BEATRICE: Bayesian fine-mapping from summary data using deep variational inference

Authors

Michael C. Schatz (ORCID: https://orcid.org/0000-0002-4118-4446)
Archana Venkataraman (ORCID: https://orcid.org/0000-0003-2653-5591)
Sayan Ghosal (ORCID: https://orcid.org/0000-0002-7525-713X)

Institutions

Boston University (US)
Johns Hopkins University (US)
Chan Zuckerberg Initiative (United States) (US)

Publication Details

Journal: Bioinformatics
Published: 2024-10-01
DOI: https://doi.org/10.1093/bioinformatics/btae590
Citations: 3
Primary Topic: Image Processing and 3D Reconstruction
Type: article
Field-Weighted Citation Impact: 0.75

Funders

National Science Foundation
National Institutes of Health

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article

BEATRICE: Bayesian fine-mapping from summary data using deep variational inference

Michael C. Schatz, Archana Venkataraman, Sayan Ghosal

Oct 1, 2024

3 citations

Bioinformatics

Image Processing and 3D Reconstruction

0.75

article

BEATRICE: Bayesian fine-mapping from summary data using deep variational inference

Michael C. Schatz, Archana Venkataraman, Sayan Ghosal

October 1, 2024article en

3 citations

Abstract

No abstract available for this paper.

BioinformaticsVol. 40(10)

Boston University (US), Johns Hopkins University (US), Chan Zuckerberg Initiative (United States) (US)

National Science Foundation, National Institutes of Health

Openalex Percentile: Top 27%

Image Processing and 3D Reconstruction

0.75

DOI Open Access PDF OpenAlex

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