1,720,970 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
Large-scale comparative bioinformatics analyses
Full text linkOne of the main and most recent challenges of modern biology is to keep-up with
growing amount of biological data coming from next generation sequencing
technologies. Keeping up with the growing volumes of experiments will be the only
way to make sense of the data and extract actionable biological insights. Large-scale
comparative bioinformatics analyses are an integral part of this procedure. When
doing comparative bioinformatics, multiple sequence alignments (MSAs) are by far
the most widely used models as they provide a unique insight into the accurate
measure of sequence similarities and are therefore instrumental to revealing genetic
and/or functional relationships among evolutionarily related species. Unfortunately,
the well-established limitation of MSA methods when dealing with very large datasets
potentially compromises all downstream analysis. In this thesis I expose the current
relevance of multiple sequence aligners, I show how their current scaling up is
leading to serious numerical stability issues and how they impact phylogenetic tree
reconstruction. For this purpose, I have developed two new methods, MEGA-Coffee,
a large scale aligner and Shootstrap a novel bootstrapping measure incorporating
MSA instability with branch support estimates when computing trees. The large
amount of computation required by these two projects was carried using Nextflow, a
new computational framework that I have developed to improve computational
efficiency and reproducibility of large-scale analyses like the one carried out in the
context of these studies.Uno de los principales y más recientes retos de la biología moderna es poder hacer
frente a la creciente cantidad de datos biológicos procedentes de las tecnologías de
secuenciación de alto rendimiento. Mantenerse al día con los crecientes volúmenes
de datos experimentales es el único modo de poder interpretar estos datos y extraer
conclusiones biológicos relevantes. Los análisis bioinformáticos comparativos a gran
escala son una parte integral de este procedimiento. Al hacer bioinformática
comparativa, los alineamientos múltiple de secuencias (MSA) son con mucho los
modelos más utilizados, ya que proporcionan una visión única de la medida exacta
de similitudes de secuencia y son, por tanto, fundamentales para inferir las
relaciones genéticas y / o funcionales entre las especies evolutivamente
relacionadas. Desafortunadamente, la conocida limitación de los métodos MSA para
analizar grandes bases de datos, puede potencialmente comprometer todos los
análisis realizados a continuación. En esta tesis expongo la relevancia actual de los
métodos de alineamientos multiples de secuencia, muestro cómo su uso en datos
masivos está dando lugar a serios problemas de estabilidad numérica y su impacto
en la reconstrucción del árbol filogenético. Para este propósito, he desarrollado dos
nuevos métodos, MEGA-café, un alineador de gran escala y Shootstrap una nueva
medida de bootstrapping que incorpora la inestabilidad del MSA con las
estimaciones de apoyo de rama en el cálculo de árboles filogéneticos. La gran
cantidad de cálculo requerido por estos dos proyectos se realizó utilizando Nextflow,
un nuevo marco computacional que se ha desarrollado para mejorar la eficiencia
computacional y la reproducibilidad del análisis a gran escala como la que se lleva a
cabo en el contexto de estos estudios.Programa de doctorat en Biomedicin
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
Large-scale comparative bioinformatics analyses
No full textOne of the main and most recent challenges of modern biology is to keep-up with growing amount of biological data coming from next generation sequencing technologies. Keeping up with the growing volumes of experiments will be the only way to make sense of the data and extract actionable biological insights. Large-scale comparative bioinformatics analyses are an integral part of this procedure. When doing comparative bioinformatics, multiple sequence alignments (MSAs) are by far the most widely used models as they provide a unique insight into the accurate measure of sequence similarities and are therefore instrumental to revealing genetic and/or functional relationships among evolutionarily related species. Unfortunately, the well-established limitation of MSA methods when dealing with very large datasets potentially compromises all downstream analysis. In this thesis I expose the current relevance of multiple sequence aligners, I show how their current scaling up is leading to serious numerical stability issues and how they impact phylogenetic tree reconstruction. For this purpose, I have developed two new methods, MEGA-Coffee, a large scale aligner and Shootstrap a novel bootstrapping measure incorporating MSA instability with branch support estimates when computing trees. The large amount of computation required by these two projects was carried using Nextflow, a new computational framework that I have developed to improve computational efficiency and reproducibility of large-scale analyses like the one carried out in the context of these studies.Uno de los principales y más recientes retos de la biología moderna es poder hacer frente a la creciente cantidad de datos biológicos procedentes de las tecnologías de secuenciación de alto rendimiento. Mantenerse al día con los crecientes volúmenes de datos experimentales es el único modo de poder interpretar estos datos y extraer conclusiones biológicos relevantes. Los análisis bioinformáticos comparativos a gran escala son una parte integral de este procedimiento. Al hacer bioinformática comparativa, los alineamientos múltiple de secuencias (MSA) son con mucho los modelos más utilizados, ya que proporcionan una visión única de la medida exacta de similitudes de secuencia y son, por tanto, fundamentales para inferir las relaciones genéticas y / o funcionales entre las especies evolutivamente relacionadas. Desafortunadamente, la conocida limitación de los métodos MSA para analizar grandes bases de datos, puede potencialmente comprometer todos los análisis realizados a continuación. En esta tesis expongo la relevancia actual de los métodos de alineamientos multiples de secuencia, muestro cómo su uso en datos masivos está dando lugar a serios problemas de estabilidad numérica y su impacto en la reconstrucción del árbol filogenético. Para este propósito, he desarrollado dos nuevos métodos, MEGA-café, un alineador de gran escala y Shootstrap una nueva medida de bootstrapping que incorpora la inestabilidad del MSA con las estimaciones de apoyo de rama en el cálculo de árboles filogéneticos. La gran cantidad de cálculo requerido por estos dos proyectos se realizó utilizando Nextflow, un nuevo marco computacional que se ha desarrollado para mejorar la eficiencia computacional y la reproducibilidad del análisis a gran escala como la que se lleva a cabo en el contexto de estos estudios.Programa de doctorat en Biomedicin
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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