1,721,027 research outputs found
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
Integrative analysis of long non-coding RNAs in dogs and their implications in canine oral melanoma, human melanoma model
No full textLes ARN longs non-codants (lncRNAs) constituent une famille d'ARN hétérogènes qui jouent un rôle majeur dans de nombreux cancers et notamment dans les mélanomes. Le chien est un modèle naturel et spontané pour l’analyse génétique comparée des cancers et, l'annotation du génome canin a récemment été enrichie avec l'identification de plus 10 000 lncRNAs. Afin de réaliser des prédictions fonctionnelles bioinformatiques des lncRNAs, nous avons caractérisé les profils d'expression des lncRNAs canins à partir de 26 tissus distincts. Nous avons défini la spécificité tissulaire de l’expression des lncRNAs et inféré leur fonctionnalité potentielle par des analyses de génomique et de transcriptomique comparatives avec des données humaines issues du projet ENCODE (ENCyclopedia Of DNA Elements). Comme chez l'homme et la souris, une grande proportion de lncRNAs canins (44 %) est exprimée de manière spécifique au sein d’un tissu. Par une approche de génomique comparative, nous avons identifié plus de 900 lncRNAs orthologues entre l’homme et le chien et pour 26 % d’entre eux, des patrons d'expression entre tissus significativement conservés (p < 0,05). Dans le cadre de l'étude des mélanomes canins, nous avons analysé les données de RNA-seq de 52 échantillons tumeurs/contrôles de mélanomes oraux. Nous avons identifié plus de 750 lncRNAs différentiellement exprimés entre la tumeur et le contrôle (FDR < 0,01), dont plus de 100 conservés avec l’homme. Ces lncRNAs constituent de bons candidats pour étudier la régulation de la progression tumorale des mélanomes chez le chien et pourront être évalués pour leurs potentiels diagnostic et thérapeutique en médecine humaine et vétérinaire.Long non-coding RNAs (lncRNAs) are a family of heterogeneous RNAs that play a major role in many cancers, particularly in melanomas. The dog is a natural and spontaneous model for the comparative genetic analysis of cancers and, the annotation of the canine genome has recently been enriched with the identification of over 10,000 lncRNAs. In order to perform functional bioinformatic predictions of lncRNAs, we have characterized the expression patterns of canine lncRNAs from 26 distinct tissues representative of the major functions of the organism. We defined the tissue specificity of lncRNAs expression and inferred their potential functionality by comparative genomic and transcriptomic analyses with human data from the ENCODE project (ENCyclopedia Of DNA Elements). As in humans and mice, we show that a large proportion of canine lncRNAs (44%) are expressed specifically within a tissue. Using a comparative genomic approach, we have identified more than 900 orthologue lncRNAs between humans and dogs, and we show that for 26% of them, tissue expression patterns are also significantly conserved (p < 0.05). In the study of canine melanomas, we investigated the lncRNAs from RNA-seq data from 52 tumour/control samples of oral melanoma. We identified more than 750lncRNAs differentially expressed between tumour and control (FDR < 0.01), of which more than 100 were conserved with humans. These lncRNAs are good candidates to study the regulation of tumour progression of melanomas in dogs and can be evaluated for their diagnostic and therapeutic potential in human and veterinary medicine
Deep learning methods for the genomic analysis of canine cancers as models for human cancers
No full textLes méthodes d’apprentissage profond (DL) se sont récemment révélées être de puissantes stratégies pour prédire l’activité régulatrice d’une séquence génomique et donc pour, in fine, évaluer l’impact des mutations régulatrices sur l’expression des gènes. L’outil Basenji propose une approche DL utilisant des réseaux de neurones convolutifs pour prédire le niveau d’expression de gènes humains. Nous avons adapté ce programme pour entraîner un modèle d’expression génique spécifique au chien et montré que ce modèle de prédiction atteignait des performances similaires à celles observées chez l’homme, avec des corrélations élevées entre les niveaux d’expression réels et ceux pré- dits (r=0,66). Pour prédire le niveau d’expression de gènes canins, nous démontrons également que l’utilisation du modèle de prédiction canin (approche intra-espèce) aboutit à de meilleures performances que le modèle humain (approche inter-espèce), notamment en lien avec certaines caractéristiques spécifiques aux séquences canines (niveau de GC, d’éléments transposable et conservation évolutive). Le chien étant un modèle naturel pour l’étude des cancers humains, nous avons également exploité ces modèles pour prédire l’impact de mutations non-codantes sur l’expression de gènes impliqués dans les cancers. Nous avons ainsi localisé 1301 mutations communes entre l’homme et le chien, suggérant un rôle fonctionnel dans la régulation de l’expression de gènes impliqués dans les cancers. Finalement, nos modèles et les outils pour les exploiter sont disponibles sur GitHub : https://github.com/ckergal/BLIMP.Deep learning (DL) methods have recently been shown to be powerful strategies for predicting the regulatory activity of a genomic sequence and thus for ultimately assessing the impact of regulatory mutations on gene expression. The Basenji tool proposes a DL approach using convolutional neural networks to predict the expression level of human genes. We adapted this program to train a dog-specific gene expression model and showed that this model achieved similar performance to that observed in humans, with high correlations between real and predicted expression levels (r=0.66). To predict the ex- pression level of canine genes, we show that the canine prediction model (within-species approach) leads to better performances than the human model (cross-species approach), particularly due to some specific features of canine sequences (GC content, transposable elements and evolutionary conservation). As the dog is a spontaneous model for human cancers, we used these models to predict the impact of non-coding mutations on the expression of genes involved in cancers. We identified 1301 common mutations to both humans and dogs, suggesting a functional role in the regulation of the expression of genes involved in cancer. Finally, models and tools to exploit them are available on GitHub: https://github.com/ckergal/BLIMP
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
- …
