Computational Biology and Bioinformatics

Computational Biology & Bioinformatics (CBB)

Biological sciences are undergoing revolutionary change in the 21st century due to high-throughput measurements of metabolites, proteins, RNA and DNA. This deluge of data has demonstrated the need to use fundamental principles from the physical sciences, mathematics, and engineering to transform the data into knowledge. This new quantitative, predictive biology is arising just in time to tackle significant challenges that the United States and the world have never faced before: climate change and sustainable clean energy. Likewise, new opportunities in synthetic biology, functional nanomaterials, and in personalized medicine require a predictive understanding of biological phenomena. To address these challenges and opportunities, researchers in the Computational Biology and Bioinformatics (CBB) group are developing new ways to characterize, simulate, and predict coupled biochemical, microbial, organismal, and environmental processes on scales ranging from the molecule to the field. CBB researchers tap into a diversity of tools, from statistical genomics and advanced analytics to empirical modeling and physics-based simulations.

CBB research seeks to:

Understand. Understanding starts with hypothesis-driven experimental designs, which require advanced measurements and deep analysis informed by genomic information. This genomic information contains the past histories of adaptations of biological systems to their environments, which forms a foundation for predicting future behavior and adaptations.

Predict. CBB research is helping to answer how and why adaptations (emergent properties) develop, and how these emergent properties allow cells, microbial communities and tissues to respond to environmental driving forces. Underlying physical dynamics and interactions lead to emergent properties of cells and microbial communities. CBB researchers use physical principles to predict the dynamic interactions between molecular machines, cells, subcellular compartments, organisms, and communities..

Control and Design. Control and design represent the ultimate understanding of biological systems. CBB researchers use advanced data analytics and simulation to decipher and model the emergent regulation of biological systems, from transcriptional regulation to the control of metabolism and the regulatory interactions between microbes. Control of biological systems is a major contributor to fitness and adaptation, giving it primary importance to the health of organisms and the environment.

Research collaboratively. To understand the complexity of natural systems, 21st century biological research must leverage multiple disciplines to develop translational insights. Researchers in the CBB group collaborate with colleagues in Microbiology, Integrative Omics, and in the Health Impacts and Exposure groups.


POC:

Computational Biology & Bioinformatics

Research Areas & Software