Work

A machine-learning framework to characterize functional disease architectures and prioritize disease variants

Year: 2025

Type: dataset

Abstract: # 09/17/2026: New Version includes the fine-mapping framework # 06/01/2026: New Version includes V2Dx framework Files to replicate for the analysis of the V2D framework.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17257764

Authors: Cheng, Siliangyu, Gazal, Steven

Institution: University of Southern California

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Institute of General Medical Sciences

Award: Characterizing genetic signatures of natural selection to understand human diseases

OpenAlex ID: W7084605943

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