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Philosophical Transactions of the Royal Society B Biological Sciences
Article . 2019 . Peer-reviewed
License: Royal Society Data Sharing and Accessibility
Data sources: Crossref
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The computational stance in biology

Authors: C. C. Wood;

The computational stance in biology

Abstract

The goal of this article is to call attention to, and to express caution about, the extensive use of computation as an explanatory concept in contemporary biology. Inspired by Dennett's ‘intentional stance’ in the philosophy of mind, I suggest that a ‘computational stance’ can be a productive approach to evaluating the value of computational concepts in biology. Such an approach allows the value of computational ideas to be assessed without being diverted by arguments about whether a particular biological system is ‘actually computing’ or not. Because there is sufficient difference of agreement among computer scientists about the essential elements that constitute computation, any doctrinaire position about the application of computational ideas seems misguided. Closely related to the concept of computation is the concept of information processing. Indeed, some influential computer scientists contend that there is no fundamental difference between the two concepts. I will argue that despite the lack of widely accepted, general definitions of information processing and computation: (1) information processing and computation are not fully equivalent and there is value in maintaining a distinction between them and (2) that such value is particularly evident in applications of information processing and computation to biology.This article is part of the theme issue ‘Liquid brains, solid brains: How distributed cognitive architectures process information’.

Related Organizations
Keywords

Information Dissemination, Animals, Computational Biology, Biology, Algorithms

  • BIP!
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    9
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    Top 10%
    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
bronze