Comparative and Population Genomics

Amit Majithia

Faculty Status
Active
Title
Assistant Professor
Email
amajithia@ucsd.edu
Phone
(858) 822-0727
Track(s)
Bioinformatics and Systems Biology
Department
Brief Research Description
Insulin resistance, functional genomics, pharmacogenetics, cardiometabolic disease, diabetes
Lab Description

Our goal is to identify genes causing insulin resistance in humans in order to find new therapeutic targets for diabetes and cardiometabolic diseases. Our approach to discovery is grounded in human genetics, clarified through systematic, high throughput experimentation in human cells, and calibrated by its relevance to clinical disease. We use massively parallel genome engineering to re-create mutations identified in patients and develop high-throughput assays to interrogate function in human cell models. We apply bioinformatics and statistics to make sense of this data integrating 1) human mutations, 2) cellular function, and 3) metabolic/glycemic phenotypes of the individuals who harbor them. Using this approach, we have discovered novel missense mutations that greatly increase risk for type 2 diabetes. As a complementary aim towards precision medicine, we develop tools for clinical genome interpretation powered by high-throughput experimental data.

Elizabeth Winzeler

Faculty Status
Active
Title
Professor
Email
ewinzeler@ucsd.edu
Phone
(858) 822-3339
Track(s)
Bioinformatics and Systems Biology
Department
Brief Research Description
My laboratory uses big data approaches to solve problems in global health. The lab also offers training in cheminformatics and chemical genomics.

Melissa Gymrek

Faculty Status
Active
Title
Assistant Professor
Title 2
Assistant Professor
Email
mgymrek@ucsd.edu
Phone
(858) 822-2496
Track(s)
Bioinformatics and Systems Biology
Department 2
BISB Research Area(s)
Brief Research Description
Contribution of complex genetic variation to human phenotypes
Lab Description

Our overall goal is to understand complex genetic variants that underlie human disease. We are particularly interested in repetitive DNA variants known as short tandem repeats (STRs) as a model for complex variation. Our work focuses on developing computational tools for analyzing and visualizing complex variation from large-scale sequencing data and applying these tools to learn about the contribution of repetitive variation to human disease.

Rob Knight

Faculty Status
Active
Title
Professor
Title 2
Affiliate Faculty
Email
rknight@ucsd.edu
Track(s)
Bioinformatics and Systems Biology
Department
BISB Research Area(s)
Brief Research Description
Human microbiome, microbial community ecology, multi-omics analyses
Lab Description

The Knight lab has broad interests in the human microbiome, the collection of trillions of microbes that inhabits our bodies, especially in developing techniques to read out these complex microbial communities and use the resulting data to understand human health, links between humans and the environment, and to prevent and cure disease. We offer a fast-paced environment with many collaborative opportunities on different projects.

Graham McVicker

Faculty Status
Active
Title
Assistant Professor
Email
gmcvicker@salk.edu
Phone
(858) 453-4100
Track(s)
Bioinformatics and Systems Biology
Brief Research Description
Human genetic variation, chromatin and gene regulation in immune cells
Lab Description

The McVicker laboratory aims to understand how chromatin state and organization are encoded by the human genome. Our approach to this problem is to exploit naturally occurring human genetic variation to identify sequence variants that disrupt chromatin function. We are currently focused on chromatin within immune cells and we are also interested in how variants that affect chromatin and gene regulation lead to disease risk. The problems that we work on often require the development of sophisticated computational and statistical methods that can extract subtle signals from noisy experimental data.

Vikas Bansal

Faculty Status
Active
Title
Assistant Professor
Email
vibansal@ucsd.edu
Phone
(858) 246-1810
Track(s)
Bioinformatics and Systems Biology
Department
Brief Research Description
Computational tools for variant calling, haplotyping and analysis of rare variants in disease association studies
Lab Description

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.

Konrad Scheffler

Faculty Status
Inactive
Title
Associate Professor
Email
kscheffler@ucsd.edu
Phone
(619) 543-6347
Track(s)
Bioinformatics and Systems Biology
Department
Brief Research Description
Probabilistic models of molecular evolution
Lab Description

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.

Jonathan Sebat

Faculty Status
Active
Title
Chief, Beyster Center for Molecular Genomics of Neuropsychiatric Diseases; Associate Professor of Psychiatry and Cellular & Molecular Medicine
Email
jsebat@ucsd.edu
Phone
(858)534-6526
Track(s)
Bioinformatics and Systems Biology
Brief Research Description
Genome informatics, psychiatric genetics, copy number variation (CNV), de novo mutation
Lab Description

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.

Nicholas Schork

Faculty Status
Active
Title
Professor
Email
nschork@scripps.edu
Phone
(858) 554-5704
Track(s)
Bioinformatics and Systems Biology
Brief Research Description
Developing mathematical, statistical, and computational models and tools to study the genetic basis of complex traits and diseases