Director of BCB
My research is currently focused on the evolution and ecology of plasmids that transfer to and replicate in a broad range of bacteria. Plasmids are mobile genetic elements found in most bacteria. Because they readily transfer between different types of bacteria under natural conditions, they play an important role in rapid bacterial adaptation to changing environments. A good example is the current epidemic of multiple antibiotic resistance in human pathogens, which is largely due to the spread of multi-drug resistance plasmids. Although plasmid-mediated gene transfer is now recognized as a key mechanism in the alarming rise of antibiotic resistance, little is known about their host range, their ability to invade bacterial populations in the absence of selection, and their genetic diversity. We are addressing these questions using various Proteobacteria and plasmids as model systems.
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Assistant Professor of Philosophy
Bert Baumgaertner's research lies at the intersection of philosophy and the cognitive and social sciences. His approach to issues in these areas is informed by a computational perspective. His dissertation applied this approach to the subject of vagueness, which he defended at the University of California, Davis in May 2013. Bert is also working on the philosophical foundations of agent-based models and is using them to address issues in social epistemology. Bert is interested in a wide range of areas in both the humanities and the sciences, especially when they come in contact with computation and evolution.
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Research Associate Professor
Dr. Celeste Brown has two research areas, how gene regulation changes in response to selection, and the evolution of disordered proteins. The link between these two disparate areas is that often proteins involved in gene regulation are disordered. The gene regulation studies involve laboratory-based research and the disordered protein studies involve bioinformatics approaches.
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My research involves theoretical modeling of evolutionary phenomena at the population level and development and applications of computational statistical methods to perform inference about evolutionary phenomena using population genetic data. I maintain a broad interest in statistical theory and philosophy of statistics, evolutionary theory, and complex systems.
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Research interests: Statistical Ecology, Biometrics, Mathematical Modeling, Theoretical Ecology, Conservation Biology, Population Dynamics
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University Distinguished Professor
Director of IBEST
The research done in Dr. Larry Forney’s laboratory centers on the diversity and distribution of prokaryotes. Both field and laboratory studies are done to explore the temporal and spatial patterns of community diversity, as well as factors that influence the dynamics of inter- and intra-species competition. In addition research is done to understand how spatial structure and the resulting environmental gradients influence the tempo and trajectory of adaptive radiations in bacterial species and the maintenance of diversity. Most of these studies are highly interdisciplinary in nature, and done in collaboration with mathematicians, statisticians, computer scientists, geologists, environmental engineers, physicians, and clinical scientists.
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Dr. Foster’s current research is focused on characterizing evolutionarily permissible ecological structures in microbial ecosystems and on developing bioinformatics for very large sequence datasets. He continues to examine simulations of evolutionary processes to design complex artifacts and optimize functions. He works in close collaboration with biologists, statisticians, mathematicians, and computer scientists.
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Research Interests: Interface of Probability Theory, Functional Analysis and Convex Geometry. In particular, small deviations of Gaussian processes; metric entropy of function spaces and operators; and intrinsic volumes of convex bodies.
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Our research investigates ecological and evolutionary aspects of adaptive radiations. Current projects span a wide range of taxa and time scales, including adaptive radiation in E. coli biofilms, evolution of island lizards in the Caribbean and Indian Ocean, and macroevolutionary dynamics of vertebrates. You will find more information about all of these projects on the research and publications pages.
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Robert works with anything that evolves. His research has included bioinformatics work in phylogenetics, new methods of Markov Chain Monte Carlo sampling, and the simulation of the geneics of the onset of breast cancer. He is currently working on evolutionary approaches to agent based simulations of international conflict and the cooperative behavior of swarms of thousands of robots.
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Our research focuses on the genomic architecture of evolving populations, developing sophisticated theory and analytical tools to harness the power of modern DNA sequencing technology. We address basic questions of evolutionary biology as well as applications to conservation and cancer biology.
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Dean of College of Science & Professor
My research focuses on developing and rigorously testing statistical methods and stochastic models to describe genetic phenomena. These include models and methods to: predict how viruses adapt; show the effect of antibiotic resistance genes encoded on plasmids; predict ancestral relationships among species; and to understand the ecological structure of bacterial communities in biofilms. This broad focus has lead to collaborations with researchers in phylogenetics, population genetics, theoretical ecology, mircobial ecology, experimental evolution, conservation genetics, and the list is growing.
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Research interests: Stochastic Processes and Mathematical Biology; especially interacting particle systems, population genetics and evolutionary biology, coalescent theory, spatial models in (microbial) ecology and epidemiology, combining experimental and theoretical approaches, diffusion processes and differential equations.
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Stephen Sauchi Lee
My general research area is Multivariate and Computational Statistics. It includes: Integrating models and methods from statistics, neural networks, machine learning, and data mining communities to discover relationships and recognize patterns in databases; modeling using regression and classification for interpretation and forecasting; extracting information and patterns; and developing computational algorithms to increase efficiency and prediction accuracy.
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My research interests are at the intersection of microbial physiology and evolution, and span from experimental and computational approaches. On one hand, we use experimental evolution as a tool to uncover novel genes and functions. On the other, we apply systems-level models of metabolism to try to predict genetic interactions, optimal phenotypes, and evolutionary outcomes of evolving populations.
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My research focuses on the ecology and evolution of species interactions. The overall aim is to better understand how coevolution shapes patterns of biodiversity and the geographic distributions of interacting species. Work in my lab addresses these issues with a combination of mathematical modeling and field studies.
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Research in the Parent lab centers on the evolutionary process of diversification in lineages exposed to novel environment. Our general approach is to (1) observe present-day patterns of biodiversity to infer past evolutionary processes, and (2) test those processes with manipulative experiments in laboratory populations. We use field observations, comparative analyses, laboratory experiments, molecular phylogenetics, and integrate them with theoretical modeling. Island systems (natural or experimental) are the main focus of our research attention.
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Research Interests: Physiological plant ecology (Ecophysiology); guided independent learning (use of information technology in science education); scientific visualization and modeling (integration of ecological processes, molecule to globe)
» View R. Robberecht's Site
My general research interests lie at the interface between genomics, evolutionary biology, and fisheries biology. Specific areas of research emphasis in my lab include the genetic architecture of complex traits, the evolution of locally adaptive phenotypes, and genomic analysis of behavioral variation in fish. I employ two study systems to investigate these issues, the rainbow trout and the zebrafish.
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Research Assistant Professor
Much of my research work and interest is focused on the applied analysis of high-throughput data, including microarray data, genotype data, and high-throughput sequencing data from machine output to data visualization and statistical assessment. This typically involves the computational manipulation and interpretation of very large datasets in a wide range of disciplines, often applying bioinformatics techniques not originally designed for a particular data type in order to ask, and answer, new and interesting biological questions.
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Our understanding of the processes of nucleotide substitution (DNA sequence evolution) has been expanding greatly over the last 10 years. Furthermore, it has become apparent that ignoring such processes as heterogeneity of base composition, substitution pattern, and rate variation among nucleotide sites can compromise attempts to estimate phylogeny from DNA sequence data. Therefore, model-based analyses of DNA sequence data have become increasingly wide spread because such approaches afford the investigator the opportunity to account for such processes explicitly.
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Associate Professor and Director, Stillinger Herbarium
I am a plant systematist and am broadly interested in the investigation of the patterns and processes that shape plant biodiversity. In general, my research is focused on the use of molecular methods to reconstruct phylogenetic relationships in plants and the application of phylogenetic methods to understand plant evolution. The evolutionary causes and consequences of processes such as hybridization, polyploidy, pollination biology, biogeography, rapid diversification, and niche evolution can only be understood in light of a robust phylogenetic hypothesis, and these hypotheses are a necessary component of modern taxonomic treatments and classification systems. Research in my lab is directed at multiple levels of plant phylogeny and current projects range from comparative phylogeography of the Pacific Northwest inland rainforest communities, to the study of species boundaries and diversification among very closely related species, to patterns of diversification among some of the major lineages comprising the plant tree of life.
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Professor; Department Head; Affiliate faculty member CATIE Costa Rica
Research interests: Conservation Genetics, Landscape Genetics, Molecular Ecology, Molecular Systematics
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University Distinguished Professor
The Wichman Lab studies viruses and their subcellular relatives, transposable elements. These two lines of research are united by a molecular approach and a strong evolutionary context.
L1 elements have been active in mammals for over 150 million years and make up about 20% of the genome. Most of the copies in the genome are ancient molecular fossils, so it is a challenge to sift through all of the old copies to find those that have been recently active.
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Michelle’s research interests lie in epidemiological and biostatistical methods. Her work includes developing multivariate diagnostic and prognostic tools for evaluation of metabolic status, study design for nutrition interventions, and evaluation of risk factors for mining injuries. She plays a large role in supporting research across UI as a statistical consultant and in training master’s level statistics students in consulting.
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Department Chair and Professor
Affiliate Professor of Bioinformatics and Computational Biology
My research interests are on problems in statistical genetics, biostatistics, and statistical methods applied to issues in natural resources. One of the topics that I work on is the analysis of human twin data. Another area of interest is the estimation of disease prevalence from various types of data, such as in groups of fish that are collected and have their tissue pooled to test for disease status.
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Developing computational methods for proteins and using these approaches to understand the underlying biophysical mechanisms that define protein structure, function and evolution.
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