Computational
Biology
Integrating data,
modeling, and theory
Illustration by Nathan Johnson | Pacific Northwest National Laboratory
Biological systems can be large. A pond-size microbial mat, for instance, or a human organ.
They can be small—the size of cells, or as tiny as molecules performing an outsize metabolic task on which life or health depends.
Whatever size, biological systems are so complex that it is a grand challenge to understand them, let alone predict, design, or control them. Adding to these challenges is the complexity of the data derived from high-throughput metabolomics, proteomics, and genomics assays.
These grand challenges are our mission. We address them by combining data analytics, model-based experimental design, and theory to interpret, predict, and design biological systems.
We statistically analyze, mine, and visualize high-throughput biological data. We model system dynamics and energetics using mathematics and physics. And we perform integrated analyses of regulatory networks and metabolic pathways.
At Pacific Northwest National Laboratory, computational biology is the organizing framework that reveals fundamental processes and principles. These include biomolecular signatures of dysbiosis; regulatory network structure; dynamics of pathways, processes, and microbial interactions; the thermodynamic characterization of molecules, pathways, and cells; and the emergence of higher-order cellular and multicellular capabilities.
We address issues of national importance, ranging from scalable bioprocesses to health to evolving terrestrial and aquatic ecosystems.
Our goal is to advance a fundamental understanding of biological processes by integrating data, modeling, and theory into the scientific process.
