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Search Results for Research Area: "Systems biology"


Faculty Search Results: Results 1 - 20 (List more/fewer results: 10 20 30 40 )
Faculty Member Brief Research Description
Peter Arvan We focus on the molecular mechanisms of protein folding and trafficking in endocrine cells, and diseases of misfolding and mistargeting.   
Scott Barolo Research Interests: Gene regulation and cell signaling in development; Structure, function, and evolution of transcriptional enhancers.   
Daniel Beard Theoretical and experimental analysis of metabolic systems, whole-body cardiovascular mechanics and transport, blood-flow regulation, mechanisms of renal solute transport.  
Michael Boehnke Statistical genetics, complex diseases, and human gene mapping, with application to type 2 diabetes and bipolar disorder  
Charles Burant Using multi 'omics approach, including high throughput metabolomics, we seek to understand the interaction between genetics and nutrients in the development of disease.  
Margit Burmeister Identifying genes involved in behavioral, neurological & psychiatric diseases, novel genetic techniques, gene expression, bioinformatics.  
Dan Burns DNA structure and dynamics; 4D nucleome and dynamics of chromatin related to .  
Sally A. Camper, Ph.D. bioinformatics, cancer, developmental biology, gene expression, genetics of disease, hearing research, hormone action, neuroscience, organogenesis reproductive biology, signaling, skeletal development, stem cell research  
Vern Carruthers Pathogenesis of parasitic infections: Mechanisms of cell invasion, egress and survival during infection  
Greg Cartee Effects of exercise, diet (calorie restriction) or aging on regulation of skeletal muscle glucose transport and insulin signaling  
Christin Carter-Su Obesity; neuronal differentiation and function; signal transduction by receptor tyrosine kinases; JAK-Stat signaling in growth, cancer and metabolism; growth hormone signaling and cellular function; tyrosine kinase adapter proteins; diabetes; cell motility   
Mark Day Our research is focused on prostate and bladder epithelial adhesion and survival and the influence of the microenvironment on these processes and on tumorigenesis in these organs.  
Andrzej Dlugosz Embryonic signaling pathways in cancer initiation, progression, and maintenance  
Mara Duncan The molecular mechanisms of membrane traffic, and how it promotes cell survival during stresses including starvation.  
dan eitzman Molecular mediators of adipose tissue inflammation and effects of inflammatory adipose tissue on vascular endpoints using mouse models  
J.T. Elder Our lab uses genetics, cell biology, and immunology to better understand psoriasis. We are transitioning from a genetic to a functional approach.   
Mohammad Fallahi-Sichani Our research is at the interface of bioengineering, cancer biology and quantitative pharmacology and combines experimental methods and data-driven computational approaches with the goal of understanding oncogenic signaling and therapeutic mechanisms in human tumors.  
Peter Freddolino Combining high-throughput experimental measurements with multiscale modeling to understand and simulate regulatory networks  
Phil Gage Cell fate decisions in neural crest and mesoderm; genetic analysis of mammalian eye development; transcription factors; cell signaling pathways  
Al Hero III We are developing predictive health and diagnostic algorithms for real time prediction and classification of health and disease using high throughput molecular, physiological, and behavioral data. A major axis of our research is to determine temporal immune system pathways and establish a baseline of health from multi-platform data with small sample size. Another major effort is to integrate disparate assay data, validated mathematical models, and behavioral data into inference algorithms. Molecular assays include gene microarrays, protein and amino acids, metabolites, and immunoassays. Physiological data include heart rate variability, blood pressure, and skin conductance. Behavioral data include physical activity level, sleep patterns, and social interaction. Mathematical models capture epidemiolical traits of viruses, gene ontology, and network dynamics.The analysis is validated on clinical ER data and and challenge studies.   
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