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Computational Sciences & Mathematics

Computational Biology & Bioinformatics

Researchers at the PNNL address the computational needs of modern biology by developing the infrastructure, databases, and software necessary to formulate and test biological models and collect and manage high-throughput data. Advancement of 21st-Century biology will be dominated by research at the convergence of biological, physical, and information sciences. A major challenge is the application of genomics knowledge to the understanding of biological structure and function in living systems. Systems biology research involves vast amounts of "-omics" data, and new technologies are in demand to capture, store, access, and analyze it. Managing the huge amounts of biological data and developing new computational methods for analysis and modeling will be key to implementing a systems approach to biology.

The computational biosciences enable 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 hypothesis derived principles. For example, following the identification of specific protein complexes involving CaM, prior knowledge of the function of the majority of these target proteins will provide the basis for the development of predictive models that relate changes in critical and easily measured cellular signals (e.g., calcium) to high-level predictions regarding cellular responses.

Computational biology at PNNL focuses on the development, efficient implementation, and application of computational tools for the study of complex biological systems. PNNL's innovative approach is user-focused and works with the scientist to design intuitive tools that precisely target the unique needs of the biological science domain. Research and development efforts are focused into three main areas: computational modeling, bioinformatics, and infrastructure development.

Advanced Computing, Mathematics, and Data


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