Predicting splicing from primary sequence with deep learning.
Genetics
Both rare and common genetic variants contribute to autism in the Faroe Islands.
Identification and functional analysis of noncoding mutations in autism
The genetic and phenotypic complexity of ASD is thought to, in part, be caused by abnormal gene regulation. Ryan Doan plans to systematically screen for noncoding mutations with the greatest likelihood of impacting gene regulation (i.e., gene promoters, splicing regulators, cis-regulatory elements) using both computational predictions and large-scale functional screening assays. Findings from this project will help to elucidate the mechanistic underpinnings of these ASD risk mutations and provide a functional database for use in the future development of therapeutics.
The NeuroDev study: Phenotypic and genetic characterization of neurodevelopmental disorders in Kenya and South Africa.
Neurodevelopmental disease genes implicated by de novo mutation and copy number variation morbidity.
Inherited and multiple de novo mutations in autism/developmental delay risk genes suggest a multifactorial model.
Genome sequencing identifies multiple deleterious variants in autism patients with more severe phenotypes.
Integrative functional genomic analysis of human brain development and neuropsychiatric risks.
Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder.
A machine-learning approach for accurate detection of copy-number variants from exome sequencing.
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