Mother-Infant Multi-omics Study
Multiple projects available with longitudinal data ready to be analyzed including metagenomic, transcriptomic, and proteomic data associated with clinical and immunologic profiles from human studies.
Multiple projects available with longitudinal data ready to be analyzed including metagenomic, transcriptomic, and proteomic data associated with clinical and immunologic profiles from human studies.
Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition influenced by both genetic and environmental factors. While rare and common genetic variants have identified over 250 ASD-associated genes and copy number variants (CNVs), the mechanisms through which environmental exposures modify genetic susceptibility remain poorly understood. A major barrier to progress has been insufficient sample size to rigorously investigate gene-environment interactions (G×E). To address this gap, we are applying novel data analytic approaches to genetic and exposure data in large biobank cohorts. This project we will investigate prenatal exposures and early-life environmental factors in one of our deeply phenotyped cohorts (ABCD, HBCD and MoBa) with genome-wide genetic data, neurodevelopmental assesments.
This project is applying integrative approaches, combining genetic association data in autism with detailed functional information on gene networks and cell-type and spatial expression of genes to define specific dimensions of phenotype and function within the autism spectrum
Hypothesis that chromatin's contribution to nuclear mechanics enables the inference of expressed genes.
- investigate morphological pathways in the transition from monomorphonuclear to polymorphonuclear cells during differentiation using data-driven and biophysical models
- connect morphological pathways to gene expression profiles
B.A., Computational Biology, Swarthmore College, 2025
2025-26 Trainee on NIH Training Grant in Bioinformatics
B.S., Bioinformatics, University of California, San Diego, 2024
B.S., Computational & Systems Biology, University of California Los Angeles, 2025
2025-28 Trainee on National Library of Medicine (NLM) Training Grant Fellowship Program
B.S., Bioengineering: Bioinformatics, University of California, San Diego, 2025
2025-26 Trainee on NIH Training Grant in Bioinformatics
B.S., Computational and Systems Biology, University of California, Los Angeles, 2023
M.S., Computational Biology and Quantitative Genetics, Harvard University, 2025