Jeffrey K. Ng

The paper develops MoDIFI, a Bayesian framework to prioritize cell lines and regulatory regions for testing noncoding variants associated with neurodevelopmental disorders.

This study uses whole-genome sequencing to analyze 9p deletion and duplication syndromes, identifying key genes and structural variants, and introduces a machine learning model for syndrome prediction.

The paper generates a mouse model with a deletion in an enhancer of EBF3, showing reduced Ebf3 expression and sex-specific behavioral and phenotypic differences.

The paper assesses clustering of missense variants in neurodevelopmental disorders and cancer, identifying proteins with significant variation patterns in each condition.

HAT is a workflow for detecting de novo variants from short-read and long-read sequencing data using parent-child trio alignments.

Whole-genome sequencing in thousands of families reveals variants relevant to simplex autism in a brain enhancer of the well-established neurodevelopmental disorder gene EBF3.

ACES is a computational workflow that queries specific sequences against multiple reference genomes to analyze conservation, generating alignment and phylogenetic data.

The paper identifies de novo variants in the 1000 Genomes Project using a GPU-based workflow, revealing cell line artifacts and cancer-related mutation profiles.

This study identifies the role of the Drosophila MLR complex in regulating triglyceride depletion and stress response in fat body adipocytes during non-feeding periods.