Genetics of gene expression and its effect on disease
By V. Emilsson, G. Thorleifsson, Bin Zhang, A. Leonardson, Florian Zink, Jun Zhu, Sonia Carlson, Agnar Helgason, G. Bragi Walters, Steinunn Gunnarsdottir and 25 more. Nature, 2008
1,415 citations recorded by the source corpus.
Subfields: Genetics, Molecular Biology, Physiology
View Paper: https://www.semanticscholar.org/paper/d7fe2790a7e05d0ae87bcf0c9a300d933bf15671
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Genetics
- Oliver Stegle
- Gonçalo R. Abecasis
- Mark J. Daly
- Richard Durbin
- Cristen J. Willer
- Yurii S. Aulchenko
- David Altshuler
- Steve Horvath
In Molecular Biology
- Oliver Stegle
- Peter Langfelder
- Steve Horvath
- Eric P. Xing
- Seyoung Kim
- Jeffrey T. Leek
- Stephen B. Montgomery
- P. Calder
In Physiology
Citations in the corpus
- Obesity, Inflammation, Toll-Like Receptor 4 and Fatty Acids (2018, background): “This inflammation is directly involved in the etiology of cardiovascular diseases, DM2, and certain cancer types [28].”
- Molecular networks as sensors and drivers of common human diseases (2009, background): “Second, the SNP–trait associations alone do not necessarily lead directly to the identification of the causal gene(s), much less elucidate the context in which the causal gene(s) operate”
- Computational solutions to large-scale data management and analysis (2010, background): “As a result, we can monitor the expression of tens of thousands of genes simultaneousl”
- Transcriptome genetics using second generation sequencing in a Caucasian population (2010, background): “This is probably due to two reasons: (1) exons capture genetic effects in splicing complexity, which is higher in higher abundance genes (Spearman rank correlation between abundance and number of transcripts in Ensembl, P , 2.”
- Progress and Promise of Genome-Wide Association Studies for Human Complex Trait Genetics (2011, background): “Several studies show that complex traitassociated variants overlap with eQTL variants (e.g., Emilsson et al. 2008; Nica et al. 2010), helping to prioritize a gene and mechanism for functional followup.”
- Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease (2013, background): “…affect the expression levels of a neighboring gene or they are the causal variant themselves, they serve as an excellent source of natural perturbation to infer causal relationships among genes and between genes and higher-order phenotypes like disease (Chen et al., 2008; Emilsson et al., 2008).”
- The cellular and signaling networks linking the immune system and metabolism in disease (2012, background): “Many other genes are associated with insulin resistance, and whole-genome expression signatures have been defined that are enriched in inflammatory gene modules in insulin-resistant mice and human”
- Systems Genetics of Complex Traits in Drosophila melanogaster (2009, background): “This 'systems genetics' approach will yield a detailed map of genetic variants associated with each organismal phenotype in each environment, provide a functional context for interpreting the phenotypes, elucidate the genetic underpinnings that govern the interdependence of multiple phenotypes, and ”
- Trait-Associated SNPs Are More Likely to Be eQTLs: Annotation to Enhance Discovery from GWAS (2010, background): “studies have highlighted the potential sensitivity of eQTL studies to cell and tissue subtypes [15,19,20].”
- Mapping the Genetic Architecture of Gene Expression in Human Liver (2008, methodology): “Several recent studies have been published that examine the extent of genetic control in blood [20–22], brain [23], and adipose [21] gene expression via genetic association testing.”
- Systems medicine: the future of medical genomics and healthcare (2009, background): “Taking advantage of expression-profiling surveys performed in extended human populations [171-174], systems biologists have started integrating physiopathology, network biology and DNA variations [175-177], providing novel insights into the mechanisms of various diseases, such as diabetes [178] and ”