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Automated Reasoning for Systems Biology and Medicine pp 425–452Cite as

Opportunities and Challenges in Applying Artificial Intelligence to Bioengineering

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Part of the book series: Computational Biology ((COBO,volume 30))

Abstract

Our capability to engineer biological systems is increasing rapidly in both speed and scale, leading to explosive growth in the complexity of bioengineering projects that can be contemplated. Artificial intelligence techniques have helped to tame such complexity in many other fields, and are beginning to be employed in the same way to the engineering of biological organisms. Using these techniques, computers represent, acquire, and employ domain knowledge to automate “more routine” processes and allow humans to instead focus more on deeper issues of science and engineering. At the same time, applying more sophisticated techniques such as these imposes new demands on biological systems experimentation, particularly with respect to representation and curation of data. This chapter surveys the current state of the art in applying artificial intelligence to bioengineering, as well as discussing opportunities and challenges for the future.

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  1. Raytheon BBN Technologies, Cambridge, MA, USA

    Fusun Yaman, Aaron Adler & Jacob Beal

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  1. Fusun Yaman
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  1. Department of Computer Science and Technology, University of Cambridge, Cambridge, UK

    Pietro Liò

  2. School of Computing, Newcastle University, Newcastle, UK

    Paolo Zuliani

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Yaman, F., Adler, A., Beal, J. (2019). Opportunities and Challenges in Applying Artificial Intelligence to Bioengineering. In: Liò, P., Zuliani, P. (eds) Automated Reasoning for Systems Biology and Medicine. Computational Biology, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-17297-8_16

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