1,720,955 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
Investigating Evolution Through the Lens of AI-driven Protein Exploration and Phylogenetic Modeling
No full textRecent advances in computational biology, artificial intelligence, and sequencing technologies have enabled new perspectives for addressing longstanding questions in evolutionary biology. Increased computational power has made large-scale simulations feasible for investigating diverse aspects of evolutionary and phylogenetic modeling. Similarly, deep learning algorithms now allow for the prediction of reasonably accurate tertiary protein structures, unlocking the potential for investigating diversity and evolution of protein structure across a broad range of organisms. This thesis presents two studies that target different aspects of evolutionary inference from unique perspectives. Yet, the share an overarching goal of presenting new perspectives on the evolutionary basis of biodiversity from comparative analyses of protein and trait evolution.
Viewing molecular evolution through the lens of protein structural diversity, the second chapter leverages deep learning models to examine olfactory receptor (OR) evolution in long-horn beetles. That is, we sought to investigate the diversity and structure of proteins encoded within recently-sequenced insect genomes using machine learning. Using two recently developed deep learning models, RoseTTAFold and AlphaFold, we predicted the tertiary structure of OR proteins in two Cerambycid species. We then investigated diversity among these OR proteins and analyzed the relationship between structural and sequence-level evolutionary distances. These findings highlight the promise of deep learning models for gaining meaningful biological insights, particularly in systems where experimental resources are limited.
The third chapter addresses evolutionary biology at a broader comparative scale, evaluating how phylogenetic assumptions influence evolutionary conclusions using statistical regression approaches. Here, we focused on a core question of comparative biology: understanding how phylogenetic modeling choices influence statistical conclusions about trait evolution. Through large-scale simulation studies and analysis of an empirical dataset containing traits associated with longevity, we assessed the sensitivity of phylogenetic regression to tree choice. Across these analyses, tree selection emerged as an important factor influencing the behavior of phylogenetic regression. The results show that an incorrect tree choice, that does not accurately represent the evolutionary history of a trait, can lead to significantly elevated false positive rates. This holds particularly true as the amount of data (species and traits) included in the analysis increases. These findings underscore the importance of thoughtful tree selection across studies in comparative biology. Together, these chapters highlight the diversity of questions and scales encompassed by evolutionary biology and contribute to a broader understanding of the field
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
Investigating Evolution Through the Lens of AI-driven Protein Exploration and Phylogenetic Modeling
No full textRecent advances in computational biology, artificial intelligence, and sequencing technologies have enabled new perspectives for addressing longstanding questions in evolutionary biology. Increased computational power has made large-scale simulations feasible for investigating diverse aspects of evolutionary and phylogenetic modeling. Similarly, deep learning algorithms now allow for the prediction of reasonably accurate tertiary protein structures, unlocking the potential for investigating diversity and evolution of protein structure across a broad range of organisms. This thesis presents two studies that target different aspects of evolutionary inference from unique perspectives. Yet, the share an overarching goal of presenting new perspectives on the evolutionary basis of biodiversity from comparative analyses of protein and trait evolution.
Viewing molecular evolution through the lens of protein structural diversity, the second chapter leverages deep learning models to examine olfactory receptor (OR) evolution in long-horn beetles. That is, we sought to investigate the diversity and structure of proteins encoded within recently-sequenced insect genomes using machine learning. Using two recently developed deep learning models, RoseTTAFold and AlphaFold, we predicted the tertiary structure of OR proteins in two Cerambycid species. We then investigated diversity among these OR proteins and analyzed the relationship between structural and sequence-level evolutionary distances. These findings highlight the promise of deep learning models for gaining meaningful biological insights, particularly in systems where experimental resources are limited.
The third chapter addresses evolutionary biology at a broader comparative scale, evaluating how phylogenetic assumptions influence evolutionary conclusions using statistical regression approaches. Here, we focused on a core question of comparative biology: understanding how phylogenetic modeling choices influence statistical conclusions about trait evolution. Through large-scale simulation studies and analysis of an empirical dataset containing traits associated with longevity, we assessed the sensitivity of phylogenetic regression to tree choice. Across these analyses, tree selection emerged as an important factor influencing the behavior of phylogenetic regression. The results show that an incorrect tree choice, that does not accurately represent the evolutionary history of a trait, can lead to significantly elevated false positive rates. This holds particularly true as the amount of data (species and traits) included in the analysis increases. These findings underscore the importance of thoughtful tree selection across studies in comparative biology. Together, these chapters highlight the diversity of questions and scales encompassed by evolutionary biology and contribute to a broader understanding of the field
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
