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Ben Weisburd

Researcher at Broad Institute

Publications -  43
Citations -  19166

Ben Weisburd is an academic researcher from Broad Institute. The author has contributed to research in topics: Gene & Exome. The author has an hindex of 16, co-authored 35 publications receiving 14285 citations. Previous affiliations of Ben Weisburd include Massachusetts Institute of Technology & University of California, San Francisco.

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Analysis of protein-coding genetic variation in 60,706 humans

Monkol Lek, +106 more
- 18 Aug 2016 - 
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.
Journal ArticleDOI

The mutational constraint spectrum quantified from variation in 141,456 humans

TL;DR: A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes.
Posted ContentDOI

Analysis of protein-coding genetic variation in 60,706 humans

Monkol Lek, +72 more
- 30 Oct 2015 - 
TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
Posted ContentDOI

Variation across 141,456 human exomes and genomes reveals the spectrum of loss-of-function intolerance across human protein-coding genes

Konrad J. Karczewski, +95 more
- 30 Jan 2019 - 
TL;DR: Using an improved human mutation rate model, human protein-coding genes are classified along a spectrum representing tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.
Journal ArticleDOI

Decoding Human Cytomegalovirus

TL;DR: The results reveal an unanticipated complexity to the HCMV coding capacity and illustrate the role of regulated changes in transcript start sites in generating this complexity.