Research Interest: Bioinformatics
| Name | PhD Program | Research Interest | Publications |
|---|---|---|
| Love, Michael WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
The Love Lab uses statistical models to infer biologically meaningful patterns in high-dimensional datasets, and develops open-source statistical software for the Bioconductor Project. At UNC-Chapel Hill, we often collaborate with groups in the Genetics Department and the Lineberger Comprehensive Cancer Center, studying how genetic variants relevant to diseases are associated with changes in molecular and cellular phenotypes. |
| Rubinsteyn, Alex WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
I work on predicting the determinants of adaptive immune responses. Most of my work has focused on T-cell epitope prediction for mutant antigens derived from cancer. I have collaborated closely with clinical groups to translate this work in personalized cancer vaccine trials. More recently I have also been working on joint T-cell and B-cell prediction for viral pathogens. The technologies and techniques applied across all of my projects are at the intersection of computational immunology, genomics, and machine learning. |
| Wirka, Robert WEBSITE |
PHD PROGRAM RESEARCH INTEREST |
Our lab uses human genetics to identify new mechanisms driving coronary artery disease (CAD). Starting with findings from genome-wide association studies (GWAS) of CAD, we identify the causal gene at a given locus, study the effect of this gene on cellular and vessel wall biology, and finally determine the molecular pathways by which this gene influences CAD risk. Within this framework, we use complex genetic mouse models and human vascular samples, single-cell transcriptomics/epigenomics and high-throughput CRISPR perturbations, as well as traditional molecular biology techniques. |
| Rau, Christoph WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Heart failure is an increasingly prevalent cause of death world-wide, but the genetic and epigenetic underpinnings of this disease remain poorly understood. Our laboratory is interested in combining in vitro, in vivo and computational techniques to identify novel markers and predictors of a failing heart. In particular, we leverage mouse populations to perform systems-level analyses with a focus on co-expression network modeling and DNA methylation, following up in primary cell culture and CRISPR-engineered mouse lines to validate our candidate genes and identify potential molecular mechanisms of disease progression and amelioration. |
| Raab, Jesse WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
We are interested in the links between epigenetics and gene regulation. Our primary focus is on understanding how changes to the composition of chromatin remodeling complexes are regulated, how their disruption affects their function, and contributes to disease. We focus on the SWI/SNF complex, which is mutated in 20% of all human tumors. This complex contains many variable subunits that can be assembled in combination to yield thousands of biochemically distinct complexes. We use a variety of computational and wet-lab techniques in cell culture and animal models to address these questions. |
| Nguyen, Juliane WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
The Nguyen lab develops the next generation of effective and safe biotherapeutics for life-threatening diseases such as cancer and myocardial infarction. We engineer novel immunomodulatory carriers based on genetically encoded materials and lipids that home to the site of disease, respond to changes in the microenvironment, and effectively deliver nucleic acids and drugs. |
| Azcarate-Peril, M. Andrea WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
We are interested in determining the mechanisms involved in the beneficial modulation of the gut microbiota by prebiotics (functional foods that stimulate growth of gut native beneficial bacteria) and probiotics (live bacteria that benefit their host). Specifically, we aim to develop prebiotic and probiotic interventions as alternatives to traditional treatments for microbiota-health related conditions, and to advance microbiota-based health surveillance methods. |
| Vincent, Benjamin WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
The Vincent laboratory focuses on immunogenomics and systems approaches to understanding tumor immunobiology, with the goal of developing clinically relevant insights and new cancer immunotherapies. Our mission is to make discoveries that help cancer patients live longer and better lives, focusing on research areas where we feel our work will lead to cures. Our core values are scientific integrity, continual growth, communication, resource stewardship, and mutual respect. |
| Won, Hyejung WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
We try to bridge the gap between genetic risk factors for psychiatric illnesses and neurobiological mechanisms by decoding the regulatory relationships of the non-coding genome. In particular, we implement Hi-C, a genome-wide chromosome conformation capture technique to identify the folding principle of the genome in human brain. We then leverage this information to identify the functional impacts of the common variants associated with neuropsychiatric disorders. |
| Griffith, Boyce WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
My group develops and deploys computational tools to predict physiological function and dysfunction. We are interested in a range of applications in medicine and biology, but our primary focus is the cardiovascular system. My group is actively developing fluid-structure interaction (FSI) models of the heart, arteries, and veins, and of cardiovascular medical devices, including bioprosthetic heart valves, ventricular assist devices, and inferior vena cava filters. We are also validating these models using in vitro and in vivo approaches. We also model cardiac electrophysiology and electro-mechanical coupling, with a focus on atrial fibrillation (AF), and aim to develop mechanistically detailed descriptions of thrombosis in AF. This work is carried out in collaboration with clinicians, engineers, computer and computational scientists, and mathematical scientists in academia, industry, and regulatory agencies. |