Research in our lab is focused on developing computational methods for the discovery and analysis of human genetic variation using high-throughput sequencing technologies. We develop algorithms and software tools for accurate and comprehensive assembly of human genomes and identifying disease associated variants.
Comparative and Population Genomics
The Viral Evolution Group (located near the UCSD hospital in Hillcrest) studies computational and statistical models of evolution, with applications to viral pathogens and other systems. Solid programming skills and knowledge of probabilistic modeling (e.g. as covered in CSE250A and CSE250B) are required. There is no wet lab component.
Our laboratory is interested in how rare and de novo mutations in the human genome contribute to patterns of genetic variation and risk for disease in humans. To this end, we are developing novel approaches to gene discovery that are based on advanced technologies for the detection of rare variants, including studies of copy number variation (CNV) and deep whole genome sequencing (WGS). Our goal is to identify genes related to psychiatric disorders and determine how genetic variants impact the function of genes and corresponding cellular pathways.
We have a wide scope of projects ranging from developing novel algorithms for studying RNA processing in diseases, development and personalized medicine, and for analyzing single-cell RNA-seq data.
The Richman Laboratory is a translational HIV research laboratory that uses basic science techniques to answer clinically relevant questions. These laboratory techniques include a wide range and combination of wet lab and computational methods. Prospective students will have exposure to aspects of both wet laboratory and computational investigation. They will also have exposure to clinical aspects of HIV disease to place their research into clinical perspective. Currently available projects include:
Our lab is interested in how the human brain is assembled. We use genetic strategies to explore causes of human disease and then link these genes to function using model systems. We are focused on diseases like mental retardation, epilepsy and autism, where brain development is disrupted. We have two full time bioinformatics (graduate student and staff programmer) developing computational solutions, database design and machine learning paradigms for large datasets in the area of genome sequencing.