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NameEmailPhD ProgramResearch InterestPublications
Leiderman, Karin
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Biochemistry & Biophysics, Bioinformatics & Computational Biology

RESEARCH INTEREST
Biophysics, Cardiovascular Biology, Cell Signaling, Computational Biology, Enzymology, Hematology, Pharmacology, Quantitative Biology, Systems Biology

I am a mathematical biologist interested in the biochemical and biophysical aspects of blood clotting and emergent behavior in biological fluid-structure interaction problems. I especially love mathematical modeling, where creativity, biological knowledge, and mathematical insight meet. My goal is to use mathematical and computational modeling as a tool to learn something new about a biological system, not just to simply match model output to experimental data. My research paradigm includes an integration of mathematical and experimental approaches, together with statistical analyses and inference, to determine mechanisms underlying complex biological phenomena. This paradigm culminates in the contextualization of my findings to both the mathematical and biological communities. My research program is focused mainly on studying the influence of biochemical and biophysical mechanisms on blood coagulation, clot formation, and bleeding.

Pyo, Brian

EMAIL

PHD PROGRAM

RESEARCH INTEREST
Pharmacology, Systems Biology, Toxicology

“I am interested in how xenobiotics (drugs, nutrients, environmental contaminants, etc.) positively or negatively affect human health. I’m also interested in developing and utilizing systems biology multi-omics approach to answer these scientific questions.”

McInerney, Katelyn

EMAIL

PHD PROGRAM

RESEARCH INTEREST
Bioinformatics, Genomics, Systems Biology

“I am most interested in what drives variation in human complex traits and diseases. For me, this broadly includes statistical genetics approaches to uncover the environmental, genetic, and gene x environment interactions that contribute to the variability in a disease or trait. I am interested in genomics, statistical, and multi-omics methodologies to both identify the source of this variation as well as how it functions. “

Rosenthal, Adam
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Microbiology & Immunology

RESEARCH INTEREST
Bacteriology, Molecular Biology, Pathogenesis & Infection, Systems Biology

Our lab uses a systems biology approach to study phenotypic heterogeneity in bacteria. We develop tools that quantify single cell bacterial transcription. We then compare dynamic measurements during vegetative growth and infection to identify regulators of gene expression and mechanisms that bacteria use to coordinate community organization. With this data we want to understand the role of heterogeneity and noise in infectious disease.

Superfine, Richard
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Applied Physical Sciences, Biomedical Engineering

RESEARCH INTEREST
Biomaterials, Biophysics, Cell Biology, Computational Biology, Systems Biology

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.

Miller, Brian
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Cell Biology & Physiology, Genetics & Molecular Biology, Microbiology & Immunology

RESEARCH INTEREST
Cancer Biology, Genetics, Immunology, Systems Biology, Translational Medicine

The Miller lab is working to improve the efficacy of immunotherapy to treat cancer. We aim to develop personalized immunotherapy approaches based on a patient’s unique cancer mutations. We have a particular interest in myeloid cells, a poorly understood group of innate immune cells that regulate nearly all aspects of the immune response. Using patient samples, mouse models, single-cell profiling, and functional genomics approaches, we are working to identify novel myeloid-directed therapies that allow us to overcome resistance and successfully treat more patients.

Brunk, Elizabeth
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Bioinformatics & Computational Biology, Chemistry, Pharmacology

RESEARCH INTEREST
Biochemistry, Bioinformatics, Biophysics, Cancer Biology, Computational Biology, Genomics, Pharmacology, Structural Biology, Systems Biology, Translational Medicine

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
EMAIL
PUBLICATIONS

PHD PROGRAM
Bioinformatics & Computational Biology, Genetics & Molecular Biology

RESEARCH INTEREST
Bioinformatics, Computational Biology, Genetics, Genomics, Immunology, Pathogenesis & Infection, Systems Biology, Virology

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.

Hagood, Jim
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Cell Biology & Physiology

RESEARCH INTEREST
Cell Biology, Molecular Biology, Systems Biology, Translational Medicine

I am a Pediatric Pulmonologist. My lab studies cell phenotype regulation in the context of lung fibrosis and lung development. We use in vitro and ex vivo models, mouse models, human tissue, and multi-omic approaches to explore fibroblast phenotypes in the formation of lung alveoli and in the pathologic modeling of lung fibrosis, and explore novel therapies for lung disease.

Possible Rotation Projects:

Markers of mechanotransduction in lung alveolar formation (immunofluorescence, bioinformatics)
Biological aging of the lung (DNA methylation)
Precision cut lung slice culture to model fibrosis and test therapies ex vivo
Fibroblast phenotype regulation in transgenic mice
Fibroblast-epithelial interactions in lung organoids

Rau, Christoph
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Bioinformatics & Computational Biology, Cell Biology & Physiology, Genetics & Molecular Biology, Pathobiology & Translational Science

RESEARCH INTEREST
Bioinformatics, Cardiovascular Biology, Computational Biology, Genetics, Genomics, Molecular Biology, Systems Biology, Translational Medicine

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.