Uncertainty quantification in variable selection for genetic fine-mapping using bayesian neural networks-Reference-Cited by-同舟云学术

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Uncertainty quantification in variable selection for genetic fine-mapping using bayesian neural networks

Published:2022-07 Issue:7 Volume:25 Page:104553
ISSN:2589-0042
Container-title:iScience
language:en
Short-container-title:iScience

Author:

Cheng Wei^ORCID,Ramachandran Sohini,Crawford Lorin

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference50 articles.

1. Universal approximation bounds for superpositions of a sigmoidal function;Barron;IEEE Trans. Inf. Theor.,1993

2. Finemap: efficient variable selection using summary data from genome-wide association studies;Benner;Bioinformatics,2016

3. The UK biobank resource with deep phenotyping and genomic data;Bycroft;Nature,2018

4. Scalable variational inference for bayesian variable selection in regression, and its accuracy in genetic association studies;Carbonetto;Bayesian Anal.,2012

5. Nonlinear variable selection via deep neural networks;Chen;J. Comput. Graph. Stat.,2021

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