1,721,029 research outputs found
Genomics of elite sporting performance: what little we know and necessary advances
No full textNumerous reports of genetic associations with performance- and injury-related phenotypes have been published over the past three decades; these studies have employed primarily the candidate gene approach to identify genes that associate with elite performance or with variation in performance-and/or injury-related traits. Although generally with small effect sizes and heavily prone to type I statistic error, the number of candidate genetic variants that can potentially explain elite athletic status, injury predisposition, or indeed response to training will be much higher than that examined by numerous biotechnology companies. Priority should therefore be given to applying whole genome technology to sufficiently large study cohorts of world-class athletes with adequately measured phenotypes where it is possible to increase statistical power. Some of the elite athlete cohorts described in the literature might suffice, and collectively, these cohorts could be used for replication purposes. Genome-wide association studies are ongoing in some of these cohorts (i.e., Genathlete, Russian, Spanish, Japanese, United States, and Jamaican cohorts), and preliminary findings include the identification of one single nucleotide polymorphism (SNP; among more than a million SNPs analyzed) that associates with sprint performance in Japanese, American (i.e., African American), and Jamaican cohorts with a combined effect size of ~2.6 (P-value <5×10(-7)) and good concordance with endurance performance between select cohorts. Further replications of these signals in independent cohorts will be required, and any replicated SNPs will be taken forward for fine-mapping/targeted resequencing and functional studies to uncover the underlying biological mechanisms. Only after this lengthy and costly process will the true potential of genetic testing in sport be determined
Statistical methods for pathway analysis of genome-wide data for association with complex genetic traits
No full textA number of statistical methods have been developed to test for associations between pathways (collections of genes related biologically) and complex genetic traits. Pathway analysis methods were originally developed for analyzing gene expression data, but recently methods have been developed to perform pathway analysis on genome-wide association study (GWAS) data. The purpose of this review is to give an overview of these methods, enabling the reader to gain an understanding of what pathway analysis involves, and to select the method most suited to their purposes. This review describes the various types of statistical methods for pathway analysis, detailing the strengths and weaknesses of each. Factors influencing the power of pathway analyses, such as gene coverage and choice of pathways to analyze, are discussed, as well as various unresolved statistical issues. Finally, a list of computer programs for performing pathway analysis on genome-wide association data is provided
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Advances in Dyslexia Genetics—New Insights Into the Role of Brain Asymmetries
No full textDyslexia is a common condition affecting up to 10% school-aged children. There is strong evidence that genetics plays an important role in dyslexia and is expected to be complex in nature. Few specific susceptibility factors have been identified so far, but their functional characterization has provided novel insights into the biology of dyslexia. In particular, they point to an unexpected role of candidate genes for dyslexia in the biology of cilia, cellular organelles required in many processes including the establishment of left-right asymmetries early in development. This observation has brought back into the spotlight the old idea of a link between dyslexia and handedness. Yet much of the genetics contributing to dyslexia remains unexplained. The lack of biological markers, clear diagnostic criteria, and homogeneous assessment strategies are just some of the factors preventing the collection of the cohorts powered enough for large-scale genetic studies. While the technology and methods to generate and handle large-scale data have reached unprecedented potential, the main challenge remains in establishing universal guidelines to collect suitable phenotype information across independent studies. These difficulties reflect the complex nature of dyslexia which is highly heterogeneous and often co-occurs with other neurodevelopmental disorders
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