Research Interest: Computational Biology
| Name | PhD Program | Research Interest | Publications |
|---|---|---|
| Johri, Parul WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Our research interests broadly span population genetics, statistical inference, and evolutionary genomics. We are interested in how evolutionary processes like changes in population size, recombination, mutation, selection and factors such as genome architecture shape patterns of genomic variation. Work in the lab involves employing computational and theoretical approaches, statistical method development, or using an empirical approach to perform evolutionary inference and ask fundamental questions in population genetics. |
| Wang, Jeremy WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Our research focuses on long-read (single-molecule) sequencing and informatics. We develop novel methods to enable more efficient *omic analysis and apply carefully architected high-performance computing approaches to improve the utility of genomics in studies of human diseases, including infectious disease, cancer, and GI. Ongoing work includes genomic epidemiology of SARS-CoV-2, MPXV, and antibiotic resistance; classification of pediatric leukemias and solid tumors in low-resource settings using nanopore transcriptome sequencing; and metagenomics/metataxonomics of mucosa-associated microbiota in inflammatory bowel diseases. |
| Nazockdast, Ehssan WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
We are interested in the physics of soft and squishy materials, especially the organization and mechanics of living cellular materials. We use theory and simulation in close collaboration with experiments to understand the complex structural and mechanical behavior of these systems. These questions and our approach to them are interdisciplinary and intersect several traditional fields, including cell biology, biophysics, fluid dynamics and applied mathematics. |
| Superfine, Richard WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Superfine’s group studies stimulus-responsive active and living materials from the scale of individual molecules to physiological tissues, including DNA, cells and microfluidic-based tissue models. We develop new techniques using advanced optical, scanning probe, and magnetic force microscopy. We pursue diverse physiological phenomena from cancer to immunology to mucus clearance in the lung. Our work includes developing systems that mimic biology, most recently in the form of engineered cilia arrays that mimic lung tissue while providing unique solutions in biomedical devices. |
| Brunk, Elizabeth WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
A growing body of work in the biomedical sciences generates and analyzes omics data; our lab’s work contributes to these efforts by focusing on the integration of different omics data types to bring mechanistic insights to the multi-scale nature of cellular processes. The focus of our research is on developing systems genomics approaches to study the impact of genomic variation on genome function. We have used this focus to study genetic and molecular variation in both natural and engineered cellular systems and approach these topics through the lens of computational biology, machine learning and advanced omics data integration. More specifically, we create methods to reveal functional relationships across genomics, transcriptomics, ribosome profiling, proteomics, structural genomics, metabolomics and phenotype variability data. Our integrative omics methods improve understanding of how cells achieve regulation at multiple scales of complexity and link to genetic and molecular variants that influence these processes. Ultimately, the goal of our research is advancing the analysis of high-throughput omics technologies to empower patient care and clinical trial selections. To this end, we are developing integrative methods to improve mutation panels by selecting more informative genetic and molecular biomarkers that match disease relevance. |
| Ferris, Marty WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
In the Ferris lab, we use genetically diverse mouse strains to better understand the role of genetic variation in immune responses to a variety of insults. We then study these variants mechanistically. We also develop genetic and genomic datasets and resources to better identify genetic features associated with these immunological differences. |
| 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. |
| 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. |
| Milner, Justin WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
The overall focus of our lab is to develop new and exciting approaches for enhancing the efficacy of cancer immunotherapies. We utilize cutting-edge techniques to identify transcriptional and epigenetic regulators controlling T cell differentiation and function in the tumor microenvironment, and we seek to leverage this insight to reprogram or tailor the activity of T cells in cancer. Our group is also interested in understanding how to harness or manipulate T cell function to improve vaccines and immunotherapies for acute and chronic infections. |