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The computational stance in biology.

C C Wood1

  • 1Santa Fe Institute , 1399 Hyde Park Road, Santa Fe, NM 87501 , USA.

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|April 23, 2019
PubMed
Summary
This summary is machine-generated.

This article cautions against overusing computation in biology, proposing a "computational stance" to evaluate its value. It argues that computation and information processing are distinct, especially in biological applications.

Keywords:
biological computationcomputationinformationinformation processing

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Area of Science:

  • Biology
  • Computer Science
  • Philosophy of Mind

Background:

  • Contemporary biology extensively uses computation as an explanatory concept.
  • There is a lack of consensus among computer scientists on the definition of computation.
  • The concepts of computation and information processing are closely related, with some arguing they are equivalent.

Purpose of the Study:

  • To caution against the extensive use of computation in contemporary biology.
  • To propose a "computational stance" for evaluating computational concepts in biology, inspired by philosophical approaches.
  • To argue for the distinction between computation and information processing in biological applications.

Main Methods:

  • Adopting a "computational stance" to assess the utility of computational ideas without debating if systems are "actually computing".
  • Analyzing the relationship and distinctions between computation and information processing.
  • Examining the specific value of these concepts in biological contexts.

Main Results:

  • A "computational stance" provides a productive framework for evaluating computational concepts in biology.
  • Computation and information processing are not fully equivalent, and maintaining this distinction is valuable.
  • The distinction between computation and information processing is particularly relevant for biological applications.

Conclusions:

  • A "computational stance" offers a pragmatic way to assess computational biology, bypassing definitional debates.
  • Distinguishing between computation and information processing enhances our understanding of biological systems.
  • Careful application of computational and information processing concepts is crucial for advancing biological research.