Systems biology is an academic field that seeks to
integrate different levels of information to
understand how biological systems function.
By studying the relationships and
interactions between various parts of
a biological system (e.g., gene and protein
networks involved in cell
signaling, metabolic pathways, organelles, cells,
physiological systems,
organisms etc.) it is hoped that eventually an
understandable model of
the whole system can be developed.
Systems biology begins with the study of genes and
proteins in an organism
using high-throughput techniques to quantify changes
in the genome and proteome
in reponse to a given perturbation.
High-throughput
techniques to study the genome include microarrays
to measure the changes in
mRNAs. High-throughput proteomics methods include
mass spectrometry, which is used to identify
proteins, detect protein
modifications, and quantify protein levels.
In contrast to much of molecular biology,
systems biology does not seek to break down a system
into all of its parts and study one part of the
process at a time, with
the hope of being able to reassemble all the parts
into a whole.
Using knowledge from molecular biology, the systems
biologist can propose hypotheses that explain a
system's behavior.
Importantly, these hypotheses can be used to
mathematically model the
system. Models are used to predict how different
changes in the system's
environment affect the system and can be iteratively
tested for their validity.
New approaches are being developed by quantitative
scientists, such as
computational biologists, statisticians,
mathematicians, computer
scientists, engineers, and physicists, to improve
our ability to make these
high-throughput measurements and create, refine, and
retest the models until the predicted
behavior accurately reflects the
phenotype seen.