Systems biology is an academic field that seeks to integrate biological data as an attempt to understand how biological systems function. By studying the relationships and interactions between various parts of a biological system (e.g. organelles, cells, physiological systems, organisms etc.) it is hoped that eventually an understandable model of the whole system can be developed. Nevertheless, the complexity of even a "simple" organism like the bacteria Escherichia coli means that this goal is likely a long ways away.
Genes, in the main, encode the proteins made within a cell. The properties of these cells can determine the diseases to which a person is susceptible. Therefore, a given disease exhibited by a patient might be explained through reference to a gene that they might possess. In systems biology, attempts are made to rationalise this in terms of the relevant molecular, cellular and physiological control mechanisms.
The studies that need to be undertaken by systems biology researchers cross several academic disciplines. At one end of the scale is medicine, which is connected via mathematics and computer science on one side and the biological sciences on the other to biochemistry and genomics. Much of systems biology is within the realm of molecular biology and physiology, but it demands tools from bioinformatics and data mining, molecular modelling, proteomics and the clinical sciences.
One area of ongoing development is, consequently, the integration of research on diverse topics. Systems biology is an interdisciplinary subject. For example, biologists must be able to converse with those people that can develop effective databases for storing and querying both clinical and genomic data. In general, systems biology requires biologists, computer scientists, chemists, engineers, mathematicians, and physicists.
Systems biology research can be hypothesis-driven or data-driven .
Hypothesis-driven, or top-down, approaches start with the definition of behaviours or properties of the system which characterise the particular state of interest. Such a state might be a particular disease, for example. The overall system is successively decomposed into subsystems until a level of description has been reached in which the subsystems may be understood to an appropriate degree. This might require investigation down to the molecular level in the extreme case.
This hierarchical process enables researchers to consider or develop hypotheses that aim to describe the system. Inconsistencies or gaps between such hypotheses and the supporting data may be rapidly uncovered and resolved.
Data-driven, or bottom-up, approaches to modelling complex biological systems involves consideration of the most basic components of these systems one by one, before integrating them into the full system-wide model. This yields detailed descriptions of each component and their functions which can lead to an understanding of the system's control mechanisms.
Many predictions concerning the impact of genomics on health care have been presented. For example, the development of novel therapeutics and the introduction of personalised treatments are conjectured and in fact are now becoming a reality as a small number of forward-thinking biotechnology companies are using this cell-biology driven approach to the development of next-generation therapeutics. However, these predictions rely upon our ability to understand and quantify the roles that specific genes possess in the context of human and pathogen physiologies. The ultimate goal of systems biology is to derive the prerequisite knowledge and tools.
One of the primary organizations that was created to further Systems biology is the Institute for Systems Biology (ISB). The ISB is an internationally renowned non-profit research institute dedicated to the study and application of systems biology. ISB's goal is to unravel the mysteries of human biology to identify strategies for predicting and preventing diseases such as cancer, diabetes and AIDS.