1,721,092 research outputs found
The interplay between genetics, the microbiome, DNA‐methylation & gene‐expression
Full text linkThere are many factors involved in the development of human diseases and traits. In recent years the field of human genetics has been very successful in linking genetic variation to diseases and traits. By conducting large-scale studies comparing the genetic make-up of affected versus non-affected participants, we have identified thousands of variants in the human genome that are more or less commonly found in cases compared to controls. These genome-wide association studies (GWAS) have been instrumental in the identification of genes linked to a multitude of diseases and traits. Variants in the functional parts of a gene can be relatively straightforward to interpret. However, not all the variants linked to disease can be directly interpreted. By using intermediate molecular data layers, such as gene expression, DNA-methylation or protein levels, we can gain more insight into the genetic variants identified by GWAS.However, we only get a limited picture of disease by focusing on genetic variation. Another important factor related to disease is the environment. But it is much harder to quantify environmental factors than to determine the genetic differences between two individuals. Using the intermediate molecular data, or biological omics, we can gain insights into the environment of individuals. The environment surrounding individuals can, for instance, influence the composition of their microbiome, but also their gene expression, DNA-methylation and protein levels. By studying the differences in these biological omics in relation to phenotypes and disease, we can learn more about the environmental factors that lead to disease. However, as with GWAS studies, we do not always know what the differences in these biological data layers mean.In this thesis we have focused on two biological omics, the gut microbiome composition and the DNA-methylome. The gut microbiome is the collection of micro-organisms that live together in the human gut; DNA-methylation is the occurrence of a methyl group bound to the DNA and this mainly occurs at cysteine-guanine pairs. In the first part of the thesis we have focused on inter-individual differences influencing, or influenced by, differences in the microbiome composition, while in the second part, we have focused on changes in DNA-methylation associated to tissue differences and on the influence of genetic variation on DNA-methylation
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
The interplay between genetics, the microbiome, DNA‐methylation & gene‐expression
Full text linkThere are many factors involved in the development of human diseases and traits. In recent years the field of human genetics has been very successful in linking genetic variation to diseases and traits. By conducting large-scale studies comparing the genetic make-up of affected versus non-affected participants, we have identified thousands of variants in the human genome that are more or less commonly found in cases compared to controls. These genome-wide association studies (GWAS) have been instrumental in the identification of genes linked to a multitude of diseases and traits. Variants in the functional parts of a gene can be relatively straightforward to interpret. However, not all the variants linked to disease can be directly interpreted. By using intermediate molecular data layers, such as gene expression, DNA-methylation or protein levels, we can gain more insight into the genetic variants identified by GWAS.However, we only get a limited picture of disease by focusing on genetic variation. Another important factor related to disease is the environment. But it is much harder to quantify environmental factors than to determine the genetic differences between two individuals. Using the intermediate molecular data, or biological omics, we can gain insights into the environment of individuals. The environment surrounding individuals can, for instance, influence the composition of their microbiome, but also their gene expression, DNA-methylation and protein levels. By studying the differences in these biological omics in relation to phenotypes and disease, we can learn more about the environmental factors that lead to disease. However, as with GWAS studies, we do not always know what the differences in these biological data layers mean.In this thesis we have focused on two biological omics, the gut microbiome composition and the DNA-methylome. The gut microbiome is the collection of micro-organisms that live together in the human gut; DNA-methylation is the occurrence of a methyl group bound to the DNA and this mainly occurs at cysteine-guanine pairs. In the first part of the thesis we have focused on inter-individual differences influencing, or influenced by, differences in the microbiome composition, while in the second part, we have focused on changes in DNA-methylation associated to tissue differences and on the influence of genetic variation on DNA-methylation
The interplay between genetics, the microbiome, DNA‐methylation & gene‐expression
Full text linkThere are many factors involved in the development of human diseases and traits. In recent years the field of human genetics has been very successful in linking genetic variation to diseases and traits. By conducting large-scale studies comparing the genetic make-up of affected versus non-affected participants, we have identified thousands of variants in the human genome that are more or less commonly found in cases compared to controls. These genome-wide association studies (GWAS) have been instrumental in the identification of genes linked to a multitude of diseases and traits. Variants in the functional parts of a gene can be relatively straightforward to interpret. However, not all the variants linked to disease can be directly interpreted. By using intermediate molecular data layers, such as gene expression, DNA-methylation or protein levels, we can gain more insight into the genetic variants identified by GWAS.However, we only get a limited picture of disease by focusing on genetic variation. Another important factor related to disease is the environment. But it is much harder to quantify environmental factors than to determine the genetic differences between two individuals. Using the intermediate molecular data, or biological omics, we can gain insights into the environment of individuals. The environment surrounding individuals can, for instance, influence the composition of their microbiome, but also their gene expression, DNA-methylation and protein levels. By studying the differences in these biological omics in relation to phenotypes and disease, we can learn more about the environmental factors that lead to disease. However, as with GWAS studies, we do not always know what the differences in these biological data layers mean.In this thesis we have focused on two biological omics, the gut microbiome composition and the DNA-methylome. The gut microbiome is the collection of micro-organisms that live together in the human gut; DNA-methylation is the occurrence of a methyl group bound to the DNA and this mainly occurs at cysteine-guanine pairs. In the first part of the thesis we have focused on inter-individual differences influencing, or influenced by, differences in the microbiome composition, while in the second part, we have focused on changes in DNA-methylation associated to tissue differences and on the influence of genetic variation on DNA-methylation
The interplay between genetics, the microbiome, DNA‐methylation & gene‐expression
Full text linkThere are many factors involved in the development of human diseases and traits. In recent years the field of human genetics has been very successful in linking genetic variation to diseases and traits. By conducting large-scale studies comparing the genetic make-up of affected versus non-affected participants, we have identified thousands of variants in the human genome that are more or less commonly found in cases compared to controls. These genome-wide association studies (GWAS) have been instrumental in the identification of genes linked to a multitude of diseases and traits. Variants in the functional parts of a gene can be relatively straightforward to interpret. However, not all the variants linked to disease can be directly interpreted. By using intermediate molecular data layers, such as gene expression, DNA-methylation or protein levels, we can gain more insight into the genetic variants identified by GWAS.However, we only get a limited picture of disease by focusing on genetic variation. Another important factor related to disease is the environment. But it is much harder to quantify environmental factors than to determine the genetic differences between two individuals. Using the intermediate molecular data, or biological omics, we can gain insights into the environment of individuals. The environment surrounding individuals can, for instance, influence the composition of their microbiome, but also their gene expression, DNA-methylation and protein levels. By studying the differences in these biological omics in relation to phenotypes and disease, we can learn more about the environmental factors that lead to disease. However, as with GWAS studies, we do not always know what the differences in these biological data layers mean.In this thesis we have focused on two biological omics, the gut microbiome composition and the DNA-methylome. The gut microbiome is the collection of micro-organisms that live together in the human gut; DNA-methylation is the occurrence of a methyl group bound to the DNA and this mainly occurs at cysteine-guanine pairs. In the first part of the thesis we have focused on inter-individual differences influencing, or influenced by, differences in the microbiome composition, while in the second part, we have focused on changes in DNA-methylation associated to tissue differences and on the influence of genetic variation on DNA-methylation
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
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