B. Elsworth
Genetics · 2016–2020
A researcher in the Science corpus: 4 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Genetics — 124 citations into it
Whom B. Elsworth trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- George Davey Smith
- Gibran Hemani
- Peter M. Visscher
- Yun Li
- Shah Ebrahim
- Jian Yang
- Brendan K. Bulik-Sullivan
- J. Bowden
- Stephen Burgess
- Frank Dudbridge
Papers from B. Elsworth's perspective
Ordered by how strongly the researchers B. Elsworth trusts endorse each paper. Same corpus, a different order for every researcher.
- 10 Years of GWAS Discovery: Biology, Function, and Translation. (American Journal of Human Genetics)
- FINEMAP: efficient variable selection using summary data from genome-wide association studies (bioRxiv)
- Detection and interpretation of shared genetic influences on 42 human traits (Nature Genetics)
- The support of human genetic evidence for approved drug indications (Nature Genetics)
- Power and Predictive Accuracy of Polygenic Risk Scores (PLoS Genetics)
- Overcoming the winner's curse: estimating penetrance parameters from case-control data.
- Genome-wide genetic data on ~500,000 UK Biobank participants (bioRxiv)
- Efficient Design for Mendelian Randomization Studies: Subsample and 2-Sample Instrumental Variable Estimators (American Journal of Epidemiology)
- Major Lipids, Apolipoproteins, and Risk of Vascular Disease
- Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator (Genetic Epidemiology)
Their papers
- The MRC IEU OpenGWAS data infrastructure (2020) — 798 citations
- Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases (2019) — 633 citations
- The MR-Base platform supports systematic causal inference across the human phenome (2018) — 6,483 citations
- LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis (2016) — 890 citations