1,721,011 research outputs found
A Monte Carlo approach for estimation of haplotype probabilities in half-sib families
No full textThe objective of this work was to propose an algorithm (HAPROB) to estimate haplotype probabilities for genotyped members of half-sib families for which parents lacked genotypic information. The algorithm had 2 basic steps. First, a Monte Carlo-based approach was used to estimate haplotype probabilities for sires conditional upon offspring genotypes and population allelic frequencies, and then offspring-haplotype probabilities were estimated conditional upon sire probabilities and population frequencies. The 2 steps were alternated iteratively until estimates of population frequencies were essentially unchanged. Simulation was used to evaluate effects of the number of Monte Carlo cycles on the accuracy of the reconstructed haplotypes. Fifty thousand cycles was found to be sufficient for the haplotype configurations considered. Accuracy of the algorithm was compared with that obtained by the public domain SIMWALK2 software. Predictions of the most likely haplotype configurations are produced by SIMWALK2, but no estimates of probability are given. The accuracy of the current approach was comparable to that obtained from SIMWALK2. The proportions of times that haplotypes were reconstructed correctly were 87.0 and 92.4% (sires and offspring) for HAPROB vs. 87.5 and 91.5% for SIMWALK2. Effects of family size on accuracy of reconstruction were examined. Accuracy of reconstruction was only about 4% for sires with 2 offspring, but accuracy among the offspring themselves was 65%. Accuracy increased quickly as family size increased and reached 100% for sires with 30 offspring. Maximum accuracy for offspring was about 96%. Estimates of haplotype probabilities produced can be used in regression analyses to estimate effects of haplotypes on quantitative phenotypes
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
In silico candidate gene mining in livestock species
No full textThe identification of genes involved in livestock production and disease is a challenge due to the multi-genic, multifactorial nature of the traits and the complexity of integration of information from different studies. Genome-wide techniques such as microarray analysis, SAGE, linkage analysis and linkage disequilibrium analysis have been extensively used in livestock and have often identified a large number of candidate genes. Selection of the most probable candidate genes for further empirical analysis remains a challenge. Novel extensive biological databases (DB) provide an opportunity for candidate gene mining. Bioinformatic methods and tools to prioritize candidate genes underlying pathways or diseases have been presented mostly for application to human disease candidate gene search. These computational methods employ data from a variety of sources to identify the most likely candidate genes from genes sets. The objectives of the study were: 1. to test a set of existing gene prioritization computational methods on real and simulated livestock traits, namely mastitis susceptibility in cattle, production in cattle, litter size in swine, and tick resistance in cattle; 2. to develop a novel method for candidate prioritization that better suits the characteristics of genomic information of livestock species (lower level of annotation, different experimental designs, etc.). The algorithm performs distinct prioritizations from multiple heterogeneous data sources, which are then integrated into one global ranking using order statistics. Information about a trait or pathway is recorded, ordered and stored from a set of known genes using multiple data sources. Then, the candidate genes are ranked based on similarity with the training properties obtained in the first step, resulting in one prioritized list for each data source. Data for linkage and association analysis, and expression analysis (2 microarray studies) were simulated for a complex trait assigning the largest effects to known, well described genes in the Gene Ontology (GO), InterPro, MEDLINE, and Kegg databases. All the other simulated major genes were assigned to genes described in one of the databases for livestock species. Real data were selected from the literature, mainly from large QTL studies, or obtained from collaborators. Software used for the analysis were: Suspect (http://www. genetics.med.ed.ac.uk/software/prospectr.php), Endevour and COeXpress (http://coxpress.sf.net). Results using simulated data showed that where annotation is missing, the accuracy of the considered algorithms decreased drastically. A new prioritization method applied to simulated data correctly ranked candidate gene only when QTL information had a high level of accuracy. Further work is needed in defining methods of weighting QTL data information
Phylogenetic analysis of the GAG region encoding the matrix protein of small ruminant lentiviruses: comparative analysis and molecular epidemiological applications
No full textLittle sequence information exists on the matrix-protein (MA) encoding region of small ruminant lentiviruses (SRLV). Fifty-two novel sequences were established and permitted a first phylogenetic analysis of this region of the SRLV genome. The variability of the MA encoding region is higher compared to the gag region encoding the capsid protein and surprisingly close to that reported for the env gene. In contrast to primate lentiviruses, the deduced amino acid sequences of the N- and C-terminal domains of MA are variable. This permitted to pinpoint a basic domain in the N-terminal domain that is conserved in all lentiviruses and likely to play an important functional role. Additionally, a seven amino acid insertion was detected in all MVV strains, which may be used to differentiate CAEV and MVV isolates. A molecular epidemiology analysis based on these sequences indicates that the Italian lentivirus strains are closely related to each other and to the CAEV-CO strain, a prototypic strain isolated three decades ago in the US. This suggests a common origin of the SRLV circulating in the monitored flocks, possibly related to the introduction of infected goats in a negative population. Finally, this study shows that the MA region is suitable for phylogenetic studies and may be applied to monitor SRLV eradication programs
A structural equation model for describing relationship between somatic cell score and milk yield in dairy goats
No full textThe relationship between milk yield and somatic cell score (log-transformed somatic cell count) in dairy goats may involve complex pathways with recursive or simultaneous effects. Structural equation models were fitted to longitudinal data on milk yield and on somatic cell scores. Data consisted of 4 repeated records of milk production and of somatic cell score from left and right halves of the udder in each of 47 dairy goats; infection status of each of the halves at each test day was also available. Results strongly suggest the existence of a within-half, first-order autoregressive process and of simultaneity of effects between somatic cell scores from the left and right halves of the udder. This indicates that the immune response to an infection is not restricted to the half of the udder in which the infection takes place and that it tends to propagate over time. The existence of a negative effect of somatic cell score on milk yield was also supported by the results; however, evidence in favor of an effect in the opposite direction, a dilution effect, was not strong
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
Full text linkWe 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
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