Skip to main content

Systems Biology Powered by Artificial Intelligence

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNAI,volume 7458)

Abstract

Systems biology is an attempt to understand biological system as system thereby triggering innovations in medical practice, drug discovery, bio-engineering, and global sustainability problems. The fundamental difficulties lies in the complexity of biological systems that have evolved through billions of years. Nevertheless, there are fundamental principles governing biological systems as complex evolvable systems that has been optimized for certain environmental constraints. Broad range of AI technologies can be applied for systems biology such as text-mining, qualitative physics, marker-passing algorithms, statistical inference, machine learning, etc. In fact, systems biology is one of the best field that AI technologies can be best applied to make high impact research that can impact real-world. This talk addresses basic issues in systems biology, especially in systems drug discovery and coral reef systems biology, and discusses how AI can contribute to make difference.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kitano, H. (2012). Systems Biology Powered by Artificial Intelligence. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-32695-0_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32694-3

  • Online ISBN: 978-3-642-32695-0

  • eBook Packages: Computer ScienceComputer Science (R0)