PhD Program: Bioinformatics & Computational Biology
| Name | PhD Program | Research Interest | Publications |
|---|---|---|
| Zannas, Anthony WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Psychosocial stress is abundant in modern societies and, when chronic or excessive, can have detrimental effects on our bodies. But how exactly does stress “get under the skin?” Our lab examines how stress shapes the human epigenome as age advances. Epigenetic changes are a set of chemical modifications that regulate gene transcription without altering the genetic code itself. We examine how lasting epigenetic patterns result from stressful experiences, accrue throughout life, and can in turn shape health or disease trajectories. We address these questions through a translational approach that combines large-scale analyses in human cohorts with mechanistic work in cellular models. We use both bioinformatics and wet lab tools. Our passion is to promote creative team work, offer strong mentorship, and foster scientific growth. |
| 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. |
| Dominguez, Daniel WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
The Dominguez lab studies how gene expression is controlled by proteins that bind RNA. RNA binding proteins control the way RNAs are transcribed, spliced, polyadenylated, exported, degraded, and translated. Areas of research include: (1) Altered RNA-protein interactions in cancer; (2) RNA binding by noncanonical domains; and (3) Cell signaling and RNA processing. |
| 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. |
| Schrider, Daniel WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
The Schrider Lab develops and applies computational tools to use population genetic datasets to make inferences about evolutionary history. Our research areas include but are not limited to: characterizing the effects natural selection on genetic variation within species, identifying genes responsible for recent adaptation, detecting genomic copy number variants and other weird types of mutations, and adapting machine learning tools for application to questions in population genetics and evolution. Study organisms include humans, the fruit fly Drosophila melanogaster and its relatives, and the malaria vector mosquito Anopheles gambiae. |
| Jiang, Yuchao WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Dr Jiang’s primary research interests lie in statistical modeling, method development and data analysis in genetics and genomics. His current research is focused on developing statistical methods and computational algorithms to better utilize and analyze different types of next-generation sequencing data under various setting, with application to data from large-scale cohort studies of human health and disease. Special focus is on single-cell transcriptomics, single-cell epigenomics, cancer genomics, tumor phylogeny, data normalization, and copy number variation detection. |
| Ward-Caviness, Cavin WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
We are actively engaged in multiple research arenas centered around understanding the associations between environmental exposures (primarily air pollution) and health outcomes. We use large clinical cohorts and electronic health records to understand associations between air pollution and health outcomes such as cardiovascular disease, metabolic disease, and aging. We use metabolomics and epigenetic data (primarily DNA methylation) to investigate molecular mechanisms, and highlight the integration of ‘omics data in a systems biology framework to better understand dysregulated pathways. Finally, we have projects centered around methods development and causal analyses to improve our understanding of the biology central to environmental health effects. |
| Liu, Yufeng WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Statistical machine learning and data mining, nonparametric statistics and functional estimation, bioinformatics, design and analysis of experiments
|
| Wu, Di WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Our group develops novel statistical bioinformatics tools and applies them in biomedical research to help understanding the precision medicine for cancer (e.g., breast cancer and lung cancer) subtypes, the disease associated integrative pathways across multiple genomic regulatory levels, and the genetics based drug repurposing mechanisms. Our recent focus includes pathway analysis, microbiome data analysis, data integration and electronica medical records (EMR). Our application fields include cancer, stem cell, autoimmune disease and oral biology. In the past, we have developed gene set testing methods with high citations, in the empirical Bayesian framework, to take care of small complex design and genewise correlation structure. These have been widely used in the microarray and RNAseq based gene expression analysis. Contamination detection for data analysis for Target DNA sequencing is work in progress. Recently, we also work on single cell sequencing data for pathway analysis with the local collaborators. |