Biology
Modeling and simulation for Biology enhance understanding at various scales and for various organisms (microbes, plants, animals, humans). This begins at the molecular level, where biological processes enable cells and organisms to adjust to changing conditions and to take advantage of available energy sources, and extends to the study of complex biological systems. This enhanced understanding facilitates the design of innovative approaches to bioremediation, energy production, and climate management.
- The computational biosciences field enables all of PNNL's thrust areas in systems biology: Cellular Stress Mechanisms, Interrogative Cell Signaling, Mechanisms of Microbial Sensing, and Regulation of Microbial Communities.
- Cataloging and organizing gene regulatory families and their relationship to protein expression and complex formation requires the application of bioinformatics and modeling capabilities that organize data, permit pattern recognition, and allow predictive models to be formulated around principles derived from hypotheses.
- Computational biology at PNNL focuses on the development, efficient implementation, and application of computational tools for the study of complex biological systems.
- Work is also ongoing on multi-scale/multi-dimensional models of organs (respiratory system, heart, brain) to elucidate environment-disease interactions.
- Physiologically based pharmacokinetic/pharmacodynamic modeling describes the fate of chemicals in the body to make constrained (based upon biological and physico-chemico principles) extrapolations from animals to humans, high to low dose, and across routes of exposures.
- Other efforts include simulating whole cell metabolism (flux of material and energy through pathways), modeling of cell signaling pathways, multiple-Monod biohydrochem flow and transport, modeling of particle deposition in airways or cell culture, modeling of peptide characteristics that determine their identification rate for mass spectrometry, and characterization of conformational, structural and energetic effects in single and clustered DNA damage.