| Systems Biology |  |
Systems 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). The 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. Techniques
used in systems biology The investigations 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.
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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.
The
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.