A probabilistic framework for identifying biosignatures using Pathway Complexity.

Philos Trans A Math Phys Eng Sci

School of Chemistry, University of Glasgow, Glasgow G12 8QQ, UK

Published: December 2017

One thing that discriminates living things from inanimate matter is their ability to generate similarly complex or non-random structures in a large abundance. From DNA sequences to folded protein structures, living cells, microbial communities and multicellular structures, the material configurations in biology can easily be distinguished from non-living material assemblies. Many complex artefacts, from ordinary bioproducts to human tools, though they are not living things, are ultimately produced by biological processes-whether those processes occur at the scale of cells or societies, they are the consequences of living systems. While these objects are not living, they cannot randomly form, as they are the product of a biological organism and hence are either technological or cultural biosignatures. A generalized approach that aims to evaluate complex objects as possible biosignatures could be useful to explore the cosmos for new life forms. However, it is not obvious how it might be possible to create such a self-contained approach. This would require us to prove rigorously that a given artefact is too complex to have formed by chance. In this paper, we present a new type of complexity measure, which we call 'Pathway Complexity', that allows us not only to threshold the abiotic-biotic divide, but also to demonstrate a probabilistic approach based on object abundance and complexity which can be used to unambiguously assign complex objects as biosignatures. We hope that this approach will not only open up the search for biosignatures beyond the Earth, but also allow us to explore the Earth for new types of biology, and to determine when a complex chemical system discovered in the laboratory could be considered alive.This article is part of the themed issue 'Reconceptualizing the origins of life'.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5686400PMC
http://dx.doi.org/10.1098/rsta.2016.0342DOI Listing

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