Systems Biology: The Big Picture

Abstract

Genomics, proteomics, and metabolomics have all vastly advanced our understanding of human biology and disease. But the functioning of even a simple system such as a single yeast cell or bacterium is much more complicated than the sum of its genes or proteins or metabolites; it’s the activity of all those components and their relationships to one another that add up to a living organism. Recognizing that complexity, the emerging field of systems biology attempts to harness the power of mathematics, engineering, and computer science to analyze and integrate data from all the “omics” and ultimately create working models of entire biological systems. “Traditionally, scientists—toxicologists included—have relied on a reductionist approach to biology,” says William Suk, director of the NIEHS Center for Risk and Integrated Sciences. Even now, many studies examine complex systems by looking at cellular components in isolation. For instance, a common experiment involves using DNA microarrays to observe the effect of a chemical exposure on thousands of genes at once. This technique can quickly tell a scientist which genes may be vulnerable to that exposure. But a systems biology approach would attempt to model not only the chemical’s effect on gene expression but also how that expression will affect protein function, and in turn how the exposure will affect cell signaling. “There’s nothing wrong with what we’ve been doing,” Suk says. “But systems biology is going to take it to another level.”