Systems biology

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Systems biology is an academic field that seeks to integrate different levels of information to understand how biological systems function. By studying the relationships and interactions between various parts of a biological system (e.g., gene and protein networks involved in cell signaling, metabolic pathways, organelles, cells, physiological systems, organisms, etc.) it is hoped that eventually an understandable model of the whole system can be developed. Since the mathematical and analytical foundation of systems biology is far from being perfect, computer simulation and heuristics are often used as research methods.

History

In 1952, the British neurophysiologists and nobel prize winners Alan Lloyd Hodgkin and Andrew Fielding Huxley constructed a mathematical model of the nerve cell. In 1960, Denis Noble developed the first computer model of a beating heart. Systems biologists invoke these pioneering pieces of work as illustrative of the systems biology project. The possibility of performing systems biology increased around the year 2000 with the completion of various genome projects and the proliferation of genomic and proteomic data, and the accompanying advances in experimental methodology.

The experimental procedures available during the 20th century necessitated 'one protein at a time' projects which have been the mainstay of molecular biology since its inception. Some biologists and biochemists believe that this approach of individual biomolecules has fostered a reductionist perspective, and that it is just the first step toward an understanding of the overall (integrated) life process, which can only be properly addressed from a systems biology persepective.

Approaches

There are two major and complementary focuses in systems biology:

  • Quantitative Systems Biology - otherwise known as "systems biology measurement", it focuses on measuring and monitoring biological systems on the system level.
  • Systems Biology Modeling - focuses on mapping, explaining and predicting systemic biological processes and events through the building of computational and visualization models.

Quantitative systems biology

This subfield is concerned with quantifying molecular reponses in a biological system to a given perturbation.

Some typical technology platforms are:

These are frequently combined with large scale perturbation methods, including gene-based (RNAi, misexpression 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 until the predicted behavior accurately reflects the phenotype seen.

Systems biology modeling

Using knowledge from molecular biology, the systems biologist can causally model the biological system of interest and propose hypotheses that explain a system's behavior. These hypotheses can then be confirmed and be used as a basis for mathematically model the system. The difference between the two modeling approaches is that causal models are used to explain the effects of a biological perturbations while mathematical models are used to predict how different perturbations in the system's environment affect the system.

Applications

Many predictions concerning the impact of genomics on health care have been proposed. For example, the development of novel therapeutics and the introduction of personalised treatments are conjectured and may become reality as a small number of biotechnology companies are using this cell-biology driven approach to the development of 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. Even with today's resources and expertise, this goal is immeasurably distant.

International conferences

Tools for systems biology

Bibliography

Books

  • H Kitano (editor). Foundations of Systems Biology. MIT Press: 2001. ISBN 0-262-11266-3
  • G Bock and JA Goode (eds).In Silico" Simulation of Biological Processes, Novartis Foundation Symposium 247. John Wiley & Sons: 2002. ISBN 0-470-84480-9
  • E Klipp, R Herwig, A Kowald, C Wierling, and H Lehrach. Systems Biology in Practice. Wiley-VCH: 2005. ISBN 3-527-31078-9
  • B Palsson. Systems Biology - Properties of Reconstructed Networks. Cambridge University Press: 2006. ISBN 9780521859035

Articles

  • Werner, E., "The Future and Limits of Systems Biology", Science STKE 2005, pe16 (2005).
  • ScienceMag.org - Special Issue: Systems Biology, Science, Vol 295, No 5560, March 1, 2002
  • Nature - Molecular Systems Biology
  • Systems Biology: An Overview - a review from the Science Creative Quarterly
  • Guardian.co.uk - 'The unselfish gene: The new biology is reasserting the primacy of the whole organism - the individual - over the behaviour of isolated genes', Johnjoe McFadden, The Guardian (May 6, 2005)

External links

See also

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de:Systembiologie et:Süsteemibioloogia fr:Biologie des systèmes it:Biologia dei sistemi ja:システム生物学 zh:系统生物学

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