Azza Althagafi

PAVS is a database of phenotype-associated variants from Saudi Arabian rare disease patients, enabling gene prioritization through phenotype-based similarity search.

This paper introduces EmbedPVP, a method that prioritizes genomic variants in genetic diseases by integrating genomic data with clinical phenotypes and background knowledge.

The paper evaluates variant prioritization methods for rare disease diagnosis using data from the Rare Genomes Project, finding that top models identify causal variants in most solved families and uncover potential candidates in unsolved ones.

The paper presents a fully annotated reference genome from a Saudi individual using de novo assembly and AI-based annotation, making all data publicly available.

DeepSVP prioritizes pathogenic structural variants by integrating genotype and phenotype data using deep learning, improving benchmark performance and identifying novel variants in consanguineous families.

The paper develops a graph-based machine learning method to predict gene-disease associations using phenotypes, functions, and anatomical expression sites, outperforming existing methods.

VSIM is a web tool for variant interpretation in personal genomes, supporting genetic counseling and premarital screening by simulating children's genomes.