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Systems biology

Encyclopedia : S : SY : SYS : Systems biology

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.

Systems biology begins with the study of genes and proteins in an organism using high-throughput techniques to quantify changes in the genome and proteome in reponse to a given perturbation. High-throughput techniques to study the genome include microarrays to measure the changes in mRNAs. High-throughput proteomics methods include mass spectrometry, which is used to identify proteins, detect protein modifications, and quantify protein levels.

In contrast to much of molecular biology, systems biology does not seek to break down a system into all of its parts and study one part of the process at a time, with the hope of being able to reassemble all the parts into a whole. Some systems biologists argue that this reductionist approach to biology must always fail, either because of nature's redundancy and complexity, or because we have not understood all the parts of the processes. Some traditionalists respond that the alleged dichotomy between holistic and reductionist approaches generally exists in the mind of observers, rather than practitioners, of science. Still others accuse systems biologists of setting vague and poorly articulated goals without proposing concrete strategies, while the projects that they actually end up working on fall so far short of the initial goals as to be reductionist according to system's biology's own terms, or simply insignificant.

Using knowledge from molecular biology, the systems biologist can propose hypotheses that explain a system's behavior. Importantly, these hypotheses can be used to mathematically model the system. Models are used to predict how different changes in the system's environment affect the system and can be iteratively tested for their validity. New approaches are being developed by quantitative scientists, such as computational biologists, statisticians, mathematicians, computer scientists, engineers, and physicists, to improve our ability to make these high-throughput measurements and create, refine, and retest the models until the predicted behavior accurately reflects the phenotype seen.

Contents

History

Many of the concepts of systems biology are not new. Biologists and biochemists have long known that the detailed (reductionist) study of individual proteins is just the first step toward an understanding of the overall (integrated) life process. The current advances in biology (coming from bioinformatics in the post genomic era) are a direct result of the success of this reductionist approach.

The available experimental procedures necessarily forced a 'one protein at a time' analysis during the middle of the 20th century. Advances in experimental methodology (high-throughput screening technologies) have made the 'global' view accessible for the first time, allowing scientific research at the overall level of the cell or the organism possible.

The point is: while biologists have always known a protein must function within the context of the whole cell, it has only recently become possible to obtain data about this functional level.

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.

Notable organizations

Organizations created to further systems biology in the United States include the Institute for Systems Biology (ISB) in Seattle, Washington, [BioX] at Stanford University, a new [Department of Systems Biology] at Harvard Medical School, and the [Systems Biology research group at Pacific Northwest National Laboratory]. The ISB is a non-profit research institute with a goal to identify strategies for predicting and preventing diseases such as cancer, diabetes and AIDS. Work at PNNL is focused on a variety of research areas, including oxidative stress and radiation, cell signaling networks, and microbial communities. There also exists the [Systems Biology Institute] based in Tokyo; the Institute for Systems Biology at St Petersburg, Russia, the Biosystems Informatics Institute in the UK, the [Ottawa Institute of Systems Biology], the [Institute for Molecular Systems Biology Zürich, Switzerland], [SystemsX]: the Swiss Initiative in Systems Biology, and the [Center for the Study of Biological Complexity].

See also

Bibliography

External links

Systems biology organization websites

Systems biology research groups

Please add other groups as appropriate

Software tools for systems biology

International conferences

Genomics topics
Genome project | Glycomics | Human Genome Project | Proteomics
Chemogenomics | Structural genomics | Pharmacogenetics | Pharmacogenomics | Toxicogenomics

Bioinformatics | Cheminformatics | Systems biology

 

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