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Biological Complexity and the Need for Computational Approaches

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Philosophy of Systems Biology

Part of the book series: History, Philosophy and Theory of the Life Sciences ((HPTL,volume 20))

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“Biological systems are highly complicated, non-linear, and require very high-dimensional and high volume data analysis. In reality, we are as human beings not good at handling such data. How can we understand biological systems in face of this complexity? This is the major challenge for biological and biomedical research. I would claim that a combination of artificial intelligence and human research is the most powerful way to proceed, rather than relying solely on the human brain in trying to understand biology… The most powerful research team will consist of highly intelligent AI systems and human researchers. Just like we need high-throughput measurement devices and next generation sequencers for any high profile research institution in systems biology today, so will highly intelligent AI systems sooner or later be mandatory for any future high profile research institution.”

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Authors and Affiliations

  1. The Systems Biology Institute, Falcon Building 5F, 5-6-9 Shirokanedai, Minato, Tokyo, 108-0071, Japan

    Hiroaki Kitano

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  1. Hiroaki Kitano
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Correspondence to Hiroaki Kitano .

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Editors and Affiliations

  1. Department of Science Education, University of Copenhagen, Copenhagen, Denmark

    Sara Green

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Kitano, H. (2017). Biological Complexity and the Need for Computational Approaches. In: Green, S. (eds) Philosophy of Systems Biology. History, Philosophy and Theory of the Life Sciences, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-319-47000-9_16

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