Institution
Vertex Pharmaceuticals
Company•Boston, Massachusetts, United States•
About: Vertex Pharmaceuticals is a company organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Ivacaftor & Protease. The organization has 2135 authors who have published 2022 publications receiving 134750 citations. The organization is also known as: Vertex Pharmaceuticals Inc. & Vertex.
Topics: Ivacaftor, Protease, Hepatitis C virus, Telaprevir, Population
Papers published on a yearly basis
Papers
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TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
12,661 citations
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Harvard University1, Broad Institute2, Boston Children's Hospital3, University of Washington4, University of Arizona5, Cardiff University6, Google7, Icahn School of Medicine at Mount Sinai8, Samsung Medical Center9, Vertex Pharmaceuticals10, University of Michigan11, University of Cambridge12, State University of New York Upstate Medical University13, Karolinska Institutet14, University of Eastern Finland15, University of Oxford16, Wellcome Trust Centre for Human Genetics17, Cedars-Sinai Medical Center18, University of Ottawa19, University of Pennsylvania20, University of North Carolina at Chapel Hill21, University of Helsinki22, University of California, San Diego23, University of Mississippi Medical Center24
TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.
8,758 citations
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TL;DR: The development, current features, and some directions for future development of the AMBER package of computer programs are described, embodying a number of the powerful tools of modern computational chemistry-molecular dynamics and free energy calculations.
2,953 citations
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TL;DR: A committee of several scientists who have been involved in the identification and characterization of these enzymes have formed a committee, with the objective of proposing a nomenclature for the human members of this protease family that is sensible and easy to use.
2,451 citations
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TL;DR: It is shown that lipid accumulation in the liver leads to subacute hepatic 'inflammation' through NF-κB activation and downstream cytokine production, which causes insulin resistance both locally in liver and systemically.
Abstract: We show that NF-κB and transcriptional targets are activated in liver by obesity and high-fat diet (HFD). We have matched this state of chronic, subacute 'inflammation' by low-level activation of NF-κB in the liver of transgenic mice, designated LIKK, by selectively expressing constitutively active IKK-b in hepatocytes. These mice exhibit a type 2 diabetes phenotype, characterized by hyperglycemia, profound hepatic insulin resistance, and moderate systemic insulin resistance, including effects in muscle. The hepatic production of proinflammatory cytokines, including IL-6, IL-1β and TNF-α, was increased in LIKK mice to a similar extent as induced by HFD in in wild-type mice. Parallel increases were observed in cytokine signaling in liver and mucscle of LIKK mice. Insulin resistance was improved by systemic neutralization of IL-6 or salicylate inhibition of IKK-β. Hepatic expression of the IκBα superrepressor (LISR) reversed the phenotype of both LIKK mice and wild-type mice fed an HFD. These findings indicate that lipid accumulation in the liver leads to subacute hepatic 'inflammation' through NF-κB activation and downstream cytokine production. This causes insulin resistance both locally in liver and systemically.
2,082 citations
Authors
Showing all 2137 results
Name | H-index | Papers | Citations |
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David Altshuler | 162 | 345 | 201782 |
Richard J. Johnson | 137 | 880 | 72201 |
Gerhard Wagner | 116 | 589 | 50309 |
Paul I.W. de Bakker | 107 | 257 | 95323 |
Peter R. Mueller | 97 | 613 | 34457 |
Annamaria Vezzani | 85 | 285 | 26008 |
Mark D. Fleming | 81 | 433 | 36107 |
Santosh Kumar | 80 | 1196 | 29391 |
Thomas Helleday | 76 | 303 | 27757 |
Nicola J. Curtin | 68 | 228 | 18255 |
Susan J. Little | 62 | 276 | 17986 |
Jeremy S. Duffield | 58 | 124 | 16037 |
Edmund V. Capparelli | 54 | 281 | 10747 |
Roy A. Black | 54 | 99 | 16878 |
Murcko Mark A | 53 | 130 | 14347 |