Systems biology has been defined as the quantitative study of biological processes as whole systems instead of isolated parts. While the term "Systems Biology" is relatively new, the goal of developing holistic approaches to understanding biological systems has a long history. However, technological and methodological advances over the last two decades have made it possible to bring new data to bear on the study of complex biological systems.
Research in the Magwene lab is aimed at understanding how genetic networks work and how they have evolved. More specifically, our lab combines wet lab experimental techniques and the development of computational and statistical methods in order to characterize the properties of gene regulatory networks. Our goal is to identify how genetic and environmental variation affects the functioning of regulatory networks, and how this variation relates to relates to intra- and interspecific patterns of phenotypic variation.
We are particuarly interested in how cells integrate signals from their external environment with information about their own internal state in order to make cellular decisions. We are using both experimental and mathematical approaches to tackle these problems. Our primary model system is the budding yeast, Saccharomyces cerevisiae, as well as other hemiascomycete fungi.
Genomic research in our lab is focused on characterizing genetic variation within and between species and exploring the consequences of that variation in terms of genetic networks and cellular phenotypes.
Computational and bioinformatics research in the Magwene lab is focused on developing analytical and algorithmic approaches for addressing problems in systems biology and evolutionary biology. Current projects focus on estimating genetic regulatory networks from high-throughput data and integrating information about gene networks into quantitative genetic models.