Research Interest: Bioinformatics
Name | PhD Program | Research Interest | Publications |
---|---|---|
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. |
Hoadley, Katherine A. WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
My research interest is in genomic characterization and integrative genomic approaches to better understand cancer. My group is part of the NCI Genome Data Analysis Center focused on RNA expression analysis. We have a number of ongoing projects including developing molecular classifications for potential clinical utility, developing methods for deconvolution to understand bulk tissue heterogeneity, analysis of driver negative cancers, and analysis of ancestry markers with cancer features. |
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
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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. |
Gordon-Larsen, Penny WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Gordon-Larsen’s work integrates biology, behavior, and environment to understand, prevent and treat obesity, cardiovascular and cardiometabolic diseases. She works with biomarker, microbiome, metabolome, genetic, weight, diet, and environment data using multilevel modeling and pathway-based analyses. She works with several longitudinal cohorts that span more than 30 years. Most of her work uses data from the US and China. Her research teams include a wide variety of scientists working in areas such as genetics, medicine, bioinformatics, biostatistics, microbiology, nutrition, and epidemiology. |
Gomez, Shawn WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Our primary research is in the area of computational systems biology, with particular interest in the study of biological signaling networks; trying to understand their structure, evolution and dynamics. In collaboration with wet lab experimentalists, we develop and apply computational models, including probabilistic graphical and multivariate methods along with more traditional engineering approaches such as system identification and control theory, to current challenges in molecular biology and medicine. Examples of recent research projects include: prediction of protein interaction networks, multivariate modeling of signal transduction networks, and development of methods for integrating large-scale genomic data sets. |
Dayan, Eran WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Our lab studies brain network connectivity in the healthy brain and in neurological and neuropsychiatric patient populations. We focus on the organizational, dynamical, and computational properties of large-scale brain networks and determine how these properties contribute to human behavior in health and disease. We strive to advance the basic understanding of brain structure and function, while making discoveries that can be translated to clinical practice. |
Carter, Charles WEBSITE PUBLICATIONS |
PHD PROGRAM RESEARCH INTEREST |
Molecular evolution and mechanistic enzymology find powerful synergy in our study of aminoacyl-tRNA synthetases, which translate the genetic code. Class I Tryptophanyl-tRNA Synthetase stores free energy as conformational strain imposed by long-range, interactions on the minimal catalytic domain (MCD) when it binds ATP. We study how this allostery works using X-ray crystallography, bioinformatics, molecular dynamics, enzyme kinetics, and thermodynamics. As coding sequences for class I and II MCDs have significant complementarity, we also pursuing their sense/antisense ancestry. Member of the Molecular & Cellular Biophysics Training Program. |