Systems biologybiological 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, cellss, physiological systems, organisms etc.) it is hoped that an understandable model of the whole system can be developed.
|Table of contents|
2 Multidisciplinary studies
4 Future benefits
5 See also
7 External links
From genes to patients
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 biological chemistry 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. 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.
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.
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.
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. 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 prerequiste knowledge and tools.
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.
|Topics within genomics|
|Genome project | Glycomics | Human Genome Project | Proteomics | Structural genomics|
|Bioinformatics | Systems biology|