Sept. 12, 2007 | Currently, there are lots of systems biology (SB) definitions floating about, and most observers agree there is room for interpretation. Institute for Systems Biology founder Lee Hood has the clearest and most encompassing view. There are two types of SB, he suggests: One sets out to decipher the function of molecular machines (e.g., proteasome) and how they execute biological functions; the second seeks to identify and decipher the function of biological networks and how they “capture, transmit, integrate and disperse biological information.”
In this context, Hood argues modern SB requires six essential features:
1. Quantitative measurements for all types of biological information.
2. Global measurements: Measure dynamic changes in all genes, mRNAs, proteins, etc., across state changes.
3. Computational and mathematical integration of different data types: DNA, RNA, protein interactions, etc., to capture distinct types of environmental information.
4. Dynamic measurements across developmental, physiological disease, or environmental exposure transitions.
5. Utilization of carefully formulated systems perturbations.
6. Integration of discovery-driven and hypothesis-driven (global or focused) measurements. The systems biology cycle: perturbation-measurement-model-hypothesis-perturbation, etc.
Not all the technologies to handle these requirements are currently available, but they are critical to achieving systems biology’s goal.