Systems Biology From Genes To Patients Multidisciplinary Studies

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.

2 Multidisciplinary studies

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 bioinformaticsBioinformatics or computational biology is the use of mathematical and informational techniques, including statistics, to solve biological problems, usually by creating or using computer programs, mathematical models or both. One of the main areas of bioi and data miningData mining also known as knowledge-discovery in databases (KDD is the practice of automatically searching large stores of data for patterns. To do this, data mining uses computational techniques from Statistics and Pattern recognition. Data mining has be, molecular modellingMolecular modelling is a collection of techniques to model or mimic the behaviour of molecules. See also Quantum mechanics Computational chemistry Molecular mechanics Molecular dynamics Monte Carlo method Conformational analysis Protein structure predicti, proteomics and the clinical science s.

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.

3 Approaches

3.1 Hypothesis-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.

3.2 Data-driven

Data-driven, or bottom-up, approaches to modelModel may refer to more than one thing: For models in society, art, fashion, and cosmetics, see; role model model (person supermodel In science and technology, a model (abstract is understood as an abstract or theoretical representation of a phenomenon,seling 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.

4 Future benefits

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.

5 See also

artificial lifeArtificial life also known as alife is the study of life through the use of human-made analogs of living systems. Computer scientist Christopher Langton coined the term in the late 1980s when he held the first "International Conference on the Synthesis an
computer simulation
gene regulatory network
model
Important publications in systems biology

6 Bibliography

Gregory Bock and Jamie A. Goode (eds), (2002) "In Silico" Simulation of Biological Processes, Novartis Foundation Symposium 247, John Wiley & Sons Ltd, , BooksEnthsiast.com
Hiroaki Kitano (editor), (2001) Foundations of Systems Biology, MIT Press; (October 15, 2001) BooksEnthsiast.com

7 External links

Topics within genomics

Genome project | Glycomics | Human Genome Project | Proteomics | Structural genomics

Bioinformatics | Systems biology

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1 From genes to patients