Abstract
How complex are the systems that systems biologists study? That depends. Some people focus on networks at the ‘omics’-scale: whole genomes, proteomes, or metabolomes. These systems can be represented by graphs with thousands of nodes and edges (see Figure 1). Others focus on small subcircuits of the network; say a circuit composed of a few proteins that functions as an amplifier, a switch or a logic gate. Typically, the graphs of these systems possess fewer than a dozen (or so) nodes. Both the large-scale and smallscale approaches have been fruitful.
Highlights
Systems biology begins with complex biological phenomena and aims to provide a simpler and more abstract framework that explains why these events occur the way they do
Systems biology can be carried out in a ‘Keplerian’ fashion - look for correlations and empirical relationships that account for data - but the ultimate hope is to arrive at a ‘Newtonian’ understanding of the simple principles that give rise to the complicated behaviors of complex biological systems
Systems biologists often model biological processes with ordinary differential equations (ODEs), but the fact is that almost none of them can be solved exactly. (The one that can be solved exactly describes exponential approach to a steady state, and it’s something every biologist should work out at some point in his or her training.) Most often, systems biologists solve their ODEs numerically, often with canned software packages like Matlab or Mathematica
Summary
Some people focus on networks at the ‘omics’-scale: whole genomes, proteomes, or metabolomes. These systems can be represented by graphs with thousands of nodes and edges (see Figure 1). Others focus on small subcircuits of the network; say a circuit composed of a few proteins that functions as an amplifier, a switch or a logic gate. The graphs of these systems possess fewer than a dozen (or so) nodes. Both the large-scale and smallscale approaches have been fruitful
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