1,720,969 research outputs found
Forbedrede beregningsmetoder for regulatorisk genomisk inferens
Get PDFEstablishing precise links between genotypes and traits is essential for enhancing breeding efficiency in agriculture and advancing personalized medicine. However, the presence of multiple variants in linkage disequilibrium confounds the identification of causal variants. By focusing on the relationship between genotypes and molecular phenotypes as intermediaries, we can better prioritize causal variants. This thesis focuses on developing and improving computational methods to enhance the accuracy, reproducibility, and scalability of genotype-to-molecular-phenotype inference, bridging the gap between genetic variation and phenotypic traits across diverse biological contexts, including human, agricultural, and aquaculture genomics. The first study presents cscQTL, a new computational approach designed to improve the sensitivity and specificity of circular RNA quantitative trait loci mapping. By systematically combining outputs from multiple circRNA detection tools and implementing a robust re-quantification strategy, cscQTL outperforms traditional approaches, enabling the discovery of novel circular RNA quantitative trait loci and their potential roles in immune-related diseases. The second study develops nf-RASQUAL, a scalable Nextflow pipeline for molecular quantitative trait loci discovery in small sample size datasets, building on the established RASQUAL approach. This pipeline enables robust mapping of molecular quantitative trait loci for gene expression and chromatin accessibility in Atlantic salmon, identifying a substantial number of loci in this key aquatic species. Through variant annotation, motif disruption, and colocalization analyses, we demonstrate the biological relevance of the discovered molecular quantitative trait loci. The third study leverages deep learning and functional genomics data to predict the regulatory impact of non-coding variants in farmed species, including cattle, pigs, chickens, and salmon. Optimized deep learning models achieve high sequence modeling accuracy and effectively prioritize functional variants through genomic prediction and expression quantitative trait loci causal variant prediction. Motif analysis and in silico mutagenesis further reveal regulatory grammar, enhancing our understanding of sequence-function relationships in non-coding regions.Kartlegging av koblinger mellom genotyper og fenotyper er sentralt for å forbedre avlseffektivitet i landbruket og fremme persontilpasset medisin. Genetisk kobling mellom nærliggende varianter kan derimot gjøre det utfordrende å avgjøre hvilken av dem som er den direkte årsaken. En metode for å bedre prioritere kausale varianter er å fokusere på forholdet mellom genotyper og molekylære fenotyper som et mellomledd. Denne avhandlingen fokuserer på å utvikle og forbedre beregningsmetoder for å øke nøyaktigheten, reproduserbarheten og skalerbarheten av inferens fra genotyper til molekylære fenotyper, og dermed bygge bro mellom genetisk variasjon og fenotypiske egenskaper på tvers av ulike biologiske kontekster, inkludert menneskelig, landbruks- og akvakulturgenomikk.submittedVersio
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
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
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