1,721,060 research outputs found
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
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
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
Localized Correlation Analysis and Genetic Association with Cardiovascular Disease
No full textVariations in gene expression are potential risk factors for atherosclerosis, which is one of the most common forms of cardiovascular disease. We performed a localized Pearson correlation test in 372 individuals from seven datasets relevant to cardiovascular disease studies. The genomes of samples were separated into 20Mb windows and correlation tests were performed locally in these windows. The localized Pearson correlation test found chr3:115Mb–135Mb was tightly connected by significantly high proportion of highly correlated pairs (P value = 0.0266 with Z-test). LSAMP, GATA2, MBD4, and other genes in the region were considered associated with cardiovascular disease because they were involved in highly correlated pairs. Furthermore, these genes were also associated with cardiovascular disease by having significantly high SNP odds ratios (P value < 0.1) between patients and controls in an independent Duke University Medical Center database. In addition, a permutation test was performed to demonstrate that chr3:115Mb–135Mb might underlie the regulation of cardiovascular disease. Finally, the localized Pearson correlation test also found some other regions that could be associated with cardiovascular disease.</p
Gene-Environment Interactions in Cardiovascular Disease
Full text linkIn this manuscript I seek to demonstrate the importance of gene-environment interactions in cardiovascular disease. This manuscript contains five studies each of which contributes to our understanding of the joint impact of genetic variation and environmental exposures to cardiovascular disease: a candidate gene study for gene-smoking interactions associated with early-onset coronary artery disease, an epidemiology study of the association between traffic-related air pollution and cardiovascular disease, a Genome-Wide Interaction Study for gene-by-traffic related air pollution interactions associated with peripheral arterial disease, a Genome-Wide Interaction Study for gene-by-traffic related air pollution interactions on coronary atherosclerosis burden, and a method for analyzing associations between high-dimensional genomics datasets. Smoking is a strong risk factors for coronary artery disease, and may play a causative role in the incidence of coronary artery disease. Smoking had been implicated as a reason for heterogeneity observed in associations between genetic variants on chromosome three and coronary artery disease. I used a family-based early-onset coronary artery disease cohort (GENECARD) to study gene-smoking interactions. I also used data from the three independent cohorts to perform a meta-analysis of gene-smoking interactions focusing on the KALRN gene and Rho-GTPase pathway. I found significant evidence for gene-smoking interactions associations involving variants in KALRN and other Rho-GTPase pathway genes on chromosome 3. Though the estimated increase in incident cardiovascular disease or cardiovascular events due to air pollution exposure is modest at 3-5%, the ubiquitous nature of air pollution exposures means it has a substantial population-level impact on cardiovascular disease. Historically genome-wide interaction studies with air pollution have not yielded genome-wide significant interactions, however by implementing statistical tools novel to this field I have discovered significant interactions between genetic variants and traffic-related air pollution that are associated with cardiovascular diseases. I studied interactions associated with peripheral arterial disease and the number of diseased coronary vessels (an indicator for coronary artery disease burden) using race-stratified cohort study designs. With peripheral arterial disease I observed that variants in both BMP8A and BMP2 showed evidence for interactions in both European-American and African-American cohorts. In BMP8A I uncovered the first genome-wide significant interaction with air pollution associated with cardiovascular disease. BMP2 gene expression is upregulated after exposure to black carbon, a major component of diesel exhaust, and coding variants within this gene showed evidence for interaction. With the number of diseased coronary vessels I observed that variants in PIGR showed significant evidence for involvement in gene-traffic related air pollution interactions. I observed that coding variation within PIGR was associated with coronary artery disease burden in a gene-by-traffic related air pollution interaction model. As PIGR is involved in the immune response it represents a strong candidate gene discovered via an unbiased genome-wide scan. The use of high dimensional data to study chronic disease is becoming commonplace. In order to properly analyze high-dimensional data without suffering from high false-discovery rate penalties, the data is often summarized in a way that takes advantage of the correlation structure. Two common approaches for this are principal components analysis and canonical correlation analysis. However neither of these approaches are appropriate when one preferentially desires to preserve structure within the data. To address this shortcoming I developed constrained canonical correlation analysis (cCCA). With cCCA one can evaluate the correlation between two high dimensional datasets while preferentially preserving structure in one of the datasets. This has uses when studying multi-variate outcomes such as cardiovascular disease using multi-variate predictors such as air pollution. Additionally cCCA can be used to create endophenotype factors that specifically explain the variation within a high-dimensional set of predictors (such as gene expression or metabolomics data) with respect to potential endophenotypes for cardiovascular disease, such as cholesterol measures.</p
Genetic Analysis of Gulf War illness: Phenotype Development, GWAS, and Gene-Environment Interaction
No full textVeterans who served in the 1990-1991 Gulf War experience debilitating chronic symptoms at extremely high rates. In the 30 years since the Gulf War, many researchers have worked to identify the cause and biological pathway of Gulf War illness (GWI). There is, however, no biomarker, ICD code, or other standardized way to identify veterans with GWI; veterans are told they have GWI based on a clinician’s assessment of their unexplained chronic symptoms. There is also little agreement on the causes and potential biological pathways of GWI. This dissertation describes phenotyping efforts, the first genome-wide association study (GWAS) of GWI, and a candidate gene-environment interaction study. First, I describe methods for developing well-documented indicators for complex phenotypes, which have generated GWI indicators that are used for the MVP and GWECB datasets. This is the only tested and published algorithm for defining GWI. This work required extensive exploratory analysis and data cleaning, as it was the first major analysis of the GWECB dataset. The variables generated through both the data cleaning and GWI algorithm have been incorporated into the GWECB. Then, I performed the first GWAS of GWI, which supports prior work in the field and suggests further candidate analyses. Top gene-set associations include response to cadmium ion, regulation of response to interferon gamma, and regulation of autophagosome maturation. Among other top associations, these results indicate association with a neuroimmune response to exposure. GWAS summary statistics will be made available. Finally, I developed a hypothesis-driven candidate gene-environment interaction study, which replicated a previously published statistically significant association of rs662/PB pill exposure with GWI. Future research building off my contributions could help identify the underlying biological pathways and causes of GWI, allowing better treatment of the underlying disease for hundreds of thousands of Gulf War Veterans.</p
- …
