International Mammalian Genome Society

17th International Mouse Genome Conference

9-12 November 2003, Braunschweig, Germany


PLENARY PRESENTATION

WEDNESDAY 12 NOVEMBER
14:00 – 14:30 HRS

SYSTEMS BIOLOGY APPROACH TO UNDERSTAND CELLULAR FUNCTIONS

Hiroaki Kitano
Sony Computer Science Laboratories

With the ever-increasing flow of high-throughput gene expression, protein interaction and genome sequence data, researchers gradually approach a system-level understanding of cells and even multi-cellular organisms. Systems biology is an emerging field that enables us to achieve in-depth understanding at the system level[1]. For this, we need to establish methodologies and techniques that enable us to understand biological systems as systems, which means to understand: (1) the structure of the system, such as gene/metabolic/signal transduction networks and physical structures, (2) the dynamics of such systems, (3) methods to control systems, and (4) methods to design and modify systems to generate desired properties.

From technical point of view, there are serious needs for standard open software that enables exchange of models and analysis results, as well as share modules for modeling and analysis. Systems Biology Markup Language (SBML) and Systems Biology Workbench (SBW) are initiatives to achieve open standard software platform for systems biology (http://www.sbml.org/) [2-4]. SBML Level-1 has been released and used in numbers of software. SBML Level-2 specification is now finalized, and started drafting SBML Level-3. SBW version 1.1 is now released with a range of modules for modeling and analysis.

On scientific front, understanding robustness of biological systems and find a way to control such systems are the major theme in systems biology. Robustness is manifested as ability to adapt to environmental perturbations, insensitivities against internal parameter changes, and graceful degradation. It emerges from certain system-level properties such as (1) feedback control, (2) redundancy, (3) modularity, and (4) structural stability. In-depth understanding of this property at various levels provides far reaching impacts to understanding of biological systems as well as possible applications to drug discovery[5].

1. Kitano, H., Systems biology: a brief overview. Science, 2002. 295(5560): p. 1662-4.

2. Hucka, M., et al., The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics, 2003. 19(4): p. 524-31.

3. Hucka, M., et al., The ERATO Systems Biology Workbench: enabling interaction and exchange between software tools for computational biology. Pac Symp Biocomput, 2002: p. 450-61.

4. Kitano, H., Standards for modeling. Nat Biotechnol, 2002. 20(4): p. 337.

5. Kitano, H., Computational systems biology. Nature, 2002. 420(6912): p. 206-10.


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