WorldWideScience

Sample records for premier genetic model

  1. Comparing balance and instep angle of premier and non- premier leg in female soccer athletics

    Directory of Open Access Journals (Sweden)

    Mahsa Mohammadzadeh

    2016-03-01

    Full Text Available This study is aimed to compare balanceand instep angle in premier and non- premier leg. The number of 30 female futsal athletics of Tehran Province (in the age of years old, in the weight of kg participated in this study. To determine premier and non- premier leg of subjects, they besides questioning requested to shoot 5 times and the leg with less error recorded as premier leg. Balance Error Scoring System (BESS test was used for evaluating static balance. 4 markers were used for evaluating instep angle according to Clark Model. For evaluating dynamic balance of subjects single-leg landing test on 3- axes force board with 1000 hertz frequency was used and the time to stability was computed in line with anteroposterior and internal- external based on sequential estimation technique. Data analyzing was done in two sections, first, instep angle was compared in different status and static and dynamic balance in premier and non- premier leg by paired t- test and then the relationship between instep angle was examined in different status with static balance (total score of balance in the test (BESS with instep angle in standing on two leg and single leg for premier leg and dynamic balance in 3 anteroposterior (AP, mediolateral (ML and vertical (V sides by using from correlation coefficient test (for normal data of Pearson correlation coefficient and Spearman abnormal data. There is significant difference between dynamic balance in premier and dynamic balance in non- premier leg of futsal athletics and the premier leg has further balance than non- premier leg. There is negative and significant relationship between dynamic balance and instep angle in all statusexcept premier leg of single- leg in vertical side. Futsal athletics in premier leg have further balance than non- premier leg.

  2. 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...

  3. Fundulus as the Premier Teleost Model in Environmental Biology: Opportunities for New Insights Using Genomics

    Science.gov (United States)

    A strong foundation of basic and applied research documents that the estuarine fish Fundulus heteroclitus and related species are unique laboratory and field models for understanding how individuals and populations interact with their environment. In this paper we summarize an ex...

  4. PREMIER MEETS THE PRESS

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    On March 14, Premier Wen Jiabao addressed the Chinese and foreign media at a press conference after the closing meeting of the Third Session of the 11th National People’s Congress. Edited highlights on a number of economic and social issues follow:

  5. PREMIER MEETS THE PRESS

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    @@ March 14.Premier Wen Jiabao addressed the Chinese and foreign media at a press conference after the closing meeting of the Third Session of the 1 lth National People's Congress.Edited highlights on a number of economic and social issues follow:

  6. Premier Wen on Domestic Policies

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    The Second Session of the 11th National People’s Congress held a press conference at the Great Hall of the People on March 13. Premier Wen Jiabao answered questions from the Chinese and foreign press. Below are highlights of his answers on domestic policies.

  7. Our Measures Are Effective, Premier

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    @@ In an exclusive interview with Xinhua News Agency in Beijing on December 27, 2009, Chinese Premier Wen Jiabao shared his visions of the current economic situation in China and the government's economic policy orientations for 2010. Here are the highlights of the interview.

  8. Precision Cleaning - Path to Premier

    Science.gov (United States)

    Mackler, Scott E.

    2008-01-01

    ITT Space Systems Division s new Precision Cleaning facility provides critical cleaning and packaging of aerospace flight hardware and optical payloads to meet customer performance requirements. The Precision Cleaning Path to Premier Project was a 2007 capital project and is a key element in the approved Premier Resource Management - Integrated Supply Chain Footprint Optimization Project. Formerly precision cleaning was located offsite in a leased building. A new facility equipped with modern precision cleaning equipment including advanced process analytical technology and improved capabilities was designed and built after outsourcing solutions were investigated and found lacking in ability to meet quality specifications and schedule needs. SSD cleans parts that can range in size from a single threaded fastener all the way up to large composite structures. Materials that can be processed include optics, composites, metals and various high performance coatings. We are required to provide verification to our customers that we have met their particulate and molecular cleanliness requirements and we have that analytical capability in this new facility. The new facility footprint is approximately half the size of the former leased operation and provides double the amount of throughput. Process improvements and new cleaning equipment are projected to increase 1st pass yield from 78% to 98% avoiding $300K+/yr in rework costs. Cost avoidance of $350K/yr will result from elimination of rent, IT services, transportation, and decreased utility costs. Savings due to reduced staff expected to net $4-500K/yr.

  9. 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....

  10. Effective Factors on Reducing the Number of Spectators in Iran Football Premier League

    Directory of Open Access Journals (Sweden)

    Amir Reza Khadem Azghadi

    2016-07-01

    Full Text Available Because of reducing the number of spectators of football premier league, this study is seeking for identifying factors put the most impact on this decline. The statistical population consisted of all spectators in Iran football premier league in 2015-16, out of which 395 spectators were randomly selected as the research samples. The data were collected via a researcher-made questionnaire. The first part of the questionnaire included demographic information and the second part, at 6 aspects, includes 35 questions analyzing the reasons for reducing the number of spectators in Iran's football Premier League. For analyzing data, it was used from first and second order confirmatory factor analysis based on structural equations through using SPSS 20 and LISREL 8.8 software. The results of first order confirmatory factor analysis showed that the measurement model of factors affecting on reducing the number of spectators of football premier league is an appropriate model and model parameters are significant. All factors are approved as effective variables on reducing the number of spectators of football premier league. The results also showed that the second order measurement model of effective factors on reducing the number of spectators of football premier league are also appropriate, and economic, facilitative, administrative, technical, cultural-social, and personal-family respectively put the most effects on reducing the number of spectators of football premier league. It is suggested for the sport marketers to analyze identified factors in this research and develop applicable strategies and guidelines for them.

  11. 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.

  12. Our Measures Are Effective,Premier

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    In an exclusive interview with Xinhua News Agency in Beijing on December 27,2009,Chinese Premier Wen Jiabao shared his visions of the current economic situation in China and the government’s economic policy orientations for 2010.Here are the highlights of the interview.

  13. 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…

  14. Cool Wool Iaunched at Premiere Vision

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    Visitors to Premiere Vision were greeted by the inspired The Woolmark Company image, rapidly becoming iconic, of a welcoming flock of stylish Merino sheep in sunglasses. It raised many a smile and set the scene for a feel- good exhibition, putting Cool Wool firmly at the doorway to the new summer season 2013.

  15. Pakistanis Eager to Welcome Premier Li Keqiang

    Institute of Scientific and Technical Information of China (English)

    Syed; Ali; Nawaz; Gilani

    2013-01-01

    <正>"We the Pakistani Nation,are very much eager to welcome Chinese Premier Li Keqiang on his first visit to Pakistan after taking over the Premiership of the People’s Republic of China whom we are enjoying deep rooted and exemplary friendship for

  16. 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)

  17. 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...

  18. Le Premier Amendement : un mythe

    Directory of Open Access Journals (Sweden)

    Claude‑Jean Bertrand

    2006-03-01

    Full Text Available Ce papier, plein de verve, d’humeur et d’humour, pose, comme sait si bien le faire l’auteur, des questions profondes sous une apparence paradoxale. Il a été présenté lors d’un colloque sur le Premier amendement organisé à l’Université Lumière-Lyon 2 les 17 et 18 janvier 2003. Certaines communications ont été publiées dans le volume XXIV, n°1 (2003, « Le premier amendement : un modèle américain des libertés » (sous la direction de Vincent Michelot de la Revue Tocqueville.

  19. MicroEnterprise Americas: Premiere Issue, 2001

    OpenAIRE

    Inter-American Development Bank (IDB)

    2001-01-01

    This premiere issue of MicroEnterprise Americas concentrates on the microfinance industry, a thriving segment of the Latin American financial sector that has rapidly expanded in the past five years. This issue explores looks at how market leaders have developed technologies, attracted investments, and developed tools for mitigating risk in the difficult financial climate of the past two years. MicroEnterprise Americas is published by the Inter-American Forum on Microenterprise, an annual even...

  20. MicroEnterprise Americas: Premiere Issue, 2001

    OpenAIRE

    Inter-American Development Bank (IDB)

    2001-01-01

    This premiere issue of MicroEnterprise Americas concentrates on the microfinance industry, a thriving segment of the Latin American financial sector that has rapidly expanded in the past five years. This issue explores looks at how market leaders have developed technologies, attracted investments, and developed tools for mitigating risk in the difficult financial climate of the past two years. MicroEnterprise Americas is published by the Inter-American Forum on Microenterprise, an annual even...

  1. Behavior genetic modeling of human fertility

    DEFF Research Database (Denmark)

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

    2001-01-01

    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...

  2. Routine Discovery of Complex Genetic Models using Genetic Algorithms.

    Science.gov (United States)

    Moore, Jason H; Hahn, Lance W; Ritchie, Marylyn D; Thornton, Tricia A; White, Bill C

    2004-02-01

    Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes.

  3. Development of Digitex premier digital angiographic systems

    Energy Technology Data Exchange (ETDEWEB)

    Miura, Yoshiaki; Miura, Yusuke; Goto, Keiichi; Imanishi, Tetsuo; Miyamoto, Wataru [Shimadzu Corp., Medical Systems Division, Kyoto (Japan)

    2003-06-01

    The technique of interventional radiology has come to be widely utilized in the field of angiography. This has brought forth a strong demand that digital angiographic systems provide high efficiency in patient examinations and high level of interventional support. This report refers to our newly developed Digitex Premier Series digital angiographic systems, designed to meet the above demands. The new systems utilize a high-speed, wide-range C-arm system, a high-resolution image intensifier, a fluid-lubricant X-ray tube, and a digital image processing system, in order to ensure high patient examination efficiency. Their IVR (interventional radiology)-Master bed-side image controller further enhances the efficiency of patient examinations, and also, their CAT (comfortable angio terminal) and FMC (file management console) improve the patient examination throughput and diagnostic workflow of the systems. (author)

  4. Behavior genetic modeling of human fertility

    DEFF Research Database (Denmark)

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

    2001-01-01

    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......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...

  5. Genetic network models: a comparative study

    Science.gov (United States)

    van Someren, Eugene P.; Wessels, Lodewyk F. A.; Reinders, Marcel J. T.

    2001-06-01

    Currently, the need arises for tools capable of unraveling the functionality of genes based on the analysis of microarray measurements. Modeling genetic interactions by means of genetic network models provides a methodology to infer functional relationships between genes. Although a wide variety of different models have been introduced so far, it remains, in general, unclear what the strengths and weaknesses of each of these approaches are and where these models overlap and differ. This paper compares different genetic modeling approaches that attempt to extract the gene regulation matrix from expression data. A taxonomy of continuous genetic network models is proposed and the following important characteristics are suggested and employed to compare the models: inferential power; predictive power; robustness; consistency; stability and computational cost. Where possible, synthetic time series data are employed to investigate some of these properties. The comparison shows that although genetic network modeling might provide valuable information regarding genetic interactions, current models show disappointing results on simple artificial problems. For now, the simplest models are favored because they generalize better, but more complex models will probably prevail once their bias is more thoroughly understood and their variance is better controlled.

  6. Metaphor Analysis of Chinese Premier Wen’s Cambridge Speech

    Institute of Scientific and Technical Information of China (English)

    LUO Luo

    2014-01-01

    Metaphor is more than an ostensible decoration of language. It is an integral part of human thought of ideologized world. This article analyzes the metaphor use of Chinese Premier Wen Jiabao’s speech at Cambridge in February 2009, in an at-tempt to display how the preferred metaphors serve the purpose of this speech and reflect Premier Wen ’s construction of Chi-na’s situation.

  7. Genetically Modified Pig Models for Human Diseases

    Institute of Scientific and Technical Information of China (English)

    Nana Fan; Liangxue Lai

    2013-01-01

    Genetically modified animal models are important for understanding the pathogenesis of human disease and developing therapeutic strategies.Although genetically modified mice have been widely used to model human diseases,some of these mouse models do not replicate important disease symptoms or pathology.Pigs are more similar to humans than mice in anatomy,physiology,and genome.Thus,pigs are considered to be better animal models to mimic some human diseases.This review describes genetically modified pigs that have been used to model various diseases including neurological,cardiovascular,and diabetic disorders.We also discuss the development in gene modification technology that can facilitate the generation of transgenic pig models for human diseases.

  8. Genetic models of homosexuality: generating testable predictions

    OpenAIRE

    Gavrilets, Sergey; Rice, William R.

    2006-01-01

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality inclu...

  9. 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...

  10. Genetic models of homosexuality: generating testable predictions.

    Science.gov (United States)

    Gavrilets, Sergey; Rice, William R

    2006-12-22

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism.

  11. Genetic models for CNS inflammation

    DEFF Research Database (Denmark)

    Owens, T; Wekerle, H; Antel, J

    2001-01-01

    The use of transgenic technology to over-express or prevent expression of genes encoding molecules related to inflammation has allowed direct examination of their role in experimental disease. This article reviews transgenic and knockout models of CNS demyelinating disease, focusing primarily on ...

  12. Genetically engineered mouse models of prostate cancer

    NARCIS (Netherlands)

    Nawijn, Martijn C.; Bergman, Andreas M.; van der Poel, Henk G.

    2008-01-01

    Objectives: Mouse models of prostate cancer are used to test the contribution of individual genes to the transformation process, evaluate the collaboration between multiple genetic lesions observed in a single tumour, and perform preclinical intervention studies in prostate cancer research. Methods:

  13. 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

  14. 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

  15. 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…

  16. Adaptive Genetic Algorithm Model for Intrusion Detection

    Directory of Open Access Journals (Sweden)

    K. S. Anil Kumar

    2012-09-01

    Full Text Available Intrusion detection systems are intelligent systems designed to identify and prevent the misuse of computer networks and systems. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Thus the emerging network security systems need be part of the life system and this ispossible only by embedding knowledge into the network. The Adaptive Genetic Algorithm Model - IDS comprising of K-Means clustering Algorithm, Genetic Algorithm and Neural Network techniques. Thetechnique is tested using multitude of background knowledge sets in DARPA network traffic datasets.

  17. Animal Models of Parkinson's Disease: Vertebrate Genetics

    Science.gov (United States)

    Lee, Yunjong; Dawson, Valina L.; Dawson, Ted M.

    2012-01-01

    Parkinson's disease (PD) is a complex genetic disorder that is associated with environmental risk factors and aging. Vertebrate genetic models, especially mice, have aided the study of autosomal-dominant and autosomal-recessive PD. Mice are capable of showing a broad range of phenotypes and, coupled with their conserved genetic and anatomical structures, provide unparalleled molecular and pathological tools to model human disease. These models used in combination with aging and PD-associated toxins have expanded our understanding of PD pathogenesis. Attempts to refine PD animal models using conditional approaches have yielded in vivo nigrostriatal degeneration that is instructive in ordering pathogenic signaling and in developing therapeutic strategies to cure or halt the disease. Here, we provide an overview of the generation and characterization of transgenic and knockout mice used to study PD followed by a review of the molecular insights that have been gleaned from current PD mouse models. Finally, potential approaches to refine and improve current models are discussed. PMID:22960626

  18. Zebra fish: an uncharted behavior genetic model.

    Science.gov (United States)

    Gerlai, Robert

    2003-09-01

    The zebra fish has been a preferred subject of genetic analysis. It produces a large number of offspring that can be kept in small aquaria, it can be easily mutagenized using chemical mutagens (e.g., ethyl nitrosourea [ENU]), and high-resolution genetic maps exist that aid identification of novel genes. Libraries containing large numbers of mutant fish have been generated, and the genetic mechanisms of the development of zebra fish, whose embryo is transparent, have been extensively studied. Given the extensive homology of its genome with that of other vertebrate species including our own and given the available genetic tools, zebra fish has become a popular model organism. Despite this popularity, however, surprisingly little is known about its behavior. It is argued that behavioral analysis is a powerful tool with which the function of the brain may be studied, and the zebra fish will represent an excellent subject of such analysis. The present paper is a proof of concept study that uses pharmacological manipulation (exposure to alcohol) to show that the zebra fish is amenable to the behavioral genetic analysis of aggression and thus may allow us to reveal molecular mechanisms of this behavioral phenomenon relevant to vertebrates.

  19. Genetic and Pharmacologic Models for Type 1 Diabetes.

    Science.gov (United States)

    Leiter, Edward H; Schile, Andrew

    2013-03-01

    Type 1 diabetes (T1D) is characterized by a partial or total insufficiency of insulin. The premiere animal model of autoimmune T cell-mediated T1D is the NOD mouse. A dominant negative mutation in the mouse insulin 2 gene (Ins2(Akita) ) produces a severe insulin deficiency syndrome without autoimmune involvement, as do a variety of transgenes overexpressed in beta cells. Pharmacologically-induced T1D (without autoimmunity) elicted by alloxan or streptozotocin at high doses can generate hyperglycemia in almost any strain of mouse by direct toxicity. Multiple low doses of streptozotocin combine direct beta cell toxicity with local inflammation to elicit T1D in a male sex-specific fashion. A summary of protocols relevant to the management of these different mouse models will be covered in this overview.

  20. Early Childhood Family Education: Implementing the Minnesota Model = Education de la premiere enfance: Mise en oeuvre de modele Minnesota = La educacion de la familia y la ninez: Poner en practica el modelo de Minnesota.

    Science.gov (United States)

    Carlson, Helen L.

    Over a decade ago, the Minnesota state legislature funded the Council on Quality Education to create nine exemplary and experimental pilot programs to support young children and their families. One of the early models was a family-oriented, structured preschool activity that featured weekly 2-hour sessions during which parents of 4-year-olds…

  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. Modeling resistance to genetic control of insects.

    Science.gov (United States)

    Alphey, Nina; Bonsall, Michael B; Alphey, Luke

    2011-02-07

    The sterile insect technique is an area-wide pest control method that reduces pest populations by releasing mass-reared sterile insects which compete for mates with wild insects. Modern molecular tools have created possibilities for improving and extending the sterile insect technique. As with any new insect control method, questions arise about potential resistance. Genetic RIDL(®)(1) (Release of Insects carrying a Dominant Lethal) technology is a proposed modification of the technique, releasing insects that are homozygous for a repressible dominant lethal genetic construct rather than being sterilized by irradiation. Hypothetical resistance to the lethal mechanism is a potential threat to RIDL strategies' effectiveness. Using population genetic and population dynamic models, we assess the circumstances under which monogenic biochemically based resistance could have a significant impact on the effectiveness of releases for population control. We assume that released insects would be homozygous susceptible to the lethal genetic construct and therefore releases would have a built-in element of resistance dilution. We find that this effect could prevent or limit the spread of resistance to RIDL constructs; the outcomes are subject to competing selective forces deriving from the fitness properties of resistance and the release ratio. Resistance that is spreading and capable of having a significant detrimental impact on population reduction is identifiable, signaling in advance a need for mitigating action.

  3. Evolutionary algorithms in genetic regulatory networks model

    CERN Document Server

    Raza, Khalid

    2012-01-01

    Genetic Regulatory Networks (GRNs) plays a vital role in the understanding of complex biological processes. Modeling GRNs is significantly important in order to reveal fundamental cellular processes, examine gene functions and understanding their complex relationships. Understanding the interactions between genes gives rise to develop better method for drug discovery and diagnosis of the disease since many diseases are characterized by abnormal behaviour of the genes. In this paper we have reviewed various evolutionary algorithms-based approach for modeling GRNs and discussed various opportunities and challenges.

  4. 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...

  5. Premiere of Film Nine-Mile Fragrance Held in Kenya

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    <正>The United Nations Environment Program (UNEP) and the United Nations Human Settlement Program (UN-HABITAT) in Kenya staged the premiere of the film Nine-Mile Fragrance depicting the Wenchuan earthquake relief efforts. The film, showing the unique culture of the Qiang ethnic group and the great spirit of love of the Chinese people in their earthquake relief work, left a deep impression on the African audience.

  6. 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.

  7. Large genetic animal models of Huntington's Disease.

    Science.gov (United States)

    Morton, A Jennifer; Howland, David S

    2013-01-01

    The dominant nature of the Huntington's disease gene mutation has allowed genetic models to be developed in multiple species, with the mutation causing an abnormal neurological phenotype in all animals in which it is expressed. Many different rodent models have been generated. The most widely used of these, the transgenic R6/2 mouse, carries the mutation in a fragment of the human huntingtin gene and has a rapidly progressive and fatal neurological phenotype with many relevant pathological changes. Nevertheless, their rapid decline has been frequently questioned in the context of a disease that takes years to manifest in humans, and strenuous efforts have been made to make rodent models that are genetically more 'relevant' to the human condition, including full length huntingtin gene transgenic and knock-in mice. While there is no doubt that we have learned, and continue to learn much from rodent models, their usefulness is limited by two species constraints. First, the brains of rodents differ significantly from humans in both their small size and their neuroanatomical organization. Second, rodents have much shorter lifespans than humans. Here, we review new approaches taken to these challenges in the development of models of Huntington's disease in large brained, long-lived animals. We discuss the need for such models, and how they might be used to fill specific niches in preclinical Huntington's disease research, particularly in testing gene-based therapeutics. We discuss the advantages and disadvantages of animals in which the prodromal period of disease extends over a long time span. We suggest that there is considerable 'value added' for large animal models in preclinical Huntington's disease research.

  8. Genetic mouse models for otitis media

    Institute of Scientific and Technical Information of China (English)

    Qingyin Zheng; Ken R Johnson

    2003-01-01

    @@ Genetics of Otitis Media (OM): OM is affected by multiple factors including eustachian tube (ET) structure and function, immune status, innate mucosal defense, genetic susceptibility, and pathogens.

  9. GENETIC-BASED NUTRITION RECOMMENDATION MODEL

    Directory of Open Access Journals (Sweden)

    S. A.A. Fayoumi

    2014-01-01

    Full Text Available Evolutionary computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being widely applied to a variety of problems in many vital fields. Also, Evolutionary Algorithms (EA which applied the principles of Evolutionary computations, such as genetic algorithm, particle swarm, ant colony and bees algorithm and so on play an important role in decision making process. EAs serve a lot of fields which can affect our life directly, such as medicine, engineering, transportations, communications. One of these vital fields is Nutrition which can be viewed from several points of view as medical, physical, social, environmental and psychological point of view. This study, presents a proposed model that shows how evolutionary computing generally and genetic algorithm specifically-as a powerful algorithm of evolutionary algorithms-can be used to recommend an appropriate nutrition style in a medical and physical sides only to each person according to his/her personal and medical measurements.

  10. 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.

  11. Genetically engineered mouse models and human osteosarcoma

    Directory of Open Access Journals (Sweden)

    Ng Alvin JM

    2012-10-01

    Full Text Available Abstract Osteosarcoma is the most common form of bone cancer. Pivotal insight into the genes involved in human osteosarcoma has been provided by the study of rare familial cancer predisposition syndromes. Three kindreds stand out as predisposing to the development of osteosarcoma: Li-Fraumeni syndrome, familial retinoblastoma and RecQ helicase disorders, which include Rothmund-Thomson Syndrome in particular. These disorders have highlighted the important roles of P53 and RB respectively, in the development of osteosarcoma. The association of OS with RECQL4 mutations is apparent but the relevance of this to OS is uncertain as mutations in RECQL4 are not found in sporadic OS. Application of the knowledge or mutations of P53 and RB in familial and sporadic OS has enabled the development of tractable, highly penetrant murine models of OS. These models share many of the cardinal features associated with human osteosarcoma including, importantly, a high incidence of spontaneous metastasis. The recent development of these models has been a significant advance for efforts to improve our understanding of the genetics of human OS and, more critically, to provide a high-throughput genetically modifiable platform for preclinical evaluation of new therapeutics.

  12. 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.

  13. 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

  14. Models of genetic counseling and their effects on multicultural genetic counseling.

    Science.gov (United States)

    Lewis, Linwood J

    2002-06-01

    This theoretical paper examines challenges to multicultural genetic counseling, counseling between culturally different clients and counselors, in the context of Kessler's typology of models of genetic counseling (Kessler S (1997) J Genet Counsel 6:287-295). It is suggested that challenges such as resistance to multicultural genetic counseling education may be due to conceptions about genetic counseling as a biomedical field that transcends questions of culture as well as lack of multicultural training or prejudice. Directions for future research and recommendations for multicultural genetic counseling education are briefly explored.

  15. Large animal models of rare genetic disorders: sheep as phenotypically relevant models of human genetic disease.

    Science.gov (United States)

    Pinnapureddy, Ashish R; Stayner, Cherie; McEwan, John; Baddeley, Olivia; Forman, John; Eccles, Michael R

    2015-09-02

    Animals that accurately model human disease are invaluable in medical research, allowing a critical understanding of disease mechanisms, and the opportunity to evaluate the effect of therapeutic compounds in pre-clinical studies. Many types of animal models are used world-wide, with the most common being small laboratory animals, such as mice. However, rodents often do not faithfully replicate human disease, despite their predominant use in research. This discordancy is due in part to physiological differences, such as body size and longevity. In contrast, large animal models, including sheep, provide an alternative to mice for biomedical research due to their greater physiological parallels with humans. Completion of the full genome sequences of many species, and the advent of Next Generation Sequencing (NGS) technologies, means it is now feasible to screen large populations of domesticated animals for genetic variants that resemble human genetic diseases, and generate models that more accurately model rare human pathologies. In this review, we discuss the notion of using sheep as large animal models, and their advantages in modelling human genetic disease. We exemplify several existing naturally occurring ovine variants in genes that are orthologous to human disease genes, such as the Cln6 sheep model for Batten disease. These, and other sheep models, have contributed significantly to our understanding of the relevant human disease process, in addition to providing opportunities to trial new therapies in animals with similar body and organ size to humans. Therefore sheep are a significant species with respect to the modelling of rare genetic human disease, which we summarize in this review.

  16. Warehouse Optimization Model Based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Guofeng Qin

    2013-01-01

    Full Text Available This paper takes Bao Steel logistics automated warehouse system as an example. The premise is to maintain the focus of the shelf below half of the height of the shelf. As a result, the cost time of getting or putting goods on the shelf is reduced, and the distance of the same kind of goods is also reduced. Construct a multiobjective optimization model, using genetic algorithm to optimize problem. At last, we get a local optimal solution. Before optimization, the average cost time of getting or putting goods is 4.52996 s, and the average distance of the same kinds of goods is 2.35318 m. After optimization, the average cost time is 4.28859 s, and the average distance is 1.97366 m. After analysis, we can draw the conclusion that this model can improve the efficiency of cargo storage.

  17. Genetic spectrum assignment model with constraints in cognitive radio networks

    Directory of Open Access Journals (Sweden)

    Fang Ye

    2011-06-01

    Full Text Available The interference constraints of genetic spectrum assignment model in cognitive radio networks are analyzed in this paper. An improved genetic spectrum assignment model is proposed. The population of genetic algorithm is divided into two sets, the feasible spectrum assignment strategies and the randomly updated spectrum assignment strategies. The penalty function is added to the utility function to achieve the spectrum assignment strategy that satisfies the interference constraints and has better fitness. The proposed method is applicable in both the genetic spectrum assignment model and the quantum genetic spectrum assignment mode. It can ensure the randomness of partial chromosomes in the population to some extent, and reduce the computational complexity caused by the constraints-free procedure after the update of population. Simulation results show that the proposed method can achieve better performance than the conventional genetic spectrum assignment model and quantum genetic spectrum assignment model

  18. Vice Premier Li Keqiang Meets Chinese and Russian Friendly Personages

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    <正>The scene: 5 pm on April 26 at the President Hotel in Moscow, and Vice Premier Li Keqiang, having just arrived in Russia for an official visit, cordially meets Chinese and Russian friendly personages from various sectors of society including people-to-people diplomatic, academic, cultural, scientific and educational, and business circles. Among them are experts and scholars in their seventies and eighties, important professionals of their respective workplaces in their prime, as well as students in the bloom of their youth.

  19. Lessons premier hospitals learned about implementing electronic health records.

    Science.gov (United States)

    DeVore, Susan D; Figlioli, Keith

    2010-04-01

    Implementing health information technology (IT) is a major strategic objective for providers. To pinpoint considerations that tie to success, the Premier health care alliance surveyed hospitals to develop an electronic health record best-practices library. Compiled from diverse health care organizations, the library outlines considerations to support "meaningful use" in the areas of computerized physician order entry, medication management, clinical documentation, reporting of measures, privacy, information exchange, management of populations' health, and personal health records. Best practices also uncovered strategies for securing executive leadership, culture change, communication, and support for clinicians. This paper summarizes lessons from the library, providing recommendations to speed up health IT implementation.

  20. Model comparisons and genetic and environmental parameter ...

    African Journals Online (AJOL)

    arc

    South African Journal of Animal Science 2005, 35 (1) ... Genetic and environmental parameters were estimated for pre- and post-weaning average daily gain ..... and BWT (and medium maternal genetic correlations) indicates that these traits ...

  1. Genetic Algorithm Approaches to Prebiobiotic Chemistry Modeling

    Science.gov (United States)

    Lohn, Jason; Colombano, Silvano

    1997-01-01

    We model an artificial chemistry comprised of interacting polymers by specifying two initial conditions: a distribution of polymers and a fixed set of reversible catalytic reactions. A genetic algorithm is used to find a set of reactions that exhibit a desired dynamical behavior. Such a technique is useful because it allows an investigator to determine whether a specific pattern of dynamics can be produced, and if it can, the reaction network found can be then analyzed. We present our results in the context of studying simplified chemical dynamics in theorized protocells - hypothesized precursors of the first living organisms. Our results show that given a small sample of plausible protocell reaction dynamics, catalytic reaction sets can be found. We present cases where this is not possible and also analyze the evolved reaction sets.

  2. Genetic models of poljes in Sicily

    Science.gov (United States)

    Di Maggio, Cipriano; Madonia, Giuliana; Vattano, Marco; De Waele, Jo

    2016-04-01

    Geomorphological and geological studies have been carried out to contribute to the recognition of controlling causes and to the definition of genetic models for poljes of Sicily. A polje is a kilometric closed depression developed mainly on karst rocks, with a conspicuously flat and alluviated bottom affected by intermittent flooding. A polje is usually characterised by relatively steep slopes enclosing an almost perfectly horizontal floor, caused by lateral solution planation related to flooding events. The origin of a polje is due to dissolution of the land surface, although geological structure generally influences its genesis. These large depressions are often elongated according to the direction of main faults, in consequence of a control due to tectonics or to differential erosion. The performed researches have shown the existence of at least seven poljes located along the north-western (chain zone) and the southern (deformed foredeep zone) areas of Sicily. These large karst depressions are developed on Mesozoic limestone/dolomitic rocks within the chain zone and on Messinian gypsum rocks within the deformed foredeep zone. They are up to 4 km in length, can reach surfaces of 3-8 km2 and are around hundred metres deep, with steep slopes and a flat bottom. Generally, they are open, occasionally active depressions and their genesis seems to be strongly controlled by structure. In particular, the studied poljes occur in two different geological/geomorphological settings: a) in graben-like tectonic depressions, where important fault slopes/scarps border the flat bottom; b) in complex depressions controlled by structure, where wide fault line slopes/scarps or large inclined degraded structural surfaces mark the poljes. Finally, landscape analysis leads to the proposition of two main genetic models in which the development of poljes is primarily due to tectonics or differential erosion followed by dissolution.

  3. 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

  4. 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

  5. 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.

  6. Research on Modeling of Genetic Networks Based on Information Measurement

    Institute of Scientific and Technical Information of China (English)

    ZHANG Guo-wei; SHAO Shi-huang; ZHANG Ying; LI Hai-ying

    2006-01-01

    As the basis of network of biology organism, the genetic network is concerned by many researchers.Current modeling methods to genetic network, especially the Boolean networks modeling method are analyzed. For modeling the genetic network, the information theory is proposed to mining the relations between elements in network. Through calculating the values of information entropy and mutual entropy in a case, the effectiveness of the method is verified.

  7. First Modelling Results of the EM Response of a CO{sub 2} Storage in the Paris Basin; Premieres modelisations de la reponse EM d'un stockage de CO{sub 2} dans le bassin Parisien

    Energy Technology Data Exchange (ETDEWEB)

    Bourgeois, B.; Girard, J.F. [BRGM, Service Amenagement et Risques Naturels, 45 - Orleans (France)

    2010-07-15

    We study the feasibility of using electrical/EM methods for monitoring the injection of supercritical CO{sub 2} at a depth of 1700 m in a saline aquifer of the Paris Basin (Dogger carbonates). We first establish the theoretical interest of resistivity methods for CO{sub 2} monitoring through the basic laws of electrical physics in porous sedimentary rocks, assuming that supercritical CO{sub 2} is a perfect insulator. Various combinations of EM sources and sensors are discussed and it is shown that the best type of array consists of a galvanic source (i.e. injection of current via a pair of electrodes A and B) and of a grid of electric (and possibly magnetic) sensors at the ground surface. Given the usual depth and thinness of CO{sub 2} storage layers, current injection at depth was investigated in order to increase the current density in the reservoir and thus enhance the CO{sub 2} response. Point injection at the reservoir depth in the so-called 'Mise a la Masse' (MAM) configuration is generally impossible in deep wells due to the presence of metallic casings. Therefore, the possibility of using a deep metallic casing as a long electrode distributing the current all along a borehole is studied. This kind of source is named 'LEMAM' (Long Electrode Mise a la Masse) in order to differentiate it from the conventional MAM. Numerical simulations are presented for the LEMAM array and for the gradient or rectangle array (RECT), for which the current is injected by a pair of point electrodes at the ground surface. The geo-electric model used is based on an area close to the Saint-Martin-de-Bossenay (SMB) oil-field, in the south-east of the Paris Basin. The storage reservoir considered in this study is the 75-m-thick 'Oolithe Blanche' formation (Mid Jurassic or Dogger, Bathonian age), located at a depth of about 1700 m below ground surface. In the models presented, the CO{sub 2} plume is simplified to a square horizontal slab of 2 km side, 70 m

  8. Modeling and simulation of critical parameters of the first chamber of the dimuon arm spectrometer of the Alice experiment; Modelisation et simulation de parametres critiques de la premiere station du spectrometre dimuons d'ALICE

    Energy Technology Data Exchange (ETDEWEB)

    Guez, D

    2003-10-01

    The Alice experiment that is dedicated to the study of ultra-relativistic heavy ion collisions, will take place in the future large hadron collider (LHC) at CERN. The dimuon arm spectrometer of the Alice experiment is devoted to the search of a new signature of the existence of the quark gluon plasma (QGP). The first chapter is dedicated to the physics notions linked to the study of QGP, a few signatures are proposed for the detection of QGP, particularly the signature concerning the production rate of quarkonium. The second chapter deals with particle detection involved in Alice experiment, the dimuon arm spectrometer is a detector dedicated to the track reconstruction of muons issued from the decay of heavy mesons from J/{psi} and {upsilon} families. The third and the fourth chapters present the studies made to integrate a reliable model of the dimuon arm in the global simulation code of Alice (Aliroot). The fifth chapter presents the software TB{sup 2} that has been developed within the framework of this thesis in order to check and control the output data when the detector is tested with a real particle beam. The sixth chapter presents the results of the tests that have been performed with a 7 GeV/c pion beam. These tests have shown that the electronic noise is coherent with the specifications of Alice experiment. A factor 1,8 between the highest and the weakest values of the gain has been measured in the chamber. The detection efficiency of the chamber has been estimated to 99% in the different cases studied. (A.C.)

  9. Tears of a Chinese Premier Hussein Ismail Hussein

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    THE day Premier Wen took office he stated.""Leaders should be closer to the masses."" His visit to comfort and talk with everyday workers in Tongchuan City, Shaanxi Province on January 1, 2005, where a few weeks previously a gas blast in the Chenjiashan Coalmine had killed 166 workers, was by no means his first. But it was the first time he publicly shed tears. In one household that had lost its breadwinner, Wen Jiabao embraced the victim's son and shared his grief. He later had a simple lunch of steamed bread and tea in a tunnel 1,300 meters belowg round as he chatted with workers at another mine in the city.

  10. L’abri premier, de Vitruve à Nils-Udo

    Directory of Open Access Journals (Sweden)

    Nathalie Huvenne

    2011-05-01

    Full Text Available Cette étude se propose de mettre en écho les écrits de Vitruve, livre second, chapitre 1 du De architectura et les créations plastiques de l’artiste contemporain Nils-Udo.Ce vis-à-vis des réflexions de Vitruve avec celles de l’artiste nous permettra de tisser un lien entre ces deux hommes et de voir dans leurs travaux respectifs des points de similitude.Le texte extrait du De architectura II, 1, sous-titré par M. Nisard, De la manière de vivre des premiers hommes, et quels ont été les commenc...

  11. Genetically modified mouse models addressing gonadotropin function.

    Science.gov (United States)

    Ratner, Laura D; Rulli, Susana B; Huhtaniemi, Ilpo T

    2014-03-01

    The development of genetically modified animals has been useful to understand the mechanisms involved in the regulation of the gonadotropin function. It is well known that alterations in the secretion of a single hormone is capable of producing profound reproductive abnormalities. Human chorionic gonadotropin (hCG) is a glycoprotein hormone normally secreted by the human placenta, and structurally and functionally it is related to pituitary LH. LH and hCG bind to the same LH/hCG receptor, and hCG is often used as an analog of LH to boost gonadotropin action. There are many physiological and pathological conditions where LH/hCG levels and actions are elevated. In order to understand how elevated LH/hCG levels may impact on the hypothalamic-pituitary-gonadal axis we have developed a transgenic mouse model with chronic hCG hypersecretion. Female mice develop many gonadal and extragonadal phenotypes including obesity, infertility, hyperprolactinemia, and pituitary and mammary gland tumors. This article summarizes recent findings on the mechanisms involved in pituitary gland tumorigenesis and hyperprolactinemia in the female mice hypersecreting hCG, in particular the relationship of progesterone with the hyperprolactinemic condition of the model. In addition, we describe the role of hyperprolactinemia as the main cause of infertility and the phenotypic abnormalities in these mice, and the use of dopamine agonists bromocriptine and cabergoline to normalize these conditions. Copyright © 2014 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish Academy of Sciences in Olsztyn. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  12. Genetic and Environmental Bases of Reading and Spelling: A Unified Genetic Dual Route Model

    Science.gov (United States)

    Bates, Timothy C.; Castles, Anne; Luciano, Michelle; Wright, Margaret J.; Coltheart, Max; Martin, Nicholas G.

    2007-01-01

    We develop and test a dual-route model of genetic effects on reading aloud and spelling, based on irregular and non-word reading and spelling performance assessed in 1382 monozygotic and dizygotic twins. As in earlier research, most of the variance in reading was due to genetic effects. However, there were three more specific conclusions: the…

  13. Functional-mixed effects models for candidate genetic mapping in imaging genetic studies.

    Science.gov (United States)

    Lin, Ja-An; Zhu, Hongtu; Mihye, Ahn; Sun, Wei; Ibrahim, Joseph G

    2014-12-01

    The aim of this paper is to develop a functional-mixed effects modeling (FMEM) framework for the joint analysis of high-dimensional imaging data in a large number of locations (called voxels) of a three-dimensional volume with a set of genetic markers and clinical covariates. Our FMEM is extremely useful for efficiently carrying out the candidate gene approaches in imaging genetic studies. FMEM consists of two novel components including a mixed effects model for modeling nonlinear genetic effects on imaging phenotypes by introducing the genetic random effects at each voxel and a jumping surface model for modeling the variance components of the genetic random effects and fixed effects as piecewise smooth functions of the voxels. Moreover, FMEM naturally accommodates the correlation structure of the genetic markers at each voxel, while the jumping surface model explicitly incorporates the intrinsically spatial smoothness of the imaging data. We propose a novel two-stage adaptive smoothing procedure to spatially estimate the piecewise smooth functions, particularly the irregular functional genetic variance components, while preserving their edges among different piecewise-smooth regions. We develop weighted likelihood ratio tests and derive their exact approximations to test the effect of the genetic markers across voxels. Simulation studies show that FMEM significantly outperforms voxel-wise approaches in terms of higher sensitivity and specificity to identify regions of interest for carrying out candidate genetic mapping in imaging genetic studies. Finally, FMEM is used to identify brain regions affected by three candidate genes including CR1, CD2AP, and PICALM, thereby hoping to shed light on the pathological interactions between these candidate genes and brain structure and function.

  14. Premier Li Keqiang and Indian Prime Minister Modi Attend Regional Forum

    Institute of Scientific and Technical Information of China (English)

    Zhang; Min

    2015-01-01

    The First Forum of Leaders of the Regions of China and India,cosponsored by the CPAFFC and the China International Friendship Cities Association(CIFCA),was held at the Great Hall of the People in Beijing on May 15.Chinese Premier Li Keqiang and his Indian counterpart Narendra Modi gave addresses.Premier Li expressed his congrat-

  15. Animal models for human genetic diseases

    African Journals Online (AJOL)

    Sharif Sons

    organisms are extensively used in applied research in agriculture, industry, and also in medicine, where they are ... in genetic disorder that is critical for embryonic .... by practical limitations and ethical concerns. ..... American journal of medical.

  16. A Mutation Model from First Principles of the Genetic Code.

    Science.gov (United States)

    Thorvaldsen, Steinar

    2016-01-01

    The paper presents a neutral Codons Probability Mutations (CPM) model of molecular evolution and genetic decay of an organism. The CPM model uses a Markov process with a 20-dimensional state space of probability distributions over amino acids. The transition matrix of the Markov process includes the mutation rate and those single point mutations compatible with the genetic code. This is an alternative to the standard Point Accepted Mutation (PAM) and BLOcks of amino acid SUbstitution Matrix (BLOSUM). Genetic decay is quantified as a similarity between the amino acid distribution of proteins from a (group of) species on one hand, and the equilibrium distribution of the Markov chain on the other. Amino acid data for the eukaryote, bacterium, and archaea families are used to illustrate how both the CPM and PAM models predict their genetic decay towards the equilibrium value of 1. A family of bacteria is studied in more detail. It is found that warm environment organisms on average have a higher degree of genetic decay compared to those species that live in cold environments. The paper addresses a new codon-based approach to quantify genetic decay due to single point mutations compatible with the genetic code. The present work may be seen as a first approach to use codon-based Markov models to study how genetic entropy increases with time in an effectively neutral biological regime. Various extensions of the model are also discussed.

  17. Statistical Inference of Biometrical Genetic Model With Cultural Transmission.

    Science.gov (United States)

    Guo, Xiaobo; Ji, Tian; Wang, Xueqin; Zhang, Heping; Zhong, Shouqiang

    2013-01-01

    Twin and family studies establish the foundation for studying the genetic, environmental and cultural transmission effects for phenotypes. In this work, we make use of the well established statistical methods and theory for mixed models to assess cultural transmission in twin and family studies. Specifically, we address two critical yet poorly understood issues: the model identifiability in assessing cultural transmission for twin and family data and the biases in the estimates when sub-models are used. We apply our models and theory to two real data sets. A simulation is conducted to verify the bias in the estimates of genetic effects when the working model is a sub-model.

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

    Institute of Scientific and Technical Information of China (English)

    Yu A-Long

    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.

  19. Genetic fuzzy system modeling and simulation of vascular behaviour

    DEFF Research Database (Denmark)

    Tang, Jiaowei; Boonen, Harrie C.M.

    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...... in principle for any physiological system that is characterized by auto-regulatory control and adaptation. Methods: Currently, one modeling approach is being investigated, Genetic Fuzzy System (GFS). In Genetic Fuzzy Systems, the model algorithm mimics the biologic genetic evolutionary process to learn...... chromosome or individual to define the fuzzy system. The model is implemented by combining the Matlab Genetic algorithm and Fuzzy system toolboxes, respectively. To test the performance of this method, experimental data sets about calculated pressure change in different blood vessels after several chemical...

  20. Multiple comparisons in genetic association studies: a hierarchical modeling approach.

    Science.gov (United States)

    Yi, Nengjun; Xu, Shizhong; Lou, Xiang-Yang; Mallick, Himel

    2014-02-01

    Multiple comparisons or multiple testing has been viewed as a thorny issue in genetic association studies aiming to detect disease-associated genetic variants from a large number of genotyped variants. We alleviate the problem of multiple comparisons by proposing a hierarchical modeling approach that is fundamentally different from the existing methods. The proposed hierarchical models simultaneously fit as many variables as possible and shrink unimportant effects towards zero. Thus, the hierarchical models yield more efficient estimates of parameters than the traditional methods that analyze genetic variants separately, and also coherently address the multiple comparisons problem due to largely reducing the effective number of genetic effects and the number of statistically "significant" effects. We develop a method for computing the effective number of genetic effects in hierarchical generalized linear models, and propose a new adjustment for multiple comparisons, the hierarchical Bonferroni correction, based on the effective number of genetic effects. Our approach not only increases the power to detect disease-associated variants but also controls the Type I error. We illustrate and evaluate our method with real and simulated data sets from genetic association studies. The method has been implemented in our freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/).

  1. Enterprise Projects Set Risk Element Transmission Chaotic Genetic Model

    Directory of Open Access Journals (Sweden)

    Cunbin Li

    2012-08-01

    Full Text Available In order to research projects set risk transfer process and improve risk management efficiency in projects management, combining chaos theory and genetic algorithm, put forward enterprise projects set risk element transmission chaos genetic model. Using logistic chaos mapping and chebyshev chaos mapping mixture, constructed a hybrid chaotic mapping system. The steps of adopting hybrid chaos mapping for genetic operation include projects set initialization, calculation of fitness, selection, crossover and mutation operators, fitness adjustment and condition judgment. The results showed that the model can simulate enterprise projects set risk transmission process very well and it also provides the basis for the enterprise managers to make decisions.

  2. The Neolithic transition in Europe: archaeological models and genetic evidence

    Directory of Open Access Journals (Sweden)

    Martin Richards

    2003-01-01

    Full Text Available The major pattern in the European gene pool is a southeast-northwest frequency gradient of classic genetic markers such as blood groups, which population geneticists initially attributed to the demographic impact of Neolithic farmers dispersing from the Near East. Molecular genetics has enriched this picture, with analyses of mitochondrial DNA and the Y chromosome allowing a more detailed exploration of alternative models for the spread of the Neolithic into Europe. This paper considers a range of possible models in the light of the detailed information now emerging from genetic studies.

  3. Yarn Strength Modelling Using Genetic Fuzzy Expert System

    Science.gov (United States)

    Banerjee, Debamalya; Ghosh, Anindya; Das, Subhasis

    2013-05-01

    This paper deals with the modelling of cotton yarn strength using genetic fuzzy expert system. Primarily a fuzzy expert system has been developed to model the cotton yarn strength from the constituent fibre parameters such as fibre strength, upper half mean length, fibre fineness and short fibre content. A binary coded genetic algorithm has been used to improve the prediction performance of the fuzzy expert system. The experimental validation confirms that the genetic fuzzy expert system has significantly better prediction accuracy and consistency than that of the fuzzy expert system.

  4. Transmission function models of finite population genetic algorithms

    NARCIS (Netherlands)

    Kemenade, C.H.M. van; Kok, J.N.; La Poutré, J.A.; Thierens, D.

    1998-01-01

    Infinite population models show a deterministic behaviour. Genetic algorithms with finite populations behave non-deterministicly. For small population sizes, the results obtained with these models differ strongly from the results predicted by the infinite population model. When the population size i

  5. Genetic programming-based chaotic time series modeling

    Institute of Scientific and Technical Information of China (English)

    张伟; 吴智铭; 杨根科

    2004-01-01

    This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust the parameters and takes them as the criteria of established models. Experiments showed the effectiveness of such improvements on chaotic time series modeling.

  6. NE TIGER Premieres New Hua Fu At Bird’s Nest

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    On the evening of September 25, China’s leading luxury fashion brand NE TIGER presented its premiere fashion show of Hua Fu(Chinese national dress) at a concert of superstars from China, Japan and South Korea,

  7. 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.

  8. 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.

  9. The Ising model in physics and statistical genetics.

    Science.gov (United States)

    Majewski, J; Li, H; Ott, J

    2001-10-01

    Interdisciplinary communication is becoming a crucial component of the present scientific environment. Theoretical models developed in diverse disciplines often may be successfully employed in solving seemingly unrelated problems that can be reduced to similar mathematical formulation. The Ising model has been proposed in statistical physics as a simplified model for analysis of magnetic interactions and structures of ferromagnetic substances. Here, we present an application of the one-dimensional, linear Ising model to affected-sib-pair (ASP) analysis in genetics. By analyzing simulated genetics data, we show that the simplified Ising model with only nearest-neighbor interactions between genetic markers has statistical properties comparable to much more complex algorithms from genetics analysis, such as those implemented in the Allegro and Mapmaker-Sibs programs. We also adapt the model to include epistatic interactions and to demonstrate its usefulness in detecting modifier loci with weak individual genetic contributions. A reanalysis of data on type 1 diabetes detects several susceptibility loci not previously found by other methods of analysis.

  10. A NEW GENETIC SIMULATED ANNEALING ALGORITHM FOR FLOOD ROUTING MODEL

    Institute of Scientific and Technical Information of China (English)

    KANG Ling; WANG Cheng; JIANG Tie-bing

    2004-01-01

    In this paper, a new approach, the Genetic Simulated Annealing (GSA), was proposed for optimizing the parameters in the Muskingum routing model. By integrating the simulated annealing method into the genetic algorithm, the hybrid method could avoid some troubles of traditional methods, such as arduous trial-and-error procedure, premature convergence in genetic algorithm and search blindness in simulated annealing. The principle and implementing procedure of this algorithm were described. Numerical experiments show that the GSA can adjust the optimization population, prevent premature convergence and seek the global optimal result.Applications to the Nanyunhe River and Qingjiang River show that the proposed approach is of higher forecast accuracy and practicability.

  11. Underground water quality model inversion of genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    MA Ruijie; LI Xin

    2009-01-01

    The underground water quality model with non-linear inversion problem is ill-posed, and boils down to solving the minimum of nonlinear function. Genetic algorithms are adopted in a number of individuals of groups by iterative search to find the optimal solution of the problem, the encoding strings as its operational objective, and achieving the iterative calculations by the genetic operators. It is an effective method of inverse problems of groundwater, with incomparable advantages and practical significances.

  12. Modeling evolution of insect resistance to genetically modified crops

    OpenAIRE

    2015-01-01

    Genetically modified crops producing insecticidal proteins from Bacillus thuringiensis (Bt) for insect control have been planted on more than 200 million ha worldwide since 1996 [1]. Evolution of resistance by insect pests threatens the continued success of Bt crops [2, 3]. To delay pest resistance, refuges of non-Bt crops are planted near Bt crops to allow survival of susceptible pests [4, 5]. We used computer simulations of a population genetic model to determine if predictions from the the...

  13. A Model of Genetic Variation in Human Social Networks

    CERN Document Server

    Fowler, James H; Christakis, Nicholas A

    2008-01-01

    Social networks influence the evolution of cooperation and they exhibit strikingly systematic patterns across a wide range of human contexts. Both of these facts suggest that variation in the topological attributes of human social networks might have a genetic basis. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a "mirror network" method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative "attract and introduce" model that generates significant heritability as well as other important network features, and we show that this model with two simple forms of heterogeneity is well suited to the modeling of real social networks in humans. These results suggest that natural selection ...

  14. 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...... 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....... The discrete time models used are multivariate variants of the discrete relative risk models. These models allow for regular parametric likelihood-based inference by exploring a coincidence of their likelihood functions and the likelihood functions of suitably defined multivariate generalized linear mixed...

  15. 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...... 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....... The discrete time models used are multivariate variants of the discrete relative risk models. These models allow for regular parametric likelihood-based inference by exploring a coincidence of their likelihood functions and the likelihood functions of suitably defined multivariate generalized linear mixed...

  16. 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

  17. Genetics of traffic assignment models for strategic transport planning

    NARCIS (Netherlands)

    Bliemer, M.C.J.; Raadsen, M.; Brederode, L.; Bell, M.; Wismans, L.J.J.; Smith, M.

    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

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

    NARCIS (Netherlands)

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

    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

  19. Genetic association in multivariate phenotypic data: power in five models

    NARCIS (Netherlands)

    Minica, C.C.; Boomsma, D.I.; van der Sluis, S.; Dolan, C.V.

    2010-01-01

    This article concerns the power of various data analytic strategies to detect the effect of a single genetic variant (GV) in multivariate data. We simulated exactly fitting monozygotic and dizygotic phenotypic data according to single and two common factor models, and simplex models. We calculated t

  20. Immune System Model Calibration by Genetic Algorithm

    NARCIS (Netherlands)

    Presbitero, A.; Krzhizhanovskaya, V.; Mancini, E.; Brands, R.; Sloot, P.

    2016-01-01

    We aim to develop a mathematical model of the human immune system for advanced individualized healthcare where medication plan is fine-tuned to fit a patient's conditions through monitored biochemical processes. One of the challenges is calibrating model parameters to satisfy existing experimental

  1. The quantitative genetics of indirect genetic effects: a selective review of modelling issues : Review

    NARCIS (Netherlands)

    Bijma, P.

    2014-01-01

    Indirect genetic effects (IGE) occur when the genotype of an individual affects the phenotypic trait value of another conspecific individual. IGEs can have profound effects on both the magnitude and the direction of response to selection. Models of inheritance and response to selection in traits sub

  2. [Improvement of genetics teaching using literature-based learning model].

    Science.gov (United States)

    Liang, Liang; Shiqian, Liang; Hongyan, Qin; Yong, Ji; Hua, Han

    2015-06-01

    Genetics is one of the most important courses for undergraduate students majoring in life science. In recent years, new knowledge and technologies are continually updated with deeper understanding of life science. However, the teaching model of genetics is still based on theoretical instruction, which makes the abstract principles hard to understand by students and directly affects the teaching effect. Thus, exploring a new teaching model is necessary. We have carried out a new teaching model, literature-based learning, in the course on Microbial Genetics for undergraduate students majoring in biotechnology since 2010. Here we comprehensively analyzed the implementation and application value of this model including pre-course knowledge, how to choose professional literature, how to organize teaching process and the significance of developing this new teaching model for students and teachers. Our literature-based learning model reflects the combination of "cutting-edge" and "classic" and makes book knowledge easy to understand, which improves students' learning effect, stimulates their interests, expands their perspectives and develops their ability. This practice provides novel insight into exploring new teaching model of genetics and cultivating medical talents capable of doing both basic and clinical research in the "precision medicine" era.

  3. Genetic variance of tolerance and the toxicant threshold model.

    Science.gov (United States)

    Tanaka, Yoshinari; Mano, Hiroyuki; Tatsuta, Haruki

    2012-04-01

    A statistical genetics method is presented for estimating the genetic variance (heritability) of tolerance to pollutants on the basis of a standard acute toxicity test conducted on several isofemale lines of cladoceran species. To analyze the genetic variance of tolerance in the case when the response is measured as a few discrete states (quantal endpoints), the authors attempted to apply the threshold character model in quantitative genetics to the threshold model separately developed in ecotoxicology. The integrated threshold model (toxicant threshold model) assumes that the response of a particular individual occurs at a threshold toxicant concentration and that the individual tolerance characterized by the individual's threshold value is determined by genetic and environmental factors. As a case study, the heritability of tolerance to p-nonylphenol in the cladoceran species Daphnia galeata was estimated by using the maximum likelihood method and nested analysis of variance (ANOVA). Broad-sense heritability was estimated to be 0.199 ± 0.112 by the maximum likelihood method and 0.184 ± 0.089 by ANOVA; both results implied that the species examined had the potential to acquire tolerance to this substance by evolutionary change.

  4. Modeling the MagnetoencephaloGram (MEG) Of Epileptic Patients Using Genetic Programming and Minimizing the Derived Models Using Genetic Algorithms

    Science.gov (United States)

    Theofilatos, Konstantinos; Georgopoulos, Efstratios; Likothanassis, Spiridon

    2009-09-01

    In this paper, a variation of traditional Genetic Programming(GP) is used to model the MagnetoencephaloGram(MEG) of Epileptic Patients. This variation is Linear Genetic Programming(LGP). LGP is a particular subset of GP wherein computer programs in population are represented as a sequence of instructions from imperative programming language or machine language. The derived models from this method were simplified using genetic algorithms. The proposed method was used to model the MEG signal of epileptic patients using 6 different datasets. Each dataset uses different number of previous values of MEG to predict the next value. The models were tested in datasets different from the ones which were used to produce them and the results were very promising.

  5. Predicting diabetic nephropathy using a multifactorial genetic model.

    Directory of Open Access Journals (Sweden)

    Ilana Blech

    Full Text Available AIMS: The tendency to develop diabetic nephropathy is, in part, genetically determined, however this genetic risk is largely undefined. In this proof-of-concept study, we tested the hypothesis that combined analysis of multiple genetic variants can improve prediction. METHODS: Based on previous reports, we selected 27 SNPs in 15 genes from metabolic pathways involved in the pathogenesis of diabetic nephropathy and genotyped them in 1274 Ashkenazi or Sephardic Jewish patients with Type 1 or Type 2 diabetes of >10 years duration. A logistic regression model was built using a backward selection algorithm and SNPs nominally associated with nephropathy in our population. The model was validated by using random "training" (75% and "test" (25% subgroups of the original population and by applying the model to an independent dataset of 848 Ashkenazi patients. RESULTS: The logistic model based on 5 SNPs in 5 genes (HSPG2, NOS3, ADIPOR2, AGER, and CCL5 and 5 conventional variables (age, sex, ethnicity, diabetes type and duration, and allowing for all possible two-way interactions, predicted nephropathy in our initial population (C-statistic = 0.672 better than a model based on conventional variables only (C = 0.569. In the independent replication dataset, although the C-statistic of the genetic model decreased (0.576, it remained highly associated with diabetic nephropathy (χ(2 = 17.79, p<0.0001. In the replication dataset, the model based on conventional variables only was not associated with nephropathy (χ(2 = 3.2673, p = 0.07. CONCLUSION: In this proof-of-concept study, we developed and validated a genetic model in the Ashkenazi/Sephardic population predicting nephropathy more effectively than a similarly constructed non-genetic model. Further testing is required to determine if this modeling approach, using an optimally selected panel of genetic markers, can provide clinically useful prediction and if generic models can be

  6. Model-free Estimation of Recent Genetic Relatedness

    Science.gov (United States)

    Conomos, Matthew P.; Reiner, Alexander P.; Weir, Bruce S.; Thornton, Timothy A.

    2016-01-01

    Genealogical inference from genetic data is essential for a variety of applications in human genetics. In genome-wide and sequencing association studies, for example, accurate inference on both recent genetic relatedness, such as family structure, and more distant genetic relatedness, such as population structure, is necessary for protection against spurious associations. Distinguishing familial relatedness from population structure with genotype data, however, is difficult because both manifest as genetic similarity through the sharing of alleles. Existing approaches for inference on recent genetic relatedness have limitations in the presence of population structure, where they either (1) make strong and simplifying assumptions about population structure, which are often untenable, or (2) require correct specification of and appropriate reference population panels for the ancestries in the sample, which might be unknown or not well defined. Here, we propose PC-Relate, a model-free approach for estimating commonly used measures of recent genetic relatedness, such as kinship coefficients and IBD sharing probabilities, in the presence of unspecified structure. PC-Relate uses principal components calculated from genome-screen data to partition genetic correlations among sampled individuals due to the sharing of recent ancestors and more distant common ancestry into two separate components, without requiring specification of the ancestral populations or reference population panels. In simulation studies with population structure, including admixture, we demonstrate that PC-Relate provides accurate estimates of genetic relatedness and improved relationship classification over widely used approaches. We further demonstrate the utility of PC-Relate in applications to three ancestrally diverse samples that vary in both size and genealogical complexity. PMID:26748516

  7. Genetic Algorithm Modeling with GPU Parallel Computing Technology

    CERN Document Server

    Cavuoti, Stefano; Brescia, Massimo; Pescapé, Antonio; Longo, Giuseppe; Ventre, Giorgio

    2012-01-01

    We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel computing technology. The model was derived from a multi-core CPU serial implementation, named GAME, already scientifically successfully tested and validated on astrophysical massive data classification problems, through a web application resource (DAMEWARE), specialized in data mining based on Machine Learning paradigms. Since genetic algorithms are inherently parallel, the GPGPU computing paradigm has provided an exploit of the internal training features of the model, permitting a strong optimization in terms of processing performances and scalability.

  8. Genetics

    Science.gov (United States)

    ... Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...

  9. International Genetically Engineered Machine (iGEM) Competition

    CSIR Research Space (South Africa)

    Sparrow, RW

    2010-07-01

    Full Text Available iGEM, the International Genetically Engineered Machine competition, is an initiative from MIT and has become the premiere undergraduate synthetic biology competition. The competing teams consist of students who work on a synthetic biology project...

  10. Dissecting genetic and environmental mutation signatures with model organisms.

    Science.gov (United States)

    Segovia, Romulo; Tam, Annie S; Stirling, Peter C

    2015-08-01

    Deep sequencing has impacted on cancer research by enabling routine sequencing of genomes and exomes to identify genetic changes associated with carcinogenesis. Researchers can now use the frequency, type, and context of all mutations in tumor genomes to extract mutation signatures that reflect the driving mutational processes. Identifying mutation signatures, however, may not immediately suggest a mechanism. Consequently, several recent studies have employed deep sequencing of model organisms exposed to discrete genetic or environmental perturbations. These studies exploit the simpler genomes and availability of powerful genetic tools in model organisms to analyze mutation signatures under controlled conditions, forging mechanistic links between mutational processes and signatures. We discuss the power of this approach and suggest that many such studies may be on the horizon.

  11. Developmental genetics in emerging rodent models: case studies and perspectives.

    Science.gov (United States)

    Mallarino, Ricardo; Hoekstra, Hopi E; Manceau, Marie

    2016-08-01

    For decades, mammalian developmental genetic studies have focused almost entirely on two laboratory models: Mus and Rattus, species that breed readily in the laboratory and for which a wealth of molecular and genetic resources exist. These species alone, however, do not capture the remarkable diversity of morphological, behavioural and physiological traits seen across rodents, a group that represents >40% of all mammal species. Due to new advances in molecular tools and genomic technologies, studying the developmental events underlying natural variation in a wide range of species for a wide range of traits has become increasingly feasible. Here we review several recent studies and discuss how they not only provided technical resources for newly emerging rodent models in developmental genetics but also are instrumental in further encouraging scientists, from a wide range of research fields, to capitalize on the great diversity in development that has evolved among rodents.

  12. Genetic programming-based chaotic time series modeling

    Institute of Scientific and Technical Information of China (English)

    张伟; 吴智铭; 杨根科

    2004-01-01

    This paper proposes a Genetic Programming-Based Modeling(GPM)algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space,and the Particle Swarm Optimization(PSO)algorithm is used for Nonlinear Parameter Estimation(NPE)of dynamic model structures. In addition,GPM integrates the results of Nonlinear Time Series Analysis(NTSA)to adjust the parameters and takes them as the criteria of established models.Experiments showed the effectiveness of such improvements on chaotic time series modeling.

  13. Relationship between Game Location and Match Result with the Amount of Aggression: Iranian Premier League Football Teams

    Directory of Open Access Journals (Sweden)

    Farhad Alahvisi

    2015-12-01

    Full Text Available The purpose of this study was to investigate the relationship between game location (host advantage, match result (win, lose or tie and the level of aggression in football teams of the Iranian Premier League. The study population consisted of Premier League Football teams (League XIII, and 60 matches (related to 4 teams that were available for the researcher, were selected as the sample. The current study can be regarded as applied and descriptive, in terms of purpose and data collection, respectively. In order to collect data, the match videos of selected teams were studied, then the results of the observations were written and recorded using Roberts et al. (1999 aggression model. The results showed that no significant difference was found between teams' aggression in host and guest matches (p>0.05. Also, a significant difference was observed between aggression and match result and the behaviors were more in lost matches (p< 0.05. In fact, mental stress caused by the loss resulted to more aggression to win. Hence, a match result, physical aggression and players' position led to significant difference in players' aggression. Therefore, the control and management of aggressive behaviors, especially at the time of failure will result in improved performance and efficiency of football teams. Also, these behaviors can be minimized by providing necessary training on anger management and negative emotions control among players.

  14. Genetic signatures of natural selection in a model invasive ascidian

    Science.gov (United States)

    Lin, Yaping; Chen, Yiyong; Yi, Changho; Fong, Jonathan J.; Kim, Won; Rius, Marc; Zhan, Aibin

    2017-01-01

    Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta. PMID:28266616

  15. Unraveling the genetics of chronic kidney disease using animal models

    NARCIS (Netherlands)

    Korstanje, Ron; DiPetrillo, K.

    2004-01-01

    Identifying genes underlying common forms of kidney disease in humans has proven difficult, expensive, and time consuming. Quantitative trait loci (QTL) for several complex traits are concordant among mice, rats, and humans, suggesting that genetic findings from these animal models are relevant to

  16. Noninvasive transcranial direct current stimulation in a genetic absence model

    NARCIS (Netherlands)

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

    2013-01-01

    The proposed area of onset for absence epilepsy characteristic of spontaneously occurring spike and slow-wave discharges (SWDs) in the genetic absence rat model is the subgranular layer of the somatosensory cortex. Modulation of the hyperexcitable cortical foci by bilateral transcranial direct curre

  17. Sparse time series chain graphical models for reconstructing genetic networks

    NARCIS (Netherlands)

    Abegaz, Fentaw; Wit, Ernst

    2013-01-01

    We propose a sparse high-dimensional time series chain graphical model for reconstructing genetic networks from gene expression data parametrized by a precision matrix and autoregressive coefficient matrix. We consider the time steps as blocks or chains. The proposed approach explores patterns of co

  18. The influence of situational variables on ball possession in the English Premier League.

    Science.gov (United States)

    Bradley, Paul Simon; Lago-Peñas, Carlos; Rey, Ezequiel; Sampaio, Jaime

    2014-12-01

    Abstract The aims of this study were twofold: (1) to examine the influence of situational variables on ball possession in elite soccer and (2) to quantify the variables that discriminate between high or low percentage ball possession teams (HPBPT and LPBPT) across different playing positions. Match performance data were collected from English Premier League matches using a multiple-camera system. Data were examined using linear regression, a 2 × 5 factorial analysis of variance and discriminant analysis. Playing against weak opposition was associated with an increase (P variables (P variables that discriminated performance between HPBPT and LPBPT were different for various playing positions, although the number of successful passes was the most common discriminating variable. The results demonstrate that HPBPT and LPBPT developed different possession strategies during matches and that selected variables such as successful passes were identified to explain these data trends across various playing positions. Combinations of variables could be used to develop a probabilistic model for predicting time spent in possession by teams.

  19. 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.

  20. From classical genetics to quantitative genetics to systems biology: modeling epistasis.

    Directory of Open Access Journals (Sweden)

    David L Aylor

    2008-03-01

    Full Text Available Gene expression data has been used in lieu of phenotype in both classical and quantitative genetic settings. These two disciplines have separate approaches to measuring and interpreting epistasis, which is the interaction between alleles at different loci. We propose a framework for estimating and interpreting epistasis from a classical experiment that combines the strengths of each approach. A regression analysis step accommodates the quantitative nature of expression measurements by estimating the effect of gene deletions plus any interaction. Effects are selected by significance such that a reduced model describes each expression trait. We show how the resulting models correspond to specific hierarchical relationships between two regulator genes and a target gene. These relationships are the basic units of genetic pathways and genomic system diagrams. Our approach can be extended to analyze data from a variety of experiments, multiple loci, and multiple environments.

  1. The significance of genetics in pathophysiologic models of premature birth.

    Science.gov (United States)

    Uberos, Jose

    2017-05-31

    Prematurity is a major health problem in all countries, especially in certain ethic groups and increasing recurrence imply the influence of genetic factors. Published genetic polymorphisms are identified in relation to the 4 pathophysiological models of prematurity described: Chorioamniotic-decidual inflammation, premature contraction pathway, decidual haemorrhage and susceptibility to environmental toxins. 240 articles are identified, 52 articles are excluded because they are not original, not written in English or duplicated. From them 125 articles were included in qualitative analysis This review aims to update recent knowledge about genes associated with premature birth.

  2. Canalization and symmetry in Boolean models for genetic regulatory networks

    Energy Technology Data Exchange (ETDEWEB)

    Reichhardt, C J Olson [Theoretical Division and Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Bassler, Kevin E [Department of Physics, University of Houston, Houston, TX 77204-5005 (United States)

    2007-04-20

    Canalization of genetic regulatory networks has been argued to be favoured by evolutionary processes due to the stability that it can confer to phenotype expression. We explore whether a significant amount of canalization and partial canalization can arise in purely random networks in the absence of evolutionary pressures. We use a mapping of the Boolean functions in the Kauffman N-K model for genetic regulatory networks onto a k-dimensional Ising hypercube (where k = K) to show that the functions can be divided into different classes strictly due to geometrical constraints. The classes can be counted and their properties determined using results from group theory and isomer chemistry. We demonstrate that partially canalizing functions completely dominate all possible Boolean functions, particularly for higher k. This indicates that partial canalization is extremely common, even in randomly chosen networks, and has implications for how much information can be obtained in experiments on native state genetic regulatory networks.

  3. Fuzzy Modelling of Knee Joint with Genetic Optimization

    Directory of Open Access Journals (Sweden)

    B. S. K. K. Ibrahim

    2011-01-01

    Full Text Available Modelling of joint properties of lower limbs in people with spinal cord injury is significantly challenging for researchers due to the complexity of the system. The objective of this study is to develop a knee joint model capable of relating electrical parameters to dynamic joint torque as well as knee angle for functional electrical stimulation application. The joint model consists of a segmental dynamic, time-invariant passive properties and uncertain time-variant active properties. The knee joint model structure comprising optimised equations of motion and fuzzy models to represent the passive viscoelasticity and active muscle properties is formulated. The model thus formulated is optimised using genetic optimization, and validated against experimental data. The developed model can be used for simulation of joint movements as well as for control development. The results show that the model developed gives an accurate dynamic characterisation of the knee joint.

  4. Learning with Admixture: Modeling, Optimization, and Applications in Population Genetics

    DEFF Research Database (Denmark)

    Cheng, Jade Yu

    2016-01-01

    Population genetics is a branch of applied mathematics. It is a translation of scientific observations into mathematical models and their manipulations in order to produce quantitative predictions about evolution. Combining knowledge from genetics, statistics, and computer science, population...... data. Ohana's admixture module is based on classical structure modeling but uses new optimization subroutines through quadratic programming, which outperform the current state-of-the-art software in both speed and accuracy. Ohana presents a new method for phylogenetic tree inference using Gaussian...... the foundation for both CoalHMM and Ohana. Optimization modeling has been the main theme throughout my PhD, and it will continue to shape my work for the years to come. The algorithms and software I developed to study historical admixture and population evolution fall into a larger family of machine learning...

  5. 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

  6. [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.

  7. A unified model of the standard genetic code.

    Science.gov (United States)

    José, Marco V; Zamudio, Gabriel S; Morgado, Eberto R

    2017-03-01

    The Rodin-Ohno (RO) and the Delarue models divide the table of the genetic code into two classes of aminoacyl-tRNA synthetases (aaRSs I and II) with recognition from the minor or major groove sides of the tRNA acceptor stem, respectively. These models are asymmetric but they are biologically meaningful. On the other hand, the standard genetic code (SGC) can be derived from the primeval RNY code (R stands for purines, Y for pyrimidines and N any of them). In this work, the RO-model is derived by means of group actions, namely, symmetries represented by automorphisms, assuming that the SGC originated from a primeval RNY code. It turns out that the RO-model is symmetric in a six-dimensional (6D) hypercube. Conversely, using the same automorphisms, we show that the RO-model can lead to the SGC. In addition, the asymmetric Delarue model becomes symmetric by means of quotient group operations. We formulate isometric functions that convert the class aaRS I into the class aaRS II and vice versa. We show that the four polar requirement categories display a symmetrical arrangement in our 6D hypercube. Altogether these results cannot be attained, neither in two nor in three dimensions. We discuss the present unified 6D algebraic model, which is compatible with both the SGC (based upon the primeval RNY code) and the RO-model.

  8. Genetic variants associated with neurodegenerative Alzheimer disease in natural models.

    Science.gov (United States)

    Salazar, Claudia; Valdivia, Gonzalo; Ardiles, Álvaro O; Ewer, John; Palacios, Adrián G

    2016-02-26

    The use of transgenic models for the study of neurodegenerative diseases has made valuable contributions to the field. However, some important limitations, including protein overexpression and general systemic compensation for the missing genes, has caused researchers to seek natural models that show the main biomarkers of neurodegenerative diseases during aging. Here we review some of these models-most of them rodents, focusing especially on the genetic variations in biomarkers for Alzheimer diseases, in order to explain their relationships with variants associated with the occurrence of the disease in humans.

  9. 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…

  10. 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…

  11. Genetic Mouse Models of Huntington's Disease: Focus on Electrophysiological Mechanisms

    Directory of Open Access Journals (Sweden)

    Carlos Cepeda

    2010-03-01

    Full Text Available The discovery of the HD (Huntington's disease gene in 1993 led to the creation of genetic mouse models of the disease and opened the doors for mechanistic studies. In particular, the early changes and progression of the disease could be followed and examined systematically. The present review focuses on the contribution of these genetic mouse models to the understanding of functional changes in neurons as the HD phenotype progresses, and concentrates on two brain areas: the striatum, the site of most conspicuous pathology in HD, and the cortex, a site that is becoming increasingly important in understanding the widespread behavioural abnormalities. Mounting evidence points to synaptic abnormalities in communication between the cortex and striatum and cell-cell interactions as major determinants of HD symptoms, even in the absence of severe neuronal degeneration and death.

  12. Exchange Rate Prediction using Neural – Genetic Model

    Directory of Open Access Journals (Sweden)

    MECHGOUG Raihane

    2012-10-01

    Full Text Available Neural network have successfully used for exchange rate forecasting. However, due to a large number of parameters to be estimated empirically, it is not a simple task to select the appropriate neural network architecture for exchange rate forecasting problem.Researchers often overlook the effect of neural network parameters on the performance of neural network forecasting. The performance of neural network is critically dependant on the learning algorithms, thenetwork architecture and the choice of the control parameters. Even when a suitable setting of parameters (weight can be found, the ability of the resulting network to generalize the data not seen during learning may be far from optimal. For these reasons it seemslogical and attractive to apply genetic algorithms. Genetic algorithms may provide a useful tool for automating the design of neural network. The empirical results on foreign exchange rate prediction indicate that the proposed hybrid model exhibits effectively improved accuracy, when is compared with some other time series forecasting models.

  13. A Building Model Framework for a Genetic Algorithm Multi-objective Model Predictive Control

    DEFF Research Database (Denmark)

    Arendt, Krzysztof; Ionesi, Ana; Jradi, Muhyiddine

    2016-01-01

    implemented only in few buildings. The following difficulties hinder the widespread usage of MPC: (1) significant model development time, (2) limited portability of models, (3) model computational demand. In the present study a new model development framework for an MPC system based on a Genetic Algorithm (GA...

  14. Inferring modulators of genetic interactions with epistatic nested effects models.

    Science.gov (United States)

    Pirkl, Martin; Diekmann, Madeline; van der Wees, Marlies; Beerenwinkel, Niko; Fröhlich, Holger; Markowetz, Florian

    2017-04-01

    Maps of genetic interactions can dissect functional redundancies in cellular networks. Gene expression profiles as high-dimensional molecular readouts of combinatorial perturbations provide a detailed view of genetic interactions, but can be hard to interpret if different gene sets respond in different ways (called mixed epistasis). Here we test the hypothesis that mixed epistasis between a gene pair can be explained by the action of a third gene that modulates the interaction. We have extended the framework of Nested Effects Models (NEMs), a type of graphical model specifically tailored to analyze high-dimensional gene perturbation data, to incorporate logical functions that describe interactions between regulators on downstream genes and proteins. We benchmark our approach in the controlled setting of a simulation study and show high accuracy in inferring the correct model. In an application to data from deletion mutants of kinases and phosphatases in S. cerevisiae we show that epistatic NEMs can point to modulators of genetic interactions. Our approach is implemented in the R-package 'epiNEM' available from https://github.com/cbg-ethz/epiNEM and https://bioconductor.org/packages/epiNEM/.

  15. Modelling genetic susceptibility to multiple sclerosis with family data.

    Science.gov (United States)

    O'Gorman, Cullen; Lin, Rui; Stankovich, James; Broadley, Simon A

    2013-01-01

    A genetic contribution to susceptibility is well established in multiple sclerosis (MS) and 57 associated genetic loci have been identified. We have undertaken a meta-analysis of familial risk studies with the aims of providing definitive figures for risks to relatives, performing a segregation analysis and estimating the proportion of the overall genetic risk that currently identified genes represent. We have used standard methods of meta-analysis combined with novel approaches to age adjustment to provide directly comparable estimates of lifetime risk. The overall recurrence risk for monozygotic twins was 18.2% and for siblings 2.7%. The recurrence risk for dizygotic twins was significantly higher than for siblings. The overall estimate of sibling relative risk (λ(S)) was 16.8. Risks for older relatives (parents, siblings, aunts, uncles and cousins) show a latitudinal gradient, in line with population risk. No latitudinal gradient for λ(S) was seen. Segregation analysis supports a multiplicative model of one locus of moderate effect with many loci of small effect. The estimated contribution of the 57 known MS loci is 18-24% of λ(S). This meta-analysis supports the notion of MS being in part the result of multiple genetic susceptibility factors and environmental factors.

  16. The 2014 presidential elections and their impact on the premier-presidential regime in Romania

    Directory of Open Access Journals (Sweden)

    Ionela Gavril

    2015-03-01

    Full Text Available First, we will demonstrate that, from an institutional perspective, Romania can labeled of premier-presidentialism regime, but the 2004 and 2009 elections have had a strong impact on the type of regime, meaning that several extra-constitutional factors led to the malfunction of the regime. Out of a total of 15 prime-minister nominations made after 1989, 8 can be considered deviations from the premier-presidential regime, their number being larger between 2004-2014 rather than in 1990-2000. The empirical analysis of the 2004-2014 period, highlighted three extra-constitutional factors that that made the premier-presidential regime be, in fact, a malfunctioning one: leadership style, crisis situations and the recent legitimacy of the president versus the parliament. By identifying the factors that influenced the regime type, we can determine some theoretical expectations following the 2014 elections. The success of a premier-presidentialism regime in Romania will be determined by the number of deviations from such a regime registered after the 2014 elections.

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

    NARCIS (Netherlands)

    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 replacem

  18. Vice Premier Zeng Peiyan Meets with Michael Cohrs, CEO of Corporate & Investment Banking of Deutsche Bank

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    <正>Invited by the CPAFFC, Michael Cohrs, Chief Executive Officer of the Corporate and Investment Banking of Deutsche Bank, visited Beijing from February 26 to 28, 2004. Vice Premier Zeng Peiyan of the State Council met with Cohrs and his party. Deutsche Bank AG, a global multipurpose bank

  19. 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

  20. Profil de l'etudiant du premier cycle des etudes medicales de Lome ...

    African Journals Online (AJOL)

    Profil de l'etudiant du premier cycle des etudes medicales de Lome et sa perception de l'enseignement de l'anatomie. ... Journal de la Recherche Scientifique de l'Universite de Lome ... aux différentes questions des paramètres étudiés.

  1. Premiere of TV Documentary Choe Chi-won Held in Beijing

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    <正>The premiere of the TV documentary Choe Chi-won was held in Beijing on August 19. The TV documentary,a joint production by the CPAFFC,the Jiangsu Provincial Association for Cultural Exchange with Foreign Countries,the

  2. A Software Pattern of the Genetic Algorithm -a Study on Reusable Object Model of Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The Genetic Algorithm (GA) has been a pop research field, butthere is little concern on GA in view of Software Engineering and this result in a serie s of problems. In this paper, we extract a GA's software pattern, draw a model d iagram of the reusable objects, analyze the advantages and disadvantages of the pattern, and give a sample code at the end. We are then able to improve the reus ability and expansibility of GA. The results make it easier to program a new GA code by using some existing successful operators, thereby reducing the difficult ies and workload of programming a GA's code, and facilitate the GA application.

  3. Exploratory Bayesian model selection for serial genetics data.

    Science.gov (United States)

    Zhao, Jing X; Foulkes, Andrea S; George, Edward I

    2005-06-01

    Characterizing the process by which molecular and cellular level changes occur over time will have broad implications for clinical decision making and help further our knowledge of disease etiology across many complex diseases. However, this presents an analytic challenge due to the large number of potentially relevant biomarkers and the complex, uncharacterized relationships among them. We propose an exploratory Bayesian model selection procedure that searches for model simplicity through independence testing of multiple discrete biomarkers measured over time. Bayes factor calculations are used to identify and compare models that are best supported by the data. For large model spaces, i.e., a large number of multi-leveled biomarkers, we propose a Markov chain Monte Carlo (MCMC) stochastic search algorithm for finding promising models. We apply our procedure to explore the extent to which HIV-1 genetic changes occur independently over time.

  4. Hierarchical Stochastic Simulation Algorithm for SBML Models of Genetic Circuits

    Directory of Open Access Journals (Sweden)

    Leandro eWatanabe

    2014-11-01

    Full Text Available This paper describes a hierarchical stochastic simulation algorithm which has been implemented within iBioSim, a tool used to model, analyze, and visualize genetic circuits. Many biological analysis tools flatten out hierarchy before simulation, but there are many disadvantages associated with this approach. First, the memory required to represent the model can quickly expand in the process. Second, the flattening process is computationally expensive. Finally, when modeling a dynamic cellular population within iBioSim, inlining the hierarchy of the model is inefficient since models must grow dynamically over time. This paper discusses a new approach to handle hierarchy on the fly to make the tool faster and more memory-efficient. This approach yields significant performance improvements as compared to the former flat analysis method.

  5. 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.

  6. Genetic Programming Modeling and Complexity Analysis of the Magnetoencephalogram of Epileptic Patients

    Science.gov (United States)

    Georgopoulos, Efstratios F.; Adamopoulos, Adam V.; Likothanassis, Spiridon D.

    In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients are modeled using a genetic programming approach. This is the first time that genetic programming is used to model MEG signal. Numerous experiments were conducted giving highly successful results. It is demonstrated that genetic programming can produce very simple nonlinear models that fit with great accuracy the observed data of MEG.

  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 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.

  9. Model reduction using the genetic algorithm and routh approximations

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    A new method of model reduction combining the genetic algorithm(GA) with the Routh approximation method is presented. It is suggested that a high-order system can be approximated by a low-order model with a time delay. The denominator parameters of the reduced-order model are determined by the Routh approximation method, then the numerator parameters and time delay are identified by the GA. The reduced-order models obtained by the proposed method will always be stable if the original system is stable and produce a good approximation to the original system in both the frequency domain and time domain. Two numerical examples show that the method is computationally simple and efficient.

  10. Genetic diversity in the SIR model of pathogen evolution.

    Science.gov (United States)

    Gordo, Isabel; Gomes, M Gabriela M; Reis, Daniel G; Campos, Paulo R A

    2009-01-01

    We introduce a model for assessing the levels and patterns of genetic diversity in pathogen populations, whose epidemiology follows a susceptible-infected-recovered model (SIR). We model the population of pathogens as a metapopulation composed of subpopulations (infected hosts), where pathogens replicate and mutate. Hosts transmit pathogens to uninfected hosts. We show that the level of pathogen variation is well predicted by analytical expressions, such that pathogen neutral molecular variation is bounded by the level of infection and increases with the duration of infection. We then introduce selection in the model and study the invasion probability of a new pathogenic strain whose fitness (R(0)(1+s)) is higher than the fitness of the resident strain (R(0)). We show that this invasion probability is given by the relative increment in R(0) of the new pathogen (s). By analyzing the patterns of genetic diversity in this framework, we identify the molecular signatures during the replacement and compare these with those observed in sequences of influenza A.

  11. Genetic diversity in the SIR model of pathogen evolution.

    Directory of Open Access Journals (Sweden)

    Isabel Gordo

    Full Text Available We introduce a model for assessing the levels and patterns of genetic diversity in pathogen populations, whose epidemiology follows a susceptible-infected-recovered model (SIR. We model the population of pathogens as a metapopulation composed of subpopulations (infected hosts, where pathogens replicate and mutate. Hosts transmit pathogens to uninfected hosts. We show that the level of pathogen variation is well predicted by analytical expressions, such that pathogen neutral molecular variation is bounded by the level of infection and increases with the duration of infection. We then introduce selection in the model and study the invasion probability of a new pathogenic strain whose fitness (R(0(1+s is higher than the fitness of the resident strain (R(0. We show that this invasion probability is given by the relative increment in R(0 of the new pathogen (s. By analyzing the patterns of genetic diversity in this framework, we identify the molecular signatures during the replacement and compare these with those observed in sequences of influenza A.

  12. 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.

  13. Gravitational Lens Modeling with Genetic Algorithms and Particle Swarm Optimizers

    CERN Document Server

    Rogers, Adam

    2011-01-01

    Strong gravitational lensing of an extended object is described by a mapping from source to image coordinates that is nonlinear and cannot generally be inverted analytically. Determining the structure of the source intensity distribution also requires a description of the blurring effect due to a point spread function. This initial study uses an iterative gravitational lens modeling scheme based on the semilinear method to determine the linear parameters (source intensity profile) of a strongly lensed system. Our 'matrix-free' approach avoids construction of the lens and blurring operators while retaining the least squares formulation of the problem. The parameters of an analytical lens model are found through nonlinear optimization by an advanced genetic algorithm (GA) and particle swarm optimizer (PSO). These global optimization routines are designed to explore the parameter space thoroughly, mapping model degeneracies in detail. We develop a novel method that determines the L-curve for each solution automa...

  14. In vivo Drosophilia genetic model for calcium oxalate nephrolithiasis.

    Science.gov (United States)

    Hirata, Taku; Cabrero, Pablo; Berkholz, Donald S; Bondeson, Daniel P; Ritman, Erik L; Thompson, James R; Dow, Julian A T; Romero, Michael F

    2012-12-01

    Nephrolithiasis is a major public health problem with a complex and varied etiology. Most stones are composed of calcium oxalate (CaOx), with dietary excess a risk factor. Because of complexity of mammalian system, the details of stone formation remain to be understood. Here we have developed a nephrolithiasis model using the genetic model Drosophila melanogaster, which has a simple, transparent kidney tubule. Drosophilia reliably develops CaOx stones upon dietary oxalate supplementation, and the nucleation and growth of microliths can be viewed in real time. The Slc26 anion transporter dPrestin (Slc26a5/6) is strongly expressed in Drosophilia kidney, and biophysical analysis shows that it is a potent oxalate transporter. When dPrestin is knocked down by RNAi in fly kidney, formation of microliths is reduced, identifying dPrestin as a key player in oxalate excretion. CaOx stone formation is an ancient conserved process across >400 My of divergent evolution (fly and human), and from this study we can conclude that the fly is a good genetic model of nephrolithiasis.

  15. The ontology of genetic susceptibility factors (OGSF) and its application in modeling genetic susceptibility to vaccine adverse events.

    Science.gov (United States)

    Lin, Yu; He, Yongqun

    2014-01-01

    Due to human variations in genetic susceptibility, vaccination often triggers adverse events in a small population of vaccinees. Based on our previous work on ontological modeling of genetic susceptibility to disease, we developed an Ontology of Genetic Susceptibility Factors (OGSF), a biomedical ontology in the domain of genetic susceptibility and genetic susceptibility factors. The OGSF framework was then applied in the area of vaccine adverse events (VAEs). OGSF aligns with the Basic Formal Ontology (BFO). OGSF defines 'genetic susceptibility' as a subclass of BFO:disposition and has a material basis 'genetic susceptibility factor'. The 'genetic susceptibility to pathological bodily process' is a subclasses of 'genetic susceptibility'. A VAE is a type of pathological bodily process. OGSF represents different types of genetic susceptibility factors including various susceptibility alleles (e.g., SNP and gene). A general OGSF design pattern was developed to represent genetic susceptibility to VAE and associated genetic susceptibility factors using experimental results in genetic association studies. To test and validate the design pattern, two case studies were populated in OGSF. In the first case study, human gene allele DBR*15:01 is susceptible to influenza vaccine Pandemrix-induced Multiple Sclerosis. The second case study reports genetic susceptibility polymorphisms associated with systemic smallpox VAEs. After the data of the Case Study 2 were represented using OGSF-based axioms, SPARQL was successfully developed to retrieve the susceptibility factors stored in the populated OGSF. A network of data from the Case Study 2 was constructed by using ontology terms and individuals as nodes and ontology relations as edges. Different social network analys is (SNA) methods were then applied to verify core OGSF terms. Interestingly, a SNA hub analysis verified all susceptibility alleles of SNPs and a SNA closeness analysis verified the susceptibility genes in Case

  16. Epidemic Modelling by Ripple-Spreading Network and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Jian-Qin Liao

    2013-01-01

    Full Text Available Mathematical analysis and modelling is central to infectious disease epidemiology. This paper, inspired by the natural ripple-spreading phenomenon, proposes a novel ripple-spreading network model for the study of infectious disease transmission. The new epidemic model naturally has good potential for capturing many spatial and temporal features observed in the outbreak of plagues. In particular, using a stochastic ripple-spreading process simulates the effect of random contacts and movements of individuals on the probability of infection well, which is usually a challenging issue in epidemic modeling. Some ripple-spreading related parameters such as threshold and amplifying factor of nodes are ideal to describe the importance of individuals’ physical fitness and immunity. The new model is rich in parameters to incorporate many real factors such as public health service and policies, and it is highly flexible to modifications. A genetic algorithm is used to tune the parameters of the model by referring to historic data of an epidemic. The well-tuned model can then be used for analyzing and forecasting purposes. The effectiveness of the proposed method is illustrated by simulation results.

  17. 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.

  18. 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…

  19. 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…

  20. Calibration of Uncertainty Analysis of the SWAT Model Using Genetic Algorithms and Bayesian Model Averaging

    Science.gov (United States)

    In this paper, the Genetic Algorithms (GA) and Bayesian model averaging (BMA) were combined to simultaneously conduct calibration and uncertainty analysis for the Soil and Water Assessment Tool (SWAT). In this hybrid method, several SWAT models with different structures are first selected; next GA i...

  1. 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.......01), attackers (2341 m, s=575, P game, high-intensity running distance was approximately 20% less than in the first 15-min period for wide midfielders (467 m, s=104 vs. 589 m, s=134, P ....01) and without ball possession (229 m, s=85 vs. 278 m, s=97, P game. Mean recovery time between very high-intensity running bouts was 72 s (s=28), with a 28% longer recovery time during the last 15 min than the first 15 min of the game (83 s, s=26 vs...

  2. Constructing the barley model for genetic transformation in Triticeae

    Institute of Scientific and Technical Information of China (English)

    LÜ Bo; WU Jia-jie; FU Dao-lin

    2015-01-01

    Barley (Hordeum vulgare L.) is one of the oldest domesticated crops, showing dramatic adaptation to various climate and environmental conditions. As a major cereal crop, barley ranks the 4th after wheat, maize and rice in terms of planting area and production al over the world. Due to its diploid nature, the cultivated barley is considered as an ideal model to study the polyploid wheat and other Triticeae species. Here, we reviewed the development, optimization, and application of transgenic approaches in barley. The most efifcient and robust genetic transformation has been built on the Agrobacterium-mediated transfer in conjunction with the immature embryo-based regeneration. We then discussed future considerations of using more practical technologies in barley transformation, such as the T-DNA/transposon tagging and the genome editing. As a cereal crop amenable to genetic transformation, barley wil serve as the most valuable carrier for global functional genomics in Triticeae and is becoming the most practical model for generating value-added products.

  3. Mathematical Modeling of Intestinal Iron Absorption Using Genetic Programming

    Science.gov (United States)

    Colins, Andrea; Gerdtzen, Ziomara P.; Nuñez, Marco T.; Salgado, J. Cristian

    2017-01-01

    Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex

  4. Integer programming model for optimizing bus timetable using genetic algorithm

    Science.gov (United States)

    Wihartiko, F. D.; Buono, A.; Silalahi, B. P.

    2017-01-01

    Bus timetable gave an information for passengers to ensure the availability of bus services. Timetable optimal condition happened when bus trips frequency could adapt and suit with passenger demand. In the peak time, the number of bus trips would be larger than the off-peak time. If the number of bus trips were more frequent than the optimal condition, it would make a high operating cost for bus operator. Conversely, if the number of trip was less than optimal condition, it would make a bad quality service for passengers. In this paper, the bus timetabling problem would be solved by integer programming model with modified genetic algorithm. Modification was placed in the chromosomes design, initial population recovery technique, chromosomes reconstruction and chromosomes extermination on specific generation. The result of this model gave the optimal solution with accuracy 99.1%.

  5. 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.

  6. An Intelligent Model for Pairs Trading Using Genetic Algorithms

    Science.gov (United States)

    Hsu, Chi-Jen; Chen, Chi-Chung; 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. PMID:26339236

  7. Controversies about the genetic model of colorectal tumorigenesis.

    Science.gov (United States)

    Waliszewski, P

    1995-01-01

    According to the genetic model, intestinal tumorigenesis is a result of the ordered in time inactivation of tumor suppressor genes and the activation of oncogenes. A tacit assumption is that both genes involved in the regulation of proliferation and growth factor-inducible genes, although inactivated, would not be changed during that process. The model requires that cancer cell population is homogenous, exists in a deterministic environment, and develops in a teleological manner. Meanwhile, tumorigenesis is rather a combination of both deterministic and stochastic molecular phenomena. Therefore, a novel notion of bifurcating point genes is defined as a generalization of the idea of tumor suppressor genes and oncogenes. Alternative stochastic mechanisms of tumorigenesis are discussed such as a decreased expression of intestinal-specific genes in cancer cells, most likely reflecting adaptation to survival within a heterogeneous, and non-equilibrated cellular population.

  8. Adaptive Fixation in Two-Locus Models of Stabilizing Selection and Genetic Drift

    OpenAIRE

    Wollstein, Andreas; Stephan, Wolfgang

    2014-01-01

    The relationship between quantitative genetics and population genetics has been studied for nearly a century, almost since the existence of these two disciplines. Here we ask to what extent quantitative genetic models in which selection is assumed to operate on a polygenic trait predict adaptive fixations that may lead to footprints in the genome (selective sweeps). We study two-locus models of stabilizing selection (with and without genetic drift) by simulations and analytically. For symmetr...

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

    OpenAIRE

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

    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...

  10. Market segmentation in two-sided markets : tv rights for premier league

    OpenAIRE

    Kind, Hans Jarle; Sørgard, Lars

    2012-01-01

    This paper analyzes market segmentation in a two-sided market that consists of media consumers and advertisers. The analysis is motivated by a European Court of Justice Decision in October 2011, which allowed viewers to take advantage of international price differences and buy access to Premier League TV matches from whichever country they like. We compare complete market segmentation with the new situation where consumers can purchase from abroad (allowing for passive sales). Clearly, such a...

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

    OpenAIRE

    Vlad Ionut Dumitrache

    2016-01-01

    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 it...

  12. 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...

  13. Tackling intraspecific genetic structure in distribution models better reflects species geographical range.

    Science.gov (United States)

    Marcer, Arnald; Méndez-Vigo, Belén; Alonso-Blanco, Carlos; Picó, F Xavier

    2016-04-01

    Genetic diversity provides insight into heterogeneous demographic and adaptive history across organisms' distribution ranges. For this reason, decomposing single species into genetic units may represent a powerful tool to better understand biogeographical patterns as well as improve predictions of the effects of GCC (global climate change) on biodiversity loss. Using 279 georeferenced Iberian accessions, we used classes of three intraspecific genetic units of the annual plant Arabidopsis thaliana obtained from the genetic analyses of nuclear SNPs (single nucleotide polymorphisms), chloroplast SNPs, and the vernalization requirement for flowering. We used SDM (species distribution models), including climate, vegetation, and soil data, at the whole-species and genetic-unit levels. We compared model outputs for present environmental conditions and with a particularly severe GCC scenario. SDM accuracy was high for genetic units with smaller distribution ranges. Kernel density plots identified the environmental variables underpinning potential distribution ranges of genetic units. Combinations of environmental variables accounted for potential distribution ranges of genetic units, which shrank dramatically with GCC at almost all levels. Only two genetic clusters increased their potential distribution ranges with GCC. The application of SDM to intraspecific genetic units provides a detailed picture on the biogeographical patterns of distinct genetic groups based on different genetic criteria. Our approach also allowed us to pinpoint the genetic changes, in terms of genetic background and physiological requirements for flowering, that Iberian A. thaliana may experience with a GCC scenario applying SDM to intraspecific genetic units.

  14. Exploring Middle School Students' Understanding of Three Conceptual Models in Genetics

    Science.gov (United States)

    Bresler Freidenreich, Hava; Golan Duncan, Ravit; Shea, Nicole

    2011-11-01

    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. Genetic literacy entails understanding three interrelated models: a genetic model that describes patterns of genetic inheritance, a meiotic model that describes the process by which genes are segregated into sex cells, and a molecular model that describes the mechanisms that link genotypes to phenotypes within an individual. Currently, much of genetics instruction, especially in terms of the molecular model, occurs at the high school level, and we know little about the ways in which middle school students can reason about these models. Furthermore, we do not know the extent to which carefully designed instruction can help younger students develop coherent and interrelated understandings in genetics. In this paper, we discuss a research study aimed at elucidating middle school students' abilities to reason about the three genetic models. As part of our research, we designed an eight-week inquiry unit that was implemented in a combined sixth- to eighth-grade science classroom. We describe our instructional design and report results based on an analysis of written assessments, clinical interviews, and artifacts of the unit. Our findings suggest that middle school students are able to successfully reason about all three genetic models.

  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. Vice Premier Zeng Peiyan Meets with Michael Cohrs,CEO of Corporate & Investment Banking of Deutsche Bank

    Institute of Scientific and Technical Information of China (English)

    LuHongwei

    2004-01-01

    Invited by the CPAFFC, Michael Cohrs, Chief Executive Officer of the Corporate and Investment Banking of Deutsche Bank, visited Beijing from February 26 to 28, 2004. Vice Premier Zeng Peiyan of the State Council met with Cohrs and his party.

  17. A time study of cancer genetic counselors using a genetic counselor-only patient care model versus a traditional combined genetic counselor plus medical geneticist care model.

    Science.gov (United States)

    Heald, Brandie; Gustafson, Shanna; Mester, Jessica; Arscott, Patricia; Lynch, Katherine; Moline, Jessica; Eng, Charis

    2013-09-01

    Analyses of time-based effort have determined that clinical genetic services are labor-intensive, although these data derive primarily from studying geneticists' efforts in the pediatric model. No studies have investigated the time and patient care activities of cancer genetic counselors (GCs) in traditional clinics with a medical geneticist (GC/MD) compared with genetic counselor-only (GCO) appointments. In this study, 6 GCs prospectively tracked time spent in patient care activities in both clinical settings. The authors found that overall, GCs' time spent per patient was lower for GCO versus GC/MD visits. No differences were seen in time spent on results disclosure, but differences were noted in case preparation, face-to-face, and follow-up times. Furthermore, no differences were seen in number of case preparation activities or topics covered during a session. These data suggest that GCO visits result in better use of GCs' time, without a trade-off in number of patient-related activities.

  18. Obesity: from animal models to human genetics to practical applications.

    Science.gov (United States)

    Warden, Craig H; Fisler, Janis S

    2010-01-01

    Although many animal models are used in genetic studies, the mouse is most common. Analysis of single-gene mutations, linkage analysis in crossbred strains, and gene targeting are the primary techniques used to associate obesity phenotypes with specific genes or alleles. The orthologous human gene can then be tested, either in linkage studies in families or in genome-wide association studies (GWAS), for effect on the phenotype. Frequent lack of concordance between mouse and human obesity genes may be due to the difference in phenotypes measured in humans (body mass index) versus mouse (fat mass or % body fat), lack of intermediate phenotypes, and the fact that identified genes account for only a small percentage of the heritability of common obesity, suggesting that many genes remain unknown. New technology allows analysis of individual genomes at a reasonable cost, making large-scale obesity genome projects in humans feasible. Such projects could identify common allelic variants that contribute to obesity and to variable individual response to obesity therapy. Currently, family history may be more predictive than genetics for risk of obesity, but individual testing could ultimately guide therapy and, in the aggregate, guide public health policy. The primary limitation to development of genotype-based diets is that successful randomized diet trials of widely ranging macronutrient content, adequately powered for finding rare Mendelian mutations, have not been performed. Copyright © 2010 Elsevier Inc. All rights reserved.

  19. 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.

  20. Structure Refinement for Vulnerability Estimation Models using Genetic Algorithm Based Model Generators

    Directory of Open Access Journals (Sweden)

    2009-01-01

    Full Text Available In this paper, a method for model structure refinement is proposed and applied in estimation of cumulative number of vulnerabilities according to time. Security as a quality characteristic is presented and defined. Vulnerabilities are defined and their importance is assessed. Existing models used for number of vulnerabilities estimation are enumerated, inspecting their structure. The principles of genetic model generators are inspected. Model structure refinement is defined in comparison with model refinement and a method for model structure refinement is proposed. A case study shows how the method is applied and the obtained results.

  1. Estimation of genetic parameters and genetic change for stillbirth in Iranian Holstein cows: a comparison between linear and threshold models

    OpenAIRE

    N.G. HOSSEIN-ZADEH

    2008-01-01

    Data on stillbirth from the Animal Breeding Center of Iran collected from January 1990 to December 2007 and comprising 668810 Holstein calving events from 2506 herds were analyzed. Linear and threshold animal and sire models were used to estimate genetic parameters and genetic trends for stillbirth in the first, second, and third parities. Mean incidence of stillbirth decreased from first to third parities: 23.7%, 22.1%, and 21.8%, respectively. Phenotypic rates of stillbirth decreased from 1...

  2. Genetics

    DEFF Research Database (Denmark)

    Christensen, Kaare; McGue, Matt

    2016-01-01

    The sequenced genomes of individuals aged ≥80 years, who were highly educated, self-referred volunteers and with no self-reported chronic diseases were compared to young controls. In these data, healthy ageing is a distinct phenotype from exceptional longevity and genetic factors that protect...

  3. Local identification of piecewise deterministic models of genetic networks

    NARCIS (Netherlands)

    Cinquemani, Eugenio; Milias-Argeitis, Andreas; Summers, Sean; Lygeros, John

    2009-01-01

    We address the identification of genetic networks under stationary conditions. A stochastic hybrid description of the genetic interactions is considered and an approximation of it in stationary conditions is derived. Contrary to traditional structure identification methods based on fitting determini

  4. 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.

  5. 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.

  6. Toward Developing Genetic Algorithms to Aid in Critical Infrastructure Modeling

    Energy Technology Data Exchange (ETDEWEB)

    2007-05-01

    Today’s society relies upon an array of complex national and international infrastructure networks such as transportation, telecommunication, financial and energy. Understanding these interdependencies is necessary in order to protect our critical infrastructure. The Critical Infrastructure Modeling System, CIMS©, examines the interrelationships between infrastructure networks. CIMS© development is sponsored by the National Security Division at the Idaho National Laboratory (INL) in its ongoing mission for providing critical infrastructure protection and preparedness. A genetic algorithm (GA) is an optimization technique based on Darwin’s theory of evolution. A GA can be coupled with CIMS© to search for optimum ways to protect infrastructure assets. This includes identifying optimum assets to enforce or protect, testing the addition of or change to infrastructure before implementation, or finding the optimum response to an emergency for response planning. This paper describes the addition of a GA to infrastructure modeling for infrastructure planning. It first introduces the CIMS© infrastructure modeling software used as the modeling engine to support the GA. Next, the GA techniques and parameters are defined. Then a test scenario illustrates the integration with CIMS© and the preliminary results.

  7. Identification of Hammerstein Model Based on Quantum Genetic Algorithm

    OpenAIRE

    Zhang Hai Li

    2013-01-01

    Nonlinear system identification is a main topic of modern identification. A new method for nonlinear system identification is presented by using Quantum Genetic Algorithm(QGA).The problems of nonlinear system identification are cast as function optimization overprameter space,and the Quantum Genetic Algorithm is adopted to solve the optimization problem. Simulation experiments show that: compared with the genetic algorithm, quantum genetic algorithm is an effective swarm intelligence algorith...

  8. Genetic fuzzy system modeling and simulation of vascular behaviour

    DEFF Research Database (Denmark)

    Tang, Jiaowei; Boonen, Harrie C.M.

    and find the optimal parameters in a Fuzzy Control set that can control the fluctuation of physical features in a blood vessel, based on experimental data (training data). Our solution is to create chromosomes or individuals composed of a sequence of parameters in the fuzzy system and find the best...... chromosome or individual to define the fuzzy system. The model is implemented by combining the Matlab Genetic algorithm and Fuzzy system toolboxes, respectively. To test the performance of this method, experimental data sets about calculated pressure change in different blood vessels after several chemical...... treatments are chosen as training and testing data sets. In the simulation, the fuzzy control system is trained by pressure data of one blood vessel and tested with pressure data of other blood vessels. Results: Right now, some rough results show that trained fuzzy control system can be used to predict...

  9. New Genetics

    Science.gov (United States)

    ... Home > Science Education > The New Genetics The New Genetics Living Laboratories Classroom Poster Order a Free Copy ... Piece to a Century-Old Evolutionary Puzzle Computing Genetics Model Organisms RNA Interference The New Genetics is ...

  10. Stress, glucocorticoids and absences in a genetic epilepsy model.

    Science.gov (United States)

    Tolmacheva, Elena A; Oitzl, Melly S; van Luijtelaar, Gilles

    2012-05-01

    Although stress can alter the susceptibility of patients and animal models to convulsive epilepsy, little is known about the role of stress and glucocorticoid hormones in absence epilepsy. We measured the basal and acute stress-induced (foot-shocks: FS) concentrations of corticosterone in WAG/Rij rats, non-epileptic inbred ACI rats and outbred Wistar rats. The WAG/Rij strain is a genetic model for absence epilepsy and comorbidity for depression, which originates from the population of Wistar rats and, therefore, shares their genetic background. In a separate experiment, WAG/Rij rats were exposed to FS on three consecutive days. Electroencephalograms (EEGs) were recorded before and after FS, and the number of absence seizures (spike-wave-discharges, SWDs) was quantified. Both WAG/Rij rats and ACI rats exhibited elevated basal levels of corticosterone and a rapid corticosterone increase in response to acute stress. The WAG/Rij rats also displayed the most rapid normalization of corticosterone during the recovery phase compared to that of ACI and Wistar rats. FS had a biphasic effect on SWDs; an initial suppression was followed by an aggravation of the SWDs. By the third day, this aggravation of seizures was present in the hour preceding FS. This increase in SWDs may arise from anticipatory stress about the upcoming FS. Together, these results suggest that the distinct secretion profile of corticosterone found in WAG/Rij rats may contribute to the severity of the epileptic phenotype. Although the acute stressor results in an initial suppression of SWDs followed by an increase in SWDs, stress prior to a predictable negative event aggravates absences.

  11. A Mathematical Model Accounting for the Organisation in Multiplets of the Genetic Code

    OpenAIRE

    Sciarrino, A.

    2001-01-01

    Requiring stability of genetic code against translation errors, modelised by suitable mathematical operators in the crystal basis model of the genetic code, the main features of the organisation in multiplets of the mitochondrial and of the standard genetic code are explained.

  12. Premier Event

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    China and Russia look to move beyond resources and light manufacturing to hi-tech trade Russian Prime Minister Vladimir Putin paid an official visit to China at the invitation of his Chinese counterpart Wen Jiabao on October 11-12, Putin’s first visit abroad since he declared his intention to run for president next year.

  13. Premier Event

    Institute of Scientific and Technical Information of China (English)

    YU YAN

    2011-01-01

    Russian Prime Minister Vladimir Putin paid an official visit to China at the invitation of his Chinese counterpart Wen Jiabao on October 11-12,Putin's first visit abroad since he declared his intention to run for president next year.The visit strengthened diversified practical cooperation and promoted the SinoRussian strategic cooperative partnership in an all-around way,said Chinese analysts.

  14. Estimation of genetic parameters and genetic change for stillbirth in Iranian Holstein cows: a comparison between linear and threshold models

    Directory of Open Access Journals (Sweden)

    N.G. HOSSEIN-ZADEH

    2008-12-01

    Full Text Available Data on stillbirth from the Animal Breeding Center of Iran collected from January 1990 to December 2007 and comprising 668810 Holstein calving events from 2506 herds were analyzed. Linear and threshold animal and sire models were used to estimate genetic parameters and genetic trends for stillbirth in the first, second, and third parities. Mean incidence of stillbirth decreased from first to third parities: 23.7%, 22.1%, and 21.8%, respectively. Phenotypic rates of stillbirth decreased from 1993 to 1998, for first, second and third calvings, and then increased from 1998 to 2007 for the first three parities. Direct heritability estimates of stillbirth for parities 1, 2 and 3 ranged from 2.2 to 8.7%, 0.6 to 5.1% and 0.1 to 3.8%, respectively, and maternal heritability estimates of stillbirth for parities 1, 2 and 3 ranged from 1.4 to 6.3%, 0.5 to 4.2% and 0.08 to 2.0%, respectively, using linear and threshold animal models. The threshold sire model estimates of heritabilities for stillbirth in this study were 0.021 to 0.071, while the linear sire model estimates of heritabilities for stillbirth in the current study were from 0.003 to 0.021 over the parities. There was a slightly increasing genetic trend for stillbirth rate in parities 1 and 2 over time with the analysis of linear animal and linear sire models. There was a significant decreasing genetic trend for stillbirth rate in parity 1 and 3 over time with the analysis of threshold animal and threshold sire models, but the genetic trend for stillbirth rate in parity 2 with these models of analysis was significantly positive. The low estimates of heritability obtained in this study implied that much of the improvement in stillbirth could be attained by improvement of production environment rather than genetic selection.;

  15. 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…

  16. 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…

  17. Genetic models for the study of luteinizing hormone receptor function

    Directory of Open Access Journals (Sweden)

    Prema eNarayan

    2015-09-01

    Full Text Available The luteinizing hormone/chorionic gonadotropin receptor, LHCGR, is essential for fertility in men and women. LHCGR binds luteinizing hormone (LH as well as the highly homologous chorionic gonadotropin (CG. Signaling from LHCGR is required for steroidogenesis and gametogenesis in males and females and for sexual differentiation in the male. The importance of LHCGR in reproductive physiology is underscored by the large number of naturally occurring inactivating and activating mutations in the receptor that result in reproductive disorders. Consequently, several genetically modified mouse models have been developed for the study of LHCGR function. They include targeted deletion of LH and LHCGR that mimic inactivating mutations in hormone and receptor, expression of a constitutively active mutant in LHCGR that mimics activating mutations associated with familial male-limited precocious puberty and transgenic models of LH and hCG overexpression. This review summarizes the salient findings from these models and their utility in understanding the physiological and pathological consequences of loss and gain of function in LHCGR signaling.

  18. Smooth-Threshold Multivariate Genetic Prediction with Unbiased Model Selection.

    Science.gov (United States)

    Ueki, Masao; Tamiya, Gen

    2016-04-01

    We develop a new genetic prediction method, smooth-threshold multivariate genetic prediction, using single nucleotide polymorphisms (SNPs) data in genome-wide association studies (GWASs). Our method consists of two stages. At the first stage, unlike the usual discontinuous SNP screening as used in the gene score method, our method continuously screens SNPs based on the output from standard univariate analysis for marginal association of each SNP. At the second stage, the predictive model is built by a generalized ridge regression simultaneously using the screened SNPs with SNP weight determined by the strength of marginal association. Continuous SNP screening by the smooth thresholding not only makes prediction stable but also leads to a closed form expression of generalized degrees of freedom (GDF). The GDF leads to the Stein's unbiased risk estimation (SURE), which enables data-dependent choice of optimal SNP screening cutoff without using cross-validation. Our method is very rapid because computationally expensive genome-wide scan is required only once in contrast to the penalized regression methods including lasso and elastic net. Simulation studies that mimic real GWAS data with quantitative and binary traits demonstrate that the proposed method outperforms the gene score method and genomic best linear unbiased prediction (GBLUP), and also shows comparable or sometimes improved performance with the lasso and elastic net being known to have good predictive ability but with heavy computational cost. Application to whole-genome sequencing (WGS) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) exhibits that the proposed method shows higher predictive power than the gene score and GBLUP methods.

  19. Toward a genetically-informed model of borderline personality disorder.

    Science.gov (United States)

    Livesley, John

    2008-02-01

    This article describes a conceptual framework for describing borderline personality disorder (BPD) based on empirical studies of the phenotypic structure and genetic architecture of personality. The proposed phenotype has 2 components: (1) a description of core self and interpersonal pathology-the defining features of personality disorder-as these features are expressed in the disorder; and (2) a set of traits based on the anxious-dependent or emotional dysregulation factor of the four-factor model of PD. Four kinds of traits are described: emotional (anxiousness, emotional reactivity, emotional intensity, and pessimistic-anhedonia), interpersonal (submissiveness, insecure attachment, social apprehensiveness, and need for approval), cognitive (cognitive dysregulation), and self-harm (behaviors and ideas). Formulation of the phenotype was guided by the conceptualization of personality as a system of interrelated sub-systems. The psychopathology associated with BPD involves most components of the system. The trait structure of the disorder is assumed to reflect the genetic architecture of personality and individual traits are assumed to be based on adaptive mechanisms. It is suggested that borderline traits are organized around the trait of anxiousness and that an important feature of BPD is dysregulation of the threat management system leading to pervasive fearfulness and unstable emotions. The interpersonal traits are assumed to be heritable characteristics that evolved to deal with interpersonal threats that arose as a result of social living. The potential for unstable and conflicted interpersonal relationships that is inherent to the disorder is assumed to result from the interplay between the adaptive structure of personality and psychosocial adversity. The etiology of the disorder is discussed in terms of biological and environmental factors associated with each component of the phenotype.

  20. Molecular genetics and animal models in autistic disorder.

    Science.gov (United States)

    Andres, Christian

    2002-01-01

    Autistic disorder is a behavioural syndrome beginning before the age of 3 years and lasting over the whole lifetime. It is characterised by impaired communication, impaired social interactions, and repetitive interests and behaviour. The prevalence is about 7/10,000 taking a restrictive definition and more than 1/500 with a broader definition, including all the pervasive developmental disorders. The importance of genetic factors has been highlighted by epidemiological studies showing that autistic disorder is one of the most genetic neuropsychiatric diseases. The relative risk of first relatives is about 100-fold higher than the risk in the normal population and the concordance in monozygotic twin is about 60%. Different strategies have been applied on the track of susceptibility genes. The systematic search of linked loci led to contradictory results, in part due to the heterogeneity of the clinical definitions, to the differences in the DNA markers, and to the different methods of analysis used. An oversimplification of the inferred model is probably also cause of our disappointment. More work is necessary to give a clearer picture. One region emerges more frequently: the long arm of chromosome 7. Several candidate genes have been studied and some gave indications of association: the Reelin gene and the Wnt2 gene. Cytogenetical abnormalities are frequent at 15q11-13, the region of the Angelman and Prader-Willi syndrome. Imprinting plays an important role in this region, no candidate gene has been identified in autism. Biochemical abnormalities have been found in the serotonin system. Association and linkage studies gave no consistent results with some serotonin receptors and in the transporter, although it seems interesting to go further in the biochemical characterisation of the serotonin transporter activity, particularly in platelets, easily accessible. Two monogenic diseases have been associated with autistic disorder: tuberous sclerosis and fragile X. A

  1. [Approach to depressogenic genes from genetic analyses of animal models].

    Science.gov (United States)

    Yoshikawa, Takeo

    2004-01-01

    Human depression or mood disorder is defined as a complex disease, making positional cloning of susceptibility genes a formidable task. We have undertaken genetic analyses of three different animal models for depression, comparing our results with advanced database resources. We first performed quantitative trait loci (QTL) analysis on two mouse models of "despair", namely, the forced swim test (FST) and tail suspension test (TST), and detected multiple chromosomal loci that control immobility time in these tests. Since one QTL detected on mouse chromosome 11 harbors the GABA A receptor subunit genes, we tested these genes for association in human mood disorder patients. We obtained significant associations of the alpha 1 and alpha 6 subunit genes with the disease, particularly in females. This result was striking, because we had previously detected an epistatic interaction between mouse chromosomes 11 and X that regulates immobility time in these animals. Next, we performed genome-wide expression analyses using a rat model of depression, learned helplessness (LH). We found that in the frontal cortex of LH rats, a disease implicated region, the LIM kinase 1 gene (Limk 1) showed greatest alteration, in this case down-regulation. By combining data from the QTL analysis of FST/TST and DNA microarray analysis of mouse frontal cortex, we identified adenylyl cyclase-associated CAP protein 1 (Cap 1) as another candidate gene for depression susceptibility. Both Limk 1 and Cap 1 are key players in the modulation of actin G-F conversion. In summary, our current study using animal models suggests disturbances of GABAergic neurotransmission and actin turnover as potential pathophysiologies for mood disorder.

  2. Identification of Hammerstein Model Based on Quantum Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Zhang Hai Li

    2013-07-01

    Full Text Available Nonlinear system identification is a main topic of modern identification. A new method for nonlinear system identification is presented by using Quantum Genetic Algorithm(QGA.The problems of nonlinear system identification are cast as function optimization overprameter space,and the Quantum Genetic Algorithm is adopted to solve the optimization problem. Simulation experiments show that: compared with the genetic algorithm, quantum genetic algorithm is an effective swarm intelligence algorithm, its salient features of the algorithm parameters, small population size, and the use of Quantum gate update populations, greatly improving the recognition in the optimization of speed and accuracy. Simulation results show the effectiveness of the proposed method.

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

    DEFF Research Database (Denmark)

    Kogelman, Lisette J. A.; Kadarmideen, Haja N.

    2016-01-01

    In many biomedical research areas, animals have been used as a model to increase the understanding of molecular mechanisms involved in human diseases. One of those areas is human obesity, where porcine models are increasingly used. The pig shows genetic and physiological features that are very...... similar to humans and have shown to be an excellent model for human obesity. Using pig populations, many genetic studies have been performed to unravel the genetic architecture of human obesity. Most of them are pinpointing toward single genes, but more and more studies focus on a systems genetics...... 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...

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

    Science.gov (United States)

    Tan, Qihua; B Hjelmborg, Jacob V; Thomassen, Mads; Jensen, Andreas Kryger; Christiansen, Lene; Christensen, Kaare; Zhao, Jing Hua; Kruse, Torben A

    2014-01-01

    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-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 on the mean level of a phenotype, they are not sufficiently straightforward to handle the kinship correlation on the time-dependent trajectories of a phenotype. We introduce a 2-level hierarchical linear model to separately assess the genetic associations with the mean level and the rate of change of a phenotype, integrating kinship correlation in the analysis. We apply our method to the Genetic Analysis Workshop 18 genome-wide association studies data on chromosome 3 to estimate the genetic effects on systolic blood pressure measured over time in large pedigrees. Our method identifies genetic variants 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 for genetic association studies in related samples using longitudinal design.

  5. Form Follows Function: A Model for Clinical Supervision of Genetic Counseling Students.

    Science.gov (United States)

    Wherley, Colleen; Veach, Patricia McCarthy; Martyr, Meredith A; LeRoy, Bonnie S

    2015-10-01

    Supervision plays a vital role in genetic counselor training, yet models describing genetic counseling supervision processes and outcomes are lacking. This paper describes a proposed supervision model intended to provide a framework to promote comprehensive and consistent clinical supervision training for genetic counseling students. Based on the principle "form follows function," the model reflects and reinforces McCarthy Veach et al.'s empirically derived model of genetic counseling practice - the "Reciprocal Engagement Model" (REM). The REM consists of mutually interactive educational, relational, and psychosocial components. The Reciprocal Engagement Model of Supervision (REM-S) has similar components and corresponding tenets, goals, and outcomes. The 5 REM-S tenets are: Learning and applying genetic information are key; Relationship is integral to genetic counseling supervision; Student autonomy must be supported; Students are capable; and Student emotions matter. The REM-S outcomes are: Student understands and applies information to independently provide effective services, develop professionally, and engage in self-reflective practice. The 16 REM-S goals are informed by the REM of genetic counseling practice and supported by prior literature. A review of models in medicine and psychology confirms the REM-S contains supervision elements common in healthcare fields, while remaining unique to genetic counseling. The REM-S shows promise for enhancing genetic counselor supervision training and practice and for promoting research on clinical supervision. The REM-S is presented in detail along with specific examples and training and research suggestions.

  6. Hubs and Authorities of the English Premier League for 2010-2011

    OpenAIRE

    Leznik, Michael

    2013-01-01

    In this work author applies well known web search algorithm Hyperlink - Induced Topic Search (HITS) to problem of ranking football teams in English Premier League (EPL). The algorithm allows the ranking of the teams using the notions of hubs and authorities well known for ranking pages in the World Wide Web. Results of the games introduced as a graph where losing team 'gives a link' to a winning team and, if draw registered both team give links to each other. In case of a win link is weighted...

  7. MODELING OF NAPHTHA PYROLYSIS WITH USING GENETIC ALGORITM

    Directory of Open Access Journals (Sweden)

    V. K. Bityukov

    2015-01-01

    Full Text Available Summary. In operation of industrial pyrolysis furnaces, the main task is the selection of the optimal mode of thermal decomposition of the feedstock, depending on the yield of the desired products under conditions of technological limitations on the process. To solve this problem for an operating reactor, this paper considers the SRT-VI Large-Capacity industrial Furnace , the mathematical model of the pyrolysis process was constructed, using a kinetic scheme which consists of primary reaction of decomposition of raw materials and secondary elementary reactions of interaction of the considered mixture components, the heat balance equation and hydrodynamics of flow in the coil. The raw material for the selected installation type is naphtha (straight-run petrol. Output parameters of the model are the molar costs of marketable hydrocarbons. The reactor is described by the equation of ideal displacement in the static mode of operation. It is assumed that all reactions have a temperature dependence that follows the Arrhenius law. The activation energies of chemical processes were estimated using the PolanyiSemenov equation and identification of pre-exponential factors was carried out using a genetic algorithm (GA. This task requires solving simultaneous system of differential equations describing the pyrolysis process and a search for a large number of unknown parameters, and therefore it is proposed to modify the GA. Optimal scheme includes Gray encoding arithmetic operators, tournament selection, with tournament ranking more than 4, crossover with partial random choice of alleys, mutations with a high probability of occurring and elitism with competitive global competition. Using the proposed approach, the parametric identification of model process is accomplished. The analysis of the simulation results with the data of operating reactor showed its suitability for use in order to control the pyrolysis process.

  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. Modeling of genetic algorithms with a finite population

    NARCIS (Netherlands)

    Kemenade, C.H.M. van

    1997-01-01

    Cross-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 algorithms, all in

  10. 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

  11. The effect of genetic selection for Johne's disease resistance n dairy cattle: Results of a genetic-epidemiological model

    NARCIS (Netherlands)

    Hulzen, van K.J.E.; Koets, A.P.; Nielen, M.; Heuven, H.C.M.; Arendonk, van J.A.M.; Klinkenberg, D.

    2014-01-01

    The objective of this study was to model genetic selection for Johne’s disease resistance and to study the effect of different selection strategies on the prevalence in the dairy cattle population. In the Netherlands, a certification-and-surveillance program is in use to reduce prevalence and presen

  12. The Integration of Cooperation Model and Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    In the photogrammetry,some researchers have applied genetic algorithms in aerial image texture classification and reducing hyper-spectrum remote sensing data.Genetic algorithm can rapidly find the solutions which are close to the optimal solution.But it is not easy to find the optimal solution.In order to solve the problem,a cooperative evolution idea integrating genetic algorithm and ant colony algorithm is presented in this paper.On the basis of the advantages of ant colony algorithm,this paper proposes the method integrating genetic algorithms and ant colony algorithm to overcome the drawback of genetic algorithms.Moreover,the paper takes designing texture classification masks of aerial images as an example to illustrate the integration theory and procedures.

  13. 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)....

  14. Cat Mammary Tumors: Genetic Models for the Human Counterpart

    Directory of Open Access Journals (Sweden)

    Filomena Adega

    2016-08-01

    Full Text Available The records are not clear, but Man has been sheltering the cat inside his home for over 12,000 years. The close proximity of this companion animal, however, goes beyond sharing the same roof; it extends to the great similarity found at the cellular and molecular levels. Researchers have found a striking resemblance between subtypes of feline mammary tumors and their human counterparts that goes from the genes to the pathways involved in cancer initiation and progression. Spontaneous cat mammary pre-invasive intraepithelial lesions (hyperplasias and neoplasias and malignant lesions seem to share a wide repertoire of molecular features with their human counterparts. In the present review, we tried to compile all the genetics aspects published (i.e., chromosomal alterations, critical cancer genes and their expression regarding cat mammary tumors, which support the cat as a valuable alternative in vitro cell and animal model (i.e., cat mammary cell lines and the spontaneous tumors, respectively, but also to present a critical point of view of some of the issues that really need to be investigated in future research.

  15. Genetic mouse models for behavioral analysis through transgenic RNAi technology.

    Science.gov (United States)

    Delic, S; Streif, S; Deussing, J M; Weber, P; Ueffing, M; Hölter, S M; Wurst, W; Kühn, R

    2008-10-01

    Pharmacological inhibitors and knockout mice have developed into routine tools to analyze the role of specific genes in behavior. Both strategies have limitations like the availability of inhibitors for only a subset of proteins and the large efforts required to construct specific mouse mutants. The recent emergence of RNA interference (RNAi)-mediated gene silencing provides a fast alternative that can be applied to any coding gene. We established an approach for the efficient generation of transgenic knockdown mice by targeted insertion of short hairpin (sh) RNA vectors into a defined genomic locus and studied the efficiency of gene silencing in the adult brain and the utility of such mice for behavioral analysis. We generated shRNA knockdown mice for the corticotropin-releasing hormone receptor type 1 (Crhr1), the leucine-rich repeat kinase 2 (Lrkk2) and the purinergic receptor P2X ligand-gated ion channel 7 (P2rx7) genes and show the ubiquitous expression of shRNA and efficient suppression of the target mRNA and protein in the brain of young and 11-month-old knockdown mice. Knockdown mice for the Crhr1 gene exhibited decreased anxiety-related behavior, an impaired stress response, and thereby recapitulate the phenotype of CRHR1 knockout mice. Our results show the feasibility of gene silencing in the adult brain and validate knockdown mice as new genetic models suitable for behavioral analysis.

  16. Modelling Agro-Met Station Observations Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Prashant Kumar

    2014-01-01

    Full Text Available The present work discusses the development of a nonlinear data-fitting technique based on genetic algorithm (GA for the prediction of routine weather parameters using observations from Agro-Met Stations (AMS. The algorithm produces the equations that best describe the temporal evolutions of daily minimum and maximum near-surface (at 2.5-meter height air temperature and relative humidity and daily averaged wind speed (at 10-meter height at selected AMS locations. These enable the forecasts of these weather parameters, which could have possible use in crop forecast models. The forecast equations developed in the present study use only the past observations of the above-mentioned parameters. This approach, unlike other prediction methods, provides explicit analytical forecast equation for each parameter. The predictions up to 3 days in advance have been validated using independent datasets, unknown to the training algorithm, with impressive results. The power of the algorithm has also been demonstrated by its superiority over persistence forecast used as a benchmark.

  17. Discrete channel modelling based on genetic algorithm and simulated annealing for training hidden Markov model

    Institute of Scientific and Technical Information of China (English)

    Zhao Zhi-Jin; Zheng Shi-Lian; Xu Chun-Yun; Kong Xian-Zheng

    2007-01-01

    Hidden Markov models (HMMs) have been used to model burst error sources of wireless channels. This paper proposes a hybrid method of using genetic algorithm (GA) and simulated annealing (SA) to train HMM for discrete channel modelling. The proposed method is compared with pure GA, and experimental results show that the HMMs trained by the hybrid method can better describe the error sequences due to SA's ability of facilitating hill-climbing at the later stage of the search. The burst error statistics of the HMMs trained by the proposed method and the corresponding error sequences are also presented to validate the proposed method.

  18. Genetic simplex modeling of Eysenck's dimensions of personality in a sample of young Australian twins.

    Science.gov (United States)

    Gillespie, Nathan A; Evans, David E; Wright, Margie M; Martin, Nicholas G

    2004-12-01

    The relative stability and magnitude of genetic and environmental effects underlying major dimensions of adolescent personality across time were investigated. The Junior Eysenck Personality Questionnaire was administered to over 540 twin pairs at ages 12, 14 and 16 years. Their personality scores were analyzed using genetic simplex modeling which explicitly took into account the longitudinal nature of the data. With the exception of the dimension lie, multivariate model fitting results revealed that familial aggregation was entirely explained by additive genetic effects. Results from simplex model fitting suggest that large proportions of the additive genetic variance observed at ages 14 and 16 years could be explained by genetic effects present at the age of 12 years. There was also evidence for smaller but significant genetic innovations at 14 and 16 years of age for male and female neuroticism, at 14 years for male extraversion, at 14 and 16 years for female psychoticism, and at 14 years for male psychoticism.

  19. Prediction and Research on Vegetable Price Based on Genetic Algorithm and Neural Network Model

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Considering the complexity of vegetables price forecast,the prediction model of vegetables price was set up by applying the neural network based on genetic algorithm and using the characteristics of genetic algorithm and neural work.Taking mushrooms as an example,the parameters of the model are analyzed through experiment.In the end,the results of genetic algorithm and BP neural network are compared.The results show that the absolute error of prediction data is in the scale of 10%;in the scope that the absolute error in the prediction data is in the scope of 20% and 15%.The accuracy of genetic algorithm based on neutral network is higher than the BP neutral network model,especially the absolute error of prediction data is within the scope of 20%.The accuracy of genetic algorithm based on neural network is obviously better than BP neural network model,which represents the favorable generalization capability of the model.

  20. 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

  1. The Relationship between Emotional Intelligence and Job Satisfaction among Coaches in Premier Under-20 Football League

    Directory of Open Access Journals (Sweden)

    Mehdi Moradi

    2012-06-01

    Full Text Available The purpose of present study was to examine the relationship between emotional intelligence and job satisfaction among coaches in premier Under-20 football league. The research method was descriptive-correlative, the performance method was survey, and data collection was done through field study. Research population consisted of 56 coaching staff in 14 teams participating in premier Under-20 football league. Finally, there were 48 questionnaires useable in data analysis. Emotional Intelligence Questionnaire (Syber Yashring and JDI (Wysocki & Kromm were used to collect the data. Descriptive statistics was used to describe data, Kolmogorov-Smirnov test was used to know whether the distribution of data was normal, and Pearson correlation and stepwise regression were applied to investigate the significance of hypotheses. Results showed that there was significant association between emotional intelligence, subscale self-awareness, subscale empathy, and subscale social skills with job satisfaction (p≤0.05. However, there was not significant association between subscale self-motivation and subscale self-control with job satisfaction. Self-awareness, empathy, and social skills (predictors predicted job satisfaction (criterion significantly. Predicted value of self-awareness, empathy, and social skills was 0.4, 0.29, and 0.26 respectively. Training and aging increase emotional intelligence so it is predicted more job satisfaction over the time. From other side, clubs and football federation as the head can create scientific atmosphere and instruct psychological coaching principles. It will lead to enjoy creative, willing players as output.

  2. Factor analysis models for structuring covariance matrices of additive genetic effects: a Bayesian implementation

    Directory of Open Access Journals (Sweden)

    Gianola Daniel

    2007-09-01

    Full Text Available Abstract Multivariate linear models are increasingly important in quantitative genetics. In high dimensional specifications, factor analysis (FA may provide an avenue for structuring (covariance matrices, thus reducing the number of parameters needed for describing (codispersion. We describe how FA can be used to model genetic effects in the context of a multivariate linear mixed model. An orthogonal common factor structure is used to model genetic effects under Gaussian assumption, so that the marginal likelihood is multivariate normal with a structured genetic (covariance matrix. Under standard prior assumptions, all fully conditional distributions have closed form, and samples from the joint posterior distribution can be obtained via Gibbs sampling. The model and the algorithm developed for its Bayesian implementation were used to describe five repeated records of milk yield in dairy cattle, and a one common FA model was compared with a standard multiple trait model. The Bayesian Information Criterion favored the FA model.

  3. Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network and pathway analyses

    Directory of Open Access Journals (Sweden)

    Lisette J. A. Kogelman

    2014-07-01

    Full Text Available Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome 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 of haplotype blocks. We built Weighted Interaction SNP Hub (WISH and differentially wired (DW networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g. NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.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 and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways

  4. Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network, and pathway analyses.

    Science.gov (United States)

    Kogelman, Lisette J A; Pant, Sameer D; Fredholm, Merete; Kadarmideen, Haja N

    2014-01-01

    Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome 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 of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g., NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.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 and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie

  5. [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.

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

    African Journals Online (AJOL)

    Adel

    intelligence like neural network, genetic algorithm, etc (El Shahat and El Shewy, ..... maximum power factor has the most powerful effect on all various machine .... Artificial Intelligence, Renewable Energy, Power System, Control Systems, PV ...

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

    Science.gov (United States)

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

    2015-10-01

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

  8. Advances in behavioral genetics modeling using Mplus: applications of factor mixture modeling to twin data.

    Science.gov (United States)

    Muthén, Bengt; Asparouhov, Tihomir; Rebollo, Irene

    2006-06-01

    This article discusses new latent variable techniques developed by the authors. As an illustration, a new factor mixture model is applied to the monozygotic-dizygotic twin analysis of binary items measuring alcohol-use disorder. In this model, heritability is simultaneously studied with respect to latent class membership and within-class severity dimensions. Different latent classes of individuals are allowed to have different heritability for the severity dimensions. The factor mixture approach appears to have great potential for the genetic analyses of heterogeneous populations. Generalizations for longitudinal data are also outlined.

  9. Description sémantique de dans un premier temps : de la composition syntagmatique au discours

    Directory of Open Access Journals (Sweden)

    Catherine Schnedecker

    2011-12-01

    Full Text Available Cet article est consacré à l’expression adverbiale réputée sérielle dans un premier temps. Y est d’abord décrit le comportement sémantique de la locution dont le sens reste, pour une bonne partie, compositionnel, étant donné l’importance de la dimension temporelle et les contraintes qu’elle fait peser sur la nature des constituants de la configuration. Ensuite, nous montrons que l’expression dans un premier temps n’est « sérielle » que dans une partie de ses emplois. Dans les autres, non signalés dans la littérature, dans un premier temps marque une relation d’altérité qui peut être « faible » (i. e. encore teintée de temporalité ou « forte » (i. e. nettement contradictoire.The aim of this paper is to describe the semantic behavior of the French expression dans un premier temps, known as a serial marker. We show how its meaning is partly compositional, given the importance of the temporal dimension and the constraints which this places on the nature of the constituents. We then show that dans un premier temps is “serial” in only some of its uses. In others, not reported in the literature, dans un premier temps expresses a relation of “otherness” which can be either “weak” (i.e. keeping a temporal value, or “strong” (i.e. sharply contradictory.

  10. A model for family-based case–control studies of genetic imprinting and epistasis

    Science.gov (United States)

    Li, Xin; Sui, Yihan; Liu, Tian; Wang, Jianxin; Li, Yongci; Lin, Zhenwu; Hegarty, John; Koltun, Walter A.; Wang, Zuoheng

    2014-01-01

    Genetic imprinting, or called the parent-of-origin effect, has been recognized to play an important role in the formation and pathogenesis of human diseases. Although the epigenetic mechanisms that establish genetic imprinting have been a focus of many genetic studies, our knowledge about the number of imprinting genes and their chromosomal locations and interactions with other genes is still scarce, limiting precise inference of the genetic architecture of complex diseases. In this article, we present a statistical model for testing and estimating the effects of genetic imprinting on complex diseases using a commonly used case–control design with family structure. For each subject sampled from a case and control population, we not only genotype its own single nucleotide polymorphisms (SNPs) but also collect its parents’ genotypes. By tracing the transmission pattern of SNP alleles from parental to offspring generation, the model allows the characterization of genetic imprinting effects based on Pearson tests of a 2 × 2 contingency table. The model is expanded to test the interactions between imprinting effects and additive, dominant and epistatic effects in a complex web of genetic interactions. Statistical properties of the model are investigated, and its practical usefulness is validated by a real data analysis. The model will provide a useful tool for genome-wide association studies aimed to elucidate the picture of genetic control over complex human diseases. PMID:23887693

  11. Les premiers textes de René Thom sur la morphogenèse et la linguistique : 1966-1970.

    OpenAIRE

    Petitot, Jean

    2015-01-01

    Au milieu des années 1960, René Thom commença à rédiger ses premiers textes sur les applications à la morphogenèse en biologie et à la syntaxe actantielle en linguistique de la théorie des déploiements universels de singularités de fonctions differentiables et de la stabilité structurelle. Cette note présente et commente ses cinq premiers articles dans ces domaines.

  12. Sur la loi de répartition du k-ième facteur premier d'un entier

    Science.gov (United States)

    de Koninck, J.-M.; Tenenbaum, G.

    2002-09-01

    Soit {pk(n)}w(n)k=1 la suite croissante des facteurs premiers distincts d'un entier n. Nous donnons, lorsque k [rightward arrow] [infty infinity], une approximation uniforme de la loi de répartition limite de la fonction arithmétique n [mapsto A:] pk(n), précisant ainsi un résultat classique d'Erdos. Deux applications en sont déduites, relatives à la médiane de cette loi et à celle de la fonction « nombre de facteurs premiers ».

  13. Mainstreaming cancer genetics: A model integrating germline BRCA testing into routine ovarian cancer clinics.

    Science.gov (United States)

    Kentwell, Maira; Dow, Eryn; Antill, Yoland; Wrede, C David; McNally, Orla; Higgs, Emily; Hamilton, Anne; Ananda, Sumitra; Lindeman, Geoffrey J; Scott, Clare L

    2017-04-01

    Owing to the rapid increase in clinical need, we aimed to implement and review the performance of a mainstreaming model of germline BRCA1/2 genetic testing in eligible women with high grade non-mucinous epithelial ovarian cancer via a Genetic Counselor embedded in the gynecology oncology clinic. The model implemented involved a specialized referral form, weekly genetics-lead multidisciplinary review of referrals, and pre- and post-test genetic counseling provided by an embedded genetic counselor during chemotherapy chair time. Performance and outcomes were retrospectively audited over the following two consecutive one year periods, including survey data on medical specialist comfort with mainstreaming and the model. Sixty-four women underwent mainstreamed BRCA1/2 testing over the two year post-implementation period with a rate of detection of BRCA1/2 pathogenic variants of 17%. The referral rate for eligible women significantly increased to over 90% (pgenetic testing results was less than five months, with >90% of patients receiving results during first line chemotherapy. Genetic counseling time decreased from 120 to 54min. Cancer specialists were comfortable with the model. The mainstreaming model proved effective, increasing uptake of genetic testing in eligible patients to over 90%; it was efficient for patients, genetic counselors and cancer specialists and acceptable to cancer specialists. It facilitated co-location of genetic and oncology service delivery but separation of clinical responsibility for genetic testing to a specialist genetics service, ensuring accurate and robust patient-centred care. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. EXTERNALITIES AND THE SIX FACETS MODEL OF TECHNOLOGY MANAGEMENT: GENETICALLY MODIFIED ORGANISMS IN AGRIBUSINESS

    OpenAIRE

    STEPHEN R. LUXMORE; CLYDE EIRÍKUR HULL

    2010-01-01

    The Six Facets Model of technology management has previously only been applied to process innovation at the firm and the industry level. In this article, the model is applied to product innovation for the first time. In the context of genetically-modified organisms in the agribusiness industry, we examine radical product innovation through the Six Facets Model. We propose, based on the history of genetically-modified organisms in agribusiness, that when applied to product innovation the Six F...

  15. Factors influencing QTL mapping accuracy under complicated genetic models by computer simulation.

    Science.gov (United States)

    Su, C F; Wang, W; Gong, S L; Zuo, J H; Li, S J

    2016-12-19

    The accuracy of quantitative trait loci (QTLs) identified using different sample sizes and marker densities was evaluated in different genetic models. Model I assumed one additive QTL; Model II assumed three additive QTLs plus one pair of epistatic QTLs; and Model III assumed two additive QTLs with opposite genetic effects plus two pairs of epistatic QTLs. Recombinant inbred lines (RILs) (50-1500 samples) were simulated according to the Models to study the influence of different sample sizes under different genetic models on QTL mapping accuracy. RILs with 10-100 target chromosome markers were simulated according to Models I and II to evaluate the influence of marker density on QTL mapping accuracy. Different marker densities did not significantly influence accurate estimation of genetic effects with simple additive models, but influenced QTL mapping accuracy in the additive and epistatic models. The optimum marker density was approximately 20 markers when the recombination fraction between two adjacent markers was 0.056 in the additive and epistatic models. A sample size of 150 was sufficient for detecting simple additive QTLs. Thus, a sample size of approximately 450 is needed to detect QTLs with additive and epistatic models. Sample size must be approximately 750 to detect QTLs with additive, epistatic, and combined effects between QTLs. The sample size should be increased to >750 if the genetic models of the data set become more complicated than Model III. Our results provide a theoretical basis for marker-assisted selection breeding and molecular design breeding.

  16. Identification of common genetic modifiers of neurodegenerative diseases from an integrative analysis of diverse genetic screens in model organisms

    Directory of Open Access Journals (Sweden)

    Chen Xi

    2012-02-01

    Full Text Available Abstract Background An array of experimental models have been developed in the small model organisms C. elegans, S. cerevisiae and D. melanogaster for the study of various neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, and expanded polyglutamine diseases as exemplified by Huntington's disease (HD and related ataxias. Genetic approaches to determine the nature of regulators of the disease phenotypes have ranged from small scale to essentially whole genome screens. The published data covers distinct models in all three organisms and one important question is the extent to which shared genetic factors can be uncovered that affect several or all disease models. Surprisingly it has appeared that there may be relatively little overlap and that many of the regulators may be organism or disease-specific. There is, however, a need for a fully integrated analysis of the available genetic data based on careful comparison of orthologues across the species to determine the real extent of overlap. Results We carried out an integrated analysis using C. elegans as the baseline model organism since this is the most widely studied in this context. Combination of data from 28 published studies using small to large scale screens in all three small model organisms gave a total of 950 identifications of genetic regulators. Of these 624 were separate genes with orthologues in C. elegans. In addition, 34 of these genes, which all had human orthologues, were found to overlap across studies. Of the common genetic regulators some such as chaperones, ubiquitin-related enzymes (including the E3 ligase CHIP which directly links the two pathways and histone deacetylases were involved in expected pathways whereas others such as the peroxisomal acyl CoA-oxidase suggest novel targets for neurodegenerative disease therapy Conclusions We identified a significant number of overlapping regulators of neurodegenerative disease models. Since the diseases

  17. 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.

  18. The WAG/Rij strain: A genetic animal model of absence epilepsy with comorbidity of depressiony

    NARCIS (Netherlands)

    Sarkisova, K.Y.; Luijtelaar, E.L.J.M. van

    2011-01-01

    A great number of clinical observations show a relationship between epilepsy and depression. Idiopathic generalized epilepsy, including absence epilepsy, has a genetic basis. The review provides evidence that WAG/Rij rats can be regarded as a valid genetic animal model of absence epilepsy with comor

  19. An implementation of continuous genetic algorithm in parameter estimation of predator-prey model

    Science.gov (United States)

    Windarto

    2016-03-01

    Genetic algorithm is an optimization method based on the principles of genetics and natural selection in life organisms. The main components of this algorithm are chromosomes population (individuals population), parent selection, crossover to produce new offspring, and random mutation. In this paper, continuous genetic algorithm was implemented to estimate parameters in a predator-prey model of Lotka-Volterra type. For simplicity, all genetic algorithm parameters (selection rate and mutation rate) are set to be constant along implementation of the algorithm. It was found that by selecting suitable mutation rate, the algorithms can estimate these parameters well.

  20. Vers une mélancolie des premiers romans ?

    OpenAIRE

    2017-01-01

    Johan Faerber :Je vais peut-être tout d’abord présenter brièvement ton premier roman, Le Black Note afin de t’interroger sur les questions rétrospectives qu’il suscite en toi et chercher ainsi à apercevoir ta propre lecture de ce moment inaugural de ton œuvre. Il s’agit, on le sait, du récit d’un groupe de jazz amateur taraudé par un modèle écrasant, celui de John Coltrane. Ce groupe sombre progressivement dans la drogue et disparaît à la mort de son leader, Paul, brûlé vif dans l’incendie de...

  1. Berlo Janet C. et Ruth B. Phillips, Amérique du Nord. Arts premiers

    OpenAIRE

    Mauzé, Marie

    2014-01-01

    Avec Amérique du Nord. Arts premiers signé de deux historiennes de l’art, Janet Berlo et Ruth Phillips, nous avons là un ouvrage qui fait partie d’une nouvelle génération de travaux sur les arts nord-amérindiens, à l’instar du livre de David W. Penney, North American Indian Art, publié en 2004. Connues pour l’excellence de leurs recherches, Berlo et Phillips proposent une étude exhaustive sur l’ensemble des arts visuels nord-amérindiens considérés dans leur contexte culturel et historique. Da...

  2. Un premier apprentissage mathématique, la construction du nombre

    OpenAIRE

    Incerti, Estelle; Migy, Pierre

    2014-01-01

    Ce travail de mémoire professionnel se penche sur la question d’un premier apprentissage mathématique fondamental, celui de la construction du nombre. Cette recherche tend à comprendre le rôle que porte l’enseignant au niveau de cet apprentissage dans les premières années de la scolarité d’un élève. Elle met en lumière les éléments théoriques nécessaires à l’acquisition du concept de nombre et les paramètres auxquels il faut prêter tout particulièrement attention en tant qu’enseignant. Au tra...

  3. Genetic Model of an Aborted Porphyry-copper System

    Science.gov (United States)

    Papp, D. C.; Nitoi, E.; Szakacs, A.

    2009-05-01

    The Neogene Sturzii shallow intrusion from the East Carpathians (Bargau Mts., Romania), hosted by Paleogene-Miocene sediments of the Transcarpatian Flysch, developed as an immature porphyry copper structure. It consists of small volumes of dacites, andesites and related contact breccias, having a surface exposure of a few km2. Hydrothermal alteration occurred in the inner part of the intrusive body. The related mineralization consists of pyrite and chalcopyrite either as small veins or disseminated within the rock. A genetic model of the intrusive structure has been developed based on an integrated petrographic, geochemical, isotopic, fluid inclusion and geophysical study. The rapidly ascending calc-alkaline magmas that generated the intrusion are mantle-derived and contaminated with lower-crustal material. Pressure estimations for amphibole reveal significant differences between values corresponding to the crystal cores and rims, suggesting that decompression occurred during its crystallization. The occurrence of exploded fluid inclusions, as well as of primary igneous garnet, also indicate decompression regime during magma uplift and/or storage. All fluid inclusions identified in dacites are aqueous; C-N-S species were not detected. The general evolution of the fluids is toward decreasing salinity with decreasing temperature. Early high-T, high salinity fluids, most likely of magmatic origin, were subjected to a boiling event, related to a change of fluid pressure from litho- to hydrostatic, and followed by dilution with meteoric fluids as indicated by low salinities. These characteristics of the fluids suggest the tendency of the intrusion to evolve towards a porphyry copper system. We estimate that the evolution stopped due to decompression that allowed cold and dilute external fluids to enter the system and because of the small size of the intrusion that cooled down rapidly and could not induce extensive and long-lasting fluid circulation. Since there is no

  4. Using genetic mouse models to gain insight into glaucoma: Past results and future possibilities.

    Science.gov (United States)

    Fernandes, Kimberly A; Harder, Jeffrey M; Williams, Pete A; Rausch, Rebecca L; Kiernan, Amy E; Nair, K Saidas; Anderson, Michael G; John, Simon W M; Howell, Gareth R; Libby, Richard T

    2015-12-01

    While all forms of glaucoma are characterized by a specific pattern of retinal ganglion cell death, they are clinically divided into several distinct subclasses, including normal tension glaucoma, primary open angle glaucoma, congenital glaucoma, and secondary glaucoma. For each type of glaucoma there are likely numerous molecular pathways that control susceptibility to the disease. Given this complexity, a single animal model will never precisely model all aspects of all the different types of human glaucoma. Therefore, multiple animal models have been utilized to study glaucoma but more are needed. Because of the powerful genetic tools available to use in the laboratory mouse, it has proven to be a highly useful mammalian system for studying the pathophysiology of human disease. The similarity between human and mouse eyes coupled with the ability to use a combination of advanced cell biological and genetic tools in mice have led to a large increase in the number of studies using mice to model specific glaucoma phenotypes. Over the last decade, numerous new mouse models and genetic tools have emerged, providing important insight into the cell biology and genetics of glaucoma. In this review, we describe available mouse genetic models that can be used to study glaucoma-relevant disease/pathobiology. Furthermore, we discuss how these models have been used to gain insights into ocular hypertension (a major risk factor for glaucoma) and glaucomatous retinal ganglion cell death. Finally, the potential for developing new mouse models and using advanced genetic tools and resources for studying glaucoma are discussed.

  5. A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission

    Science.gov (United States)

    Anacleto, Osvaldo; Garcia-Cortés, Luis Alberto; Lipschutz-Powell, Debby; Woolliams, John A.; Doeschl-Wilson, Andrea B.

    2015-01-01

    There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations. PMID:26405030

  6. Developing Novel Therapeutic Approaches in Small Cell Lung Carcinoma Using Genetically Engineered Mouse Models and Human Circulating Tumor Cells

    Science.gov (United States)

    2015-10-01

    Using Genetically Engineered Mouse Models and Human Circulating Tumor Cells PRINCIPAL INVESTIGATOR: Jeffrey Engelman MD PhD CONTRACTING...SUBTITLE Developiing Novel Therapeutic Approaches in Small Cell Lung 5a. CONTRACT NUMBER Carcinoma Using Genetically Engineered Mouse Models and 5b...biomarkers. 15. SUBJECT TERMS Small cell lung cancer (SCLC), Genetically engineered mouse model (GEMM), BH3 mimetic, TORC inhibitor, Apoptosis

  7. A parametric model for analyzing anticipation in genetically predisposed families

    DEFF Research Database (Denmark)

    Larsen, Klaus; Petersen, Janne; Bernstein, Inge

    2009-01-01

    Anticipation, i.e. a decreasing age-at-onset in subsequent generations has been observed in a number of genetically triggered diseases. The impact of anticipation is generally studied in affected parent-child pairs. These analyses are restricted to pairs in which both individuals have been affect...

  8. A realistic model under which the genetic code is optimal.

    Science.gov (United States)

    Buhrman, Harry; van der Gulik, Peter T S; Klau, Gunnar W; Schaffner, Christian; Speijer, Dave; Stougie, Leen

    2013-10-01

    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 comparing this value with a distribution of values belonging to codes generated by random permutations of amino acid assignments, the level of error robustness of a genetic code can be quantified. We present a calculation in which the standard genetic code is shown to be optimal. We obtain this result by (1) using recently updated values of polar requirement as input; (2) fixing seven assignments (Ile, Trp, His, Phe, Tyr, Arg, and Leu) based on aptamer considerations; and (3) using known biosynthetic relations of the 20 amino acids. This last point is reflected in an approach of subdivision (restricting the random reallocation of assignments to amino acid subgroups, the set of 20 being divided in four such subgroups). The three approaches to explain robustness of the code (specific selection for robustness, amino acid-RNA interactions leading to assignments, or a slow growth process of assignment patterns) are reexamined in light of our findings. We offer a comprehensive hypothesis, stressing the importance of biosynthetic relations, with the code evolving from an early stage with just glycine and alanine, via intermediate stages, towards 64 codons carrying todays meaning.

  9. Linguini Models of Molecular Genetic Mapping and Fingerprinting.

    Science.gov (United States)

    Thompson, James N., Jr.; Gray, Stanton B.; Hellack, Jenna J.

    1997-01-01

    Presents an exercise using linguini noodles to demonstrate an aspect of DNA fingerprinting. DNA maps that show genetic differences can be produced by digesting a certain piece of DNA with two or more restriction enzymes both individually and in combination. By rearranging and matching linguini fragments, students can recreate the original pattern…

  10. Finding model parameters: Genetic algorithms and the numerical modelling of quartz luminescence

    Energy Technology Data Exchange (ETDEWEB)

    Adamiec, Grzegorz [Department of Radioisotopes, Institute of Physics, Silesian University of Technology, ul. Krzywoustego 2, 44-100 Gliwice (Poland)]. E-mail: grzegorz.adamiec@polsl.pl; Bluszcz, Andrzej [Department of Radioisotopes, Institute of Physics, Silesian University of Technology, ul. Krzywoustego 2, 44-100 Gliwice (Poland); Bailey, Richard [Department of Geography, Royal Holloway, University of London, Egham, Surrey, TW20 0EX (United Kingdom); Garcia-Talavera, Marta [LIBRA, Centro I-D, Campus Miguel Delibes, 47011 Valladolid (Spain)

    2006-08-15

    The paper presents an application of genetic algorithms (GAs) to the problem of finding appropriate parameter values for the numerical simulation of quartz thermoluminescence (TL). We show that with the use of GAs it is possible to achieve a very good match between simulated and experimentally measured characteristics of quartz, for example the thermal activation characteristics of fired quartz. The rate equations of charge transport in the numerical model of luminescence in quartz contain a large number of parameters (trap depths, frequency factors, populations, charge capture probabilities, optical detrapping probabilities, and recombination probabilities). Given that comprehensive models consist of over 10 traps, finding model parameters proves a very difficult task. Manual parameter changes are very time consuming and allow only a limited degree of accuracy. GAs provide a semi-automatic way of finding appropriate parameters.

  11. [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

  12. 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…

  13. [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

  14. 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 possessio...

  15. Modelling and genetic algorithm based optimisation of inverse supply chain

    Science.gov (United States)

    Bányai, T.

    2009-04-01

    (Recycling of household appliances with emphasis on reuse options). The purpose of this paper is the presentation of a possible method for avoiding the unnecessary environmental risk and landscape use through unprovoked large supply chain of collection systems of recycling processes. In the first part of the paper the author presents the mathematical model of recycling related collection systems (applied especially for wastes of electric and electronic products) and in the second part of the work a genetic algorithm based optimisation method will be demonstrated, by the aid of which it is possible to determine the optimal structure of the inverse supply chain from the point of view economical, ecological and logistic objective functions. The model of the inverse supply chain is based on a multi-level, hierarchical collection system. In case of this static model it is assumed that technical conditions are permanent. The total costs consist of three parts: total infrastructure costs, total material handling costs and environmental risk costs. The infrastructure-related costs are dependent only on the specific fixed costs and the specific unit costs of the operation points (collection, pre-treatment, treatment, recycling and reuse plants). The costs of warehousing and transportation are represented by the material handling related costs. The most important factors determining the level of environmental risk cost are the number of out of time recycled (treated or reused) products, the number of supply chain objects and the length of transportation routes. The objective function is the minimization of the total cost taking into consideration the constraints. However a lot of research work discussed the design of supply chain [8], but most of them concentrate on linear cost functions. In the case of this model non-linear cost functions were used. The non-linear cost functions and the possible high number of objects of the inverse supply chain leaded to the problem of choosing a

  16. Genetic mouse models to study blood–brain barrier development and function

    OpenAIRE

    Sohet, Fabien; Daneman, Richard

    2013-01-01

    The blood–brain barrier (BBB) is a complex physiological structure formed by the blood vessels of the central nervous system (CNS) that tightly regulates the movement of substances between the blood and the neural tissue. Recently, the generation and analysis of different genetic mouse models has allowed for greater understanding of BBB development, how the barrier is regulated during health, and its response to disease. Here we discuss: 1) Genetic mouse models that have been used to study th...

  17. Progress and Prospects for Genetic Modification of Nonhuman Primate Models in Biomedical Research

    OpenAIRE

    Chan, Anthony W. S.

    2013-01-01

    The growing interest of modeling human diseases using genetically modified (transgenic) nonhuman primates (NHPs) is a direct result of NHPs (rhesus macaque, etc.) close relation to humans. NHPs share similar developmental paths with humans in their anatomy, physiology, genetics, and neural functions; and in their cognition, emotion, and social behavior. The NHP model within biomedical research has played an important role in the development of vaccines, assisted reproductive technologies, and...

  18. A p-Adic Model of DNA Sequence and Genetic Code

    CERN Document Server

    Dragovich, Branko

    2007-01-01

    Using basic properties of p-adic numbers, we consider a simple new approach to describe main aspects of DNA sequence and genetic code. Central role in our investigation plays an ultrametric p-adic information space which basic elements are nucleotides, codons and genes. We show that a 5-adic model is appropriate for DNA sequence. This 5-adic model, combined with 2-adic distance, is also suitable for genetic code and for a more advanced employment in genomics. We find that genetic code degeneracy is related to the p-adic distance between codons.

  19. New canine models of copper toxicosis: diagnosis, treatment, and genetics.

    Science.gov (United States)

    Fieten, Hille; Penning, Louis C; Leegwater, Peter A J; Rothuizen, Jan

    2014-05-01

    The One Health principle recognizes that human health, animal health, and environmental health are inextricably linked. An excellent example is the study of naturally occurring copper toxicosis in dogs to help understand human disorders of copper metabolism. Besides the Bedlington terrier, where copper toxicosis is caused by a mutation in the COMMD1 gene, more complex hereditary forms of copper-associated hepatitis were recognized recently in other dog breeds. The Labrador retriever is one such breed, where an interplay between genetic susceptibility and exposure to copper lead to clinical copper toxicosis. Purebred dog populations are ideal for gene mapping studies, and because genes involved in copper metabolism are highly conserved across species, newly identified gene mutations in the dog may help unravel the genetic complexity of different human forms of copper toxicosis. Furthermore, increasing knowledge with respect to diagnosis and treatment strategies will benefit both species.

  20. Random regressions models to describe the genetic variation of milk yield over multiple parities in Buffaloes

    Directory of Open Access Journals (Sweden)

    H. Tonhati

    2010-02-01

    Full Text Available The objectives of this study were to estimate (covariance functions for additive genetic and permanent environmental effects, as well as the genetic parameters for milk yield over multiple parities, using random regressions models (RRM. Records of 4,757 complete lactations of Murrah breed buffaloes from 12 herds were analyzed. Ages at calving were between 2 and 11 years. The model included the additive genetic and permanent environmental random effects and the fixed effects of contemporary groups (herd, year and calving season and milking frequency (1 or 2. A cubic regression on Legendre orthogonal polynomials of ages was used to model the mean trend. The additive genetic and permanent environmental effects were modeled by Legendre orthogonal polynomials. Residual variances were considered homogenous or heterogeneous, modeled through variance functions or step functions with 5, 7 or 10 classes. Results from Akaike’s and Schwarz’s Bayesian information criterion indicated that a RRM considering a third order polynomial for the additive genetic and permanent environmental effects and a step function with 5 classes for residual variances fitted best. Heritability estimates obtained by this model varied from 0.10 to 0.28. Genetic correlations were high between consecutive ages, but decreased when intervals between ages increased

  1. 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.

  2. 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.

  3. 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.

  4. Baboons as a model to study genetics and epigenetics of human disease.

    Science.gov (United States)

    Cox, Laura A; Comuzzie, Anthony G; Havill, Lorena M; Karere, Genesio M; Spradling, Kimberly D; Mahaney, Michael C; Nathanielsz, Peter W; Nicolella, Daniel P; Shade, Robert E; Voruganti, Saroja; VandeBerg, John L

    2013-01-01

    A major challenge for understanding susceptibility to common human diseases is determining genetic and environmental factors that influence mechanisms underlying variation in disease-related traits. The most common diseases afflicting the US population are complex diseases that develop as a result of defects in multiple genetically controlled systems in response to environmental challenges. Unraveling the etiology of these diseases is exceedingly difficult because of the many genetic and environmental factors involved. Studies of complex disease genetics in humans are challenging because it is not possible to control pedigree structure and often not practical to control environmental conditions over an extended period of time. Furthermore, access to tissues relevant to many diseases from healthy individuals is quite limited. The baboon is a well-established research model for the study of a wide array of common complex diseases, including dyslipidemia, hypertension, obesity, and osteoporosis. It is possible to acquire tissues from healthy, genetically characterized baboons that have been exposed to defined environmental stimuli. In this review, we describe the genetic and physiologic similarity of baboons with humans, the ability and usefulness of controlling environment and breeding, and current genetic and genomic resources. We discuss studies on genetics of heart disease, obesity, diabetes, metabolic syndrome, hypertension, osteoporosis, osteoarthritis, and intrauterine growth restriction using the baboon as a model for human disease. We also summarize new studies and resources under development, providing examples of potential translational studies for targeted interventions and therapies for human disease.

  5. Examining the External Training Load of an English Premier League Football Team With Special Reference to Acceleration.

    Science.gov (United States)

    Akenhead, Richard; Harley, Jamie A; Tweddle, Simon P

    2016-09-01

    Akenhead, R, Harley, J, and Tweddle, S. Examining the external training load of an English Premier League football team with special reference to acceleration. J Strength Cond Res 30(9): 2424-2432, 2016-Practitioners and coaches often use external training load variables such as distance run and the number of high-speed running (HSR) activities to quantify football training. However, an important component of the external load may be overlooked when acceleration activities are not considered. The aim of this study was to describe the within-microcycle distribution of external load, including acceleration, during in-season 1-game weeks in an elite football team. Global Positioning System technology was used to collect time-motion data from 12 representative 7-day microcycles across a competitive season (48 training days, 295 data sets). Training time, total distance (TD), high-speed running (HSR) distance (>5.8 m·s), sprint running distance (>6.7 m·s) and acceleration variables were recorded during each training session. Data were analysed for interday and interposition differences using mixed linear modeling. The distribution of external load was characterized by the second training day of the microcycle (5 days prematch) exhibiting the highest values for all variables of training load, with the fourth day (1 day prematch) exhibiting the lowest values. Central midfield players covered ∼8-16% greater TD than other positions excluding wide midfielders (p ≤ 0.03, d = 0.2-0.4) and covered ∼17% greater distance accelerating 1-2 m·s than central defenders (p = 0.03, d = 0.7). When expressed relative to training duration and TD, the magnitude of interday and interposition differences were markedly reduced (p = 0.03, d = 0.2-0.3). When managing the distribution of training load, practitioners should be aware of the intensity of training sessions and consider the density of external load within sessions.

  6. Ontology driven modeling for the knowledge of genetic susceptibility to disease.

    Science.gov (United States)

    Lin, Yu; Sakamoto, Norihiro

    2009-05-12

    For the machine helped exploring the relationships between genetic factors and complex diseases, a well-structured conceptual framework of the background knowledge is needed. However, because of the complexity of determining a genetic susceptibility factor, there is no formalization for the knowledge of genetic susceptibility to disease, which makes the interoperability between systems impossible. Thus, the ontology modeling language OWL was used for formalization in this paper. After introducing the Semantic Web and OWL language propagated by W3C, we applied text mining technology combined with competency questions to specify the classes of the ontology. Then, an N-ary pattern was adopted to describe the relationships among these defined classes. Based on the former work of OGSF-DM (Ontology of Genetic Susceptibility Factors to Diabetes Mellitus), we formalized the definition of "Genetic Susceptibility", "Genetic Susceptibility Factor" and other classes by using OWL-DL modeling language; and a reasoner automatically performed the classification of the class "Genetic Susceptibility Factor". The ontology driven modeling is used for formalization the knowledge of genetic susceptibility to complex diseases. More importantly, when a class has been completely formalized in an ontology, the OWL reasoning can automatically compute the classification of the class, in our case, the class of "Genetic Susceptibility Factors". With more types of genetic susceptibility factors obtained from the laboratory research, our ontologies always needs to be refined, and many new classes must be taken into account to harmonize with the ontologies. Using the ontologies to develop the semantic web needs to be applied in the future.

  7. 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

  8. Towards a formal design model based on a genetic design model system

    DEFF Research Database (Denmark)

    Storga, Mario; Andreasen, Mogens Myrup; Marjanovic, Dorian

    2005-01-01

    The research presented in this article is aimed to the investigation of the nature, building and practical role of a Design Ontology as a potential framework for the more efficient product development data-, information- and knowledge- description, -explanation, -understanding and -reusing...... by IEEE, provides us definitions for the most general and universal concepts, that we used in our research for derivation of terms definitions and axioms in the Design Ontology. The Design Ontology was evaluated using the OntoEdit® ontology engineering environment, on a real product example, and based....... In this article, we briefly summarize our experience of converting informal definitions of the concepts from the product development domain based on the existing theoretical background into formal design model. As a main data source for extracting the content of a design ontology, Genetic Design Model System...

  9. Towards a formal design model based on a genetic design model system

    DEFF Research Database (Denmark)

    Storga, Mario; Andreasen, Mogens Myrup; Marjanovic, Dorian

    2005-01-01

    . In this article, we briefly summarize our experience of converting informal definitions of the concepts from the product development domain based on the existing theoretical background into formal design model. As a main data source for extracting the content of a design ontology, Genetic Design Model System......The research presented in this article is aimed to the investigation of the nature, building and practical role of a Design Ontology as a potential framework for the more efficient product development data-, information- and knowledge- description, -explanation, -understanding and -reusing...... by IEEE, provides us definitions for the most general and universal concepts, that we used in our research for derivation of terms definitions and axioms in the Design Ontology. The Design Ontology was evaluated using the OntoEdit® ontology engineering environment, on a real product example, and based...

  10. Modelling the loss of genetic diversity in vole populations in a spatially and temporally varying environment

    DEFF Research Database (Denmark)

    Topping, Christopher John; Østergaard, Siri; Pertoldi, Cino

    2003-01-01

    a genetically explicit individual-based model (IBM) coupled to a dynamic landscape model was used to obtain measures for the genetic status of simulated vole populations. The rate of loss of expected heterozygosity (He) was calculated for simulated populations using two levels of spatial and temporal...... heterogeneity. Results showed that both spatial and temporal heterogeneity exerted an influence on the rate of loss of genetic diversity, but the precise effect was a balance between the effects of population sub-structuring, the frequency of founder effects and population size. These were in turn related...... of heterozygosity was corrected for the harmonic mean of the population size, the rate of loss was almost identical in the four scenarios. Unlike classical genetic models, IBMs are flexible enough to mimic real population processes under a range of environmental and behavioural conditions. We conclude that IBMs...

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

    DEFF Research Database (Denmark)

    Tan, Q.

    2013-01-01

    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...... 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....... Our results show that the method efficiently handles relatedness in detecting genetic variations that affect the mean level or the rate of change for a phenotype of interest....

  12. 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.

  13. A New Modeling Method Based on Genetic Neural Network for Numeral Eddy Current Sensor

    Institute of Scientific and Technical Information of China (English)

    Along Yu; Zheng Li

    2006-01-01

    In this paper, we present a method used to the numeral eddy current sensor modeling based on 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 scaling and high precision. The maximum nonlinearity error can be reduced to 0.037% using GNN. However, the maximum nonlinearity error is 0.075% using least square method (LMS).

  14. 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 m

  15. 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

  16. Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle.

    Science.gov (United States)

    Canaza-Cayo, Ali William; Lopes, Paulo Sávio; da Silva, Marcos Vinicius Gualberto Barbosa; de Almeida Torres, Robledo; Martins, Marta Fonseca; Arbex, Wagner Antonio; Cobuci, Jaime Araujo

    2015-10-01

    A total of 32,817 test-day milk yield (TDMY) records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM) using Legendre's polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield (PSi) and the genetic trend of 305-day milk yield (305MY) were evaluated. The fit quality criteria used indicated RRM employing the Legendre's polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from -0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from -0.98 to 1.00, respectively. The use of PS7 would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits.

  17. Ocean circulation model predicts high genetic structure observed in a long-lived pelagic developer.

    Science.gov (United States)

    Sunday, J M; Popovic, I; Palen, W J; Foreman, M G G; Hart, M W

    2014-10-01

    Understanding the movement of genes and individuals across marine seascapes is a long-standing challenge in marine ecology and can inform our understanding of local adaptation, the persistence and movement of populations, and the spatial scale of effective management. Patterns of gene flow in the ocean are often inferred based on population genetic analyses coupled with knowledge of species' dispersive life histories. However, genetic structure is the result of time-integrated processes and may not capture present-day connectivity between populations. Here, we use a high-resolution oceanographic circulation model to predict larval dispersal along the complex coastline of western Canada that includes the transition between two well-studied zoogeographic provinces. We simulate dispersal in a benthic sea star with a 6-10 week pelagic larval phase and test predictions of this model against previously observed genetic structure including a strong phylogeographic break within the zoogeographical transition zone. We also test predictions with new genetic sampling in a site within the phylogeographic break. We find that the coupled genetic and circulation model predicts the high degree of genetic structure observed in this species, despite its long pelagic duration. High genetic structure on this complex coastline can thus be explained through ocean circulation patterns, which tend to retain passive larvae within 20-50 km of their parents, suggesting a necessity for close-knit design of Marine Protected Area networks. © 2014 John Wiley & Sons Ltd.

  18. Identifying future models for delivering genetic services: a nominal group study in primary care

    Directory of Open Access Journals (Sweden)

    Davies Peter

    2005-04-01

    Full Text Available Background To enable primary care medical practitioners to generate a range of possible service delivery models for genetic counselling services and critically assess their suitability. Methods Modified nominal group technique using in primary care professional development workshops. Results 37 general practitioners in Wales, United Kingdom too part in the nominal group process. The practitioners who attended did not believe current systems were sufficient to meet anticipated demand for genetic services. A wide range of different service models was proposed, although no single option emerged as a clear preference. No argument was put forward for genetic assessment and counselling being central to family practice, neither was there a voice for the view that the family doctor should become skilled at advising patients about predictive genetic testing and be able to counsel patients about the wider implications of genetic testing for patients and their family members, even for areas such as common cancers. Nevertheless, all the preferred models put a high priority on providing the service in the community, and often co-located in primary care, by clinicians who had developed expertise. Conclusion There is a need for a wider debate about how healthcare systems address individual concerns about genetic concerns and risk, especially given the increasing commercial marketing of genetic tests.

  19. 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.

  20. Adaptive fixation in two-locus models of stabilizing selection and genetic drift.

    Science.gov (United States)

    Wollstein, Andreas; Stephan, Wolfgang

    2014-10-01

    The relationship between quantitative genetics and population genetics has been studied for nearly a century, almost since the existence of these two disciplines. Here we ask to what extent quantitative genetic models in which selection is assumed to operate on a polygenic trait predict adaptive fixations that may lead to footprints in the genome (selective sweeps). We study two-locus models of stabilizing selection (with and without genetic drift) by simulations and analytically. For symmetric viability selection we find that ∼16% of the trajectories may lead to fixation if the initial allele frequencies are sampled from the neutral site-frequency spectrum and the effect sizes are uniformly distributed. However, if the population is preadapted when it undergoes an environmental change (i.e., sits in one of the equilibria of the model), the fixation probability decreases dramatically. In other two-locus models with general viabilities or an optimum shift, the proportion of adaptive fixations may increase to >24%. Similarly, genetic drift leads to a higher probability of fixation. The predictions of alternative quantitative genetics models, initial conditions, and effect-size distributions are also discussed.

  1. A bivariate quantitative genetic model for a linear Gaussian trait and a survival trait

    Directory of Open Access Journals (Sweden)

    Damgaard Lars

    2005-12-01

    Full Text Available Abstract With the increasing use of survival models in animal breeding to address the genetic aspects of mainly longevity of livestock but also disease traits, the need for methods to infer genetic correlations and to do multivariate evaluations of survival traits and other types of traits has become increasingly important. In this study we derived and implemented a bivariate quantitative genetic model for a linear Gaussian and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted. Model parameters were inferred from their marginal posterior distributions. The required fully conditional posterior distributions were derived and issues on implementation are discussed. The twoWeibull baseline parameters were updated jointly using a Metropolis-Hastingstep. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. Simulation results showed that the estimated marginal posterior distributions covered well and placed high density to the true parameter values used in the simulation of data. In conclusion, the proposed method allows inferring additive genetic and environmental correlations, and doing multivariate genetic evaluation of a linear Gaussian trait and a survival trait.

  2. A bivariate quantitative genetic model for a linear Gaussian trait and a survival trait.

    Science.gov (United States)

    Damgaard, Lars Holm; Korsgaard, Inge Riis

    2006-01-01

    With the increasing use of survival models in animal breeding to address the genetic aspects of mainly longevity of livestock but also disease traits, the need for methods to infer genetic correlations and to do multivariate evaluations of survival traits and other types of traits has become increasingly important. In this study we derived and implemented a bivariate quantitative genetic model for a linear Gaussian and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted. Model parameters were inferred from their marginal posterior distributions. The required fully conditional posterior distributions were derived and issues on implementation are discussed. The two Weibull baseline parameters were updated jointly using a Metropolis-Hasting step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. Simulation results showed that the estimated marginal posterior distributions covered well and placed high density to the true parameter values used in the simulation of data. In conclusion, the proposed method allows inferring additive genetic and environmental correlations, and doing multivariate genetic evaluation of a linear Gaussian trait and a survival trait.

  3. Revising explanatory models to accommodate anomalous genetic phenomena: Problem solving in the context of discovery

    Science.gov (United States)

    Hafner, Robert; Stewart, Jim

    Past problem-solving research has provided a basis for helping students structure their knowledge and apply appropriate problem-solving strategies to solve problems for which their knowledge (or mental models) of scientific phenomena is adequate (model-using problem solving). This research examines how problem solving in the domain of Mendelian genetics proceeds in situations where solvers' mental models are insufficient to solve problems at hand (model-revising problem solving). Such situations require solvers to use existing models to recognize anomalous data and to revise those models to accommodate the data. The study was conducted in the context of 9-week high school genetics course and addressed: the heuristics charactenstic of successful model-revising problem solving: the nature of the model revisions, made by students as well as the nature of model development across problem types; and the basis upon which solvers decide that a revised model is sufficient (that t has both predictive and explanatory power).

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

    DEFF Research Database (Denmark)

    Tan, Q.

    2013-01-01

    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...... 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....... Our results show that the method efficiently handles relatedness in detecting genetic variations that affect the mean level or the rate of change for a phenotype of interest....

  5. Query Optimization Using Genetic Algorithms in the Vector Space Model

    CERN Document Server

    Mashagba, Eman Al; Nassar, Mohammad Othman

    2011-01-01

    In information retrieval research; Genetic Algorithms (GA) can be used to find global solutions in many difficult problems. This study used different similarity measures (Dice, Inner Product) in the VSM, for each similarity measure we compared ten different GA approaches based on different fitness functions, different mutations and different crossover strategies to find the best strategy and fitness function that can be used when the data collection is the Arabic language. Our results shows that the GA approach which uses one-point crossover operator, point mutation and Inner Product similarity as a fitness function is the best IR system in VSM.

  6. Forward and backward models for fault diagnosis based on parallel genetic algorithms

    Institute of Scientific and Technical Information of China (English)

    Yi LIU; Ying LI; Yi-jia CAO; Chuang-xin GUO

    2008-01-01

    In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.

  7. Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

    Science.gov (United States)

    Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

    2012-08-01

    A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three

  8. 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.

  9. Learning genetic inquiry through the use, revision, and justification of explanatory models

    Science.gov (United States)

    Cartier, Jennifer Lorraine

    Central to the process of inquiry in science is the construction and assessment of models that can be used to explain (and in some cases, predict) natural phenomena. This dissertation is a qualitative study of student learning in a high school biology course that was designed to give students opportunities to learn about genetic inquiry in part by providing them with authentic experiences doing inquiry in the discipline. With the aid of a computer program that generates populations of "fruit flies", the students in this class worked in groups structured like scientific communities to build, revise, and defend explanatory models for various inheritance phenomena. Analysis of the ways in which the first cohort of students assessed their inheritance models revealed that all students assessed models based upon empirical fit (data/model match). However, in contrast to the practice of scientists and despite explicit instruction, students did not consistently apply conceptual assessment criteria to their models. That is, they didn't seek consistency between underlying concepts or processes in their models and those of other important genetic models, such as meiosis. This is perhaps in part because they lacked an understanding of models as conceptual rather than physical entities. Subsequently, the genetics curriculum was altered in order to create more opportunities for students to address epistemological issues associated with model assessment throughout the course. The second cohort of students' understanding of models changed over the nine-week period: initially the majority of students equated scientific models with "proof" (generally physical) of "theories"; at the end of the course, most students demonstrated understanding of the conceptual nature of scientific models and the need to justify such knowledge according to both its empirical utility and conceptual consistency. Through model construction and assessment (i.e. scientific inquiry), students were able to

  10. GESP: A computer program for modeling genetic effective population size, inbreeding, and divergence in substructured populations.

    Science.gov (United States)

    Olsson, Fredrik; Laikre, Linda; Hössjer, Ola; Ryman, Nils

    2017-03-24

    The genetically effective population size (Ne) is of key importance for quantifying rates of inbreeding and genetic drift, and is often used in conservation management to set targets for genetic viability. The concept was developed for single, isolated populations and the mathematical means for analyzing the expected Ne in complex, subdivided populations have previously not been available. We recently developed such analytical theory and central parts of that work have now been incorporated into a freely available software tool presented here. GESP (Genetic Effective population size, inbreeding, and divergence in Substructured Populations) is R-based and designed to model short and long term patterns of genetic differentiation and effective population size of subdivided populations. The algorithms performed by GESP allow exact computation of global and local inbreeding and eigenvalue effective population size, predictions of genetic divergence among populations (GST) as well as departures from random mating (FIS, FIT) while varying i) subpopulation census and effective size, separately or including trend of the global population size, ii) rate and direction of migration between all pairs of subpopulations, iii) degree of relatedness and divergence among subpopulations, iv) ploidy (haploid or diploid), and v) degree of selfing. Here, we describe GESP and exemplify its use in conservation genetics modeling. This article is protected by copyright. All rights reserved.

  11. 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.

  12. From Cells to Islands: An unified Model of Cellular Parallel Genetic Algorithms

    CERN Document Server

    Simoncini, David; Verel, Sébastien; Clergue, Manuel

    2008-01-01

    This paper presents the Anisotropic selection scheme for cellular Genetic Algorithms (cGA). This new scheme allows to enhance diversity and to control the selective pressure which are two important issues in Genetic Algorithms, especially when trying to solve difficult optimization problems. Varying the anisotropic degree of selection allows swapping from a cellular to an island model of parallel genetic algorithm. Measures of performances and diversity have been performed on one well-known problem: the Quadratic Assignment Problem which is known to be difficult to optimize. Experiences show that, tuning the anisotropic degree, we can find the accurate trade-off between cGA and island models to optimize performances of parallel evolutionary algorithms. This trade-off can be interpreted as the suitable degree of migration among subpopulations in a parallel Genetic Algorithm.

  13. 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.

  14. Stochastic dynamic simulation modeling including multitrait genetics to estimate genetic, technical, and financial consequences of dairy farm reproduction and selection strategies

    Science.gov (United States)

    The objective of this study was to develop a daily stochastic dynamic dairy simulation model which included multi-trait genetics, and to evaluate the effects of various reproduction and selection strategies on the genetic, technical and financial performance of a dairy herd. The 12 correlated geneti...

  15. Product versus additive threshold models for analysis of reproduction outcomes in animal genetics.

    Science.gov (United States)

    David, I; Bodin, L; Gianola, D; Legarra, A; Manfredi, E; Robert-Granié, C

    2009-08-01

    The phenotypic observation of some reproduction traits (e.g., insemination success, interval from lambing to insemination) is the result of environmental and genetic factors acting on 2 individuals: the male and female involved in a mating couple. In animal genetics, the main approach (called additive model) proposed for studying such traits assumes that the phenotype is linked to a purely additive combination, either on the observed scale for continuous traits or on some underlying scale for discrete traits, of environmental and genetic effects affecting the 2 individuals. Statistical models proposed for studying human fecundability generally consider reproduction outcomes as the product of hypothetical unobservable variables. Taking inspiration from these works, we propose a model (product threshold model) for studying a binary reproduction trait that supposes that the observed phenotype is the product of 2 unobserved phenotypes, 1 for each individual. We developed a Gibbs sampling algorithm for fitting a Bayesian product threshold model including additive genetic effects and showed by simulation that it is feasible and that it provides good estimates of the parameters. We showed that fitting an additive threshold model to data that are simulated under a product threshold model provides biased estimates, especially for individuals with high breeding values. A main advantage of the product threshold model is that, in contrast to the additive model, it provides distinct estimates of fixed effects affecting each of the 2 unobserved phenotypes.

  16. Disease-threat model explains acceptance of genetically modified products

    Directory of Open Access Journals (Sweden)

    Prokop Pavol

    2013-01-01

    Full Text Available Natural selection favoured survival of individuals who were able to avoid disease. The behavioural immune system is activated especially when our sensory system comes into contact with disease-connoting cues and/or when these cues resemble disease threat. We investigated whether or not perception of modern risky technologies, risky behaviour, expected reproductive goals and food neophobia are associated with the behavioural immune system related to specific attitudes toward genetically modified (GM products. We found that respondents who felt themselves more vulnerable to infectious diseases had significantly more negative attitudes toward GM products. Females had less positive attitudes toward GM products, but engaging in risky behaviours, the expected reproductive goals of females and food neophobia did not predict attitudes toward GM products. Our results suggest that evolved psychological mechanisms primarily designed to protect us against pathogen threat are activated by modern technologies possessing potential health risks.

  17. Hybrid model based on Genetic Algorithms and SVM applied to variable selection within fruit juice classification.

    Science.gov (United States)

    Fernandez-Lozano, C; Canto, C; Gestal, M; Andrade-Garda, J M; Rabuñal, J R; Dorado, J; Pazos, A

    2013-01-01

    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.

  18. Modeling of multivariate longitudinal phenotypes in family genetic studies with Bayesian multiplicity adjustment

    OpenAIRE

    Ding, Lili; Kurowski, Brad G; He, Hua; Alexander, Eileen S.; Mersha, Tesfaye B.; Fardo, David W.; Zhang, Xue; Pilipenko, Valentina V; Kottyan, Leah; Martin, Lisa J.

    2014-01-01

    Genetic studies often collect data on multiple traits. Most genetic association analyses, however, consider traits separately and ignore potential correlation among traits, partially because of difficulties in statistical modeling of multivariate outcomes. When multiple traits are measured in a pedigree longitudinally, additional challenges arise because in addition to correlation between traits, a trait is often correlated with its own measures over time and with measurements of other family...

  19. Investigating the genetic architecture of conditional strategies using the environmental threshold model.

    Science.gov (United States)

    Buzatto, Bruno A; Buoro, Mathieu; Hazel, Wade N; Tomkins, Joseph L

    2015-12-22

    The threshold expression of dichotomous phenotypes that are environmentally cued or induced comprise the vast majority of phenotypic dimorphisms in colour, morphology, behaviour and life history. Modelled as conditional strategies under the framework of evolutionary game theory, the quantitative genetic basis of these traits is a challenge to estimate. The challenge exists firstly because the phenotypic expression of the trait is dichotomous and secondly because the apparent environmental cue is separate from the biological signal pathway that induces the switch between phenotypes. It is the cryptic variation underlying the translation of cue to phenotype that we address here. With a 'half-sib common environment' and a 'family-level split environment' experiment, we examine the environmental and genetic influences that underlie male dimorphism in the earwig Forficula auricularia. From the conceptual framework of the latent environmental threshold (LET) model, we use pedigree information to dissect the genetic architecture of the threshold expression of forceps length. We investigate for the first time the strength of the correlation between observable and cryptic 'proximate' cues. Furthermore, in support of the environmental threshold model, we found no evidence for a genetic correlation between cue and the threshold between phenotypes. Our results show strong correlations between observable and proximate cues and less genetic variation for thresholds than previous studies have suggested. We discuss the importance of generating better estimates of the genetic variation for thresholds when investigating the genetic architecture and heritability of threshold traits. By investigating genetic architecture by means of the LET model, our study supports several key evolutionary ideas related to conditional strategies and improves our understanding of environmentally cued decisions.

  20. Melanoma prognostic model using tissue microarrays and genetic algorithms.

    Science.gov (United States)

    Gould Rothberg, Bonnie E; Berger, Aaron J; Molinaro, Annette M; Subtil, Antonio; Krauthammer, Michael O; Camp, Robert L; Bradley, William R; Ariyan, Stephan; Kluger, Harriet M; Rimm, David L

    2009-12-01

    As a result of the questionable risk-to-benefit ratio of adjuvant therapies, stage II melanoma is currently managed by observation because available clinicopathologic parameters cannot identify the 20% to 60% of such patients likely to develop metastatic disease. Here, we propose a multimarker molecular prognostic assay that can help triage patients at increased risk of recurrence. Protein expression for 38 candidates relevant to melanoma oncogenesis was evaluated using the automated quantitative analysis (AQUA) method for immunofluorescence-based immunohistochemistry in formalin-fixed, paraffin-embedded specimens from a cohort of 192 primary melanomas collected during 1959 to 1994. The prognostic assay was built using a genetic algorithm and validated on an independent cohort of 246 serial primary melanomas collected from 1997 to 2004. Multiple iterations of the genetic algorithm yielded a consistent five-marker solution. A favorable prognosis was predicted by ATF2 ln(non-nuclear/nuclear AQUA score ratio) of more than -0.052, p21(WAF1) nuclear compartment AQUA score of more than 12.98, p16(INK4A) ln(non-nuclear/nuclear AQUA score ratio) of < or = -0.083, beta-catenin total AQUA score of more than 38.68, and fibronectin total AQUA score of < or = 57.93. Primary tumors that met at least four of these five conditions were considered a low-risk group, and those that met three or fewer conditions formed a high-risk group (log-rank P < .0001). Multivariable proportional hazards analysis adjusting for clinicopathologic parameters shows that the high-risk group has significantly reduced survival on both the discovery (hazard ratio = 2.84; 95% CI, 1.46 to 5.49; P = .002) and validation (hazard ratio = 2.72; 95% CI, 1.12 to 6.58; P = .027) cohorts. This multimarker prognostic assay, an independent determinant of melanoma survival, might be beneficial in improving the selection of stage II patients for adjuvant therapy.

  1. 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.

  2. Strategies for injury prevention in Brazilian football: Perceptions of physiotherapists and practices of premier league teams.

    Science.gov (United States)

    Meurer, Maurício Couto; Silva, Marcelo Faria; Baroni, Bruno Manfredini

    2017-07-25

    To describe the physiotherapists perceptions and the current practices for injury prevention in elite football (soccer) clubs in Brazil. Cross-sectional study. Group of Science in Sports & Exercise, Federal University of Healthy Sciences of Porto Alegre (Brazil). 16 of the 20 football clubs involved in the Brazilian premier league 2015. Physiotherapists answered a structured questionnaire. Most physiotherapists (∼88%) were active in design, testing and application of prevention programs. Previous injury, muscle imbalance, fatigue, hydration, fitness, diet, sleep/rest and age were considered "very important" or "important" injury risk factors by all respondents. The methods most commonly used to detect athletes' injury risk were: monitoring of biochemical markers (100% of teams), isokinetic dynamometry (81%), questionnaires (75%), functional movement screen (56%), fleximetry (56%) and horizontal jump tests (50%). All clubs used strength training, functional training, core exercises and balance/proprioception exercises in their injury prevention program; and Nordic hamstring exercise and other eccentric exercises were used by 94% of clubs. "FIFA 11+" prevention program was adapted by 88% of clubs. Physiotherapists perceptions and current practices of injury prevention within Brazilian elite football clubs were similar to those employed in developed countries. There remains a gap between clinical practice and scientific evidence in high performance football. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Mohsen Javani

    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.

  4. Elastic-plastic model identification for rock surrounding an underground excavation based on immunized genetic algorithm.

    Science.gov (United States)

    Gao, Wei; Chen, Dongliang; Wang, Xu

    2016-01-01

    To compute the stability of underground engineering, a constitutive model of surrounding rock must be identified. Many constitutive models for rock mass have been proposed. In this model identification study, a generalized constitutive law for an elastic-plastic constitutive model is applied. Using the generalized constitutive law, the problem of model identification is transformed to a problem of parameter identification, which is a typical and complicated optimization. To improve the efficiency of the traditional optimization method, an immunized genetic algorithm that is proposed by the author is applied in this study. In this new algorithm, the principle of artificial immune algorithm is combined with the genetic algorithm. Therefore, the entire computation efficiency of model identification will be improved. Using this new model identification method, a numerical example and an engineering example are used to verify the computing ability of the algorithm. The results show that this new model identification algorithm can significantly improve the computation efficiency and the computation effect.

  5. A simple algorithm to estimate genetic variance in an animal threshold model using Bayesian inference

    Directory of Open Access Journals (Sweden)

    Heringstad Bjørg

    2010-07-01

    Full Text Available Abstract 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 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 (covariance components within an animal threshold model framework. Methods In the proposed algorithm, individuals are classified as either "informative" or "non-informative" with respect to genetic (covariance components. The "non-informative" individuals are characterized by their Mendelian sampling deviations (deviance from the mid-parent mean being completely confounded with a single residual on the underlying liability scale. For threshold models, residual variance on the underlying scale is not identifiable. Hence, variance of fully confounded Mendelian sampling deviations cannot be identified either, but can be inferred from the between-family variation. In the new algorithm, breeding values are sampled as in a standard animal model using the full relationship matrix, but genetic (covariance components are inferred from the sampled breeding values and relationships between "informative" individuals (usually parents only. The latter is analogous to a sire-dam model (in cases with no individual records on the parents. Results When applied to simulated data sets, the standard animal threshold model failed to produce useful results since samples of genetic variance always drifted towards infinity, while the new algorithm produced proper parameter estimates essentially identical to the results from a sire-dam model (given the fact that no individual records exist for the parents. Furthermore, the new algorithm showed much faster Markov chain mixing properties for genetic parameters (similar to

  6. Significance of genetic information in risk assessment and individual classification using silicosis as a case model

    Energy Technology Data Exchange (ETDEWEB)

    McCanlies, E.; Landsittel, D.P.; Yucesoy, B.; Vallyathan, V.; Luster, M.L.; Sharp, D.S. [NIOSH, Morgantown, WV (United States)

    2002-06-01

    Over the last decade the role of genetic data in epidemiological research has expanded considerably. The authors recently published a case-control study that evaluated the interaction between silica exposure and minor variants in the genes coding for interleukin-1alpha. (IL-1alpha), interleukin-1 receptor antagonist (IL-1RA) and tumor necrosis factor alpha (TNFalpha) as risk factors associated with silicosis, a fibrotic lung disease. In contrast, this report uses data generated from these studies to illustrate the utility of genetic information for the purposes of risk assessment and clinical prediction. Specifically, this study addresses how, given a known exposure, genetic information affects the characterization of risk groups. Relative operating characteristic (ROC) curves were then used to determine the impact of genetic information on individual classification. Logistic regression modeling procedures were used to estimate the predicted probability of developing silicosis. This probability was then used to construct predicted risk deciles, first for a model with occupational exposure only and then for a model containing occupational exposure and genetic main effects and interactions. The results indicate that genetic information plays a valuable role in effectively characterizing risk groups and mechanisms of disease operating in a substantial proportion of the population. However, in the case of fibrotic lung disease caused by silica exposure, information about the presence or absence of the minor variants of IL-1alpha, IL-1RA and TNFalpha is unlikely to be a useful tool for individual classification.

  7. Modeling the genetic and environmental association between peer group deviance and cannabis use in male twins

    Science.gov (United States)

    Gillespie, Nathan A; Neale, Michael C; Jacobson, Kristen; Kendler, Kenneth S

    2009-01-01

    Background Peer group deviance (PGD) is strongly linked to liability to drug use including cannabis. Our aim was to model the genetic and environmental association, including direction of causation, between PGD and cannabis use (CU). Method Results were based on 1753 adult males from the Mid-Atlantic Twin Registry with complete CU and PGD data measured retrospectively at three time intervals between 15 and 25 years using a life-history calendar. Results At all ages, multivariate modeling showed that familial aggregation in PGD was explained by a combination of additive genetic and shared environmental effects, Moreover the significant PGD-CU association was best explained by a CU to PGD causal model in which large portions of the additive genetic (50% to 78%) and shared environmental variance (25% to 73%) in PGD were explained by CU. Conclusions Until recently PGD was assumed to be an environmental, upstream risk factor for CU. Our data are not consistent with this hypothesis. Rather, they suggest that the liability to affiliate with deviant peers is better explained by a combination of genetic and environmental factors that are indexed by CU which sits as a “risk indicator” in the causal pathway between genetic and environmental risks and the expression of PGD. This is consistent with a process of social selection by which the genetic and environmental risks in CU largely drive the propensity to affiliate with deviant peers. PMID:19207350

  8. Progress and Outlooks in a Genetic Absence Epilepsy Model (WAG/Rij)

    NARCIS (Netherlands)

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

    2014-01-01

    The WAG/Rij model is a well characterized and validated genetic animal epilepsy model in which the for absence epilepsy highly characteristic spike-wave discharges (SWDs) develop spontaneously. In this review we discuss first some older and many new studies, with an emphasis on pharmacological and n

  9. 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 a

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

    Science.gov (United States)

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

    2016-06-08

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

  11. 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 a

  12. 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...

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

    NARCIS (Netherlands)

    Kramer, K.; Werf, van der 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 for

  14. Predicting Modeling Method of Ship Radiated Noise Based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Guohui Li

    2016-01-01

    Full Text Available Because the forming mechanism of underwater acoustic signal is complex, it is difficult to establish the accurate predicting model. In this paper, we propose a nonlinear predicting modeling method of ship radiated noise based on genetic algorithm. Three types of ship radiated noise are taken as real underwater acoustic signal. First of all, a basic model framework is chosen. Secondly, each possible model is done with genetic coding. Thirdly, model evaluation standard is established. Fourthly, the operation of genetic algorithm such as crossover, reproduction, and mutation is designed. Finally, a prediction model of real underwater acoustic signal is established by genetic algorithm. By calculating the root mean square error and signal error ratio of underwater acoustic signal predicting model, the satisfactory results are obtained. The results show that the proposed method can establish the accurate predicting model with high prediction accuracy and may play an important role in the further processing of underwater acoustic signal such as noise reduction and feature extraction and classification.

  15. 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

  16. Comparison of multiplicative heterogeneous variance adjustment models for genetic evaluations.

    Science.gov (United States)

    Márkus, Sz; Mäntysaari, E A; Strandén, I; Eriksson, J-Å; Lidauer, M H

    2014-06-01

    Two heterogeneous variance adjustment methods and two variance models were compared in a simulation study. The method used for heterogeneous variance adjustment in the Nordic test-day model, which is a multiplicative method based on Meuwissen (J. Dairy Sci., 79, 1996, 310), was compared with a restricted multiplicative method where the fixed effects were not scaled. Both methods were tested with two different variance models, one with a herd-year and the other with a herd-year-month random effect. The simulation study was built on two field data sets from Swedish Red dairy cattle herds. For both data sets, 200 herds with test-day observations over a 12-year period were sampled. For one data set, herds were sampled randomly, while for the other, each herd was required to have at least 10 first-calving cows per year. The simulations supported the applicability of both methods and models, but the multiplicative mixed model was more sensitive in the case of small strata sizes. Estimation of variance components for the variance models resulted in different parameter estimates, depending on the applied heterogeneous variance adjustment method and variance model combination. Our analyses showed that the assumption of a first-order autoregressive correlation structure between random-effect levels is reasonable when within-herd heterogeneity is modelled by year classes, but less appropriate for within-herd heterogeneity by month classes. Of the studied alternatives, the multiplicative method and a variance model with a random herd-year effect were found most suitable for the Nordic test-day model for dairy cattle evaluation.

  17. Peat moss fuels R and D: Premier Tech is using sphagnum peat moss to develop all kinds of sophisticated products

    Energy Technology Data Exchange (ETDEWEB)

    Desiront, A.

    2004-10-01

    Development by Premier Tech, a Quebec multinational company, of a unique system for recycling construction waste using peat moss as the starting material, is reported. Premier Tech enjoys a high profile in sectors such as the life sciences, wastewater treatment systems, industrial packaging and a variety of other fields not readily associated with peat moss. The best known products of the company, the Allegro line of growth media designed to promote greenhouse growing, Biomax compost and the Promix plant growth media, all based on research on mycorrhizal association, and the development strategy guiding the company's operations, are described briefly. The company's Ecoflo and Ecoprocess filters for treating domestic and municipal wastewater, both of which played significant roles in recovering evidence from the rubble of the World Trade Center after September 11, 2001, are highlighted.

  18. Modeling of trophospheric ozone concentrations using genetically trained multi-level cellular neural networks

    Science.gov (United States)

    Ozcan, H. Kurtulus; Bilgili, Erdem; Sahin, Ulku; Ucan, O. Nuri; Bayat, Cuma

    2007-09-01

    Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.

  19. Modeling of Trophospheric Ozone Concentrations Using Genetically Trained Multi-Level Cellular Neural Networks

    Institute of Scientific and Technical Information of China (English)

    H. Kurtulus OZCAN; Erdem BILGILI; Ulku SAHIN; O. Nuri UCAN; Cuma BAYAT

    2007-01-01

    Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.

  20. 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

    environmental factors driving potentially adaptive genetic variation in G. nivalis. Techniques presented in this paper offer an efficient method for identifying potentially adaptive genetic variation and associated environmental forces of selection, providing an important step forward for the conservation......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...... variation, phylogeographic history, and population demographic processes all contribute to spatially structured genetic variation, however few current models attempt to separate these confounding effects. To illustrate the benefits of using a spatially-explicit model for identifying potentially adaptive...

  1. A population genetics model of linkage disequilibrium in admixed populations

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Understanding linkage disequilibrium (LD) created in admixed population and the rate of decay in the disequilibrium over evolution is an important subject in population genetics theory and in disease gene mapping in human populations. The present study represents the theoretical investigation of effects of gene frequencies, levels of LD and admixture proportions of donor populations on the evolutionary dynamics of the LD of the admixed population. We examined the conditions under which the admixed population reached linkage equilibrium or the peak level of the LD. The study reveals the inappropriateness in approximating the dynamics of the LD generated by population admixture by the commonly used formula in literature. An appropriate equation for the dynamics is proposed. The distinct feature of the newly suggested formula is that the value of the nonlinear component of the LD remains constant in the first generation of the population evolution. Comparison between the predicted disequilibrium dynamics shows that the error will be caused by using the old formula, and thus resulting in a misguidance in using the evolutionary information of the admixed population in gene mapping.

  2. 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.

  3. 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

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

    Directory of Open Access Journals (Sweden)

    Shahid Ali

    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

  5. Progress and prospects for genetic modification of nonhuman primate models in biomedical research.

    Science.gov (United States)

    Chan, Anthony W S

    2013-01-01

    The growing interest of modeling human diseases using genetically modified (transgenic) nonhuman primates (NHPs) is a direct result of NHPs (rhesus macaque, etc.) close relation to humans. NHPs share similar developmental paths with humans in their anatomy, physiology, genetics, and neural functions; and in their cognition, emotion, and social behavior. The NHP model within biomedical research has played an important role in the development of vaccines, assisted reproductive technologies, and new therapies for many diseases. Biomedical research has not been the primary role of NHPs. They have mainly been used for safety evaluation and pharmacokinetics studies, rather than determining therapeutic efficacy. The development of the first transgenic rhesus macaque (2001) revolutionized the role of NHP models in biomedicine. Development of the transgenic NHP model of Huntington's disease (2008), with distinctive clinical features, further suggested the uniqueness of the model system; and the potential role of the NHP model for human genetic disorders. Modeling human genetic diseases using NHPs will continue to thrive because of the latest advances in molecular, genetic, and embryo technologies. NHPs rising role in biomedical research, specifically pre-clinical studies, is foreseeable. The path toward the development of transgenic NHPs and the prospect of transgenic NHPs in their new role in future biomedicine needs to be reviewed. This article will focus on the advancement of transgenic NHPs in the past decade, including transgenic technologies and disease modeling. It will outline new technologies that may have significant impact in future NHP modeling and will conclude with a discussion of the future prospects of the transgenic NHP model.

  6. 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

  7. Linear vs. piecewise Weibull model for genetic evaluation of sires for longevity in Simmental cattle

    Directory of Open Access Journals (Sweden)

    Nikola Raguž

    2014-09-01

    Full Text Available This study was focused on genetic evaluation of longevity in Croatian Simmental cattle using linear and survival models. The main objective was to create a genetic model that is most appropriate to describe the longevity data. Survival analysis, using piecewise Weibull proportional hazards model, used all information on the length of productive life including censored as well as uncensored observations. Linear models considered culled animals only. The relative milk production within herd had a highest impact on cows’ longevity. In comparison of estimated genetic parameters among methods, survival analysis yielded higher heritability value (0.075 than linear sire (0.037 and linear animal model (0.056. When linear models were used, genetic trend of Simmental bulls for longevity was slightly increasing over the years, unlike a decreasing trend in case of survival analysis methodology. Average reliability of bulls’ breeding values was higher in case of survival analysis. The rank correlations between survival analysis and linear models bulls’ breeding values for longevity were ranged between 0.44 and 0.46 implying huge differences in ranking of sires.

  8. Dynamic semiparametric Bayesian models for genetic mapping of complex trait with irregular longitudinal data.

    Science.gov (United States)

    Das, Kiranmoy; Li, Jiahan; Fu, Guifang; Wang, Zhong; Li, Runze; Wu, Rongling

    2013-02-10

    Many phenomena of fundamental importance to biology and biomedicine arise as a dynamic curve, such as organ growth and HIV dynamics. The genetic mapping of these traits is challenged by longitudinal variables measured at irregular and possibly subject-specific time points, in which case nonnegative definiteness of the estimated covariance matrix needs to be guaranteed. We present a semiparametric approach for genetic mapping within the mixture-model setting by jointly modeling mean and covariance structures for irregular longitudinal data. Penalized spline is used to model the mean functions of individual quantitative trait locus (QTL) genotypes as latent variables, whereas an extended generalized linear model is used to approximate the covariance matrix. The parameters for modeling the mean-covariances are estimated by MCMC, using the Gibbs sampler and the Metropolis-Hastings algorithm. We derive the full conditional distributions for the mean and covariance parameters and compute Bayes factors to test the hypothesis about the existence of significant QTLs. We used the model to screen the existence of specific QTLs for age-specific change of body mass index with a sparse longitudinal data set. The new model provides powerful means for broadening the application of genetic mapping to reveal the genetic control of dynamic traits.

  9. Translating therapies for Huntington's disease from genetic animal models to clinical trials.

    Science.gov (United States)

    Hersch, Steven M; Ferrante, Robert J

    2004-07-01

    Genetic animal models of inherited neurological diseases provide an opportunity to test potential treatments and explore their promise for translation to humans experiencing these diseases. Therapeutic trials conducted in mouse models of Huntington's disease have identified a growing number of potential therapies that are candidates for clinical trials. Although it is very exciting to have these candidates, there has been increasing concern about the feasibility and desirability of taking all of the compounds that may work in mice and testing them in patients with HD. There is a need to begin to prioritize leads emerging from transgenic mouse studies; however, it is difficult to compare results between compounds and laboratories, and there are also many additional factors that can affect translation to humans. Among the important issues are what constitutes an informative genetic model, what principals should be followed in designing and conducting experiments using genetic animal models, how can results from different laboratories and in different models be compared, what body of evidence is desirable to fully inform clinical decision making, and what factors contribute to the equipoise in determining whether preclinical information about a therapy makes clinical study warranted. In the context of Huntington's disease, we will review the current state of genetic models and their successes in putting forward therapeutic leads, provide a guide to assessing studies in mouse models, and discuss some of the salient issues related to translation from mice to humans.

  10. Insights into the genetic basis of systemic sclerosis: immunity in human disease and in mouse models

    Directory of Open Access Journals (Sweden)

    Wu M

    2014-09-01

    Full Text Available Minghua Wu, Maureen D Mayes Division of Rheumatology and Clinical Immunogenetics, Department of Internal Medicine, University of Texas Medical School at Houston, Houston, TX, USA Abstract: Systemic sclerosis (SSc; scleroderma is a chronic, multisystem autoimmune disease characterized by vasculopathy, fibrosis, and autoantibodies. In the past decade, great efforts have been made to investigate genetic susceptibility for SSc. To date, over 20 gene loci have been identified as risk factors for SSc in large genome-wide association studies and confirmed by independent replication studies. However, the biological relevance of these genetic associations is still largely unknown. Exploring the mechanism behind these risk loci is essential to better understand disease pathogenesis and to identify novel therapeutic targets. Mouse model studies including knockout, knockin and knockdown of these genes can advance our understanding of pathogenic cellular and molecular mechanisms in human disease. Although such mouse model systems do not exactly correspond to human disease, they can provide insight into pathological mechanisms that influence disease pathways. In this review, we discuss recent findings regarding the genetic basis of SSc in the setting of genetic manipulation of these pathways in murine models. Keywords: GWAS, Immunochip study, type I interferon pathway, genetic mutation animal models

  11. WOMBAT: a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML).

    Science.gov (United States)

    Meyer, Karin

    2007-11-01

    WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses. Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from (http://agbu. une.edu.au/~kmeyer/wombat.html).

  12. Operant-based instrumental learning for analysis of genetically modified models of Huntington's disease.

    Science.gov (United States)

    Trueman, R C; Dunnett, S B; Brooks, S P

    2012-06-01

    Huntington's disease is the result of an expanded CAG repeat in the gene that codes for the protein huntingtin and results in a progressive sequelae of motor, cognitive and psychiatric symptoms. The development of genetically modified rodent models of Huntington's disease has led to the need for sensitive behavioural phenotyping. Operant tests for rodents have been developed that can determine the functional deficits in these genetically modified models, from motor, cognitive and emotional domains. The current review discusses tests that employ operant equipment, an automated and highly flexible method for testing rodents. Different operant paradigms are examined in relation to their relevance to Huntington's disease symptomology, as well as summarising research to date on genetic models with these tests.

  13. Stellar Structure Modeling using a Parallel Genetic Algorithm for Objective Global Optimization

    CERN Document Server

    Metcalfe, T S

    2002-01-01

    Genetic algorithms are a class of heuristic search techniques that apply basic evolutionary operators in a computational setting. We have designed a fully parallel and distributed hardware/software implementation of the generalized optimization subroutine PIKAIA, which utilizes a genetic algorithm to provide an objective determination of the globally optimal parameters for a given model against an observational data set. We have used this modeling tool in the context of white dwarf asteroseismology, i.e., the art and science of extracting physical and structural information about these stars from observations of their oscillation frequencies. The efficient, parallel exploration of parameter-space made possible by genetic-algorithm-based numerical optimization led us to a number of interesting physical results: (1) resolution of a hitherto puzzling discrepancy between stellar evolution models and prior asteroseismic inferences of the surface helium layer mass for a DBV white dwarf; (2) precise determination of...

  14. A synthetic framework for modeling the genetic basis of phenotypic plasticity and its costs.

    Science.gov (United States)

    Zhai, Yi; Lv, Yafei; Li, Xin; Wu, Weimiao; Bo, Wenhao; Shen, Dengfeng; Xu, Fang; Pang, Xiaoming; Zheng, Bingsong; Wu, Rongling

    2014-01-01

    The phenotype of an individual is controlled not only by its genes, but also by the environment in which it grows. A growing body of evidence shows that the extent to which phenotypic changes are driven by the environment, known as phenotypic plasticity, is also under genetic control, but an overall picture of genetic variation for phenotypic plasticity remains elusive. Here, we develop a model for mapping quantitative trait loci (QTLs) that regulate environment-induced plastic response. This model enables geneticists to test whether there exist actual QTLs that determine phenotypic plasticity and, if there are, further test how plasticity QTLs control the costs of plastic response by dissecting the genetic correlation of phenotypic plasticity and trait value. The model was used to analyze real data for grain yield of winter wheat (Triticum aestivum), leading to the detection of pleiotropic QTLs and epistatic QTLs that affect phenotypic plasticity and its cost in this crop.

  15. 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

  16. A test of genetic models for the evolutionary maintenance of same-sex sexual behaviour.

    Science.gov (United States)

    Hoskins, Jessica L; Ritchie, Michael G; Bailey, Nathan W

    2015-06-22

    The evolutionary maintenance of same-sex sexual behaviour (SSB) has received increasing attention because it is perceived to be an evolutionary paradox. The genetic basis of SSB is almost wholly unknown in non-human animals, though this is key to understanding its persistence. Recent theoretical work has yielded broadly applicable predictions centred on two genetic models for SSB: overdominance and sexual antagonism. Using Drosophila melanogaster, we assayed natural genetic variation for male SSB and empirically tested predictions about the mode of inheritance and fitness consequences of alleles influencing its expression. We screened 50 inbred lines derived from a wild population for male-male courtship and copulation behaviour, and examined crosses between the lines for evidence of overdominance and antagonistic fecundity selection. Consistent variation among lines revealed heritable genetic variation for SSB, but the nature of the genetic variation was complex. Phenotypic and fitness variation was consistent with expectations under overdominance, although predictions of the sexual antagonism model were also supported. We found an unexpected and strong paternal effect on the expression of SSB, suggesting possible Y-linkage of the trait. Our results inform evolutionary genetic mechanisms that might maintain low but persistently observed levels of male SSB in D. melanogaster, but highlight a need for broader taxonomic representation in studies of its evolutionary causes. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  17. Philibert Delorme’s Divine Proportions and the Composition of the Premier Tome de l’Architecture

    Directory of Open Access Journals (Sweden)

    Sara Galletti

    2014-06-01

    Full Text Available In his 'Premier tome de l’architecture' (1567 — the first original, comprehensive architectural treatise written by a French author — Philibert Delorme (c. 1514–1570 claims to be the first to formulate a theory of divine proportions, which he describes as a set of rules recorded in the Old Testament as directly dictated by God to men for the construction of the Ark of Noah, the Ark of the Covenant, and the Temple and House of Solomon. Yet the author does not develop the theory of divine proportions in the 'Premier tome' and postpones it instead to the second volume of his treatise. As a second volume was never published (and likely never written, Delorme readers are left with a handful of less-than-coherent references and illustrations of a theory that remains largely obscure. Yet the elements of theory of divine proportions contained in the 'Premier tome' provide historians with an understanding of the genesis of the treatise itself, thus ultimately helping to raise broader questions about the book and its author. This paper shows how Delorme’s divine proportions offer a key to understanding the conception and composition of his treatise as well as to the process of intellectual development of the author and the changes in the nature and scope of his written work.

  18. 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

    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...... 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...... and Yucatan) are obtained by genetic engineering of somatic cells and animal cloning by somatic cell nuclear transfer. Primary minipig fibroblasts are genetically modified in culture by transposon-based transgenesis and/or homologous recombination with AAV-transduced constructs. The designed pig cells...

  19. Do clones degenerate over time? Explaining the genetic variability of asexuals through population genetic models

    Directory of Open Access Journals (Sweden)

    Drozd Pavel

    2011-03-01

    Full Text Available Abstract Background Quest for understanding the nature of mechanisms governing the life span of clonal organisms lasts for several decades. Phylogenetic evidence for recent origins of most clones is usually interpreted as proof that clones suffer from gradual age-dependent fitness decay (e.g. Muller's ratchet. However, we have shown that a neutral drift can also qualitatively explain the observed distribution of clonal ages. This finding was followed by several attempts to distinguish the effects of neutral and non-neutral processes. Most recently, Neiman et al. 2009 (Ann N Y Acad Sci.:1168:185-200. reviewed the distribution of asexual lineage ages estimated from a diverse array of taxa and concluded that neutral processes alone may not explain the observed data. Moreover, the authors inferred that similar types of mechanisms determine maximum asexual lineage ages in all asexual taxa. In this paper we review recent methods for distinguishing the effects of neutral and non-neutral processes and point at methodological problems related with them. Results and Discussion We found that contemporary analyses based on phylogenetic data are inadequate to provide any clear-cut answer about the nature and generality of processes affecting evolution of clones. As an alternative approach, we demonstrate that sequence variability in asexual populations is suitable to detect age-dependent selection against clonal lineages. We found that asexual taxa with relatively old clonal lineages are characterised by progressively stronger deviations from neutrality. Conclusions Our results demonstrate that some type of age-dependent selection against clones is generally operational in asexual animals, which cover a wide taxonomic range spanning from flatworms to vertebrates. However, we also found a notable difference between the data distribution predicted by available models of sequence evolution and those observed in empirical data. These findings point at the

  20. A cost-effectiveness model of genetic testing for the evaluation of families with hypertrophic cardiomyopathy.

    Science.gov (United States)

    Ingles, Jodie; McGaughran, Julie; Scuffham, Paul A; Atherton, John; Semsarian, Christopher

    2012-04-01

    Traditional management of families with hypertrophic cardiomyopathy (HCM) involves periodic lifetime clinical screening of family members, an approach that does not identify all gene carriers owing to incomplete penetrance and significant clinical heterogeneity. Limitations in availability and cost have meant genetic testing is not part of routine clinical management for many HCM families. To determine the cost-effectiveness of the addition of genetic testing to HCM family management, compared with clinical screening alone. A probabilistic Markov decision model was used to determine cost per quality-adjusted life-year and cost for each life-year gained when genetic testing is included in the management of Australian families with HCM, compared with the conventional approach of periodic clinical screening alone. The incremental cost-effectiveness ratio (ICER) was $A785 (£510 or €587) per quality-adjusted life-year gained, and $A12 720 (£8261 or €9509) per additional life-year gained making genetic testing a very cost-effective strategy. Sensitivity analyses showed that the cost of proband genetic testing was an important variable. As the cost of proband genetic testing decreased, the ICER decreased and was cost saving when the cost fell below $A248 (£161 or €185). In addition, the mutation identification rate was also important in reducing the overall ICER, although even at the upper limits, the ICER still fell well within accepted willingness to pay bounds. The addition of genetic testing to the management of HCM families is cost-effective in comparison with the conventional approach of regular clinical screening. This has important implications for the evaluation of families with HCM, and suggests that all should have access to specialised cardiac genetic clinics that can offer genetic testing.

  1. Fixed Points in Discrete Models for Regulatory Genetic Networks

    Directory of Open Access Journals (Sweden)

    Orozco Edusmildo

    2007-01-01

    Full Text Available It is desirable to have efficient mathematical methods to extract information about regulatory iterations between genes from repeated measurements of gene transcript concentrations. One piece of information is of interest when the dynamics reaches a steady state. In this paper we develop tools that enable the detection of steady states that are modeled by fixed points in discrete finite dynamical systems. We discuss two algebraic models, a univariate model and a multivariate model. We show that these two models are equivalent and that one can be converted to the other by means of a discrete Fourier transform. We give a new, more general definition of a linear finite dynamical system and we give a necessary and sufficient condition for such a system to be a fixed point system, that is, all cycles are of length one. We show how this result for generalized linear systems can be used to determine when certain nonlinear systems (monomial dynamical systems over finite fields are fixed point systems. We also show how it is possible to determine in polynomial time when an ordinary linear system (defined over a finite field is a fixed point system. We conclude with a necessary condition for a univariate finite dynamical system to be a fixed point system.

  2. Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

    Science.gov (United States)

    Row, Jeffrey R.; Knick, Steven T.; Oyler-McCance, Sara J.; Lougheed, Stephen C.; Fedy, Bradley C.

    2017-01-01

    Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

  3. Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations.

    Science.gov (United States)

    Row, Jeffrey R; Knick, Steven T; Oyler-McCance, Sara J; Lougheed, Stephen C; Fedy, Bradley C

    2017-06-01

    Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R(2) values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

  4. 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.

  5. [Determination of Virtual Surgery Mass Point Spring Model Parameters Based on Genetic Algorithms].

    Science.gov (United States)

    Chen, Ying; Hu, Xuyi; Zhu, Qiguang

    2015-12-01

    Mass point-spring model is one of the commonly used models in virtual surgery. However, its model parameters have no clear physical meaning, and it is hard to set the parameter conveniently. We, therefore, proposed a method based on genetic algorithm to determine the mass-spring model parameters. Computer-aided tomography (CAT) data were used to determine the mass value of the particle, and stiffness and damping coefficient were obtained by genetic algorithm. We used the difference between the reference deformation and virtual deformation as the fitness function to get the approximate optimal solution of the model parameters. Experimental results showed that this method could obtain an approximate optimal solution of spring parameters with lower cost, and could accurately reproduce the effect of the actual deformation model as well.

  6. Chemical genetics and drug screening in Drosophila cancer models

    Institute of Scientific and Technical Information of China (English)

    Mara Gladstone; Tin Tin Su

    2011-01-01

    Drug candidates often fail in preclinical and clinical testing because of reasons of efficacy and/or safety.It would be time- and cost-efficient to have screening models that reduce the rate of such false positive candidates that appear promising at first but fail later.In this regard,it would be particularly useful to have a rapid and inexpensive whole animal model that can pre-select hits from high-throughput screens but before testing in costly rodent assays.Drosophila melanogaster has emerged as a potential whole animal model for drug screening.Of particular interest have been drugs that must act in the context of multi-cellularity such as those for neurological disorders and cancer.A recent review provides a comprehensive summary of drug screening in Drosophila,but with an emphasis on neurodegenerative disorders.Here,we review Drosophila screens in the literature aimed at cancer therapeutics.

  7. Increased numbers of orexin/hypocretin neurons in a genetic rat depression model

    DEFF Research Database (Denmark)

    Mikrouli, Elli; Wörtwein, Gitta; Soylu, Rana

    2011-01-01

    The Flinders Sensitive Line (FSL) rat is a genetic animal model of depression that displays characteristics similar to those of depressed patients including lower body weight, decreased appetite and reduced REM sleep latency. Hypothalamic neuropeptides such as orexin/hypocretin, melanin-concentra......The Flinders Sensitive Line (FSL) rat is a genetic animal model of depression that displays characteristics similar to those of depressed patients including lower body weight, decreased appetite and reduced REM sleep latency. Hypothalamic neuropeptides such as orexin/hypocretin, melanin...

  8. [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.

  9. Genetic algorithm-based multi-objective model for scheduling of linear construction projects

    OpenAIRE

    Senouci, Ahmed B.; Al-Derham, H.R.

    2007-01-01

    This paper presents a genetic algorithm-based multi-objective optimization model for the scheduling of linear construction projects. The model allows construction planners to generate and evaluate optimal/near-optimal construction scheduling plans that minimize both project time and cost. The computations in the present model are organized in three major modules. A scheduling module that develops practical schedules for linear construction projects. A cost module that computes the project's c...

  10. Overview of KRAS-Driven Genetically Engineered Mouse Models of Non-Small Cell Lung Cancer.

    Science.gov (United States)

    Sheridan, Clare; Downward, Julian

    2015-01-01

    KRAS, the most frequently mutated oncogene in non-small cell lung cancer, has been utilized extensively to model human lung adenocarcinomas. The results from such studies have enhanced considerably an understanding of the relationship between KRAS and the development of lung cancer. Detailed in this overview are the features of various KRAS-driven genetically engineered mouse models (GEMMs) of non-small cell lung cancer, their utilization, and the potential of these models for the study of lung cancer biology.

  11. Premier Wen Jiabao Chaired a State Council Executive Meeting to Review and Deploy the Program to Further Implement the Restructuring and Reinvigoration Plan for Key Industries

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    @@ Premier Wen Jiabao chaired a State Council executive meeting to review and deploy the program to further implement the restructuring and reinvigoration plan for key industries on February 24th,2010.

  12. Stress, glucocorticoids and absences in a genetic epilepsy model

    NARCIS (Netherlands)

    Tolmacheva, E.A.; Oitzl, M.S.; Luijtelaar, E.L.J.M. van

    2012-01-01

    Although stress can alter the susceptibility of patients and animal models to convulsive epilepsy, little is known about the role of stress and glucocorticoid hormones in absence epilepsy. We measured the basal and acute stress-induced (foot-shocks: FS) concentrations of corticosterone in WAG/Rij ra

  13. First attempts of linking modelling, Postharvest behaviour and Melon Genetics

    NARCIS (Netherlands)

    Tijskens, L.M.M.; Santos, Don N.; Obando-Ulloa, J.M.; Moreno, E.; Schouten, R.E.

    2008-01-01

    The onset of climacteric is associated with the end of melon fruit shelf-life. The aim of this research was to develop practical and applicable models of fruit ripening changes (hardness, moisture loss) also able to discriminate between climacteric and non-climacteric behaviour. The decrease in firm

  14. A genetically humanized mouse model for hepatitis C virus infection.

    NARCIS (Netherlands)

    Dorner, M.; Horwitz, J.A.; Robbins, J.B.; Barry, W.T.; Feng, Q.; Mu, K.; Jones, C.T.; Schoggins, J.W.; Catanese, M.T.; Burton, D.R.; Law, M.; Rice, C.M.; Ploss, A.

    2011-01-01

    Hepatitis C virus (HCV) remains a major medical problem. Antiviral treatment is only partially effective and a vaccine does not exist. Development of more effective therapies has been hampered by the lack of a suitable small animal model. Although xenotransplantation of immunodeficient mice with hum

  15. Using genetic data to improve species distribution models.

    Science.gov (United States)

    Bouyer, Jérémy; Lancelot, Renaud

    2017-03-23

    Tsetse flies (Diptera, Glossinidae) transmit human and animal trypanosomoses in Africa, respectively a neglected human disease (sleeping sickness) and the most important constraint to cattle production in infested countries (nagana). We recently developed a methodology to map landscape friction (i.e. resistance to movement) for tsetse in West Africa. The goal was to identify natural barriers to tsetse dispersal, and potentially isolated tsetse populations for targeting elimination programmes. Most species distribution models neglect landscape functional connectivity whereas environmental factors affecting suitability or abundance are not necessarily the same as those influencing gene flows. Geographic distributions of a given species can be seen as the intersection between biotic (B), abiotic (A) and movement (M) factors (BAM diagram). Here we show that the suitable habitat for Glossina palpalis gambiensis as modelled by Maxent can be corrected by landscape functional connectivity (M) extracted from our friction analysis. This procedure did not degrade the specificity of the distribution model (P=0.751) whereas the predicted distribution area was reduced. The added value of this approach is that it reveals unconnected habitat patches. The approach we developed on tsetse to inform landscape connectivity (M) is reproducible and does not rely on expert knowledge. It can be applied to any species: we call for a generalization of the use of M to improve distribution models. Copyright © 2017. Published by Elsevier B.V.

  16. 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.

  17. 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

  18. Hospital arrival time and functional outcome after acute ischaemic stroke: results from the PREMIER study.

    Science.gov (United States)

    León-Jiménez, C; Ruiz-Sandoval, J L; Chiquete, E; Vega-Arroyo, M; Arauz, A; Murillo-Bonilla, L M; Ochoa-Guzmán, A; Carrillo-Loza, K; Ramos-Moreno, A; Barinagarrementeria, F; Cantú-Brito, C

    2014-05-01

    Information regarding hospital arrival times after acute ischaemic stroke (AIS) has mainly been gathered from countries with specialised stroke units. Little data from emerging nations is available. We aim to identify factors associated with achieving hospital arrival times of less than 1, 3, and 6 hours, and analyse how arrival times are related to functional outcomes after AIS. We analysed data from patients with AIS included in the PREMIER study (Primer Registro Mexicano de Isquemia Cerebral) which defined time from symptom onset to hospital arrival. The functional prognosis at 30 days and at 3, 6, and 12 months was evaluated using the modified Rankin Scale. Among 1096 patients with AIS, 61 (6%) arrived in <1 hour, 250 (23%) in <3 hours, and 464 (42%) in <6 hours. The factors associated with very early (<1 hour) arrival were family history of ischemic heart disease and personal history of migraines; in <3 hours: age 40-69 years, family history of hypertension, personal history of dyslipidaemia and ischaemic heart disease, and care in a private hospital; in <6 hours: migraine, previous stroke, ischaemic heart disease, care in a private hospital, and family history of hypertension. Delayed hospital arrival was associated with lacunar stroke and alcoholism. Only 2.4% of patients underwent thrombolysis. Regardless of whether or not thrombolysis was performed, arrival time in <3 hours was associated with lower mortality at 3 and 6 months, and with fewer in-hospital complications. A high percentage of patients had short hospital arrival times; however, less than 3% underwent thrombolysis. Although many factors were associated with early hospital arrival, it is a priority to identify in-hospital barriers to performing thrombolysis. Copyright © 2013 Sociedad Española de Neurología. Published by Elsevier Espana. All rights reserved.

  19. PREMIERS RESULTATS SUR LES COMPORTEMENTS DE SUBSISTANCE SOLUTREENS A LA GROTTE ROCHEFORT (MAYENNE, FRANCE

    Directory of Open Access Journals (Sweden)

    Céline Bemilli

    2013-09-01

    Full Text Available Le site de la grotte Rochefort (Mayenne, France a livré depuis 2005 plusieurs centaines de restes fauniques issus des couches Solutréennes. Le Renne et le Cheval en sont les principales composantes et reflètent le fond commun du régime alimentaire des Solutréens. Nous présenterons ici les premiers résultats de l’analyse archéozoologique concernant l’exploitation de ces deux principaux taxons. Plusieurs recollages ont été réalisés. L’exceptionnelle conservation des restes permet, outre une excellente lecture des traces de découpe, une première reconstitution des modalités d’acquisition et d’exploitation des animaux, ainsi que leur saison d’abattage. La rareté des ensembles fauniques solutréens fouillés et étudiés récemment donne à celui de la grotte Rochefort un impact particulier et inédit.Several hundreds faunal remains were discovered since 2005 in the Solutrean‘s level at Rochefort cave (Mayenne, France. Reindeer and Horse are the main taxa identified and are the baseline of the Solutrean diet. We present here the preliminary results of the faunal analysis and discuss the exploitation of these two main taxa. A number of refits were possible. At the same time, the exceptional preservation of the artefacts together with well-defined cut marks allows to reconstruct procurement and use patterns of these animals as well as the season they were killed. Recently excavated and analysed Solutrean faunal assemblages are rare which make the yet unreported Rochefort cave faunal assemblage even more important and unprecedented.

  20. Model organisms for genetics in the domain Archaea: methanogens, halophiles, Thermococcales and Sulfolobales.

    Science.gov (United States)

    Leigh, John A; Albers, Sonja-Verena; Atomi, Haruyuki; Allers, Thorsten

    2011-07-01

    The tree of life is split into three main branches: eukaryotes, bacteria, and archaea. Our knowledge of eukaryotic and bacteria cell biology has been built on a foundation of studies in model organisms, using the complementary approaches of genetics and biochemistry. Archaea have led to some exciting discoveries in the field of biochemistry, but archaeal genetics has been slow to get off the ground, not least because these organisms inhabit some of the more inhospitable places on earth and are therefore believed to be difficult to culture. In fact, many species can be cultivated with relative ease and there has been tremendous progress in the development of genetic tools for both major archaeal phyla, the Euryarchaeota and the Crenarchaeota. There are several model organisms available for methanogens, halophiles, and thermophiles; in the latter group, there are genetic systems for Sulfolobales and Thermococcales. In this review, we present the advantages and disadvantages of working with each archaeal group, give an overview of their different genetic systems, and direct the neophyte archaeologist to the most appropriate model organism.

  1. Integrating Genetic, Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity.

    Directory of Open Access Journals (Sweden)

    Sergi Mas

    Full Text Available We propose an integrative approach that combines structural magnetic resonance imaging data (MRI, diffusion tensor imaging data (DTI, neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38 and a validation set (N = 18. Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder.

  2. Integrating Genetic, Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity.

    Science.gov (United States)

    Mas, Sergi; Gassó, Patricia; Morer, Astrid; Calvo, Anna; Bargalló, Nuria; Lafuente, Amalia; Lázaro, Luisa

    2016-01-01

    We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder.

  3. Genetically modified mouse models for premature ovarian failure (POF).

    Science.gov (United States)

    Jagarlamudi, Krishna; Reddy, Pradeep; Adhikari, Deepak; Liu, Kui

    2010-02-01

    Premature ovarian failure (POF) is a complex disorder that affects approximately 1% of women. POF is characterized by the depletion of functional ovarian follicles before the age of 40 years, and clinically, patients may present with primary amenorrhea or secondary amenorrhea. Although some genes have been hypothesized to be candidates responsible for POF, the etiology of most of the cases is idiopathic, with the underlying causes still unidentified because of the heterogeneity of the disease. In this review, we consider some mutant mouse models that exhibit phenotypes which are comparable to human POF, and we suggest that the use of these mouse models may help us to gain a better understanding of the molecular mechanisms underlying POF in humans.

  4. Drosophila as a genetic model for studying pathogenic human viruses.

    Science.gov (United States)

    Hughes, Tamara T; Allen, Amanda L; Bardin, Joseph E; Christian, Megan N; Daimon, Kansei; Dozier, Kelsey D; Hansen, Caom L; Holcomb, Lisa M; Ahlander, Joseph

    2012-02-05

    Viruses are infectious particles whose viability is dependent on the cells of living organisms, such as bacteria, plants, and animals. It is of great interest to discover how viruses function inside host cells in order to develop therapies to treat virally infected organisms. The fruit fly Drosophila melanogaster is an excellent model system for studying the molecular mechanisms of replication, amplification, and cellular consequences of human viruses. In this review, we describe the advantages of using Drosophila as a model system to study human viruses, and highlight how Drosophila has been used to provide unique insight into the gene function of several pathogenic viruses. We also propose possible directions for future research in this area.

  5. 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.

  6. Genetically engineered mucin mouse models for inflammation and cancer

    Science.gov (United States)

    Joshi, Suhasini; Kumar, Sushil; Bafna, Sangeeta; Rachagani, Satyanarayana; Wagner, Kay-Uwe; Jain, Maneesh

    2015-01-01

    Mucins are heavily O-glycosylated proteins primarily produced by glandular and ductal epithelial cells, either in membrane-tethered or secretory forms, for providing lubrication and protection from various exogenous and endogenous insults. However, recent studies have linked their aberrant overexpression with infection, inflammation, and cancer that underscores their importance in tissue homeostasis. In this review, we present current status of the existing mouse models that have been developed to gain insights into the functional role(s) of mucins under physiological and pathological conditions. Knockout mouse models for membrane-associated (Muc1 and Muc16) and secretory mucins (Muc2) have helped us to elucidate the role of mucins in providing effective and protective barrier functions against pathological threats, participation in disease progression, and improved our understanding of mucin interaction with biotic and abiotic environmental components. Emphasis is also given to available transgenic mouse models (MUC1 and MUC7), which has been exploited to understand the context-dependent regulation and therapeutic potential of human mucins during inflammation and cancer. PMID:25634251

  7. 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.

  8. Using genetic algorithm based simulated annealing penalty function to solve groundwater management model

    Institute of Scientific and Technical Information of China (English)

    吴剑锋; 朱学愚; 刘建立

    1999-01-01

    The genetic algorithm (GA) is a global and random search procedure based on the mechanics of natural selection and natural genetics. A new optimization method of the genetic algorithm-based simulated annealing penalty function (GASAPF) is presented to solve groundwater management model. Compared with the traditional gradient-based algorithms, the GA is straightforward and there is no need to calculate derivatives of the objective function. The GA is able to generate both convex and nonconvex points within the feasible region. It can be sure that the GA converges to the global or at least near-global optimal solution to handle the constraints by simulated annealing technique. Maximum pumping example results show that the GASAPF to solve optimization model is very efficient and robust.

  9. Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape.

    Science.gov (United States)

    Baker, Robert L; Leong, Wen Fung; Brock, Marcus T; Markelz, R J Cody; Covington, Michael F; Devisetty, Upendra K; Edwards, Christine E; Maloof, Julin; Welch, Stephen; Weinig, Cynthia

    2015-10-01

    Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange.

  10. Analysis of genetic variation and potential applications in genome-scale metabolic modeling

    Directory of Open Access Journals (Sweden)

    João Gonçalo Rocha Cardoso

    2015-02-01

    Full Text Available Genetic variation is the motor of evolution and allows organisms to overcome the environmental challenges they encounter. It can be both beneficial and harmful in the process of engineering cell factories for the production of proteins and chemicals. Throughout the history of biotechnology, there have been efforts to exploit genetic variation in our favor to create strains with favorable phenotypes. Genetic variation can either be present in natural populations or it can be artificially created by mutagenesis and selection or adaptive laboratory evolution. On the other hand, unintended genetic variation during a long term production process may lead to significant economic losses and it is important to understand how to control this type of variation. With the emergence of next-generation sequencing technologies, genetic variation in microbial strains can now be determined on an unprecedented scale and resolution by re-sequencing thousands of strains systematically. In this article, we review challenges in the integration and analysis of large-scale re-sequencing data, present an extensive overview of bioinformatics methods for predicting the effects of genetic variants on protein function, and discuss approaches for interfacing existing bioinformatics approaches with genome-scale models of cellular processes in order to predict effects of sequence variation on cellular phenotypes.

  11. Temperature drift modeling of MEMS gyroscope based on genetic-Elman neural network

    Science.gov (United States)

    Chong, Shen; Rui, Song; Jie, Li; Xiaoming, Zhang; Jun, Tang; Yunbo, Shi; Jun, Liu; Huiliang, Cao

    2016-05-01

    In order to improve the temperature drift modeling precision of a tuning fork micro-electromechanical system (MEMS) gyroscope, a novel multiple inputs/single output model based on genetic algorithm (GA) and Elman neural network (Elman NN) is proposed. First, the temperature experiment of MEMS gyroscope is carried out and the outputs of MEMS gyroscope and temperature sensors are collected; then the temperature drift model based on temperature, temperature variation rate and the coupling term is proposed, and the Elman NN is employed to guarantee the generalization ability of the model; at last the genetic algorithm is used to tune the parameters of Elman NN in order to improve the modeling precision. The Allan analysis results validate that, compared to traditional single input/single output model, the novel multiple inputs/single output model can guarantee high accurate fitting ability because the proposed model can provide more plentiful controllable information. By the way, the generalization ability of the Elman neural network can be improved significantly due to the parameters are optimized by genetic algorithm.

  12. Quantitative genetic modeling and inference in the presence of nonignorable missing data.

    Science.gov (United States)

    Steinsland, Ingelin; Larsen, Camilla Thorrud; Roulin, Alexandre; Jensen, Henrik

    2014-06-01

    Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

  13. Genetically modified mouse models for the study of nonalcoholic fatty liver disease

    Institute of Scientific and Technical Information of China (English)

    Perumal Nagarajan; M Jerald Mahesh Kumar; Ramasamy Venkatesan; Subeer S Majundar; Ramesh C Juyal

    2012-01-01

    Nonalcoholic fatty liver disease (NAFLD) is associated with obesity,insulin resistance,and type 2 diabetes.NAFLD represents a large spectrum of diseases ranging from (1) fatty liver (hepatic steatosis); (2) steatosis with inflammation and necrosis; to (3) cirrhosis.The animal models to study NAFLD/nonalcoholic steatohepatitis (NASH) are extremely useful,as there are still many events to be elucidated in the pathology of NASH.The study of the established animal models has provided many clues in the pathogenesis of steatosis and steatohepatitis,but these remain incompletely understood.The different mouse models can be classified in two large groups.The first one includes genetically modified (transgenic or knockout) mice that spontaneously develop liver disease,and the second one includes mice that acquire the disease after dietary or pharmacological manipulation.Although the molecular mechanism leading to the development of hepatic steatosis in the pathogenesis of NAFLD is complex,genetically modified animal models may be a key for the treatment of NAFLD.Ideal animal models for NASH should closely resemble the pathological characteristics observed in humans.To date,no single animal model has encompassed the full spectrum of human disease progression,but they can imitate particular characteristics of human disease.Therefore,it is important that the researchers choose the appropriate animal model.This review discusses various genetically modified animal models developed and used in research on NAFLD.

  14. Genetic and Modeling Approaches Reveal Distinct Components of Impulsive Behavior.

    Science.gov (United States)

    Nautiyal, Katherine M; Wall, Melanie M; Wang, Shuai; Magalong, Valerie M; Ahmari, Susanne E; Balsam, Peter D; Blanco, Carlos; Hen, René

    2017-01-18

    Impulsivity is an endophenotype found in many psychiatric disorders including substance use disorders, pathological gambling, and attention deficit hyperactivity disorder. Two behavioral features often considered in impulsive behavior are behavioral inhibition (impulsive action) and delayed gratification (impulsive choice). However, the extent to which these behavioral constructs represent distinct facets of behavior with discrete biological bases is unclear. To test the hypothesis that impulsive action and impulsive choice represent statistically independent behavioral constructs in mice, we collected behavioral measures of impulsivity in a single cohort of mice using well-validated operant behavioral paradigms. Mice with manipulation of serotonin 1B receptor (5-HT1BR) expression were included as a model of disordered impulsivity. A factor analysis was used to characterize correlations between the measures of impulsivity and to identify covariates. Using two approaches, we dissociated impulsive action from impulsive choice. First, the absence of 5-HT1BRs caused increased impulsive action, but not impulsive choice. Second, based on an exploratory factor analysis, a two-factor model described the data well, with measures of impulsive action and choice separating into two independent factors. A multiple-indicator multiple-causes analysis showed that 5-HT1BR expression and sex were significant covariates of impulsivity. Males displayed increased impulsivity in both dimensions, whereas 5-HT1BR expression was a predictor of increased impulsive action only. These data support the conclusion that impulsive action and impulsive choice are distinct behavioral phenotypes with dissociable biological influences that can be modeled in mice. Our work may help inform better classification, diagnosis, and treatment of psychiatric disorders, which present with disordered impulsivity.Neuropsychopharmacology advance online publication, 18 January 2017; doi:10.1038/npp.2016.277.

  15. Mouse genetic models for temporomandibular joint development and disorders.

    Science.gov (United States)

    Suzuki, A; Iwata, J

    2016-01-01

    The temporomandibular joint (TMJ) is a synovial joint essential for hinge and sliding movements of the mammalian jaw. Temporomandibular joint disorders (TMD) are dysregulations of the muscles or the TMJ in structure, function, and physiology, and result in pain, limited mandibular mobility, and TMJ noise and clicking. Although approximately 40-70% adults in the USA have at least one sign of TMD, the etiology of TMD remains largely unknown. Here, we highlight recent advances in our understanding of TMD in mouse models. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  16. 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...... 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......" or "non-informative" with respect to genetic (co)variance components. The "non-informative" individuals are characterized by their Mendelian sampling deviations (deviance from the mid-parent mean) being completely confounded with a single residual on the underlying liability scale. For threshold models...

  17. Neuropathology and Animal Models of Autism: Genetic and Environmental Factors

    Directory of Open Access Journals (Sweden)

    Bharathi S. Gadad

    2013-01-01

    Full Text Available Autism is a heterogeneous behaviorally defined neurodevelopmental disorder. It is defined by the presence of marked social deficits, specific language abnormalities, and stereotyped repetitive patterns of behavior. Because of the variability in the behavioral phenotype of the disorder among patients, the term autism spectrum disorder has been established. In the first part of this review, we provide an overview of neuropathological findings from studies of autism postmortem brains and identify the cerebellum as one of the key brain regions that can play a role in the autism phenotype. We review research findings that indicate possible links between the environment and autism including the role of mercury and immune-related factors. Because both genes and environment can alter the structure of the developing brain in different ways, it is not surprising that there is heterogeneity in the behavioral and neuropathological phenotypes of autism spectrum disorders. Finally, we describe animal models of autism that occur following insertion of different autism-related genes and exposure to environmental factors, highlighting those models which exhibit both autism-like behavior and neuropathology.

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

    Science.gov (United States)

    Wang, Chunkao; Da, Yang

    2014-01-01

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

  19. Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data.

    Science.gov (United States)

    Wang, Joanne H; Pappas, Derek; De Jager, Philip L; Pelletier, Daniel; de Bakker, Paul Iw; Kappos, Ludwig; Polman, Chris H; Chibnik, Lori B; Hafler, David A; Matthews, Paul M; Hauser, Stephen L; Baranzini, Sergio E; Oksenberg, Jorge R

    2011-01-18

    Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant

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

    Science.gov (United States)

    Xu, Hanfu; O'Brochta, David A

    2015-07-07

    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.

  1. 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.

  2. 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.

  3. Stochastic dynamic simulation modeling including multitrait genetics to estimate genetic, technical, and financial consequences of dairy farm reproduction and selection strategies.

    Science.gov (United States)

    Kaniyamattam, K; Elzo, M A; Cole, J B; De Vries, A

    2016-10-01

    The objective of this study was to develop a daily stochastic dynamic dairy simulation model that included multitrait genetics and to evaluate the effects of reduced genetic models and various reproduction and selection strategies on the genetic, technical, and financial performance of a dairy herd. The 12 correlated genetic traits included in the 2014 lifetime net merit (NM$) index were modeled for each animal. For each animal, a true breeding value (TBV) for each trait was calculated as the average of the sire's and dam's TBV, plus a fraction of the inbreeding and Mendelian sampling variability. Similarly, an environmental component for each trait was calculated and was partitioned into a permanent and a daily (temporary) effect. The combined TBV and environmental effects were converted into the phenotypic performance of each animal. Hence, genetics and phenotypic performances were associated. Estimated breeding values (EBV) were also simulated. Genetic trends for each trait for the service sire were based on expected trends in US Holsteins. Surplus heifers were culled based on various ranking criteria to maintain a herd size of 1,000 milking cows. In the first 8 scenarios, culling of surplus heifers was either random or based on the EBV of NM$. Four different genetic models, depending on the presence or absence of genetic trends or genetic and environmental correlations, or both, were evaluated to measure the effect of excluding multitrait genetics on animal performance. In the last 5 scenarios, the full genetic model was used and culling of surplus heifers was either random or based on the EBV of NM$ or the EBV of milk. Sexed semen use and reliability of the EBV were also varied. Each scenario was simulated for 15yr into the future. Results showed that genetic models without all 12 genetic trends and genetic and environmental correlations provided biased estimates of the genetic, technical, and financial performance of the dairy herd. Average TBV of NM$ of all

  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 a...

  5. 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.

  6. 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…

  7. 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…

  8. Models to estimate genetic parameters in crossbred dairy cattle populations under selection.

    NARCIS (Netherlands)

    Werf, van der J.H.J.

    1990-01-01

    Estimates of genetic parameters needed to control breeding programs, have to be regularly updated, due to changing environments and ongoing selection and crossing of populations. Restricted maximum likelihood methods optimally provide these estimates, assuming that the statisticalgenetic model u

  9. 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

    on the mean level of a phenotype, they are not sufficiently straightforward to handle the kinship correlation on the time-dependent trajectories of a phenotype. We introduce a 2-level hierarchical linear model to separately assess the genetic associations with the mean level and the rate of change...

  10. 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 availab...

  11. Anti-epileptogenesis: Electrophysiology, diffusion tensor imaging and behavior in a genetic absence model

    NARCIS (Netherlands)

    Luijtelaar, E.L.J.M. van; Mishra, A.M.; Edelbroek, P.M.; Coman, D.; Frankenmolen, N.L.; Schaapsmeerders, P.; Covolato, G.; Danielson, N.; Niermann, H.C.M.; Janeczko, K.; Kiemeneij, A.; Burinov, J.; Bashyal, C.; Coquillette, M.; Luttjohann, A.K.; Hyder, F.; Blumenfeld, H.; Rijn, C.M. van

    2013-01-01

    The beneficial effects of chronic and early pharmacological treatment with ethosuximide on epileptogenesis were studied in a genetic absence epilepsy model comorbid for depression. It was also investigated whether there is a critical treatment period and treatment length. Cortical excitability in th

  12. Reverse engineering gene networks: Integrating genetic perturbations with dynamical modeling

    Science.gov (United States)

    Tegnér, Jesper; Yeung, M. K. Stephen; Hasty, Jeff; Collins, James J.

    2003-01-01

    While the fundamental building blocks of biology are being tabulated by the various genome projects, microarray technology is setting the stage for the task of deducing the connectivity of large-scale gene networks. We show how the perturbation of carefully chosen genes in a microarray experiment can be used in conjunction with a reverse engineering algorithm to reveal the architecture of an underlying gene regulatory network. Our iterative scheme identifies the network topology by analyzing the steady-state changes in gene expression resulting from the systematic perturbation of a particular node in the network. We highlight the validity of our reverse engineering approach through the successful deduction of the topology of a linear in numero gene network and a recently reported model for the segmentation polarity network in Drosophila melanogaster. Our method may prove useful in identifying and validating specific drug targets and in deconvolving the effects of chemical compounds. PMID:12730377

  13. Genetic Mouse Models: The Powerful Tools to Study Fat Tissues.

    Science.gov (United States)

    Kong, Xingxing; Williams, Kevin W; Liu, Tiemin

    2017-01-01

    Obesity and Type 2 diabetes (T2D) are associated with a variety of comorbidities that contribute to mortality around the world. Although significant effort has been expended in understanding mechanisms that mitigate the consequences of this epidemic, the field has experienced limited success thus far. The potential ability of brown adipose tissue (BAT) to counteract obesity and metabolic disease in rodents (and potentially in humans) has been a topical realization. Recently, there is also another thermogenic fat cell called beige adipocytes, which are located among white adipocytes and share similar activated responses to cyclic AMP as classical BAT. In this chapter, we review contemporary molecular strategies to investigate the role of adipose tissue depots in metabolism. In particular, we will discuss the generation of adipose tissue-specific knockout and overexpression of target genes in various mouse models. We will also discuss how to use different Cre (cyclization recombination) mouse lines to investigate diverse types of adipocytes.

  14. On models of the genetic code generated by binary dichotomic algorithms.

    Science.gov (United States)

    Gumbel, Markus; Fimmel, Elena; Danielli, Alberto; Strüngmann, Lutz

    2015-02-01

    In this paper we introduce the concept of a BDA-generated model of the genetic code which is based on binary dichotomic algorithms (BDAs). A BDA-generated model is based on binary dichotomic algorithms (BDAs). Such a BDA partitions the set of 64 codons into two disjoint classes of size 32 each and provides a generalization of known partitions like the Rumer dichotomy. We investigate what partitions can be generated when a set of different BDAs is applied sequentially to the set of codons. The search revealed that these models are able to generate code tables with very different numbers of classes ranging from 2 to 64. We have analyzed whether there are models that map the codons to their amino acids. A perfect matching is not possible. However, we present models that describe the standard genetic code with only few errors. There are also models that map all 64 codons uniquely to 64 classes showing that BDAs can be used to identify codons precisely. This could serve as a basis for further mathematical analysis using coding theory, for example. The hypothesis that BDAs might reflect a molecular mechanism taking place in the decoding center of the ribosome is discussed. The scan demonstrated that binary dichotomic partitions are able to model different aspects of the genetic code very well. The search was performed with our tool Beady-A. This software is freely available at http://mi.informatik.hs-mannheim.de/beady-a. It requires a JVM version 6 or higher.

  15. Modelling soil water retention using support vector machines with genetic algorithm optimisation.

    Science.gov (United States)

    Lamorski, Krzysztof; Sławiński, Cezary; Moreno, Felix; Barna, Gyöngyi; Skierucha, Wojciech; Arrue, José L

    2014-01-01

    This work presents point pedotransfer function (PTF) models of the soil water retention curve. The developed models allowed for estimation of the soil water content for the specified soil water potentials: -0.98, -3.10, -9.81, -31.02, -491.66, and -1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM) methodology was used for model development. A new methodology for elaboration of retention function models is proposed. Alternative to previous attempts known from literature, the ν-SVM method was used for model development and the results were compared with the formerly used the C-SVM method. For the purpose of models' parameters search, genetic algorithms were used as an optimisation framework. A new form of the aim function used for models parameters search is proposed which allowed for development of models with better prediction capabilities. This new aim function avoids overestimation of models which is typically encountered when root mean squared error is used as an aim function. Elaborated models showed good agreement with measured soil water retention data. Achieved coefficients of determination values were in the range 0.67-0.92. Studies demonstrated usability of ν-SVM methodology together with genetic algorithm optimisation for retention modelling which gave better performing models than other tested approaches.

  16. Extraction of battery parameters of the equivalent circuit model using a multi-objective genetic algorithm

    Science.gov (United States)

    Brand, Jonathan; Zhang, Zheming; Agarwal, Ramesh K.

    2014-02-01

    A simple but reasonably accurate battery model is required for simulating the performance of electrical systems that employ a battery for example an electric vehicle, as well as for investigating their potential as an energy storage device. In this paper, a relatively simple equivalent circuit based model is employed for modeling the performance of a battery. A computer code utilizing a multi-objective genetic algorithm is developed for the purpose of extracting the battery performance parameters. The code is applied to several existing industrial batteries as well as to two recently proposed high performance batteries which are currently in early research and development stage. The results demonstrate that with the optimally extracted performance parameters, the equivalent circuit based battery model can accurately predict the performance of various batteries of different sizes, capacities, and materials. Several test cases demonstrate that the multi-objective genetic algorithm can serve as a robust and reliable tool for extracting the battery performance parameters.

  17. Location Model and Optimization of Seaborne Petroleum Logistics Distribution Center Based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Chu-Liangyong

    2013-06-01

    Full Text Available The network of Chinese Waterborne Petroleum Logistics (CWPL is so complex that reasonably disposing and choosing Chinese Waterborne Petroleum Logistics Distribution Center (CWPLDC take on the important theory value and the practical significance. In the study, the network construct of CWPL distribution is provided and the corresponding mathematical model for locating CWPLDC is established, which is a nonlinear mixed interger model. In view of the nonlinerar programming characteristic of model, the genetic algorithm as the solution strategy is put forward here, the strategies of hybrid coding, constraint elimination , fitness function and genetic operator are given followed the algorithm. The result indicates that this model is effective and reliable. This method could also be applicable for other types of large-scale logistics distribution center optimization.

  18. IQ heritability estimation: analyzing genetically-informative data with structural equation models.

    Science.gov (United States)

    Gallardo Pujol, David; García-Forero, Carlos; Kramp, Uwe; Maydeu-Olivares, Albert; Andrés-Pueyo, Antonio

    2007-02-01

    When analyzing genetic data, Structural Equations Modeling (SEM) provides a straightforward methodology to decompose phenotypic variance using a model-based approach. Furthermore, several models can be easily implemented, tested, and compared using SEM, allowing the researcher to obtain valuable information about the sources of variability. This methodology is briefly described and applied to re-analyze a Spanish set of IQ data using the biometric ACE model. In summary, we report heritability estimates that are consistent with those of previous studies and support substantial genetic contribution to phenotypic IQ; around 40% of the variance can be attributable to it. With regard to the environmental contribution, shared environment accounts for 50% of the variance, and non-shared environment accounts for the remaining 10%. These results are discussed in the text.

  19. 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

  20. 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

  1. Genetic analysis of somatic cell score in Norwegian cattle using random regression test-day models.

    Science.gov (United States)

    Odegård, J; Jensen, J; Klemetsdal, G; Madsen, P; Heringstad, B

    2003-12-01

    The dataset used in this analysis contained a total of 341,736 test-day observations of somatic cell scores from 77,110 primiparous daughters of 1965 Norwegian Cattle sires. Initial analyses, using simple random regression models without genetic effects, indicated that use of homogeneous residual variance was appropriate. Further analyses were carried out by use of a repeatability model and 12 random regression sire models. Legendre polynomials of varying order were used to model both permanent environmental and sire effects, as did the Wilmink function, the Lidauer-Mäntysaari function, and the Ali-Schaeffer function. For all these models, heritability estimates were lowest at the beginning (0.05 to 0.07) and higher at the end (0.09 to 0.12) of lactation. Genetic correlations between somatic cell scores early and late in lactation were moderate to high (0.38 to 0.71), whereas genetic correlations for adjacent DIM were near unity. Models were compared based on likelihood ratio tests, Bayesian information criterion, Akaike information criterion, residual variance, and predictive ability. Based on prediction of randomly excluded observations, models with 4 coefficients for permanent environmental effect were preferred over simpler models. More highly parameterized models did not substantially increase predictive ability. Evaluation of the different model selection criteria indicated that a reduced order of fit for sire effects was desireable. Models with zeroth- or first-order of fit for sire effects and higher order of fit for permanent environmental effects probably underestimated sire variance. The chosen model had Legendre polynomials with 3 coefficients for sire, and 4 coefficients for permanent environmental effects. For this model, trajectories of sire variance and heritability were similar assuming either homogeneous or heterogeneous residual variance structure.

  2. [The discussion of the infiltrative model of chemical knowledge stepping into genetics teaching in agricultural institute or university].

    Science.gov (United States)

    Zou, Ping; Luo, Pei-Gao

    2010-05-01

    Chemistry is an important group of basic courses, while genetics is one of the important major-basic courses in curriculum of many majors in agricultural institutes or universities. In order to establish the linkage between the major course and the basic course, the ability of application of the chemical knowledge previously learned in understanding genetic knowledge in genetics teaching is worthy of discussion for genetics teachers. In this paper, the authors advocate to apply some chemical knowledge previously learned to understand genetic knowledge in genetics teaching with infiltrative model, which could help students learn and understand genetic knowledge more deeply. Analysis of the intrinsic logistic relationship among the knowledge of different courses and construction of the integral knowledge network are useful for students to improve their analytic, comprehensive and logistic abilities. By this way, we could explore a new teaching model to develop the talents with new ideas and comprehensive competence in agricultural fields.

  3. PTEN Gene: A Model for Genetic Diseases in Dermatology

    Directory of Open Access Journals (Sweden)

    Corrado Romano

    2012-01-01

    Full Text Available PTEN gene is considered one of the most mutated tumor suppressor genes in human cancer, and it’s likely to become the first one in the near future. Since 1997, its involvement in tumor suppression has smoothly increased, up to the current importance. Germline mutations of PTEN cause the PTEN hamartoma tumor syndrome (PHTS, which include the past-called Cowden, Bannayan-Riley-Ruvalcaba, Proteus, Proteus-like, and Lhermitte-Duclos syndromes. Somatic mutations of PTEN have been observed in glioblastoma, prostate cancer, and brest cancer cell lines, quoting only the first tissues where the involvement has been proven. The negative regulation of cell interactions with the extracellular matrix could be the way PTEN phosphatase acts as a tumor suppressor. PTEN gene plays an essential role in human development. A recent model sees PTEN function as a stepwise gradation, which can be impaired not only by heterozygous mutations and homozygous losses, but also by other molecular mechanisms, such as transcriptional regression, epigenetic silencing, regulation by microRNAs, posttranslational modification, and aberrant localization. The involvement of PTEN function in melanoma and multistage skin carcinogenesis, with its implication in cancer treatment, and the role of front office in diagnosing PHTS are the main reasons why the dermatologist should know about PTEN.

  4. Migraine pathophysiology: lessons from mouse models and human genetics.

    Science.gov (United States)

    Ferrari, Michel D; Klever, Roselin R; Terwindt, Gisela M; Ayata, Cenk; van den Maagdenberg, Arn M J M

    2015-01-01

    Migraine is a common, disabling, and undertreated episodic brain disorder that is more common in women than in men. Unbiased genome-wide association studies have identified 13 migraine-associated variants pointing at genes that cluster in pathways for glutamatergic neurotransmission, synaptic function, pain sensing, metalloproteinases, and the vasculature. The individual pathogenetic contribution of each gene variant is difficult to assess because of small effect sizes and complex interactions. Six genes with large effect sizes were identified in patients with rare monogenic migraine syndromes, in which hemiplegic migraine and non-hemiplegic migraine with or without aura are part of a wider clinical spectrum. Transgenic mouse models with human monogenic-migraine-syndrome gene mutations showed migraine-like features, increased glutamatergic neurotransmission, cerebral hyperexcitability, and enhanced susceptibility to cortical spreading depression, which is the electrophysiological correlate of aura and a putative trigger for migraine. Enhanced susceptibility to cortical spreading depression increased sensitivity to focal cerebral ischaemia, and blocking of cortical spreading depression improved stroke outcome in these mice. Changes in female hormone levels in these mice modulated cortical spreading depression susceptibility in much the same way that hormonal fluctuations affect migraine activity in patients. These findings confirm the multifactorial basis of migraine and might allow new prophylactic options to be developed, not only for migraine but potentially also for migraine-comorbid disorders such as epilepsy, depression, and stroke. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Estimates of genetic parameters for growth traits in Brahman cattle using random regression and multitrait models.

    Science.gov (United States)

    Bertipaglia, T S; Carreño, L O D; Aspilcueta-Borquis, R R; Boligon, A A; Farah, M M; Gomes, F J; Machado, C H C; Rey, F S B; da Fonseca, R

    2015-08-01

    Random regression models (RRM) and multitrait models (MTM) were used to estimate genetic parameters for growth traits in Brazilian Brahman cattle and to compare the estimated breeding values obtained by these 2 methodologies. For RRM, 78,641 weight records taken between 60 and 550 d of age from 16,204 cattle were analyzed, and for MTM, the analysis consisted of 17,385 weight records taken at the same ages from 12,925 cattle. All models included the fixed effects of contemporary group and the additive genetic, maternal genetic, and animal permanent environmental effects and the quadratic effect of age at calving (AAC) as covariate. For RRM, the AAC was nested in the animal's age class. The best RRM considered cubic polynomials and the residual variance heterogeneity (5 levels). For MTM, the weights were adjusted for standard ages. For RRM, additive heritability estimates ranged from 0.42 to 0.75, and for MTM, the estimates ranged from 0.44 to 0.72 for both models at 60, 120, 205, 365, and 550 d of age. The maximum maternal heritability estimate (0.08) was at 140 d for RRM, but for MTM, it was highest at weaning (0.09). The magnitude of the genetic correlations was generally from moderate to high. The RRM adequately modeled changes in variance or covariance with age, and provided there was sufficient number of samples, increased accuracy in the estimation of the genetic parameters can be expected. Correlation of bull classifications were different in both methods and at all the ages evaluated, especially at high selection intensities, which could affect the response to selection.

  6. 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

  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. Multiscale modeling for classification of SAR imagery using hybrid EM algorithm and genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    Xianbin Wen; Hua Zhang; Jianguang Zhang; Xu Jiao; Lei Wang

    2009-01-01

    A novel method that hybridizes genetic algorithm (GA) and expectation maximization (EM) algorithm for the classification of syn-thetic aperture radar (SAR) imagery is proposed by the finite Gaussian mixtures model (GMM) and multiscale autoregressive (MAR)model. This algorithm is capable of improving the global optimality and consistency of the classification performance. The experiments on the SAR images show that the proposed algorithm outperforms the standard EM method significantly in classification accuracy.

  9. 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...... categorizing only the most extreme SCS observations as mastitic, and such cases of subclinical infections may be the most closely related to clinical (treated) mastitis...

  10. Application of the CUDA programming model in the simulation of genetic sequences evolution

    Directory of Open Access Journals (Sweden)

    Freddy Yasmany Chávez

    2017-03-01

    Full Text Available Simulation is a powerful approach in the study of the molecular evolution of genetic sequences and their divergence over time; there are different procedures for the simulation of molecular evolution, but all of them have high computational complexity, and in most cases the genetic sequences have large size, increasing the execution time of the implementations of those procedures. Based on this problem, this paper describes a proposal of parallelization model using CUDA technology and the results of this proposal are compared with its sequential equivalent.

  11. Toward a biaxial model of "bipolar" affective disorders: further exploration of genetic, molecular and cellular substrates.

    Science.gov (United States)

    Askland, Kathleen

    2006-08-01

    Current epidemiologic and genetic evidence strongly supports the heritability of bipolar disease. Inconsistencies across linkage and association analyses have been primarily interpreted as suggesting polygenic, nonMendelian and variably-penetrant inheritance (i.e., in terms of interacting disease models). An equally-likely explanation for this genetic complexity is that trait, locus and allelic heterogeneities (i.e., a heterogeneous disease model) are primarily responsible for observed variability at the population level. The two models of genetic complexity are not mutually-exclusive, and are in fact likely to co-exist both in trait determination and disease expression. However, the current model proposes that, while both types of complex genetics are likely central to observable affective trait spectra, inheritance patterns, gross phenotypic categories and treatment-responsiveness in affective disease (as well as the widespread inconsistencies across such studies) may be primarily explained in terms of a heterogeneous disease model. Gene-gene, gene-protein and protein-protein interactions, then, are most likely to serve as trait determinants and 'phenotypic modifiers' rather than as primary pathogenic determinants. Moreover, while locus heterogeneity indicates the presence of multiple susceptibility genes at the population level, it does not necessitate polygenic inheritance at the individual or pedigree level. Rather, it is compatible with the possibility of mono- or bigenic determination of disease susceptibility within individuals/pedigrees. More specifically, the biaxial model proposes that integration of specific findings from genetic linkage and association studies, ion channels research as well as pharmacologic mechanism, phenotypic specificity and effectiveness studies suggests that each gene of potential etiologic significance in primary affective illness might be categorized into one of two classes, according to their primary role in neuronal

  12. A wavelet-linear genetic programming model for sodium (Na+) concentration forecasting in rivers

    Science.gov (United States)

    Ravansalar, Masoud; Rajaee, Taher; Zounemat-Kermani, Mohammad

    2016-06-01

    The prediction of water quality parameters in water resources such as rivers is of importance issue that needs to be considered in better management of irrigation systems and water supplies. In this respect, this study proposes a new hybrid wavelet-linear genetic programming (WLGP) model for prediction of monthly sodium (Na+) concentration. The 23-year monthly data used in this study, were measured from the Asi River at the Demirköprü gauging station located in Antakya, Turkey. At first, the measured discharge (Q) and Na+ datasets are initially decomposed into several sub-series using discrete wavelet transform (DWT). Then, these new sub-series are imposed to the ad hoc linear genetic programming (LGP) model as input patterns to predict monthly Na+ one month ahead. The results of the new proposed WLGP model are compared with LGP, WANN and ANN models. Comparison of the models represents the superiority of the WLGP model over the LGP, WANN and ANN models such that the Nash-Sutcliffe efficiencies (NSE) for WLGP, WANN, LGP and ANN models were 0.984, 0.904, 0.484 and 0.351, respectively. The achieved results even points to the superiority of the single LGP model than the ANN model. Continuously, the capability of the proposed WLGP model in terms of prediction of the Na+ peak values is also presented in this study.

  13. Modelling Soil Water Retention Using Support Vector Machines with Genetic Algorithm Optimisation

    Directory of Open Access Journals (Sweden)

    Krzysztof Lamorski

    2014-01-01

    Full Text Available This work presents point pedotransfer function (PTF models of the soil water retention curve. The developed models allowed for estimation of the soil water content for the specified soil water potentials: –0.98, –3.10, –9.81, –31.02, –491.66, and –1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM methodology was used for model development. A new methodology for elaboration of retention function models is proposed. Alternative to previous attempts known from literature, the ν-SVM method was used for model development and the results were compared with the formerly used the C-SVM method. For the purpose of models’ parameters search, genetic algorithms were used as an optimisation framework. A new form of the aim function used for models parameters search is proposed which allowed for development of models with better prediction capabilities. This new aim function avoids overestimation of models which is typically encountered when root mean squared error is used as an aim function. Elaborated models showed good agreement with measured soil water retention data. Achieved coefficients of determination values were in the range 0.67–0.92. Studies demonstrated usability of ν-SVM methodology together with genetic algorithm optimisation for retention modelling which gave better performing models than other tested approaches.

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

    Science.gov (United States)

    Clegg, J.; Robinson, M. P.

    2012-10-01

    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.

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

    Science.gov (United States)

    Clegg, J; Robinson, M P

    2012-10-01

    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.

  16. Picroilmenites in Yakutian kimberlites: variations and genetic models

    Science.gov (United States)

    Ashchepkov, I. V.; Alymova, N. V.; Logvinova, A. M.; Vladykin, N. V.; Kuligin, S. S.; Mityukhin, S. I.; Downes, H.; Stegnitsky, Yu. B.; Prokopiev, S. A.; Salikhov, R. F.; Palessky, V. S.; Khmel'nikova, O. S.

    2014-09-01

    Major and trace element variations in picroilmenites from Late Devonian kimberlite pipes in Siberia reveal similarities within the region in general, but show individual features for ilmenites from different fields and pipes. Empirical ilmenite thermobarometry (Ashchepkov et al., 2010), as well as common methods of mantle thermobarometry and trace element geochemical modeling, shows long compositional trends for the ilmenites. These are a result of complex processes of polybaric fractionation of protokimberlite melts, accompanied by the interaction with mantle wall rocks and dissolution of previous wall rock and metasomatic associations. Evolution of the parental magmas for the picroilmenites was determined for the three distinct phases of kimberlite activity from Yubileynaya and nearby Aprelskaya pipes, showing heating and an increase of Fe# (Fe# = Fe / (Fe + Mg) a.u.) of mantle peridotite minerals from stage to stage and splitting of the magmatic system in the final stages. High-pressure (5.5-7.0 GPa) Cr-bearing Mg-rich ilmenites (group 1) reflect the conditions of high-temperature metasomatic rocks at the base of the mantle lithosphere. Trace element patterns are enriched to 0.1-10/relative to primitive mantle (PM) and have flattened, spoon-like or S- or W-shaped rare earth element (REE) patterns with Pb > 1. These result from melting and crystallization in melt-feeding channels in the base of the lithosphere, where high-temperature dunites, harzburgites and pyroxenites were formed. Cr-poor ilmenite megacrysts (group 2) trace the high-temperature path of protokimberlites developed as result of fractional crystallization and wall rock assimilation during the creation of the feeder systems prior to the main kimberlite eruption. Inflections in ilmenite compositional trends probably reflect the mantle layering and pulsing melt intrusion during melt migration within the channels. Group 2 ilmenites have inclined REE enriched patterns (10-100)/PM with La / Ybn ~ 10

  17. 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.

  18. 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

    2017-06-21

    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

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

    DEFF Research Database (Denmark)

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

    2011-01-01

    of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted....... The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable...

  20. Insights into granulosa cell tumors using spontaneous or genetically engineered mouse models.

    Science.gov (United States)

    Kim, So-Youn

    2016-03-01

    Granulosa cell tumors (GCTs) are rare sex cord-stromal tumors that have been studied for decades. However, their infrequency has delayed efforts to research their etiology. Recently, mutations in human GCTs have been discovered, which has led to further research aimed at determining the molecular mechanisms underlying the disease. Mouse models have been important tools for studying GCTs, and have provided means to develop and improve diagnostics and therapeutics. Thus far, several genetically modified mouse models, along with one spontaneous mouse model, have been reported. This review summarizes the phenotypes of these mouse models and their applicability in elucidating the mechanisms of granulosa cell tumor development.

  1. A Genetic Algorithm for the Calibration of a Micro-Simulation Model

    CERN Document Server

    Espinosa, Omar Baqueiro

    2012-01-01

    This paper describes the process followed to calibrate a micro-simulation model for the Altmark region in Germany and a Derbyshire region in the UK. The calibration process is performed in three main steps: first, a subset of input and output variables to use for the calibration process is selected from the complete parameter space in the model; second, the calibration process is performed using a genetic algorithm calibration approach; finally, a comparison between the real data and the data obtained from the best fit model is done to verify the accuracy of the model.

  2. 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...

  3. 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.

  4. Learning from small fry: the zebrafish as a genetic model organism for aquaculture fish species.

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    Dahm, Ralf; Geisler, Robert

    2006-01-01

    In recent years, the zebrafish has become one of the most prominent vertebrate model organisms used to study the genetics underlying development, normal body function, and disease. The growing interest in zebrafish research was paralleled by an increase in tools and methods available to study zebrafish. While zebrafish research initially centered on mutagenesis screens (forward genetics), recent years saw the establishment of reverse genetic methods (morpholino knock-down, TILLING). In addition, increasingly sophisticated protocols for generating transgenic zebrafish have been developed and microarrays are now available to characterize gene expression on a near genome-wide scale. The identification of loci underlying specific traits is aided by genetic, physical, and radiation hybrid maps of the zebrafish genome and the zebrafish genome project. As genomic resources for aquacultural species are increasingly being generated, a meaningful interaction between zebrafish and aquacultural research now appears to be possible and beneficial for both sides. In particular, research on nutrition and growth, stress, and disease resistance in the zebrafish can be expected to produce results applicable to aquacultural fish, for example, by improving husbandry and formulated feeds. Forward and reverse genetics approaches in the zebrafish, together with the known conservation of synteny between the species, offer the potential to identify and verify candidate genes for quantitative trait loci (QTLs) to be used in marker-assisted breeding. Moreover, some technologies from the zebrafish field such as TILLING may be directly transferable to aquacultural research and production.

  5. Rule-based models of the interplay between genetic and environmental factors in childhood allergy.

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    Susanne Bornelöv

    Full Text Available Both genetic and environmental factors are important for the development of allergic diseases. However, a detailed understanding of how such factors act together is lacking. To elucidate the interplay between genetic and environmental factors in allergic diseases, we used a novel bioinformatics approach that combines feature selection and machine learning. In two materials, PARSIFAL (a European cross-sectional study of 3113 children and BAMSE (a Swedish birth-cohort including 2033 children, genetic variants as well as environmental and lifestyle factors were evaluated for their contribution to allergic phenotypes. Monte Carlo feature selection and rule based models were used to identify and rank rules describing how combinations of genetic and environmental factors affect the risk of allergic diseases. Novel interactions between genes were suggested and replicated, such as between ORMDL3 and RORA, where certain genotype combinations gave odds ratios for current asthma of 2.1 (95% CI 1.2-3.6 and 3.2 (95% CI 2.0-5.0 in the BAMSE and PARSIFAL children, respectively. Several combinations of environmental factors appeared to be important for the development of allergic disease in children. For example, use of baby formula and antibiotics early in life was associated with an odds ratio of 7.4 (95% CI 4.5-12.0 of developing asthma. Furthermore, genetic variants together with environmental factors seemed to play a role for allergic diseases, such as the use of antibiotics early in life and COL29A1 variants for asthma, and farm living and NPSR1 variants for allergic eczema. Overall, combinations of environmental and life style factors appeared more frequently in the models than combinations solely involving genes. In conclusion, a new bioinformatics approach is described for analyzing complex data, including extensive genetic and environmental information. Interactions identified with this approach could provide useful hints for further in-depth studies

  6. Simplified process model discovery based on role-oriented genetic mining.

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    Zhao, Weidong; Liu, Xi; Dai, Weihui

    2014-01-01

    Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.

  7. Glycogen Storage Disease Type Ia in Canines: A Model for Human Metabolic and Genetic Liver Disease

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    Andrew Specht

    2011-01-01

    Full Text Available A canine model of Glycogen storage disease type Ia (GSDIa is described. Affected dogs are homozygous for a previously described M121I mutation resulting in a deficiency of glucose-6-phosphatase-α. Metabolic, clinicopathologic, pathologic, and clinical manifestations of GSDIa observed in this model are described and compared to those observed in humans. The canine model shows more complete recapitulation of the clinical manifestations seen in humans including “lactic acidosis”, larger size, and longer lifespan compared to other animal models. Use of this model in preclinical trials of gene therapy is described and briefly compared to the murine model. Although the canine model offers a number of advantages for evaluating potential therapies for GSDIa, there are also some significant challenges involved in its use. Despite these challenges, the canine model of GSDIa should continue to provide valuable information about the potential for generating curative therapies for GSDIa as well as other genetic hepatic diseases.

  8. 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...

  9. A post-developmental genetic screen for zebrafish models of inherited liver disease.

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    Seok-Hyung Kim

    Full Text Available Nonalcoholic fatty liver disease (NAFLD is one of the most common causes of chronic liver disease such as simple steatosis, nonalcoholic steatohepatitis (NASH, cirrhosis and fibrosis. However, the molecular pathogenesis and genetic variations causing NAFLD are poorly understood. The high prevalence and incidence of NAFLD suggests that genetic variations on a large number of genes might be involved in NAFLD. To identify genetic variants causing inherited liver disease, we used zebrafish as a model system for a large-scale mutant screen, and adopted a whole genome sequencing approach for rapid identification of mutated genes found in our screen. Here, we report on a forward genetic screen of ENU mutagenized zebrafish. From 250 F2 lines of ENU mutagenized zebrafish during post-developmental stages (5 to 8 days post fertilization, we identified 19 unique mutant zebrafish lines displaying visual evidence of hepatomegaly and/or steatosis with no developmental defects. Histological analysis of mutants revealed several specific phenotypes, including common steatosis, micro/macrovesicular steatosis, hepatomegaly, ballooning, and acute hepatocellular necrosis. This work has identified multiple post-developmental mutants and establishes zebrafish as a novel animal model for post-developmental inherited liver disease.

  10. A post-developmental genetic screen for zebrafish models of inherited liver disease.

    Science.gov (United States)

    Kim, Seok-Hyung; Wu, Shu-Yu; Baek, Jeong-In; Choi, Soo Young; Su, Yanhui; Flynn, Charles R; Gamse, Joshua T; Ess, Kevin C; Hardiman, Gary; Lipschutz, Joshua H; Abumrad, Naji N; Rockey, Don C

    2015-01-01

    Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease such as simple steatosis, nonalcoholic steatohepatitis (NASH), cirrhosis and fibrosis. However, the molecular pathogenesis and genetic variations causing NAFLD are poorly understood. The high prevalence and incidence of NAFLD suggests that genetic variations on a large number of genes might be involved in NAFLD. To identify genetic variants causing inherited liver disease, we used zebrafish as a model system for a large-scale mutant screen, and adopted a whole genome sequencing approach for rapid identification of mutated genes found in our screen. Here, we report on a forward genetic screen of ENU mutagenized zebrafish. From 250 F2 lines of ENU mutagenized zebrafish during post-developmental stages (5 to 8 days post fertilization), we identified 19 unique mutant zebrafish lines displaying visual evidence of hepatomegaly and/or steatosis with no developmental defects. Histological analysis of mutants revealed several specific phenotypes, including common steatosis, micro/macrovesicular steatosis, hepatomegaly, ballooning, and acute hepatocellular necrosis. This work has identified multiple post-developmental mutants and establishes zebrafish as a novel animal model for post-developmental inherited liver disease.

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

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    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.

  12. Kernel Approach for Modeling Interaction Effects in Genetic Association Studies of Complex Quantitative Traits.

    Science.gov (United States)

    Broadaway, K Alaine; Duncan, Richard; Conneely, Karen N; Almli, Lynn M; Bradley, Bekh; Ressler, Kerry J; Epstein, Michael P

    2015-07-01

    The etiology of complex traits likely involves the effects of genetic and environmental factors, along with complicated interaction effects between them. Consequently, there has been interest in applying genetic association tests of complex traits that account for potential modification of the genetic effect in the presence of an environmental factor. One can perform such an analysis using a joint test of gene and gene-environment interaction. An optimal joint test would be one that remains powerful under a variety of models ranging from those of strong gene-environment interaction effect to those of little or no gene-environment interaction effect. To fill this demand, we have extended a kernel machine based approach for association mapping of multiple SNPs to consider joint tests of gene and gene-environment interaction. The kernel-based approach for joint testing is promising, because it incorporates linkage disequilibrium information from multiple SNPs simultaneously in analysis and permits flexible modeling of interaction effects. Using simulated data, we show that our kernel machine approach typically outperforms the traditional joint test under strong gene-environment interaction models and further outperforms the traditional main-effect association test under models of weak or no gene-environment interaction effects. We illustrate our test using genome-wide association data from the Grady Trauma Project, a cohort of highly traumatized, at-risk individuals, which has previously been investigated for interaction effects. © 2015 WILEY PERIODICALS, INC.

  13. Measuring genetic distances between breeds: use of some distances in various short term evolution models

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    SanCristobal Magali

    2002-07-01

    Full Text Available Abstract Many works demonstrate the benefits of using highly polymorphic markers such as microsatellites in order to measure the genetic diversity between closely related breeds. But it is sometimes difficult to decide which genetic distance should be used. In this paper we review the behaviour of the main distances encountered in the literature in various divergence models. In the first part, we consider that breeds are populations in which the assumption of equilibrium between drift and mutation is verified. In this case some interesting distances can be expressed as a function of divergence time, t, and therefore can be used to construct phylogenies. Distances based on allele size distribution (such as (δμ2 and derived distances, taking a mutation model of microsatellites, the Stepwise Mutation Model, specifically into account, exhibit large variance and therefore should not be used to accurately infer phylogeny of closely related breeds. In the last section, we will consider that breeds are small populations and that the divergence times between them are too small to consider that the observed diversity is due to mutations: divergence is mainly due to genetic drift. Expectation and variance of distances were calculated as a function of the Wright-Malécot inbreeding coefficient, F. Computer simulations performed under this divergence model show that the Reynolds distance [57]is the best method for very closely related breeds.

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

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    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.

  15. Relationship between obesity phenotypes and genetic determinants in a mouse model for juvenile obesity.

    Science.gov (United States)

    Brockmann, Gudrun A; Schäfer, Nadine; Hesse, Claudia; Heise, Sebastian; Neuschl, Christina; Wagener, Asja; Churchill, Gary A; Li, Renhua

    2013-09-16

    Obesity, a state of imbalance between lean mass and fat mass, is important for the etiology of diseases affected by the interplay of multiple genetic and environmental factors. Although genome-wide association studies have repeatedly associated genes with obesity and body weight, the mechanisms underlying the interaction between the muscle and adipose tissues remain unknown. Using 351 mice (at 10 wk of age) of an intercross population between Berlin Fat Mouse Inbred (BFMI) and C57BL/6NCrl (B6N) mice, we examined the causal relationships between genetic variations and multiple traits: body lean mass and fat mass, adipokines, and bone mineral density. Furthermore, evidence from structural equation modeling suggests causality among these traits. In the BFMI model, juvenile obesity affects lean mass and impairs bone mineral density via adipokines secreted from the white adipose tissues. While previous studies have indicated that lean mass has a causative effect on adiposity, in the Berlin Fat Mouse model that has been selected for juvenile obesity (at 9 wk of age) for >90 generations, however, the causality is switched from fat mass to lean mass. In addition, linkage studies and statistical modeling have indicated that quantitative trait loci on chromosomes 5 and 6 affect both lean mass and fat mass. These lines of evidence indicate that the muscle and adipose tissues interact with one another and the interaction is modulated by genetic variations that are shaped by selections. Experimental examinations are necessary to verify the biological role of the inferred causalities.

  16. 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.

  17. A Songbird Animal Model for Dissecting the Genetic Bases of Autism Spectrum Disorder

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    S. Carmen Panaitof

    2012-01-01

    Full Text Available The neural and genetic bases of human language development and associated neurodevelopmental disorders, including autism spectrum disorder (ASD, in which language impairment represents a core deficit, are poorly understood. Given that no single animal model can fully capture the behavioral and genetic complexity of ASD, work in songbird, an experimentally tractable animal model of vocal learning, can complement the valuable tool of rodent genetic models and contribute important insights to our understanding of the communication deficits observed in ASD. Like humans, but unlike traditional laboratory animals such as rodents or non-human primates, songbirds exhibit the capacity of vocal learning, a key subcomponent of language. Human speech and birdsong reveal important parallels, highlighting similar developmental critical periods, a homologous cortico-basal ganglia-thalamic circuitry, and a critical role for social influences in the learning of vocalizations. Here I highlight recent advances in using the songbird model to probe the cellular and molecular mechanisms underlying the formation and function of neural circuitry for birdsong and, by analogy, human language, with the ultimate goal of identifying any shared or human unique biological pathways underscoring language development and its disruption in ASD.

  18. 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.

  19. Precise Network Modeling of Systems Genetics Data Using the Bayesian Network Webserver.

    Science.gov (United States)

    Ziebarth, Jesse D; Cui, Yan

    2017-01-01

    The Bayesian Network Webserver (BNW, http://compbio.uthsc.edu/BNW ) is an integrated platform for Bayesian network modeling of biological datasets. It provides a web-based network modeling environment that seamlessly integrates advanced algorithms for probabilistic causal modeling and reasoning with Bayesian networks. BNW is designed for precise modeling of relatively small networks that contain less than 20 nodes. The structure learning algorithms used by BNW guarantee the discovery of the best (most probable) network structure given the data. To facilitate network modeling across multiple biological levels, BNW provides a very flexible interface that allows users to assign network nodes into different tiers and define the relationships between and within the tiers. This function is particularly useful for modeling systems genetics datasets that often consist of multiscalar heterogeneous genotype-to-phenotype data. BNW enables users to, within seconds or minutes, go from having a simply formatted input file containing a dataset to using a network model to make predictions about the interactions between variables and the potential effects of experimental interventions. In this chapter, we will introduce the functions of BNW and show how to model systems genetics datasets with BNW.

  20. 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.

  1. Improving the User Query for the Boolean Model Using Genetic Algorithms

    CERN Document Server

    Nassar, Mohammad Othman; Mashagba, Eman Al

    2011-01-01

    The Use of genetic algorithms in the Information retrieval (IR) area, especially in optimizing a user query in Arabic data collections is presented in this paper. Very little research has been carried out on Arabic text collections. Boolean model have been used in this research. To optimize the query using GA we used different fitness functions, different mutation strategies to find which is the best strategy and fitness function that can be used with Boolean model when the data collection is the Arabic language. Our results show that the best GA strategy for the Boolean model is the GA (M2, Precision) method.

  2. 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.

  3. 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.

  4. Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

    Science.gov (United States)

    Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

    2016-09-01

    Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that

  5. Elaboration of the definition of genetic counseling into a model for counselee decision-making.

    Science.gov (United States)

    Bringle, R G; Antley, R M

    1980-01-01

    Genetic counselors are generally trained in genetics only and often have no basis for determining when a counselee has made an informed decision and the counselor's function is complete. A theory of genetic counseling (GC) is offered which interrelates genetic information, psychological responses, learning theory, and decision making, reflecting a shift from a eugenic orientation to an orientation concerned with the physical and mental well-being of counselees. GC is 1st defined as enabling the counselee to comprehend the medical facts of genetic disorders, heredity, risks, and alternatives, as well as to make a healthy adjustment to a family member's disorder and risk of recurrence. The process of learning is broken down into a hierarchical relationship between acquisition, understanding, and personalization of facts, and applied to the GC situation; e.g. "the options are as follows;" "they can be exercised by couples in certain ways;" and "we have the following choices to make." Personalization of knowledge means integration into one's own value system where it will affect decisions made, a process affected by factors such as stress. Often, the information provided by GC is not the only information the counselee possesses, and it will be integrated with other conceptions. Normative social influences (e.g. a family's attitude towards abortion) affect the behavioral intention. And finally, the behavioral intention is not always equivalent to the actual behavior. These process are all related to the way in which a family deals with the stress caused by a genetic disorder. GC outcomes are easier to measure than those of psychological counseling. Extending the model to clinical application implies 1) assessment; 2) setting objectives; 3) counseling; and 4) evaluation.

  6. Modeling host genetic regulation of influenza pathogenesis in the collaborative cross.

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    Martin T Ferris

    2013-02-01

    Full Text Available Genetic variation contributes to host responses and outcomes following infection by influenza A virus or other viral infections. Yet narrow windows of disease symptoms and confounding environmental factors have made it difficult to identify polymorphic genes that contribute to differential disease outcomes in human populations. Therefore, to control for these confounding environmental variables in a system that models the levels of genetic diversity found in outbred populations such as humans, we used incipient lines of the highly genetically diverse Collaborative Cross (CC recombinant inbred (RI panel (the pre-CC population to study how genetic variation impacts influenza associated disease across a genetically diverse population. A wide range of variation in influenza disease related phenotypes including virus replication, virus-induced inflammation, and weight loss was observed. Many of the disease associated phenotypes were correlated, with viral replication and virus-induced inflammation being predictors of virus-induced weight loss. Despite these correlations, pre-CC mice with unique and novel disease phenotype combinations were observed. We also identified sets of transcripts (modules that were correlated with aspects of disease. In order to identify how host genetic polymorphisms contribute to the observed variation in disease, we conducted quantitative trait loci (QTL mapping. We identified several QTL contributing to specific aspects of the host response including virus-induced weight loss, titer, pulmonary edema, neutrophil recruitment to the airways, and transcriptional expression. Existing whole-genome sequence data was applied to identify high priority candidate genes within QTL regions. A key host response QTL was located at the site of the known anti-influenza Mx1 gene. We sequenced the coding regions of Mx1 in the eight CC founder strains, and identified a novel Mx1 allele that showed reduced ability to inhibit viral replication

  7. Le premier Aurignacien en France méditerranéenne : un bilan

    Directory of Open Access Journals (Sweden)

    Frédéric Bazile

    2002-01-01

    Full Text Available Identifié au début des années 1970 (La Laouza puis l'Esquictio-Grapaou dans les Gorges du Gardon, l'Aurignacien initial, au sens d'antérieur à l'Aurignacien I classique (Archaïque? Aurignacien «0»? Protoaurignacien?, est également connu en Provence (Rainaude et dans le Bassin de l'Aude (grotte Tournai et sans doute Traouc de la Fado. Il était vraisemblablement présent à la Balauzière (sous un Aurignacien ancien classique et à la Grotte Nicolas (Gard à l'abri Rothschild et, plus au Nord, dans l'abri du Pécheur (Ardéche. Sa présence dans la moyenne vallée du Rhône à la grotte Mandrin (Drome est également vraisemblable, ouvrant un premier jalon (outre Roclaine nécessairement à revisiter vers des sites plus septentrionaux aux affinités typologiques et technologiques troublantes tels Arcy (Grotte du Renne et le Trou de la Mère Clochette. Ce "technocomplexe», bien situé sur le plan chronologique, témoignent d'une forte unité culturele de la Campante et la Vénétie à la Catalogne, en passant par la Ligurie, sans doute l'un des foyers pricipaux. Il apparaît brutalement à la fin de l'Interstade wûrmien, sus-jacent, avec ou sans lacune de sédimentation et/ou d'érosion, à des dépôts livrant des industries moustériennes de faciès très différents selon la région concernée.Identificado a inicios de 1970 en la garganta de Gardon, primero en La Laouza, después en Esquicho-Grapaou, el Aurihaciense inicial en sentido de anterioridad al Auriñaciense I clásico, (Arcaico, «0», Protoaurihaciense es también conocido en Provence (Rainaude y el en valle del Aude (Tournai y Traouc de la Fado. Esta también presente de manera clara en Balauzière (bajo un Auriñaciense antiguo clásico y en la Grotte Nicolas (Gard en el abri Rothschild y, más al norte, en el abri Pêcheur (Ardéche. Su presencia en el valle medio del Rôdano en la grotte Mandrin en Drome (otro yacimiento séria Roclaine sirve como jalon hacia sitios m

  8. A genetic investigation of various growth models to describe growth of lambs of two contrasting breeds.

    Science.gov (United States)

    Lambe, N R; Navajas, E A; Simm, G; Bünger, L

    2006-10-01

    This study compared the use of various models to describe growth in lambs of 2 contrasting breeds from birth to slaughter. Live BW records (n = 7559) from 240 Texel and 231 Scottish Blackface (SBF) lambs weighed at 2-wk intervals were modeled. Biologically relevant variables were estimated for each lamb from modified versions of the logistic, Gompertz, Richards, and exponential models, and from linear regression. In both breeds, all nonlinear models fitted the data well, with an average coefficient of determination (R2) of > 0.98. The linear model had a lower average R2 than any of the nonlinear models (growth patterns, but the Akaike's information criteria value (which weighs log-likelihood by number of parameters estimated) was similar to that of the Gompertz model. Variables A, B, C, and D were moderately to highly heritable in Texel lambs (h2 = 0.33 to 0.87), and genetic correlations between variables within-model ranged from -0.80 to 0.89, suggesting some flexibility to change the shape of the growth curve when selecting for different variables. In SBF lambs, only variables from the logistic and Gompertz models had moderate heritabilities (0.17 to 0.56), but with high genetic correlations between variables within each model ( 0.92). Selection on growth variables seems promising (in Texel more than SBF), but high genetic correlations between variables may restrict the possibilities to change the growth curve shape. A random regression model was also fitted to the data to allow predictions of growth rates at relevant time points. Heritabilities for growth rates differed markedly at various stages of growth and between the 2 breeds (Texel: 0.14 to 0.74; SBF: 0.07 to 0.34), with negative correlations between growth rate at 60 d of age and growth rate at finishing. Following these results, future studies should investigate genetic relationships between relevant growth curve variables and other important production traits, such as carcass composition and meat

  9. Evaluation of Genetic Algorithm Concepts using Model Problems. Part 1; Single-Objective Optimization

    Science.gov (United States)

    Holst, Terry L.; Pulliam, Thomas H.

    2003-01-01

    A genetic-algorithm-based optimization approach is described and evaluated using a simple hill-climbing model problem. The model problem utilized herein allows for the broad specification of a large number of search spaces including spaces with an arbitrary number of genes or decision variables and an arbitrary number hills or modes. In the present study, only single objective problems are considered. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all problems attempted. The most difficult problems - those with large hyper-volumes and multi-mode search spaces containing a large number of genes - require a large number of function evaluations for GA convergence, but they always converge.

  10. 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

  11. Genetic parameters for tunisian holsteins using a test-day random regression model.

    Science.gov (United States)

    Hammami, H; Rekik, B; Soyeurt, H; Ben Gara, A; Gengler, N

    2008-05-01

    Genetic parameters of milk, fat, and protein yields were estimated in the first 3 lactations for registered Tunisian Holsteins. Data included 140,187; 97,404; and 62,221 test-day production records collected on 22,538; 15,257; and 9,722 first-, second-, and third-parity cows, respectively. Records were of cows calving from 1992 to 2004 in 96 herds. (Co)variance components were estimated by Bayesian methods and a 3-trait-3-lactation random regression model. Gibbs sampling was used to obtain posterior distributions. The model included herd x test date, age x season of calving x stage of lactation [classes of 25 days in milk (DIM)], production sector x stage of lactation (classes of 5 DIM) as fixed effects, and random regression coefficients for additive genetic, permanent environmental, and herd-year of calving effects, which were defined as modified constant, linear, and quadratic Legendre coefficients. Heritability estimates for 305-d milk, fat and protein yields were moderate (0.12 to 0.18) and in the same range of parameters estimated in management systems with low to medium production levels. Heritabilities of test-day milk and protein yields for selected DIM were higher in the middle than at the beginning or the end of lactation. Inversely, heritabilities of fat yield were high at the peripheries of lactation. Genetic correlations among 305-d yield traits ranged from 0.50 to 0.86. The largest genetic correlation was observed between the first and second lactation, potentially due to the limited expression of genetic potential of superior cows in later lactations. Results suggested a lack of adaptation under the local management and climatic conditions. Results should be useful to implement a BLUP evaluation for the Tunisian cow population; however, results also indicated that further research focused on data quality might be needed.

  12. A cost analysis of a cancer genetic service model in the UK.

    Science.gov (United States)

    Slade, Ingrid; Hanson, Helen; George, Angela; Kohut, Kelly; Strydom, Ann; Wordsworth, Sarah; Rahman, Nazneen

    2016-07-01

    Technological advances in DNA sequencing have made gene testing fast and more affordable. Evidence of effectiveness and cost-effectiveness of genetic service models is essential for the successful translation of sequencing improvements for patient benefit, but remain sparse in the genetics literature. In particular, there is a lack of detailed cost data related to genetic services. A detailed micro-costing of 28 possible pathways relating to breast and/or ovarian cancer and BRCA testing was carried out by defining service activities and establishing associated costs. These data were combined with patient-level data from a Royal Marsden Cancer Genetics Service audit over a 6-month period during which BRCA testing was offered to individuals at ≥10 % risk of having a mutation, in line with current NICE guidance. The average cost across all patient pathways was £2227.39 (range £376.51 to £13,553.10). The average cost per pathway for an affected person was £1897.75 compared to £2410.53 for an unaffected person. Of the women seen in the Cancer Genetics Service during the audit, 38 % were affected with breast and/or ovarian cancer, and 62 % were unaffected but concerned about their family history. The most efficient service strategy is to identify unaffected relatives from an affected individual with an identified BRCA mutation. Implementation of this strategy would require more comprehensive testing of all eligible cancer patients, which could be achieved by integrating BRCA testing into oncology services. Such integration would be also more time-efficient and deliver greater equity of access to BRCA testing than the standard service model.

  13. 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.

  14. A coupled model tree genetic algorithm scheme for flow and water quality predictions in watersheds

    Science.gov (United States)

    Preis, Ami; Ostfeld, Avi

    2008-02-01

    SummaryThe rapid advance in information processing systems along with the increasing data availability have directed research towards the development of intelligent systems that evolve models of natural phenomena automatically. This is the discipline of data driven modeling which is the study of algorithms that improve automatically through experience. Applications of data driven modeling range from data mining schemes that discover general rules in large data sets, to information filtering systems that automatically learn users' interests. This study presents a data driven modeling algorithm for flow and water quality load predictions in watersheds. The methodology is comprised of a coupled model tree-genetic algorithm scheme. The model tree predicts flow and water quality constituents while the genetic algorithm is employed for calibrating the model tree parameters. The methodology is demonstrated through base runs and sensitivity analysis for daily flow and water quality load predictions on a watershed in northern Israel. The method produced close fits in most cases, but was limited in estimating the peak flows and water quality loads.

  15. 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

    2017-06-19

    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.

  16. The effect of match standard and referee experience on the objective and subjective match workload of English Premier League referees.

    Science.gov (United States)

    Weston, M; Bird, S; Helsen, W; Nevill, A; Castagna, C

    2006-06-01

    The aim of the present study was to examine the effect of match standard and referee experience on the objective and subjective workload of referees during English Premier League and Football League soccer matches. We also examined the relationship between heart rate (HR) and ratings of perceived exertion (RPE) for assessing match intensity in soccer referees. Heart rate responses were recorded using short-range telemetry and RPE scores were collected using a 10-point scale. Analysis revealed a significant relationship between mean match HR and match RPE scores (r=0.485, pReferee experience had no effect on match HR and RPE responses to Premier League and Football League matches. The results of the present study demonstrate the validity of using HR and RPE as a measure of global match intensity in soccer referees. Referee experience had no effect on the referees' objective and subjective match workload assessments, whereas match intensity was correlated to competition standard. These findings have implications for fitness preparation and evaluation in soccer referees. When progressing to a higher level of competition, referees should ensure that appropriate levels of fitness are developed in order to enable them to cope with an increase in physical match demands.

  17. A genetic algorithm based global search strategy for population pharmacokinetic/pharmacodynamic model selection.

    Science.gov (United States)

    Sale, Mark; Sherer, Eric A

    2015-01-01

    The current algorithm for selecting a population pharmacokinetic/pharmacodynamic model is based on the well-established forward addition/backward elimination method. A central strength of this approach is the opportunity for a modeller to continuously examine the data and postulate new hypotheses to explain observed biases. This algorithm has served the modelling community well, but the model selection process has essentially remained unchanged for the last 30 years. During this time, more robust approaches to model selection have been made feasible by new technology and dramatic increases in computation speed. We review these methods, with emphasis on genetic algorithm approaches and discuss the role these methods may play in population pharmacokinetic/pharmacodynamic model selection.

  18. Bayesian model selection in complex linear systems, as illustrated in genetic association studies.

    Science.gov (United States)

    Wen, Xiaoquan

    2014-03-01

    Motivated by examples from genetic association studies, this article considers the model selection problem in a general complex linear model system and in a Bayesian framework. We discuss formulating model selection problems and incorporating context-dependent a priori information through different levels of prior specifications. We also derive analytic Bayes factors and their approximations to facilitate model selection and discuss their theoretical and computational properties. We demonstrate our Bayesian approach based on an implemented Markov Chain Monte Carlo (MCMC) algorithm in simulations and a real data application of mapping tissue-specific eQTLs. Our novel results on Bayes factors provide a general framework to perform efficient model comparisons in complex linear model systems.

  19. A bivariate quantitative genetic model for a threshold trait and a survival trait

    Directory of Open Access Journals (Sweden)

    Damgaard Lars

    2006-11-01

    Full Text Available Abstract Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.

  20. A bivariate quantitative genetic model for a threshold trait and a survival trait.

    Science.gov (United States)

    Damgaard, Lars Holm; Korsgaard, Inge Riis

    2006-01-01

    Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.

  1. In-depth metabolic phenotyping of genetically engineered mouse models in obesity and diabetes.

    Science.gov (United States)

    Lee, Hui-Young; Jeong, Kyeong-Hoon; Choi, Cheol Soo

    2014-10-01

    The world-wide prevalence of obesity and diabetes has increased sharply during the last two decades. Accordingly, the metabolic phenotyping of genetically engineered mouse models is critical for evaluating the functional roles of target genes in obesity and diabetes, and for developing new therapeutic targets. In this review, we discuss the practical meaning of metabolic phenotyping, the strategy of choosing appropriate tests, and considerations when designing and performing metabolic phenotyping in mice.

  2. Next-generation sequencing approaches in genetic rodent model systems to study functional effects of human genetic variation

    NARCIS (Netherlands)

    Guryev, Victor; Cuppen, Edwin

    2009-01-01

    Rapid advances in DNA sequencing improve existing techniques and enable new approaches in genetics and functional genomics, bringing about unprecedented coverage, resolution and sensitivity. Enhanced toolsets can facilitate the untangling of connections between genomic variation, environmental

  3. Next-generation sequencing approaches in genetic rodent model systems to study functional effects of human genetic variation.

    NARCIS (Netherlands)

    Guryev, V.; Cuppen, E.

    2009-01-01

    Rapid advances in DNA sequencing improve existing techniques and enable new approaches in genetics and functional genomics, bringing about unprecedented coverage, resolution and sensitivity. Enhanced toolsets can facilitate the untangling of connections between genomic variation, environmental facto

  4. Next-generation sequencing approaches in genetic rodent model systems to study functional effects of human genetic variation

    NARCIS (Netherlands)

    Guryev, Victor; Cuppen, Edwin

    2009-01-01

    Rapid advances in DNA sequencing improve existing techniques and enable new approaches in genetics and functional genomics, bringing about unprecedented coverage, resolution and sensitivity. Enhanced toolsets can facilitate the untangling of connections between genomic variation, environmental facto

  5. Les premiers romans noirs français : simples exercices de style ou trahisons littéraires complexes ?

    Directory of Open Access Journals (Sweden)

    Anne Cadin

    2011-02-01

    Full Text Available Les premiers romans noirs français, imités des hard-boiled novels, ont été écrits sous pseudonyme : Malet devient Harding ; Vian, Sullivan ; Queneau, Mara et Arcouët, Stewart. Quelle part de trahison anime ces auteurs ? Sert-elle à faire vendre ou à dénoncer l’invasion de la culture américaine et le goût du scandale ? Si stratégie publicitaire et séduction du lecteur entrent en jeu, le processus de trahison est néanmoins volontairement miné par ces romanciers : il devient source de réflexion sur la lecture et l’écriture.The first French romans noirs, modeled on the so-called “hard-boiled” novels, were written under pseudonyms : Malet becomes Harding ; Vian, Sullivan ; Queneau, Mara, and Arcouët, Stewart. To what degree are these authors motivated by betrayal ? Is it employed merely for marketing purposes, or to denounce the invasion of American culture and a certain taste for scandal ? If advertising tactics and the seduction of the reader are undeniable elements of such novels, these writers nevertheless consciously sabotage the process of betrayal, transforming it into a source of reflection about reading and writing.

  6. The Effect of Autonomy-Supportive Behaviors of Coaches on Need Satisfaction and Sport Commitment of Elite Female Players in Handball Premier League

    Directory of Open Access Journals (Sweden)

    Sedigheh Hosseinpoor Delavar

    2012-01-01

    Full Text Available This study determined the effects of autonomy-supportive behaviors on satisfying the psychological needs and commitment of female handball players in premier league in Iran. Here, we used descriptive research (survey method. The statistical population of 237 players was selected as our samples. We administered three questionnaires for autonomy-Supportive behaviors, psychological needs and commitment including perceived autonomy-supportive behaviors of coaches in sport (PASSES, satisfaction of the psychological needs in sports and sports Commitment Scale (SCMS questionnaires. We applied multiple regression analysis and structural equation modeling (SEM to analyze the data. Results showed there was a positive correlation between autonomy-supportive behaviors with the psychological needs of competence and commitment of athletes. On the other hand, the players `commitment correlated positively with psychological needs. Results of multivariate regression showed that the autonomy-supportive behaviors were predictor of psychological needs and commitment of players. The path analysis, also, established mediator role of psychological needs between autonomy-supportive behavior of the coach and players` commitment. Thus, the self-determination Theory among the elite players and sports teams was confirmed.

  7. 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.

  8. Bayesian modeling for genetic anticipation in presence of mutational heterogeneity: a case study in Lynch syndrome.

    Science.gov (United States)

    Boonstra, Philip S; Mukherjee, Bhramar; Taylor, Jeremy M G; Nilbert, Mef; Moreno, Victor; Gruber, Stephen B

    2011-12-01

    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 inferential conclusions. We compare the fit of four-candidate random effects distributions via Bayesian model fit diagnostics. A related statistical issue here is isolating the confounding effect of changes in secular trends, screening, and medical practices that may affect time to disease detection across birth cohorts. Using historic cancer registry data, we borrow from relative survival analysis methods to adjust for changes in age-specific incidence across birth cohorts. Our motivating case study comes from a Danish cancer register of 124 families with mutations in mismatch repair (MMR) genes known 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.

  9. Modeling variation in early life mortality in the western lowland gorilla: Genetic, maternal and other effects.

    Science.gov (United States)

    Ahsan, Monica H; Blomquist, Gregory E

    2015-06-01

    Uncovering sources of variation in gorilla infant mortality informs conservation and life history research efforts. The international studbook for the western lowland gorilla provides information on a sample of captive gorillas large enough for which to analyze genetic, maternal, and various other effects on early life mortality in this critically endangered species. We assess the importance of variables such as sex, maternal parity, paternal age, and hand rearing with regard to infant survival. We also quantify the proportions of variation in mortality influenced by heritable variation and maternal effects from these pedigree and survival data using variance component estimation. Markov chain Monte Carlo simulations of generalized linear mixed models produce variance component distributions in an animal model framework that employs all pedigree information. Two models, one with a maternal identity component and one with both additive genetic and maternal identity components, estimate variance components for different age classes during the first 2 years of life. This is informative of the extent to which mortality risk factors change over time during gorilla infancy. Our results indicate that gorilla mortality is moderately heritable with the strongest genetic influence just after birth. Maternal effects are most important during the first 6 months of life. Interestingly, hand-reared infants have lower mortality for the first 6 months of life. Aside from hand rearing, we found other predictors commonly used in studies of primate infant mortality to have little influence in these gorilla data.

  10. Automatic calibration of urban drainage model using a novel multi-objective genetic algorithm.

    Science.gov (United States)

    di Pierro, F; Djordjević, S; Kapelan, Z; Khu, S T; Savić, D; Walters, G A

    2005-01-01

    In order to successfully calibrate an urban drainage model, multiple calibration criteria should be considered. This raises the issue of adopting a method for comparing different solutions (parameter sets) according to a set of objectives. Amongst the global optimization techniques that have blossomed in recent years, Multi Objective Genetic Algorithms (MOGA) have proved effective in numerous engineering applications, including sewer network modelling. Most of the techniques rely on the condition of Pareto efficiency to compare different solutions. However, as the number of criteria increases, the ratio of Pareto optimal to feasible solutions increases as well. The pitfalls are twofold: the efficiency of the genetic algorithm search worsens and decision makers are presented with an overwhelming number of equally optimal solutions. This paper proposes a new MOGA, the Preference Ordering Genetic Algorithm, which alleviates the drawbacks of conventional Pareto-based methods. The efficacy of the algorithm is demonstrated on the calibration of a physically-based, distributed sewer network model and the results are compared with those obtained by NSGA-II, a widely used MOGA.

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

    Science.gov (United States)

    Cho, C I; Alam, M; Choi, T J; Choy, Y H; Choi, J G; Lee, S S; Cho, K H

    2016-05-01

    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

  12. Mouse models for studying genetic influences on factors determining smoking cessation success in humans

    Science.gov (United States)

    Hall, F. Scott; Markou, Athina; Levin, Edward D.; Uhl, George R.

    2014-01-01

    Humans differ in their ability to quit using addictive substances, including nicotine, the major psychoactive ingredient in tobacco. For tobacco smoking, a substantial body of evidence, largely derived from twin studies, indicates that approximately half of these individual differences in ability to quit are heritable [1, 2], genetic influences that likely overlap with those for other addictive substances [3]. Both twin and molecular genetic studies support overlapping influences on nicotine addiction vulnerability and smoking cessation success, although there is little formal analysis of the twin data that supports this important point [2, 3]. None of the current datasets provides clear data concerning which heritable factors might provide robust dimensions around which individuals differ in ability to quit smoking. One approach to this problem is to test mice with genetic variations in genes that contain human variants that alter quit-success. This review considers which features of quit success should be included in a comprehensive approach to elucidating the genetics of quit success, and how those features may be modeled in mice. PMID:22304675

  13. Bayesian methods for multivariate modeling of pleiotropic SNP associations and genetic risk prediction

    Directory of Open Access Journals (Sweden)

    Stephen W Hartley

    2012-09-01

    Full Text Available Genome-wide association studies (GWAS have identified numerous associations between genetic loci and individual phenotypes; however, relatively few GWAS have attempted to detect pleiotropic associations, in which loci are simultaneously associated with multiple distinct phenotypes. We show that pleiotropic associations can be directly modeled via the construction of simple Bayesian networks, and that these models can be applied to produce single or ensembles of Bayesian classifiers that leverage pleiotropy to improve genetic risk prediction.The proposed method includes two phases: (1 Bayesian model comparison, to identify SNPs associated with one or more traits; and (2 cross validation feature selection, in which a final set of SNPs is selected to optimize prediction.To demonstrate the capabilities and limitations of the method, a total of 1600 case-control GWAS datasets with 2 dichotomous phenotypes were simulated under 16 scenarios, varying the association strengths of causal SNPs, the size of the discovery sets, the balance between cases and controls, and the number of pleiotropic causal SNPs.Across the 16 scenarios, prediction accuracy varied from 90% to 50%. In the 14 scenarios that included pleiotropically-associated SNPs, the pleiotropic model search and prediction methods consistently outperformed the naive model search and prediction. In the 2 scenarios in which there were no true pleiotropic SNPs, the differences between the pleiotropic and naive model searches were minimal.

  14. Application of micro-genetic algorithm for calibration of kinetic parameters in HCCI engine combustion model

    Institute of Scientific and Technical Information of China (English)

    Haozhong HUANG; Wanhua SU

    2008-01-01

    The micro-genetic algorithm (μGA) as a highly effective optimization method, is applied to calibrate to a newly developed reduced chemical kinetic model (40 species and 62 reactions) for the homogeneous charge compression ignition (HCCI) combustion of n-heptane to improve its autoignition predictions for different engine operating conditions. The seven kinetic parameters of the calibrated model are determined using a combination of the Micro-Genetic Algorithm and the SENKIN program of CHEMKIN chemical kinetics software package. Simulation results show that the autoignition predictions of the calibrated model agree better with those of the detailed chemical kinetic model (544 species and 2 446 reactions) than the original model over the range of equivalence ratios from 0.1-1.3 and temperature from 300-3 000 K. The results of this study have demonstrated that the μGA is an effective tool to facilitate the calibration of a large number of kinetic parameters in a reduced kinetic model.

  15. Comparison of different models for genetic evaluation of egg weight in Mazandaran fowl.

    Science.gov (United States)

    Zamani, P; Jasouri, M; Moradi, M R

    2015-01-01

    1. The aim of the present study was to compare different models to estimate variance components for egg weight (EW) in laying hens. 2. The data set included 67 542 EW records of 18 245 Mazandaran hens at 24, 28, 30, 32 and 84 weeks of age, during 19 consecutive generations. Variance components were estimated using multi-trait, repeatability, fixed regression and random regression models (MTM, RM, FRM and RRM, respectively) by Average Information-Restricted Maximum Likelihood algorithm (AI-REML). The models were compared based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). 3. The MTM was the best model followed by the Legendre RRMs. A RRM with 2nd degree of fit for fixed regression and 3(rd) and 2(nd) degrees of fit for random regressions of direct additive genetic and permanent environmental effects, respectively, was the best RRM. The FRM and RM were not proper models to fit the data. However, nesting curves within contemporary groups improved the fit of FRM. 4. Heritability estimates for EW by MTM (0.06-0.41) were close to the estimates obtained by the best RRM (0.09-0.45). In both MTM and RRM, positive genetic correlations were estimated for EW records at different ages, with higher correlations for adjacent records. 5. The results suggest that MTM is the best model for EW data, at least when the records are taken at relatively few age points. Though selection based on EW at higher ages might be more precise, 30 or 32 weeks of age could be considered as the most appropriate time points for selection on EW to maximise genetic improvement per time unit.

  16. 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)

  17. Optimization of a Reduced Chemical Kinetic Model for HCCI Engine Simulations by Micro-Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A reduced chemical kinetic model (44 species and 72 reactions) for the homogeneous charge compression ignition (HCCI) combustion of n-heptane was optimized to improve its autoignition predictions under different engine operating conditions. The seven kinetic parameters of the optimized model were determined by using the combination of a micro-genetic algorithm optimization methodology and the SENKIN program of CHEMKIN chemical kinetics software package. The optimization was performed within the range of equivalence ratios 0.2-1.2, initial temperature 310-375 K and initial pressure 0.1-0.3 MPa. The engine simulations show that the optimized model agrees better with the detailed chemical kinetic model (544 species and 2 446 reactions) than the original model does.

  18. 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.

  19. Frequency Extrapolation by Floating Genetic Algorithm Based on GTD Model for Radar Cross Section

    Institute of Scientific and Technical Information of China (English)

    YANG Zhenglong; FANG Dagang; SHENG Weixing; LIU Tiejun; ZHUANG Jing

    2001-01-01

    A frequency extrapolation scheme isdeveloped to effectively predict radar cross section us-ing floating genetic algorithm based on the GTD (ge-ometry theory of diffraction) model. The parameter-ized model to extrapolate the frequency response tohigher (or lower) frequency band is used and somepractical targets are calculated to test the effective-ness of the method. The influence of extrapolationon the range profile is studied. Furthermore, the re-lationship between the fitting precision and extrap-olation ability is considered. Different extrapolationprocedures are discussed.

  20. Illuminating cancer systems with genetically engineered mouse models and coupled luciferase reporters in vivo.

    Science.gov (United States)

    Kocher, Brandon; Piwnica-Worms, David

    2013-06-01

    Bioluminescent imaging (BLI) is a powerful noninvasive tool that has dramatically accelerated the in vivo interrogation of cancer systems and longitudinal analysis of mouse models of cancer over the past decade. Various luciferase enzymes have been genetically engineered into mouse models (GEMM) of cancer, which permit investigation of cellular and molecular events associated with oncogenic transcription, posttranslational processing, protein-protein interactions, transformation, and oncogene addiction in live cells and animals. Luciferase-coupled GEMMs ultimately serve as a noninvasive, repetitive, longitudinal, and physiologic means by which cancer systems and therapeutic responses can be investigated accurately within the autochthonous context of a living animal.

  1. Parameter Estimation of a Plucked String Synthesis Model Using a Genetic Algorithm with Perceptual Fitness Calculation

    Directory of Open Access Journals (Sweden)

    Riionheimo Janne

    2003-01-01

    Full Text Available We describe a technique for estimating control parameters for a plucked string synthesis model using a genetic algorithm. The model has been intensively used for sound synthesis of various string instruments but the fine tuning of the parameters has been carried out with a semiautomatic method that requires some hand adjustment with human listening. An automated method for extracting the parameters from recorded tones is described in this paper. The calculation of the fitness function utilizes knowledge of the properties of human hearing.

  2. Optimal approximation of head-related transfer function's pole-zero model based on genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jie; MA Hao; WU Zhen-yang

    2006-01-01

    In the research on spatial hearing and virtual auditory space,it is important to effectively model the head-related transfer functions (HRTFs).Based on the analysis of the HRTFs' spectrum and some perspectives of psychoacoustics,this paper applied multiple demes' parallel and real-valued coding genetic algorithm (GA) to approximate the HRTFs' zero-pole model.Using the logarithmic magnitude's error criterion for the human auditory sense,the results show that the performance of the GA is on the average 39% better than that of the traditional Prony method,and 46% better than that of the Yule-Walker algorithm.

  3. Using genetic algorithm to learn neural network identifier for modeling gyro startup drift rate

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Studies the modeling of gyro startup drift rate from acquired experimental gyro startup drift rate data and the nonlinear dynamic models of gyro startup drift rate related temperature established by time-delay neural network which enables the gyro temperature drift rate to be compensated in the process of startup and the gyro instant startup to be implemented. And introduces an improved genetic algorithm to learn the weights of neural network identifier to avoid stacking into the local minimal value and achieve rapid convergence.

  4. 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.

  5. 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.

  6. Evaluation of Genetic Algorithm Concepts Using Model Problems. Part 2; Multi-Objective Optimization

    Science.gov (United States)

    Holst, Terry L.; Pulliam, Thomas H.

    2003-01-01

    A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

  7. A Tutorial of the Poisson Random Field Model in Population Genetics

    Directory of Open Access Journals (Sweden)

    Praveen Sethupathy

    2008-01-01

    Full Text Available Population genetics is the study of allele frequency changes driven by various evolutionary forces such as mutation, natural selection, and random genetic drift. Although natural selection is widely recognized as a bona-fide phenomenon, the extent to which it drives evolution continues to remain unclear and controversial. Various qualitative techniques, or so-called “tests of neutrality”, have been introduced to detect signatures of natural selection. A decade and a half ago, Stanley Sawyer and Daniel Hartl provided a mathematical framework, referred to as the Poisson random field (PRF, with which to determine quantitatively the intensity of selection on a particular gene or genomic region. The recent availability of large-scale genetic polymorphism data has sparked widespread interest in genome-wide investigations of natural selection. To that end, the original PRF model is of particular interest for geneticists and evolutionary genomicists. In this article, we will provide a tutorial of the mathematical derivation of the original Sawyer and Hartl PRF model.

  8. Cotton chromosome substitution lines crossed with cultivars: genetic model evaluation and seed trait analyses.

    Science.gov (United States)

    Wu, Jixiang; McCarty, Jack C; Jenkins, Johnie N

    2010-05-01

    Seed from upland cotton, Gossypium hirsutum L., provides a desirable and important nutrition profile. In this study, several seed traits (protein content, oil content, seed hull fiber content, seed index, seed volume, embryo percentage) for F(3) hybrids of 13 cotton chromosome substitution lines crossed with five elite cultivars over four environments were evaluated. Oil and protein were expressed both as percentage of total seed weight and as an index which is the grams of product/100 seeds. An additive and dominance (AD) genetic model with cytoplasmic effects was designed, assessed by simulations, and employed to analyze these seed traits. Simulated results showed that this model was sufficient for analyzing the data structure with F(3) and parents in multiple environments without replications. Significant cytoplasmic effects were detected for seed oil content, oil index, seed index, seed volume, and seed embryo percentage. Additive effects were significant for protein content, fiber content, protein index, oil index, fiber index, seed index, seed volume, and embryo percentage. Dominance effects were significant for oil content, oil index, seed index, and seed volume. Cytoplasmic and additive effects for parents and dominance effects in homozygous and heterozygous forms were predicted. Favorable genetic effects were predicted in this study and the results provided evidence that these seed traits can be genetically improved. In addition, chromosome associations with AD effects were detected and discussed in this study.

  9. Genetic rodent models of obesity-associated ovarian dysfunction and subfertility: insights into polycystic ovary syndrome

    Directory of Open Access Journals (Sweden)

    Isabel eHuang-Doran

    2016-06-01

    Full Text Available 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. The molecular mechanisms underlying this causality, however, 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 offer a promising platform in which to address mechanistic questions about reproductive dysfunction in the context of metabolic disease. The impact of primary perturbations in rodent gonadotrophin or androgen signaling has been similarly interrogated. The insights gained from such models, however, have been limited by the relatively poor fidelity of rodent models to human PCOS. In this minireview 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.

  10. Genetic Optimization for Associative Semantic Ranking Models of Satellite Images by Land Cover

    Directory of Open Access Journals (Sweden)

    Nil Kilicay-Ergin

    2013-06-01

    Full Text Available Associative methods for content-based image ranking by semantics are attractive due to the similarity of generated models to human models of understanding. Although they tend to return results that are better understood by image analysts, the induction of these models is difficult to build due to factors that affect training complexity, such as coexistence of visual patterns in same images, over-fitting or under-fitting and semantic representation differences among image analysts. This article proposes a methodology to reduce the complexity of ranking satellite images for associative methods. Our approach employs genetic operations to provide faster and more accurate models for ranking by semantic using low level features. The added accuracy is provided by a reduction in the likelihood to reach local minima or to overfit. The experiments show that, using genetic optimization, associative methods perform better or at similar levels as state-of-the-art ensemble methods for ranking. The mean average precision (MAP of ranking by semantic was improved by 14% over similar associative methods that use other optimization techniques while maintaining smaller size for each semantic model.

  11. Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift.

    Science.gov (United States)

    Reali, Florencia; Griffiths, Thomas L

    2010-02-07

    Scientists studying how languages change over time often make an analogy between biological and cultural evolution, with words or grammars behaving like traits subject to natural selection. Recent work has exploited this analogy by using models of biological evolution to explain the properties of languages and other cultural artefacts. However, the mechanisms of biological and cultural evolution are very different: biological traits are passed between generations by genes, while languages and concepts are transmitted through learning. Here we show that these different mechanisms can have the same results, demonstrating that the transmission of frequency distributions over variants of linguistic forms by Bayesian learners is equivalent to the Wright-Fisher model of genetic drift. This simple learning mechanism thus provides a justification for the use of models of genetic drift in studying language evolution. In addition to providing an explicit connection between biological and cultural evolution, this allows us to define a 'neutral' model that indicates how languages can change in the absence of selection at the level of linguistic variants. We demonstrate that this neutral model can account for three phenomena: the s-shaped curve of language change, the distribution of word frequencies, and the relationship between word frequencies and extinction rates.

  12. 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

  13. 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.

  14. Optimization of Land Use Suitability for Agriculture Using Integrated Geospatial Model and Genetic Algorithms

    Science.gov (United States)

    Mansor, S. B.; Pormanafi, S.; Mahmud, A. R. B.; Pirasteh, S.

    2012-08-01

    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.

  15. 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.

  16. Somatic genetics empowers the mouse for modeling and interrogating developmental and disease processes.

    Science.gov (United States)

    Landrette, Sean F; Xu, Tian

    2011-07-01

    With recent advances in genomic technologies, candidate human disease genes are being mapped at an accelerated pace. There is a clear need to move forward with genetic tools that can efficiently validate these mutations in vivo. Murine somatic mutagenesis is evolving to fulfill these needs with tools such as somatic transgenesis, humanized rodents, and forward genetics. By combining these resources one is not only able to model disease for in vivo verification, but also to screen for mutations and pathways integral to disease progression and therapeutic intervention. In this review, we briefly outline the current advances in somatic mutagenesis and discuss how these new tools, especially the piggyBac transposon system, can be applied to decipher human biology and disease.

  17. Les premiers colons de l’ancienne Haïti et leurs attaches en métropole, à l’aube des premiers établissements (1650-1700)

    OpenAIRE

    Hroděj, Philippe

    2012-01-01

    Au moment où les premiers établissements durables voient le jour dans ce qui va devenir la partie française de Saint-Domingue, les colons ne sont qu’une poignée. Il est nécessaire d’abord de raisonner sur le nombre, source d’isolement, renforcé par le relief qui compartimente les différents quartiers, par l’éloignement des Petites Antilles, par des liens commerciaux longtemps aléatoires et par le fait dominant que sont les guerres quasi continues, du fait des délais d’application des traités ...

  18. 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.

  19. A simple algorithm for optimization and model fitting: AGA (asexual genetic algorithm)

    Science.gov (United States)

    Cantó, J.; Curiel, S.; Martínez-Gómez, E.

    2009-07-01

    Context: Mathematical optimization can be used as a computational tool to obtain the optimal solution to a given problem in a systematic and efficient way. For example, in twice-differentiable functions and problems with no constraints, the optimization consists of finding the points where the gradient of the objective function is zero and using the Hessian matrix to classify the type of each point. Sometimes, however it is impossible to compute these derivatives and other type of techniques must be employed such as the steepest descent/ascent method and more sophisticated methods such as those based on the evolutionary algorithms. Aims: We present a simple algorithm based on the idea of genetic algorithms (GA) for optimization. We refer to this algorithm as AGA (asexual genetic algorithm) and apply it to two kinds of problems: the maximization of a function where classical methods fail and model fitting in astronomy. For the latter case, we minimize the chi-square function to estimate the parameters in two examples: the orbits of exoplanets by taking a set of radial velocity data, and the spectral energy distribution (SED) observed towards a YSO (Young Stellar Object). Methods: The algorithm AGA may also be called genetic, although it differs from standard genetic algorithms in two main aspects: a) the initial population is not encoded; and b) the new generations are constructed by asexual reproduction. Results: Applying our algorithm in optimizing some complicated functions, we find the global maxima within a few iterations. For model fitting to the orbits of exoplanets and the SED of a YSO, we estimate the parameters and their associated errors.

  20. 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