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Computational systems biology

Nature volume 420, pages 206–210 (2002)Cite this article

Abstract

To understand complex biological systems requires the integration of experimental and computational research — in other words a systems biology approach. Computational biology, through pragmatic modelling and theoretical exploration, provides a powerful foundation from which to address critical scientific questions head-on. The reviews in this Insight cover many different aspects of this energetic field, although all, in one way or another, illuminate the functioning of modular circuits, including their robustness, design and manipulation. Computational systems biology addresses questions fundamental to our understanding of life, yet progress here will lead to practical innovations in medicine, drug discovery and engineering.

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Figure 1: Linkage of a basic systems-biology research cycle with drug discovery and treatment cycles.

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Acknowledgements

I thank S. Imai, J. Doyle, J. Tyson, T.-M. Yi, N. Hiroi and M. Morohashi for their useful comments on the manuscript. This research is, in part, supported by: the Rice Genome and Simulation Project (Ministry of Agriculture), International Standard Development area of International Joint Research Grant (New Energy and Industrial Technology Development Organization (NEDO)/Japanese Ministry of Economy, Trade and Industry (METI)), Exploratory Research for Advanced Technology (ERATO) and Institute for Bioinformatics Research and Development (BIRD) program (Japan Science and Technology Corporation), and through the special coordination funds for promoting science and technology from the Japanese government's Ministry of Education, Culture, Sports, Science, and Technology.

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Authors and Affiliations

  1. Sony Computer Science Laboratories Inc., 3-14-13 Higashi-gotanda, Shinagwa, 141-0022, Tokyo

    Hiroaki Kitano

  2. ERATO Kitano Symbiotic Systems Project, Japan Science and Technology Corporation, and The Systems Biology Institute, Suite 6A, M31, 6-31-15 Jingu-mae, Shibuya, 150-0001, Tokyo

    Hiroaki Kitano

  3. School of Fundamental Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, 223-8522, Kanagawa, Japan

    Hiroaki Kitano

  4. Control and Dynamical Systems, California Institute of Technology, Pasadena, 91125, USA

    Hiroaki Kitano

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Kitano, H. Computational systems biology. Nature 420, 206–210 (2002). https://doi.org/10.1038/nature01254

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