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Perspectives on systems biology

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Abstract

Systems biology is a new field in biology that aims at system-level understanding of biological systems, such as cells and organisms. Molecular biology has already made remarkable contribution to our understanding of biological systems, and its current focus is on the identification of genes and the functions of their products; that is, on the components of systems. There is no doubt that molecular biology will progress even faster and finally identify all the components of biological systems. As such a moment approaches, major importance need to be placed on the establishment of methodologies and techniques that enable us to understand biological systems as systems. This paper overviews the field of systems biology.

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Authors and Affiliations

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

    Hiroaki Kitano

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

    Hiroaki Kitano

  3. California Institute of Technology Pasadena, 91125, California, U.S.A.

    Hiroaki Kitano

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  1. Hiroaki Kitano
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Correspondence to Hiroaki Kitano.

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Hiroaki Kitano, Ph.D.: Hiroaki Kitano is a Senior Researcher at Sony Computer Science Laboratories, Inc., a Project Director of Kitano Symbiotic Systems Project, Japan Science and Technology Corporation and a visiting associate at California Institute of Technology. He received a B.A. in Physics from the International Christian University, Tokyo, and a Ph.D. in Computer Science from Kyoto University. Since 1988, he has been a visiting researcher at the Center for Machine Translation at Carnegie Mellon University. Kitano received Computers and Thought Award from the International Joint Conferences on Artificial Intelligence in 1993. His research interests include RoboCup, computational molecular biology, engineering use of the mophogenesis process, and evolutionary systems.

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Kitano, H. Perspectives on systems biology. New Gener Comput 18, 199–216 (2000). https://doi.org/10.1007/BF03037529

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  • DOI: https://doi.org/10.1007/BF03037529

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