Bulletin of Mathematical Biology

, Volume 43, Issue 1, pp 59–67 | Cite as

Limits on the computing power of biological systems

  • Michael Conrad
  • Arnon Rosenthal


The theory of computational complexity and certain explicitly-stated hypotheses imply limitations on the information processing power of biological systems. Parallelism, special purpose organization, and analog mechanisms may provide speedup critical for life processes, but have little power in the face of exponential growth. We show that “polynomially simulatable” biological systems cannot exhibit dynamic behavior which produces the solution of an intractable problem. The argument implies that parallelism does not allow biological systems to defeat the exponential explosion, but rather is important because it allows polynomial time algorithms to be used more efficiently.


Biological System Free Energy Problem Instance Simulation Program Digital Computer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Society for Mathematical Biology 1981

Authors and Affiliations

  • Michael Conrad
    • 1
  • Arnon Rosenthal
    • 2
  1. 1.Department of Computer Science and BiologyWayne State UniversityDetroitU.S.A.
  2. 2.Department of Computer and Communication SciencesUniversity of MichiganAnn ArborU.S.A.

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