biology is the study of the interactions between the components
of a biological system, and how these interactions give rise to
the function and behavior of that system (for example, the enzymes
and metabolites in a metabolic pathway).
systems biology approach is characterised by a cycle of theory,
computational modelling and experiment to quantitatively describe
cells or cell processes. Since the objective is a model of all the
interactions in a system, the experimental techniques that most
suit systems biology are those that are system-wide and attempt
to be as complete as possible. Therefore, transcriptomics, metabolomics,
proteomics and high-throughput techniques are used to collect quantitative
data for the construction and validation of models.
used in systems biology
The defining feature of System Biology is the ability to obtain,
integrate and analyze complex data from multiple experimental sources
using interdisciplinary tools. Some typical technology platforms
- Gene expression measurement through DNA microarrays and SAGE
- Protein levels through two-dimensional gel electrophoresis and
mass spectrometry, including phosphoproteomics and other methods
to detect chemically modified proteins.
- metabolomics for small-molecule metabolites
- glycomics for sugars
- interactomics for interactomes
investigations are frequently combined with large scale perturbation
methods, including gene-based (RNAi, miss-expression of wild type
and mutant genes) and chemical approaches using small molecule libraries.
Robots and automated sensors enable such large-scale experimentation
and data acquisition. These technologies are still emerging and
many face problems that the larger the quantity of data produced,
the lower the quality. A wide variety of quantitative scientists
(computational biologists, statisticians, mathematicians, computer
scientists, engineers, and physicists) are working to improve the
quality of these approaches and to create, refine, and retest the
models to accurately reflect observations.
of a single level of biological organization (such as those listed
above) are usually referred to as Systematic Systems Biology. Other
areas of Systems Biology includes Integrative Systems Biology, which
seeks to integrate different types of information to advance the
understanding the biological whole, and Dynamic Systems Biology,
which aims to uncover how the biological whole changes over time
(during evolution, for example, the onset of disease or in response
to a perturbation). Functional Genomics may also be considered a
sub-field of Systems Biology.
systems biology approach often involves the development of mechanistic
models, such as the reconstruction of dynamic systems from the quantitative
properties of their elementary building blocks. For instance, a
cellular network can be modelled mathematically using methods coming
from chemical kinetics and control theory. Due to the large number
of parameters, variables and constraints in cellular networks, numerical
and computational techniques are often used. Other aspects of computer
science and informatics are also used in systems biology. These
include new forms of computational model, such as the use of process
calculi to model biological processes, the integration of information
from the literature, using techniques of information extraction
and text mining, the development of online databases and repositories
for sharing data and models (such as BioModels Database), and the
development of syntactically and semantically sound ways of representing
biological models, such as the Systems Biology Markup Language.