
Computational
Biology
Computational
Biology
Integrating data,
modeling, and theory
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 person.
They can also be small—the size of cells, or as tiny as molecules performing a metabolic task on which life or health depends.
Whatever their size, biological systems are complex and it’s a challenge to understand them, let alone predict, design, or control any aspect of these systems. Pacific Northwest National Laboratory (PNNL) is at the forefront of scientific innovation in this field, using artificial intelligence to analyze complex biological data and employing advanced instrumentation and methodologies to uncover biological dark matter—advancing our nation's leadership in the rapidly emerging global bioeconomy.
Addressing these challenges is our mission. We do so by combining data analytics, model-based experimental design, and theory to interpret, predict, and design biological systems.
At PNNL, computational biology is the organizing framework used to reveal fundamental processes and principles.
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.
Research in this area includes data mining, statistical analysis, and visualization of high-throughput biological data; modeling system dynamics and energetics using mathematics and physics; and integrated analyses of regulatory networks and metabolic pathways.