Allan Bayat

The paper introduces the LMSz method to construct gene-specific growth charts for rare disorders using z-scores, showing gene-specific centiles and trends in anthropometric data.

This study explores the lived experiences of 91 adults with KBG syndrome, revealing high rates of comorbidities and challenges in adulthood.

The paper describes three patients with AGAP1 deletion variants and uses a Drosophila model to identify endolysosomal trafficking defects and stress response abnormalities linked to neurodevelopmental disorders.

The paper shows that an OGT variant causes reduced pluripotent stem cell self-renewal and lower stem cell marker levels in mouse embryonic stem cells.

The paper reports a cohort of 17 patients with pathogenic KCNH5 variants causing neurodevelopmental disorders and epilepsy, identifying genotype-phenotype correlations.

The paper reclassifies DYRK1A variants using an integrative approach, showing some previously reported pathogenic variants do not cause obvious phenotypes.

The paper introduces an AI-driven method that uses facial images to prioritize exome data, achieving 99% top-10 accuracy in identifying disease-causing genes.

The paper evaluates clinical features, flow cytometry, and facial image analysis to classify GPIBDs and identify gene-specific patterns, finding that facial recognition software is most effective for gene prediction.