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NameEmailPhD ProgramResearch InterestPublications
Vision, Todd
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Bioinformatics & Computational Biology, Biology

RESEARCH INTEREST
Bioinformatics, Computational Biology, Evolutionary Biology, Genomics, Plant Biology

Our lab uses computational and molecular tools to study the evolution of genome organization, primarily in the flowering plants. Areas of
investigation include the origin and consequences of differences in gene order within populations and between species, the evolutionary and functional diversification of gene families (phytome.org), and the application of genomics to evolutionary model organisms (mimulusevolution.org).  We also are involved in a number of cyberinfrastructure initiatives through the National Evolutionary Synthesis Center (nescent.org), including work on digital scientific libraries (datadryad.org), open bioinformatic software development (e.g. gmod.org) and the application of semantic web technologies to biological data integration (phenoscape.org).

Weeks, Kevin
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Bioinformatics & Computational Biology, Chemistry, Genetics & Molecular Biology

RESEARCH INTEREST
Biochemistry, Bioinformatics, Biophysics, Chemical Biology, Computational Biology, Drug Discovery, Quantitative Biology, Structural Biology, Virology

One of the most amazing discoveries of recent years has been the profound role of RNA in regulating all areas of biology. Further, the functions of many RNA molecules require that an RNA fold back on itself to create intricately and complexly folded structures. Until recently, however, we had little idea of the broad contributions of RNA structure and function because there simply did not exist rigorous methods for understanding RNA molecules in cells and viruses. The vision of our laboratory is therefore, first, to invent novel chemical microscopes that reveal quantitative structure and function interrelationships for RNA and, second, to apply these RNA technologies to broadly important problems in biology. Mentoring and research in the lab are highly interdisciplinary. Students learn to integrate ideas and concepts spanning chemical and computational biology, and technology development, and extending to practical applications in virology, understanding biological processes in cells, and discovery of small molecule ligands targeted against medically important RNAs. Each student has a distinct project which they drive to an impactful conclusion, but do so as part of the lab team which, collectively, has shown an amazing ability to solve big problems in RNA biology. The overarching goal of mentoring in the lab is to prepare students for long-term leadership roles in science.

Yeh, Jen Jen
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Cell Biology & Physiology, Pharmacology

RESEARCH INTEREST
Bioinformatics, Cancer Biology, Computational Biology, Drug Discovery, Genomics, Molecular Biology, Molecular Medicine, Pharmacology, Translational Medicine

We are a translational cancer research lab. The overall goal of our research is to find therapeutic targets and biomarkers for patients with pancreatic cancer and to translate our results to the clinic. In order to accomplish this, we analyze patient tumors using a combination of genomics and proteomics to study the patient tumor and tumor microenvironment, identify and validate targets using forward and reverse genetic approaches in both patient-derived cell lines and mouse models. At the same time, we evaluate novel therapeutics for promising targets in mouse models in order to better predict clinical response in humans.

Zhang, Qi
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Biochemistry & Biophysics

RESEARCH INTEREST
Biochemistry, Biophysics, Computational Biology, Drug Discovery, Systems Biology

Our laboratory is focusing on developing and applying solution-state NMR methods, together with computational and biochemical approaches, to understand the molecular basis of nucleic acid functions that range from enzymatic catalysis to gene regulation. In particular, we aim to visualize, with atomic resolution, the entire dynamic processes of ribozyme catalysis, riboswitch-based gene regulation, and co-transciptional folding of mRNA. The principles deduced from these studies will provide atomic basis for rational manipulation of RNA catalysis and folding, and for de novo design of small molecules that target specific RNA signals. Research program in the laboratory provides diverse training opportunities in areas of spectroscopy, biophysics, structural biology, computational modeling, and biochemistry.

Calabrese, J. Mauro
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Bioinformatics & Computational Biology, Genetics & Molecular Biology, Pharmacology

RESEARCH INTEREST
Bioinformatics, Cell Biology, Computational Biology, Genetics, Genomics, Molecular Biology, Pharmacology, Stem Cells

Our lab is trying to understand the mechanisms by which long noncoding RNAs orchestrate the epigenetic control of gene expression. Relevant examples of this type of gene regulation occur in the case of X-chromosome inactivation and autosomal imprinting. We specialize in genomics, but rely a combination of techniques —  including genetics, proteomics, and molecular, cell and computational biology — to study these processes in both mouse and human stem and somatic cell systems.

Purvis, Jeremy
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Bioinformatics & Computational Biology, Genetics & Molecular Biology

RESEARCH INTEREST
Cancer Biology, Cell Signaling, Computational Biology, Molecular Biology, Systems Biology

We study the behavior of individual cells with a specific focus on “irreversible” cell fate decisions such as apoptosis, senescence, and differentiation. Why do genetically identical cells choose different fates? How much are these decisions controlled by the cell itself and how much is influenced by its environment? We address these questions using a variety of experimental and computational approaches including time-lapse microscopy, single-molecule imaging, computational modeling, and machine learning. Our ultimate goal is to not only understand how cells make decisions under physiological conditions—but to discover how to manipulate these decisions to treat disease.

Zou, Fei
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Bioinformatics & Computational Biology

RESEARCH INTEREST
Computational Biology, Genetics, Genomics

My research has been concentrated on the areas of statistical genetics and genomics to investigate the role of genetic variations on complex quantitative traits and diseases. I work primarily in the development, as well as the examination of statistical properties, of theoretical methodologies appropriate for the interpretation of genetic data.

Dowen, Jill
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Biochemistry & Biophysics, Bioinformatics & Computational Biology, Biology, Genetics & Molecular Biology

RESEARCH INTEREST
Bioinformatics, Cancer Biology, Computational Biology, Genomics, Molecular Biology

My lab studies how genes function within the three-dimensional context of the nucleus to control development and prevent disease. We combine genomic approaches (ChIP-Seq, ChIA-PET) and genome editing tools (CRISPR) to study the epigenetic mechanisms by which transcriptional regulatory elements control gene expression in embryonic stem cells.  Our current research efforts are divided into 3 areas: 1) Mapping the folding pattern of the genome 2) Dynamics of three-dimensional genome organization as cells differentiate and 3) Functional analysis of altered chromosome structure in cancer and other diseases.

Stein, Jason
WEBSITE
EMAIL
PUBLICATIONS

PHD PROGRAM
Bioinformatics & Computational Biology, Neuroscience

RESEARCH INTEREST
Bioinformatics, Computational Biology, Developmental Biology, Genomics, Neurobiology

We are a lab exploring how variations in the genome change the structure and development of the brain, and in doing so, create risk for neuropsychiatric illness. We study genetic effects on multiple aspects of the human brain, from macroscale phenotypes like gross human brain structure measured with MRI to molecular phenotypes like gene expression and chromatin accessibility measured with genome-sequencing technologies. We also use neural progenitor cells as a modifiable and high fidelity model system to understand how disease-associated variants affect brain development.