摘要翻译：
生物区别于无生命的一件事是它们能够大量产生类似复杂或非随机的结构。从DNA序列到折叠的蛋白质结构、活细胞、微生物群落和多细胞结构，生物中的物质构型很容易与非生物物质组合区分开来。复杂有机体的产品也是如此，它们本身可以构造复杂的工具、机器和人工制品。虽然这些物体不是活的，但它们不能随机形成，因为它们是生物有机体的产物，因此是技术或文化的生物特征。问题是，如何将一种旨在将复杂对象评估为可能的生物特征的方法概括出来并不明显。然而，如果有可能的话，这种自成一体的方法可能有助于探索宇宙中的新生命形式。这将要求我们严格地证明一个给定的人工制品太复杂了，不可能是偶然形成的。在本文中，我们提出了一种新的复杂性度量--路径复杂性，它不仅允许我们对非生物-生物的划分进行阈值化，而且证明了一种基于对象丰度和复杂性的概率方法，可以用来明确地将复杂对象分配为生物特征。我们希望这种方法不仅打开了寻找地球以外生物特征的大门，而且让我们能够探索地球上新类型的生物，以及观察实验室中发现的复杂化学系统何时可以被认为是活的。
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英文标题：
《A Probabilistic Framework for Quantifying Biological Complexity》
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作者：
Stuart M. Marshall, Alastair R. G. Murray, and Leroy Cronin
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最新提交年份：
2017
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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一级分类：Computer Science        计算机科学
二级分类：Information Theory        信息论
分类描述：Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
涵盖信息论和编码的理论和实验方面。包括ACM学科类E.4中的材料，并与H.1.1有交集。
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一级分类：Mathematics        数学
二级分类：Information Theory        信息论
分类描述：math.IT is an alias for cs.IT. Covers theoretical and experimental aspects of information theory and coding.
它是cs.it的别名。涵盖信息论和编码的理论和实验方面。
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英文摘要：
  One thing that discriminates living things from inanimate matter is their ability to generate similarly complex or non-random architectures 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. This is also true of the products of complex organisms that can themselves construct complex tools, machines, and artefacts. Whilst 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. The problem is that it is not obvious how it might be possible to generalise an approach that aims to evaluate complex objects as possible biosignatures. However, if it was possible such a self-contained approach could be useful to explore the cosmos for new life forms. 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, Pathway Complexity, that allows us to not only threshold the abiotic-biotic divide, but to demonstrate a probabilistic approach based upon object abundance and complexity which can be used to unambiguously assign complex objects as biosignatures. We hope that this approach not only opens up the search for biosignatures beyond earth, but allow us to explore earth for new types of biology, as well as observing when a complex chemical system discovered in the laboratory could be considered alive.
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PDF链接：
https://arxiv.org/pdf/1705.03460