PROJECT FEED

With a 4-letter code our genomes instruct when, where and to what extent each gene should be expresses. This underlies the acquisition of cellular identify during embryonic development; A cell at a specific position in the embryo, at a specific time in development expresses a subset of genes at precise levels, dictating a distinct repertoire of proteins that shape cellular morphology and behavior. Correspondingly, misregulation of gene expression often underlies developmental disorders. In the lab we work to decode these regulatory instructions from the genome. We use a combination of genome editing (via CRISPR) to alter the DNA and redout the consequences on gene expression during development (in fly embryos) and cellular differentiation (in mammalian cells). We perform live imaging with super regulation microscopy to capture how genome folding facilitate the transfer of regulatory information from one piece of DNA to an often distant target gene and capture gene activity in real-time. We also develop and employ high-throughput functional genomics assays reporting on genome folding and DNA binding events across cell-types and developmental time. We use the experimental data to train and test machine learning models, to predict gene regulation from the DNA sequence. A student in the lab will have the opportunity to partake in these efforts to crack the code that underlies the specification of cell fates. Work will primarily entail molecular cloning to facilitate genome editing, as well as genetic crosses and live imaging to capture gene regulation in action.

LABS's interests are in developing and applying statistical, machine learning, and artificial intelligence (ML/AI) methodologies to “big data” in multi-omics and medical data for aging and diseases such as Alzheimer’s disease. We emphasize utilizing advanced ML/AI techniques and multi-omics data, including MRI, genetics, transcriptomics, and proteomics, to solve clinically relevant problems for precision medicine. The applicant will learn to process medical imaging data (e.g., brain MRI) using AI/ML and related computational tools for this project. All relevant directions can be pursued based on discussions, interests, and expertise.