates of left ventricular mass between 61% and 81%. Association analyses of cardiac remodeling traits, corrected for population structure, body size and heart rate, revealed 17 genome-wide significant loci, including several loci containing previously implicated genes. Cardiac tissue gene expression profiling, expression quantitative trait loci, expression-phenotype correlation, and coding sequence variation analyses were performed to prioritize candidate genes and to generate hypotheses for downstream mechanistic studies. Using this approach, we have validated a novel gene, Myh14, as a negative regulator of ISO-induced left ventricular mass hypertrophy in an in vivo mouse model and demonstrated the up-regulation of immediate early gene Myc, fetal gene Nppb, and fibrosis gene Lgals3 in ISO-treated Myh14 deficient hearts compared to controls.

  12. Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach

    Science.gov (United States)

    Row, Jeff R; Oyler-McCance, Sara J.; Fike, Jennifer; O'Donnell, Michael; Doherty, Kevin E.; Aldridge, Cameron L.; Bowen, Zachary H.; Fedy, Brad C.

    2015-01-01

    Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape

  13. Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery

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    Liqiang Zhang

    2013-01-01

    Full Text Available The parameters of a well predicted model can be used as health characteristics for Lithium-ion battery. This article reports a parallelized parameter identification of the thermal-electrochemical model, which significantly reduces the time consumption of parameter identification. Since the P2D model has the most predictability, it is chosen for further research and expanded to the thermal-electrochemical model by coupling thermal effect and temperature-dependent parameters. Then Genetic Algorithm is used for parameter identification, but it takes too much time because of the long time simulation of model. For this reason, a computer cluster is built by surplus computing resource in our laboratory based on Parallel Computing Toolbox and Distributed Computing Server in MATLAB. The performance of two parallelized methods, namely Single Program Multiple Data (SPMD and parallel FOR loop (PARFOR, is investigated and then the parallelized GA identification is proposed. With this method, model simulations running parallelly and the parameter identification could be speeded up more than a dozen times, and the identification result is batter than that from serial GA. This conclusion is validated by model parameter identification of a real LiFePO4 battery.

  14. Using Workflow Modeling to Identify Areas to Improve Genetic Test Processes in the University of Maryland Translational Pharmacogenomics Project.

    Science.gov (United States)

    Cutting, Elizabeth M; Overby, Casey L; Banchero, Meghan; Pollin, Toni; Kelemen, Mark; Shuldiner, Alan R; Beitelshees, Amber L

    Delivering genetic test results to clinicians is a complex process. It involves many actors and multiple steps, requiring all of these to work together in order to create an optimal course of treatment for the patient. We used information gained from focus groups in order to illustrate the current process of delivering genetic test results to clinicians. We propose a business process model and notation (BPMN) representation of this process for a Translational Pharmacogenomics Project being implemented at the University of Maryland Medical Center, so that personalized medicine program implementers can identify areas to improve genetic testing processes. We found that the current process could be improved to reduce input errors, better inform and notify clinicians about the implications of certain genetic tests, and make results more easily understood. We demonstrate our use of BPMN to improve this important clinical process for CYP2C19 genetic testing in patients undergoing invasive treatment of coronary heart disease.

  15. Modelling biological control with wild-type and genetically modified baculoviruses in the Helicoverpa armigera-cotton system

    NARCIS (Netherlands)

    Sun, X.; Werf, van der W.; Bianchi, F.J.J.A.; Hu, Z.; Vlak, J.M.

    2006-01-01

    A comprehensive model was developed to simulate virus epizootics in a stage structured insect population and analyse scenarios for the biological control of cotton bollworm (CBW), Helicoverpa armigera, in cotton, using wild-type or genetically modified baculoviruses. In simulations on dosage and

  16. Bayesian Modeling for Genetic Anticipation in Presence of Mutational Heterogeneity: A Case Study in Lynch Syndrome

    DEFF Research Database (Denmark)

    Boonstra, Philip S; Mukherjee, Bhramar; Taylor, Jeremy M G

    2011-01-01

    to cause hereditary nonpolyposis colorectal cancer, also called Lynch syndrome (LS). We find evidence for a decrease in AOO between generations in this article. Our model predicts family-level anticipation effects that are potentially useful in genetic counseling clinics for high-risk families....

  17. Structural equation modeling in the genetically informative study of the covariation of intelligence, working memory and planning

    Directory of Open Access Journals (Sweden)

    Voronin I.

    2016-01-01

    Full Text Available Structural equation modelling (SEM has become an important tool in behaviour genetic research. The application of SEM for multivariate twin analysis allows revealing the structure of genetic and environmental factors underlying individual differences in human traits. We outline the framework of twin method and SEM, describe SEM implementation of a multivariate twin model and provide an example of a multivariate twin study. The study included 901 adolescent twin pairs from Russia. We measured general cognitive ability and characteristics of working memory and planning. The individual differences in working memory and planning were explained mostly by person-specific environment. The variability of intelligence is related to genes, family environment, and person specific environment. Moderate and weak associations between intelligence, working memory, and planning were entirely explained by shared environmental effects.

  18. Generic Science Skills Enhancement of Students through Implementation of IDEAL Problem Solving Model on Genetic Information Course

    Science.gov (United States)

    Zirconia, A.; Supriyanti, F. M. T.; Supriatna, A.

    2018-04-01

    This study aims to determine generic science skills enhancement of students through implementation of IDEAL problem-solving model on genetic information course. Method of this research was mixed method, with pretest-posttest nonequivalent control group design. Subjects of this study were chemistry students enrolled in biochemistry course, consisted of 22 students in the experimental class and 19 students in control class. The instrument in this study was essayed involves 6 indicators generic science skills such as indirect observation, causality thinking, logical frame, self-consistent thinking, symbolic language, and developing concept. The results showed that genetic information course using IDEAL problem-solving model have been enhancing generic science skills in low category with of 20,93%. Based on result for each indicator, showed that there are indicators of generic science skills classified in the high category.

  19. Genetic and chemical modifiers of a CUG toxicity model in Drosophila.

    Directory of Open Access Journals (Sweden)

    Amparo Garcia-Lopez

    2008-02-01

    Full Text Available Non-coding CUG repeat expansions interfere with the activity of human Muscleblind-like (MBNL proteins contributing to myotonic dystrophy 1 (DM1. To understand this toxic RNA gain-of-function mechanism we developed a Drosophila model expressing 60 pure and 480 interrupted CUG repeats in the context of a non-translatable RNA. These flies reproduced aspects of the DM1 pathology, most notably nuclear accumulation of CUG transcripts, muscle degeneration, splicing misregulation, and diminished Muscleblind function in vivo. Reduced Muscleblind activity was evident from the sensitivity of CUG-induced phenotypes to a decrease in muscleblind genetic dosage and rescue by MBNL1 expression, and further supported by the co-localization of Muscleblind and CUG repeat RNA in ribonuclear foci. Targeted expression of CUG repeats to the developing eye and brain mushroom bodies was toxic leading to rough eyes and semilethality, respectively. These phenotypes were utilized to identify genetic and chemical modifiers of the CUG-induced toxicity. 15 genetic modifiers of the rough eye phenotype were isolated. These genes identify putative cellular processes unknown to be altered by CUG repeat RNA, and they include mRNA export factor Aly, apoptosis inhibitor Thread, chromatin remodelling factor Nurf-38, and extracellular matrix structural component Viking. Ten chemical compounds suppressed the semilethal phenotype. These compounds significantly improved viability of CUG expressing flies and included non-steroidal anti-inflammatory agents (ketoprofen, muscarinic, cholinergic and histamine receptor inhibitors (orphenadrine, and drugs that can affect sodium and calcium metabolism such as clenbuterol and spironolactone. These findings provide new insights into the DM1 phenotype, and suggest novel candidates for DM1 treatments.

  20. An F2 pig resource population as a model for genetic studies of obesity and obesity-related diseases in humans

    DEFF Research Database (Denmark)

    Kogelman, Lisette; Kadarmideen, Haja; Mark, Thomas

    2013-01-01

    Obesity is a rising worldwide public health problem. Difficulties to precisely measure various obesity traits and the genetic heterogeneity in human have been major impediments to completely disentangle genetic factors causing obesity. The pig is a relevant model for studying human obesity...... and obesity-related (OOR) traits. Using founder breeds divergent with respect to obesity traits we have created an F2 pig resource population (454 pigs), which has been intensively phenotyped for 36 OOR traits. The main rationale for our study is to characterize the genetic architecture of OOR traits in the F...... and genetic variation in the F2 population, respectively. This fulfills the purpose of creating a resource population divergent for OOR traits. Strong genetic correlations were found between weight and lean mass at dual energy x-ray absorptiometry (DXA) scanning (0.56 – 0.97). Weight and conformation also...

  1. A genetic algorithm solution for a nuclear power plant risk-cost maintenance model

    International Nuclear Information System (INIS)

    Tong Jiejuan; Mao Dingyuan; Xue Dazhi

    2004-01-01

    Reliability Centered Maintenance (RCM) is one of the popular maintenance optimization methods according to certain kinds of priorities. Traditional RCM usually analyzes and optimizes the maintenance strategy from the viewpoint of component instead of the whole maintenance program impact. Research presented in this paper is a pilot study using PSA techniques in RCM. How to reflect the effect on component unavailability by the maintenance activities such as surveillance testing and preventive maintenance in PSA model is discussed firstly. Based on the discussion, a maintenance risk-cost model is established for global maintenance optimization in a nuclear power plant, and a genetic algorithm (GA) is applied to solve such a model to get the global optimized maintenance strategy. Finally, the result got from a simple test case based on a risk-cost model consisting of 10 components is presented

  2. Genetic epidemiology of Scheuermann's disease

    DEFF Research Database (Denmark)

    Damborg, Frank; Engell, Vilhelm; Nielsen, Jan

    2011-01-01

    The genetic/environmental etiology of Scheuermann's disease is unclear. We estimated the heritability of the disease using an etiological model adjusted for sex and time of diagnosis, and examined whether the prevalence of Scheuermann's disease was constant over time.......The genetic/environmental etiology of Scheuermann's disease is unclear. We estimated the heritability of the disease using an etiological model adjusted for sex and time of diagnosis, and examined whether the prevalence of Scheuermann's disease was constant over time....

  3. Modelling the Interplay between Lifestyle Factors and Genetic Predisposition on Markers of Type 2 Diabetes Mellitus Risk.

    Science.gov (United States)

    Walker, Celia G; Solis-Trapala, Ivonne; Holzapfel, Christina; Ambrosini, Gina L; Fuller, Nicholas R; Loos, Ruth J F; Hauner, Hans; Caterson, Ian D; Jebb, Susan A

    2015-01-01

    The risk of developing type 2 diabetes mellitus (T2DM) is determined by a complex interplay involving lifestyle factors and genetic predisposition. Despite this, many studies do not consider the relative contributions of this complex array of factors to identify relationships which are important in progression or prevention of complex diseases. We aimed to describe the integrated effect of a number of lifestyle changes (weight, diet and physical activity) in the context of genetic susceptibility, on changes in glycaemic traits in overweight or obese participants following 12-months of a weight management programme. A sample of 353 participants from a behavioural weight management intervention were included in this study. A graphical Markov model was used to describe the impact of the intervention, by dividing the effects into various pathways comprising changes in proportion of dietary saturated fat, physical activity and weight loss, and a genetic predisposition score (T2DM-GPS), on changes in insulin sensitivity (HOMA-IR), insulin secretion (HOMA-B) and short and long term glycaemia (glucose and HbA1c). We demonstrated the use of graphical Markov modelling to identify the importance and interrelationships of a number of possible variables changed as a result of a lifestyle intervention, whilst considering fixed factors such as genetic predisposition, on changes in traits. Paths which led to weight loss and change in dietary saturated fat were important factors in the change of all glycaemic traits, whereas the T2DM-GPS only made a significant direct contribution to changes in HOMA-IR and plasma glucose after considering the effects of lifestyle factors. This analysis shows that modifiable factors relating to body weight, diet, and physical activity are more likely to impact on glycaemic traits than genetic predisposition during a behavioural intervention.

  4. Genetic Analysis of Elevated Mastitis Risk Based on Mastitis Indicator Data

    DEFF Research Database (Denmark)

    Sørensen, Lars Peter; Løvendahl, Peter

    Whole-genome sequences and multiple trait phenotypes from large numbers of individuals will soon be available. Well established statistical modeling approaches enable the genetic analyses of complex trait phenotypes while accounting for a variety of additive and non-additive genetic mechanisms....... These modeling approaches have proven to be highly useful to determine population genetic parameters as well as prediction of genetic risk or value. We present statistical modelling approaches that use prior biological information for evaluating the collective action of sets of genetic variants. We have applied...

  5. Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

    Directory of Open Access Journals (Sweden)

    Ajay Singh

    2016-06-01

    Full Text Available A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM considering different order of Legendre polynomial for the additive genetic effect (4th order and the permanent environmental effect (5th order. Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11 to 0.99 (TD-4 and TD-5. The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.

  6. Developing a Model of Advanced Training to Promote Career Advancement for Certified Genetic Counselors: An Investigation of Expanded Skills, Advanced Training Paths, and Professional Opportunities.

    Science.gov (United States)

    Baty, Bonnie J; Trepanier, Angela; Bennett, Robin L; Davis, Claire; Erby, Lori; Hippman, Catriona; Lerner, Barbara; Matthews, Anne; Myers, Melanie F; Robbins, Carol B; Singletary, Claire N

    2016-08-01

    There are currently multiple paths through which genetic counselors can acquire advanced knowledge and skills. However, outside of continuing education opportunities, there are few formal training programs designed specifically for the advanced training of genetic counselors. In the genetic counseling profession, there is currently considerable debate about the paths that should be available to attain advanced skills, as well as the skills that might be needed for practice in the future. The Association of Genetic Counseling Program Directors (AGCPD) convened a national committee, the Committee on Advanced Training for Certified Genetic Counselors (CATCGC), to investigate varied paths to post-master's training and career development. The committee began its work by developing three related grids that view career advancement from the viewpoints of the skills needed to advance (skills), ways to obtain these skills (paths), and existing genetic counselor positions that offer career change or advancement (positions). Here we describe previous work related to genetic counselor career advancement, the charge of the CATCGC, our preliminary work in developing a model through which to view genetic counselor advanced training and career advancement opportunities, and our next steps in further developing and disseminating the model.

  7. Electron microscopy using the genetically encoded APEX2 tag in cultured mammalian cells

    Science.gov (United States)

    Martell, Jeffrey D; Deerinck, Thomas J; Lam, Stephanie S; Ellisman, Mark H; Ting, Alice Y

    2018-01-01

    Electron microscopy (EM) is the premiere technique for high-resolution imaging of cellular ultrastructure. Unambiguous identification of specific proteins or cellular compartments in electron micrographs, however, remains challenging because of difficulties in delivering electron-dense contrast agents to specific subcellular targets within intact cells. We recently reported enhanced ascorbate peroxidase 2 (APEX2) as a broadly applicable genetic tag that generates EM contrast on a specific protein or subcellular compartment of interest. This protocol provides guidelines for designing and validating APEX2 fusion constructs, along with detailed instructions for cell culture, transfection, fixation, heavy-metal staining, embedding in resin, and EM imaging. Although this protocol focuses on EM in cultured mammalian cells, APEX2 is applicable to many cell types and contexts, including intact tissues and organisms, and is useful for numerous applications beyond EM, including live-cell proteomic mapping. This protocol, which describes procedures for sample preparation from cell monolayers and cell pellets, can be completed in 10 d, including time for APEX2 fusion construct validation, cell growth, and solidification of embedding resins. Notably, the only additional steps required relative to a standard EM sample preparation are cell transfection and a 2- to 45-min staining period with 3,3′-diaminobenzidine (DAB) and hydrogen peroxide (H2O2). PMID:28796234

  8. Genetic Homogenization of Composite Materials

    Directory of Open Access Journals (Sweden)

    P. Tobola

    2009-04-01

    Full Text Available The paper is focused on numerical studies of electromagnetic properties of composite materials used for the construction of small airplanes. Discussions concentrate on the genetic homogenization of composite layers and composite layers with a slot. The homogenization is aimed to reduce CPU-time demands of EMC computational models of electrically large airplanes. First, a methodology of creating a 3-dimensional numerical model of a composite material in CST Microwave Studio is proposed focusing on a sufficient accuracy of the model. Second, a proper implementation of a genetic optimization in Matlab is discussed. Third, an association of the optimization script and a simplified 2-dimensional model of the homogeneous equivalent model in Comsol Multiphysics is proposed considering EMC issues. Results of computations are experimentally verified.

  9. Genetic modification of chondrocytes with insulin-like growth factor-1 enhances cartilage healing in an equine model.

    Science.gov (United States)

    Goodrich, L R; Hidaka, C; Robbins, P D; Evans, C H; Nixon, A J

    2007-05-01

    Gene therapy with insulin-like growth factor-1 (IGF-1) increases matrix production and enhances chondrocyte proliferation and survival in vitro. The purpose of this study was to determine whether arthroscopically-grafted chondrocytes genetically modified by an adenovirus vector encoding equine IGF-1 (AdIGF-1) would have a beneficial effect on cartilage healing in an equine femoropatellar joint model. A total of 16 horses underwent arthroscopic repair of a single 15 mm cartilage defect in each femoropatellar joint. One joint received 2 x 10(7) AdIGF-1 modified chondrocytes and the contralateral joint received 2 x 10(7) naive (unmodified) chondrocytes. Repairs were analysed at four weeks, nine weeks and eight months after surgery. Morphological and histological appearance, IGF-1 and collagen type II gene expression (polymerase chain reaction, in situ hybridisation and immunohistochemistry), collagen type II content (cyanogen bromide and sodium dodecyl sulphate-polyacrylamide gel electrophoresis), proteoglycan content (dimethylmethylene blue assay), and gene expression for collagen type I, matrix metalloproteinase (MMP)-1, MMP-3, MMP-13, aggrecanase-1, tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) and TIMP-3 were evaluated. Genetic modification of chondrocytes significantly increased IGF-1 mRNA and ligand production in repair tissue for up to nine weeks following transplantation. The gross and histological appearance of IGF-1 modified repair tissue was improved over control defects. Gross filling of defects was significantly improved at four weeks, and a more hyaline-like tissue covered the lesions at eight months. Histological outcome at four and nine weeks post-transplantation revealed greater tissue filling of defects transplanted with genetically modified chondrocytes, whereas repair tissue in control defects was thin and irregular and more fibrous. Collagen type II expression in IGF-1 gene-transduced defects was increased 100-fold at four weeks and

  10. Linear reaction norm models for genetic merit prediction of Angus cattle under genotype by environment interaction.

    Science.gov (United States)

    Cardoso, F F; Tempelman, R J

    2012-07-01

    The objectives of this work were to assess alternative linear reaction norm (RN) models for genetic evaluation of Angus cattle in Brazil. That is, we investigated the interaction between genotypes and continuous descriptors of the environmental variation to examine evidence of genotype by environment interaction (G×E) in post-weaning BW gain (PWG) and to compare the environmental sensitivity of national and imported Angus sires. Data were collected by the Brazilian Angus Improvement Program from 1974 to 2005 and consisted of 63,098 records and a pedigree file with 95,896 animals. Six models were implemented using Bayesian inference and compared using the Deviance Information Criterion (DIC). The simplest model was M(1), a traditional animal model, which showed the largest DIC and hence the poorest fit when compared with the 4 alternative RN specifications accounting for G×E. In M(2), a 2-step procedure was implemented using the contemporary group posterior means of M(1) as the environmental gradient, ranging from -92.6 to +265.5 kg. Moreover, the benefits of jointly estimating all parameters in a 1-step approach were demonstrated by M(3). Additionally, we extended M(3) to allow for residual heteroskedasticity using an exponential function (M(4)) and the best fitting (smallest DIC) environmental classification model (M(5)) specification. Finally, M(6) added just heteroskedastic residual variance to M(1). Heritabilities were less at harsh environments and increased with the improvement of production conditions for all RN models. Rank correlations among genetic merit predictions obtained by M(1) and by the best fitting RN models M(3) (homoskedastic) and M(5) (heteroskedastic) at different environmental levels ranged from 0.79 and 0.81, suggesting biological importance of G×E in Brazilian Angus PWG. These results suggest that selection progress could be optimized by adopting environment-specific genetic merit predictions. The PWG environmental sensitivity of

  11. Genetic parameters and genetic trends in the Chinese × European Tiameslan composite pig line. I. Genetic parameters

    Directory of Open Access Journals (Sweden)

    Legault Christian

    2000-01-01

    Full Text Available Abstract Genetic parameters of body weight at 4 (W4 w, 8 (W8 w and 22 (W22 w weeks of age, days from 20 to 100 kg (DT, average backfat thickness at 100 kg (ABT, teat number (TEAT, number of good teats (GTEAT, total number of piglets born (TNB, born alive (NBA and weaned (NW per litter, and birth to weaning survival rate (SURV were estimated in the Chinese × European Tiameslan composite line using restricted maximum likelihood methodology applied to a multiple trait animal model. Performance data from a total of 4 881 males and 4 799 females from 1 341 litters were analysed. Different models were fitted to the data in order to estimate the importance of maternal effects on production traits, as well as genetic correlations between male and female performance. The results showed the existence of significant maternal effects on W4w, W8w and ABT and of variance heterogeneity between sexes for W22w, DT, ABT and GTEAT. Genetic correlations between sexes were 0.79, 0.71 and 0.82, respectively, for W22w, DT and ABT and above 0.90 for the other traits. Heritability estimates were larger than (ABT and TEAT or similar to (other traits average literature values. Some genetic antagonism was evidenced between production traits, particularly W4w, W8w and ABT, and reproductive traits.

  12. Population genetics without intraspecific data

    DEFF Research Database (Denmark)

    Thorne, Jeffrey L; Choi, Sang Chul; Yu, Jiaye

    2007-01-01

    A central goal of computational biology is the prediction of phenotype from DNA and protein sequence data. Recent models of sequence change use in silico prediction systems to incorporate the effects of phenotype on evolutionary rates. These models have been designed for analyzing sequence data...... populations, and parameters of interspecific models should have population genetic interpretations. We show, with two examples, how population genetic interpretations can be assigned to evolutionary models. The first example considers the impact of RNA secondary structure on sequence change, and the second...... reflects the tendency for protein tertiary structure to influence nonsynonymous substitution rates. We argue that statistical fit to data should not be the sole criterion for assessing models of sequence change. A good interspecific model should also yield a clear and biologically plausible population...

  13. Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

    Science.gov (United States)

    Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.

    2017-01-01

    This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

  14. Spatial Impairment and Memory in Genetic Disorders: Insights from Mouse Models

    Directory of Open Access Journals (Sweden)

    Sang Ah Lee

    2017-02-01

    Full Text Available Research across the cognitive and brain sciences has begun to elucidate some of the processes that guide navigation and spatial memory. Boundary geometry and featural landmarks are two distinct classes of environmental cues that have dissociable neural correlates in spatial representation and follow different patterns of learning. Consequently, spatial navigation depends both on the type of cue available and on the type of learning provided. We investigated this interaction between spatial representation and memory by administering two different tasks (working memory, reference memory using two different environmental cues (rectangular geometry, striped landmark in mouse models of human genetic disorders: Prader-Willi syndrome (PWScrm+/p− mice, n = 12 and Beta-catenin mutation (Thr653Lys-substituted mice, n = 12. This exploratory study provides suggestive evidence that these models exhibit different abilities and impairments in navigating by boundary geometry and featural landmarks, depending on the type of memory task administered. We discuss these data in light of the specific deficits in cognitive and brain function in these human syndromes and their animal model counterparts.

  15. Non-human Primate Models for Brain Disorders - Towards Genetic Manipulations via Innovative Technology.

    Science.gov (United States)

    Qiu, Zilong; Li, Xiao

    2017-04-01

    Modeling brain disorders has always been one of the key tasks in neurobiological studies. A wide range of organisms including worms, fruit flies, zebrafish, and rodents have been used for modeling brain disorders. However, whether complicated neurological and psychiatric symptoms can be faithfully mimicked in animals is still debatable. In this review, we discuss key findings using non-human primates to address the neural mechanisms underlying stress and anxiety behaviors, as well as technical advances for establishing genetically-engineered non-human primate models of autism spectrum disorders and other disorders. Considering the close evolutionary connections and similarity of brain structures between non-human primates and humans, together with the rapid progress in genome-editing technology, non-human primates will be indispensable for pathophysiological studies and exploring potential therapeutic methods for treating brain disorders.

  16. CoaSim: A Flexible Environment for Simulating Genetic Data under Coalescent Models

    DEFF Research Database (Denmark)

    Mailund; Schierup, Mikkel Heide; Pedersen, Christian Nørgaard Storm

    2005-01-01

    get insight into these. Results We have created the CoaSim application as a flexible environment for Monte various types of genetic data under equilibrium and non-equilibrium coalescent variety of applications. Interaction with the tool is through the Guile version scripting language. Scheme scripts......Background Coalescent simulations are playing a large role in interpreting large scale intra- polymorphism surveys and for planning and evaluating association studies. Coalescent of data sets under different models can be compared to the actual data to test different evolutionary factors and thus...

  17. Genetic and genomic analysis modeling of germline c-MYC overexpression and cancer susceptibility

    Directory of Open Access Journals (Sweden)

    Nunes Virginia

    2008-01-01

    Full Text Available Abstract Background Germline genetic variation is associated with the differential expression of many human genes. The phenotypic effects of this type of variation may be important when considering susceptibility to common genetic diseases. Three regions at 8q24 have recently been identified to independently confer risk of prostate cancer. Variation at 8q24 has also recently been associated with risk of breast and colorectal cancer. However, none of the risk variants map at or relatively close to known genes, with c-MYC mapping a few hundred kilobases distally. Results This study identifies cis-regulators of germline c-MYC expression in immortalized lymphocytes of HapMap individuals. Quantitative analysis of c-MYC expression in normal prostate tissues suggests an association between overexpression and variants in Region 1 of prostate cancer risk. Somatic c-MYC overexpression correlates with prostate cancer progression and more aggressive tumor forms, which was also a pathological variable associated with Region 1. Expression profiling analysis and modeling of transcriptional regulatory networks predicts a functional association between MYC and the prostate tumor suppressor KLF6. Analysis of MYC/Myc-driven cell transformation and tumorigenesis substantiates a model in which MYC overexpression promotes transformation by down-regulating KLF6. In this model, a feedback loop through E-cadherin down-regulation causes further transactivation of c-MYC. Conclusion This study proposes that variation at putative 8q24 cis-regulator(s of transcription can significantly alter germline c-MYC expression levels and, thus, contribute to prostate cancer susceptibility by down-regulating the prostate tumor suppressor KLF6 gene.

  18. Utility of computer simulations in landscape genetics

    Science.gov (United States)

    Bryan K. Epperson; Brad H. McRae; Kim Scribner; Samuel A. Cushman; Michael S. Rosenberg; Marie-Josee Fortin; Patrick M. A. James; Melanie Murphy; Stephanie Manel; Pierre Legendre; Mark R. T. Dale

    2010-01-01

    Population genetics theory is primarily based on mathematical models in which spatial complexity and temporal variability are largely ignored. In contrast, the field of landscape genetics expressly focuses on how population genetic processes are affected by complex spatial and temporal environmental heterogeneity. It is spatially explicit and relates patterns to...

  19. A Realistic Model under which the Genetic Code is Optimal

    NARCIS (Netherlands)

    Buhrman, H.; van der Gulik, P.T.S.; Klau, G.W.; Schaffner, C.; Speijer, D.; Stougie, L.

    2013-01-01

    The genetic code has a high level of error robustness. Using values of hydrophobicity scales as a proxy for amino acid character, and the mean square measure as a function quantifying error robustness, a value can be obtained for a genetic code which reflects the error robustness of that code. By

  20. Application of random number generators in genetic algorithms to improve rainfall-runoff modelling

    Science.gov (United States)

    Chlumecký, Martin; Buchtele, Josef; Richta, Karel

    2017-10-01

    The efficient calibration of rainfall-runoff models is a difficult issue, even for experienced hydrologists. Therefore, fast and high-quality model calibration is a valuable improvement. This paper describes a novel methodology and software for the optimisation of a rainfall-runoff modelling using a genetic algorithm (GA) with a newly prepared concept of a random number generator (HRNG), which is the core of the optimisation. The GA estimates model parameters using evolutionary principles, which requires a quality number generator. The new HRNG generates random numbers based on hydrological information and it provides better numbers compared to pure software generators. The GA enhances the model calibration very well and the goal is to optimise the calibration of the model with a minimum of user interaction. This article focuses on improving the internal structure of the GA, which is shielded from the user. The results that we obtained indicate that the HRNG provides a stable trend in the output quality of the model, despite various configurations of the GA. In contrast to previous research, the HRNG speeds up the calibration of the model and offers an improvement of rainfall-runoff modelling.

  1. Bayesian inference on genetic merit under uncertain paternity

    Directory of Open Access Journals (Sweden)

    Tempelman Robert J

    2003-09-01

    Full Text Available Abstract A hierarchical animal model was developed for inference on genetic merit of livestock with uncertain paternity. Fully conditional posterior distributions for fixed and genetic effects, variance components, sire assignments and their probabilities are derived to facilitate a Bayesian inference strategy using MCMC methods. We compared this model to a model based on the Henderson average numerator relationship (ANRM in a simulation study with 10 replicated datasets generated for each of two traits. Trait 1 had a medium heritability (h2 for each of direct and maternal genetic effects whereas Trait 2 had a high h2 attributable only to direct effects. The average posterior probabilities inferred on the true sire were between 1 and 10% larger than the corresponding priors (the inverse of the number of candidate sires in a mating pasture for Trait 1 and between 4 and 13% larger than the corresponding priors for Trait 2. The predicted additive and maternal genetic effects were very similar using both models; however, model choice criteria (Pseudo Bayes Factor and Deviance Information Criterion decisively favored the proposed hierarchical model over the ANRM model.

  2. Compensatory mechanisms in genetic models of neurodegeneration: are the mice better than humans?

    Directory of Open Access Journals (Sweden)

    Grzegorz eKreiner

    2015-03-01

    Full Text Available Neurodegenerative diseases are one of the main causes of mental and physical disabilities. Neurodegeneration has been estimated to begin many years before the first clinical symptoms manifest, and even a prompt diagnosis at this stage provides very little advantage for a more effective treatment as the currently available pharmacotherapies are based on disease symptomatology. The etiology of the majority of neurodegenerative diseases remains unknown, and even for those diseases caused by identified genetic mutations, the direct pathways from gene alteration to final cell death have not yet been fully elucidated. Advancements in genetic engineering have provided many transgenic mice that are used as an alternative to pharmacological models of neurodegenerative diseases. Surprisingly, even the models reiterating the same causative mutations do not fully recapitulate the inevitable neuronal loss, and some fail to even show phenotypic alterations, which suggests the possible existence of compensatory mechanisms. A better evaluation of these mechanisms may not only help us to explain why neurodegenerative diseases are mostly late-onset disorders in humans but may also provide new markers and targets for novel strategies designed to extend neuronal function and survival. The aim of this mini-review is to draw attention to this under-explored field in which investigations may reasonably contribute to unveiling hidden reserves in the organism.

  3. Genetic Rodent Models of Obesity-Associated Ovarian Dysfunction and Subfertility: Insights into Polycystic Ovary Syndrome

    Science.gov (United States)

    Huang-Doran, Isabel; Franks, Stephen

    2016-01-01

    Polycystic ovary syndrome (PCOS) is the most common endocrinopathy affecting women and a leading cause of female infertility worldwide. Defined clinically by the presence of hyperandrogenemia and oligomenorrhoea, PCOS represents a state of hormonal dysregulation, disrupted ovarian follicle dynamics, and subsequent oligo- or anovulation. The syndrome’s prevalence is attributed, at least partly, to a well-established association with obesity and insulin resistance (IR). Indeed, the presence of severe PCOS in human genetic obesity and IR syndromes supports a causal role for IR in the pathogenesis of PCOS. However, the molecular mechanisms underlying this causality, as well as the important role of hyperandrogenemia, remain poorly elucidated. As such, treatment of PCOS is necessarily empirical, focusing on symptom alleviation. The generation of knockout and transgenic rodent models of obesity and IR offers a promising platform in which to address mechanistic questions about reproductive dysfunction in the context of metabolic disease. Similarly, the impact of primary perturbations in rodent gonadotrophin or androgen signaling has been interrogated. However, the insights gained from such models have been limited by the relatively poor fidelity of rodent models to human PCOS. In this mini review, we evaluate the ovarian phenotypes associated with rodent models of obesity and IR, including the extent of endocrine disturbance, ovarian dysmorphology, and subfertility. We compare them to both human PCOS and other animal models of the syndrome (genetic and hormonal), explore reasons for their discordance, and consider the new opportunities that are emerging to better understand and treat this important condition. PMID:27375552

  4. Parent of origin, mosaicism, and recurrence risk: probabilistic modeling explains the broken symmetry of transmission genetics.

    Science.gov (United States)

    Campbell, Ian M; Stewart, Jonathan R; James, Regis A; Lupski, James R; Stankiewicz, Paweł; Olofsson, Peter; Shaw, Chad A

    2014-10-02

    Most new mutations are observed to arise in fathers, and increasing paternal age positively correlates with the risk of new variants. Interestingly, new mutations in X-linked recessive disease show elevated familial recurrence rates. In male offspring, these mutations must be inherited from mothers. We previously developed a simulation model to consider parental mosaicism as a source of transmitted mutations. In this paper, we extend and formalize the model to provide analytical results and flexible formulas. The results implicate parent of origin and parental mosaicism as central variables in recurrence risk. Consistent with empirical data, our model predicts that more transmitted mutations arise in fathers and that this tendency increases as fathers age. Notably, the lack of expansion later in the male germline determines relatively lower variance in the proportion of mutants, which decreases with paternal age. Subsequently, observation of a transmitted mutation has less impact on the expected risk for future offspring. Conversely, for the female germline, which arrests after clonal expansion in early development, variance in the mutant proportion is higher, and observation of a transmitted mutation dramatically increases the expected risk of recurrence in another pregnancy. Parental somatic mosaicism considerably elevates risk for both parents. These findings have important implications for genetic counseling and for understanding patterns of recurrence in transmission genetics. We provide a convenient online tool and source code implementing our analytical results. These tools permit varying the underlying parameters that influence recurrence risk and could be useful for analyzing risk in diverse family structures. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

  5. A mouse model of spontaneous preterm birth based on the genetic ablation of biglycan and decorin

    Science.gov (United States)

    Calmus, Megan L.; Macksoud, Elyse E.; Tucker, Richard; Iozzo, Renato V.; Lechner, Beatrice E.

    2011-01-01

    Preterm premature rupture of membranes is responsible for one third of preterm births. Ehlers-Danlos syndrome (EDS) is associated with preterm premature rupture of membranes in humans. Notably, an EDS variant is caused by a genetic mutation resulting in abnormal secretion of biglycan and decorin, two small leucine-rich proteoglycans highly expressed in reproductive tissues. Because biglycan/decorin null mutant (Bgn−/−Dcn−/−) mice demonstrate phenotypic changes similar to EDS, we utilized this model to test whether either or both biglycan and decorin play a role in the attainment of successful term gestation. Wild-type, biglycan null mutant, decorin null mutant and biglycan/decorin null mutant pregnancies were assessed for length of gestation, pup and placenta weight and litter size. Quantitative real-time polymerase chain reaction was performed to measure biglycan and decorin gene expression and immunohistochemistry was performed to assess protein expression in placenta and fetal membranes at embryonic day E12, E15 and E18. Bgn−/−Dcn−/− dams displayed preterm birth, whereas the possession of at least two biglycan or decorin wild-type alleles was protective of preterm birth. Bgn−/−Dcn−/− pups were decreased at postnatal day P1 but not at E18. Biglycan and decorin were upregulated in the placenta in each other’s absence and were developmentally regulated in fetal membranes, suggesting that these two proteoglycans demonstrate genetic complementation and contribute to gestational success in a dose dependent manner. Thus, the biglycan/decorin null mutant mouse is a model of genetically induced preterm birth and perinatal loss. This model presents novel targets for preventive or therapeutic manipulation of preterm birth. PMID:21502335

  6. Genetic parameter estimates for weaning weight and Kleiber ratio in goats

    Directory of Open Access Journals (Sweden)

    China Supakorn

    2012-04-01

    Full Text Available The research was conducted to evaluate the factors affecting on weaning weight (WW and Kleiber ratio (KR and toestimate genetic parameters for two traits in goats. The fixed factors affecting both traits indicated that year-season of birth,sex, birth type and regression of the Thai Native (TN, Boer (BO and Saanen (SA influenced on WW and KR (P<0.05. Malesin this population were heavier (P<0.05 than females. Weaning weights and KR of single kid were significantly higher (P<0.05 than other birth rearing types. Bivariate analysis of three models (Model 1: without maternal genetic effect, Model 2:with maternal genetic effect and am = 0, and Model 3: with maternal genetic effect and am  0 were used to estimate geneticparameters for this research. Estimated direct heritabilities from all models were 0.26 to 0.38 for WW, and 0.22 to 0.35 for KR.Estimated maternal heritabilities from Model 2 and 3 were 0.09 and 0.12 for WW and 0.08 and 0.11 for KR, respectively. Thedirect genetic and phenotypic correlations between WW and KR were positive and moderate values. Maternal genetic correlationsbetween them were positive and of low values. An antagonistic direct-maternal correlations from Model 3 withintraits and between traits indicated that offspring of does with superior maternal abilities probably may provide an inferiordirect genetic effect in the same trait and between traits. It was therefore possible to rapidly improve WW and KR in thisgoat population through selection, while the adverse effects of direct-maternal correlation within and between traits shouldbe considered. The best fit model would be a model including maternal genetic effect without a direct-maternal genetic covariance.

  7. Controlling complexity: the clinical relevance of mouse complex genetics

    Czech Academy of Sciences Publication Activity Database

    Forejt, Jiří

    2013-01-01

    Roč. 21, č. 11 (2013), s. 1191-1196 ISSN 1018-4813 Institutional support: RVO:68378050 Keywords : Mouse model * Forward genetics * Rewiev Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Genetics and heredity (medical genetics to be 3) Impact factor: 4.225, year: 2013

  8. Expansion Under Climate Change: The Genetic Consequences.

    Science.gov (United States)

    Garnier, Jimmy; Lewis, Mark A

    2016-11-01

    Range expansion and range shifts are crucial population responses to climate change. Genetic consequences are not well understood but are clearly coupled to ecological dynamics that, in turn, are driven by shifting climate conditions. We model a population with a deterministic reaction-diffusion model coupled to a heterogeneous environment that develops in time due to climate change. We decompose the resulting travelling wave solution into neutral genetic components to analyse the spatio-temporal dynamics of its genetic structure. Our analysis shows that range expansions and range shifts under slow climate change preserve genetic diversity. This is because slow climate change creates range boundaries that promote spatial mixing of genetic components. Mathematically, the mixing leads to so-called pushed travelling wave solutions. This mixing phenomenon is not seen in spatially homogeneous environments, where range expansion reduces genetic diversity through gene surfing arising from pulled travelling wave solutions. However, the preservation of diversity is diminished when climate change occurs too quickly. Using diversity indices, we show that fast expansions and range shifts erode genetic diversity more than slow range expansions and range shifts. Our study provides analytical insight into the dynamics of travelling wave solutions in heterogeneous environments.

  9. Causal models in epidemiology: past inheritance and genetic future

    Directory of Open Access Journals (Sweden)

    Kriebel David

    2006-07-01

    Full Text Available Abstract The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional

  10. Genetic basis of a cognitive complexity metric.

    Directory of Open Access Journals (Sweden)

    Narelle K Hansell

    Full Text Available Relational complexity (RC is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using the classical twin model, we estimated the heritability of RC and genetic overlap with intelligence (IQ, reasoning, and working memory in a twin and sibling sample aged 15-29 years (N = 787. Further, in an exploratory search for genetic loci contributing to RC, we examined associated genetic markers and genes in our Discovery sample and selected loci for replication in four independent samples (ALSPAC, LBC1936, NTR, NCNG, followed by meta-analysis (N>6500 at the single marker level. Twin modelling showed RC is highly heritable (67%, has considerable genetic overlap with IQ (59%, and is a major component of genetic covariation between reasoning and working memory (72%. At the molecular level, we found preliminary support for four single-marker loci (one in the gene DGKB, and at a gene-based level for the NPS gene, having influence on cognition. These results indicate that genetic sources influencing relational processing are a key component of the genetic architecture of broader cognitive abilities. Further, they suggest a genetic cascade, whereby genetic factors influencing capacity limitation in relational processing have a flow-on effect to more complex cognitive traits, including reasoning and working memory, and ultimately, IQ.

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

    Directory of Open Access Journals (Sweden)

    D. Arends

    2018-02-01

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

  12. The evolution of menstruation: a new model for genetic assimilation: explaining molecular origins of maternal responses to fetal invasiveness.

    Science.gov (United States)

    Emera, Deena; Romero, Roberto; Wagner, Günter

    2012-01-01

    Why do humans menstruate while most mammals do not? Here, we present our answer to this long-debated question, arguing that (i) menstruation occurs as a mechanistic consequence of hormone-induced differentiation of the endometrium (referred to as spontaneous decidualization, or SD); (ii) SD evolved because of maternal-fetal conflict; and (iii) SD evolved by genetic assimilation of the decidualization reaction, which is induced by the fetus in non-menstruating species. The idea that menstruation occurs as a consequence of SD has been proposed in the past, but here we present a novel hypothesis on how SD evolved. We argue that decidualization became genetically stabilized in menstruating lineages, allowing females to prepare for pregnancy without any signal from the fetus. We present three models for the evolution of SD by genetic assimilation, based on recent advances in our understanding of the mechanisms of endometrial differentiation and implantation. Testing these models will ultimately shed light on the evolutionary significance of menstruation, as well as on the etiology of human reproductive disorders like endometriosis and recurrent pregnancy loss. Copyright © 2012 WILEY Periodicals, Inc.

  13. Comparison of premier CAMPY enzyme immunoassay (EIA), ProSpecT Campylobacter EIA, and ImmunoCard STAT! CAMPY tests with culture for laboratory diagnosis of Campylobacter enteric infections.

    Science.gov (United States)

    Granato, Paul A; Chen, Li; Holiday, Iris; Rawling, Russell A; Novak-Weekley, Susan M; Quinlan, Tammy; Musser, Kimberlee A

    2010-11-01

    Campylobacter enteritis is a food-borne or waterborne illness caused almost exclusively by Campylobacter jejuni and, to a lesser extent, by Campylobacter coli. These organisms produce indistinguishable clinical diseases and together represent the second most common cause of bacterial diarrhea in the United States and the leading cause of enteric infection throughout the world. The conventional approach to the laboratory diagnosis of Campylobacter enteritis is based on the recovery of the organism from a stool specimen, which requires the use of a specialized medium incubated at 42°C for several days in an artificially created microaerophilic environment. Recently, several commercially available enzyme immunoassays (EIAs) have been developed for the direct detection of C. jejuni and C. coli in stool specimens. This study compared conventional culture with three EIA methods, the Premier CAMPY EIA (Meridian Bioscience, Cincinnati, OH), the ProSpecT Campylobacter EIA (Remel, Lenexa, KS), and the ImmunoCard STAT! CAMPY test (Meridian Bioscience, Cincinnati, OH), for the detection of C. jejuni and C. coli in 485 patient stool samples. Discordant results were arbitrated by using an in-house, real-time PCR assay that was developed and validated by a public health reference laboratory. Following analyses of the discrepant specimens by PCR, the sensitivity and specificity of both the Premier CAMPY and ProSpecT Campylobacter EIAs were 99.3% and 98%, respectively, while the ImmunoCard STAT! CAMPY test had a sensitivity of 98.5% and a specificity of 98.2%. By use of the PCR test as the reference standard, culture detected 127 of 135 Campylobacter-positive stool specimens, yielding a sensitivity of 94.1%. These results showed that the three EIAs evaluated in this study provide a rapid and reliable alternative for the laboratory diagnosis of enteric infections with C. jejuni and C. coli and that conventional culture may no longer be recognized as the "gold standard" for

  14. Enhanced hexose fermentation by Saccharomyces cerevisiae through integration of stoichiometric modeling and genetic screening.

    Science.gov (United States)

    Quarterman, Josh; Kim, Soo Rin; Kim, Pan-Jun; Jin, Yong-Su

    2015-01-20

    In order to determine beneficial gene deletions for ethanol production by the yeast Saccharomyces cerevisiae, we performed an in silico gene deletion experiment based on a genome-scale metabolic model. Genes coding for two oxidative phosphorylation reactions (cytochrome c oxidase and ubiquinol cytochrome c reductase) were identified by the model-based simulation as potential deletion targets for enhancing ethanol production and maintaining acceptable overall growth rate in oxygen-limited conditions. Since the two target enzymes are composed of multiple subunits, we conducted a genetic screening study to evaluate the in silico results and compare the effect of deleting various portions of the respiratory enzyme complexes. Over two-thirds of the knockout mutants identified by the in silico study did exhibit experimental behavior in qualitative agreement with model predictions, but the exceptions illustrate the limitation of using a purely stoichiometric model-based approach. Furthermore, there was a substantial quantitative variation in phenotype among the various respiration-deficient mutants that were screened in this study, and three genes encoding respiratory enzyme subunits were identified as the best knockout targets for improving hexose fermentation in microaerobic conditions. Specifically, deletion of either COX9 or QCR9 resulted in higher ethanol production rates than the parental strain by 37% and 27%, respectively, with slight growth disadvantages. Also, deletion of QCR6 led to improved ethanol production rate by 24% with no growth disadvantage. The beneficial effects of these gene deletions were consistently demonstrated in different strain backgrounds and with four common hexoses. The combination of stoichiometric modeling and genetic screening using a systematic knockout collection was useful for narrowing a large set of gene targets and identifying targets of interest. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Time series segmentation: a new approach based on Genetic Algorithm and Hidden Markov Model

    Science.gov (United States)

    Toreti, A.; Kuglitsch, F. G.; Xoplaki, E.; Luterbacher, J.

    2009-04-01

    The subdivision of a time series into homogeneous segments has been performed using various methods applied to different disciplines. In climatology, for example, it is accompanied by the well-known homogenization problem and the detection of artificial change points. In this context, we present a new method (GAMM) based on Hidden Markov Model (HMM) and Genetic Algorithm (GA), applicable to series of independent observations (and easily adaptable to autoregressive processes). A left-to-right hidden Markov model, estimating the parameters and the best-state sequence, respectively, with the Baum-Welch and Viterbi algorithms, was applied. In order to avoid the well-known dependence of the Baum-Welch algorithm on the initial condition, a Genetic Algorithm was developed. This algorithm is characterized by mutation, elitism and a crossover procedure implemented with some restrictive rules. Moreover the function to be minimized was derived following the approach of Kehagias (2004), i.e. it is the so-called complete log-likelihood. The number of states was determined applying a two-fold cross-validation procedure (Celeux and Durand, 2008). Being aware that the last issue is complex, and it influences all the analysis, a Multi Response Permutation Procedure (MRPP; Mielke et al., 1981) was inserted. It tests the model with K+1 states (where K is the state number of the best model) if its likelihood is close to K-state model. Finally, an evaluation of the GAMM performances, applied as a break detection method in the field of climate time series homogenization, is shown. 1. G. Celeux and J.B. Durand, Comput Stat 2008. 2. A. Kehagias, Stoch Envir Res 2004. 3. P.W. Mielke, K.J. Berry, G.W. Brier, Monthly Wea Rev 1981.

  16. Monsieur Etienne Blanc Premier vice-président de la Région Auvergne-Rhône-Alpes Délégué aux finances, à l'administration générale, aux économies budgétaires et aux politiques transfrontalières

    CERN Multimedia

    Bennett, Sophia Elizabeth

    2017-01-01

    Monsieur Etienne Blanc Premier vice-président de la Région Auvergne-Rhône-Alpes Délégué aux finances, à l'administration générale, aux économies budgétaires et aux politiques transfrontalières

  17. Testing the limits of the 'joint account' model of genetic information: a legal thought experiment.

    Science.gov (United States)

    Foster, Charles; Herring, Jonathan; Boyd, Magnus

    2015-05-01

    We examine the likely reception in the courtroom of the 'joint account' model of genetic confidentiality. We conclude that the model, as modified by Gilbar and others, is workable and reflects, better than more conventional legal approaches, both the biological and psychological realities and the obligations owed under Articles 8 and 10 of the European Convention on Human Rights (ECHR). Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  18. How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data

    Science.gov (United States)

    Yashin, Anatoliy I.; Arbeev, Konstantin G.; Wu, Deqing; Arbeeva, Liubov; Kulminski, Alexander; Kulminskaya, Irina; Akushevich, Igor; Ukraintseva, Svetlana V.

    2016-01-01

    Background and Objective To clarify mechanisms of genetic regulation of human aging and longevity traits, a number of genome-wide association studies (GWAS) of these traits have been performed. However, the results of these analyses did not meet expectations of the researchers. Most detected genetic associations have not reached a genome-wide level of statistical significance, and suffered from the lack of replication in the studies of independent populations. The reasons for slow progress in this research area include low efficiency of statistical methods used in data analyses, genetic heterogeneity of aging and longevity related traits, possibility of pleiotropic (e.g., age dependent) effects of genetic variants on such traits, underestimation of the effects of (i) mortality selection in genetically heterogeneous cohorts, (ii) external factors and differences in genetic backgrounds of individuals in the populations under study, the weakness of conceptual biological framework that does not fully account for above mentioned factors. One more limitation of conducted studies is that they did not fully realize the potential of longitudinal data that allow for evaluating how genetic influences on life span are mediated by physiological variables and other biomarkers during the life course. The objective of this paper is to address these issues. Data and Methods We performed GWAS of human life span using different subsets of data from the original Framingham Heart Study cohort corresponding to different quality control (QC) procedures and used one subset of selected genetic variants for further analyses. We used simulation study to show that approach to combining data improves the quality of GWAS. We used FHS longitudinal data to compare average age trajectories of physiological variables in carriers and non-carriers of selected genetic variants. We used stochastic process model of human mortality and aging to investigate genetic influence on hidden biomarkers of aging

  19. Breeding rootstocks for Prunus species: Advances in genetic and genomics of peach and cherry as a model

    Directory of Open Access Journals (Sweden)

    Verónica Guajardo

    2015-08-01

    Full Text Available Prunus rootstock is an important choice in optimizing productivity of grafted cultivars. Nevertheless, many Prunus rootstocks are notoriously intolerant to hypoxia which is caused by waterlogging and/or heavy soils. There is no available information to help select Prunus rootstocks that are tolerant to stress conditions such as root hypoxia caused by excess moisture. Information from genetic maps has demonstrated a high level of synteny among Prunus species, and this suggests that they all share a similar genomic structure. It should be possible to identify the genetic determinants involved in tolerance to hypoxia and other traits in Prunus rootstocks by applying methods to identify regions of the genome involved in the expression of important traits; these have been developed mainly in peach which is the model species for the genus. Molecular markers that are tightly linked to major genes would be useful in marker-assisted selection (MAS to optimize new rootstock selection. This article provides insight on the advances in the development of molecular markers, genetic maps, and gene identification in Prunus, mainly in peach; the aim is to provide a general approach for identifying the genetic determinants of hypoxia stress in rootstocks.

  20. Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network and pathway analyses

    DEFF Research Database (Denmark)

    Kogelman, Lisette; Pant, Sameer Dinkar; Fredholm, Merete

    2014-01-01

    .g. metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index...... investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation...... of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation...