规定性信息定义中的二分法表明了规定性数据和规定性算法:生物符号学在基因组系统中的应用。

Q1 Mathematics
David J D'Onofrio, David L Abel, Donald E Johnson
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引用次数: 1

摘要

近年来,分子生物学和计算机科学领域的合作创造了细胞基因组学中发现的控制论和生物符号学关系与计算系统中发现的信息和语言关系之间的协同作用。生物信息的“意义”往往是通过指令或形式生物功能的实际产生来体现的。这样的信息被称为规定性信息(PI)。PI程序组织并执行一组规定的选择。在细胞系统中对这一术语的进一步研究导致了其定义的二分法,这表明规定的数据和规定的算法都是PI的组成部分。本文着眼于这种二分法,表达在遗传密码和在蛋白质合成的中心教条。遗传算法的一个例子是模仿核糖体,并检查蛋白质合成过程是用来区分PI数据从PI算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Dichotomy in the definition of prescriptive information suggests both prescribed data and prescribed algorithms: biosemiotics applications in genomic systems.

Dichotomy in the definition of prescriptive information suggests both prescribed data and prescribed algorithms: biosemiotics applications in genomic systems.

Dichotomy in the definition of prescriptive information suggests both prescribed data and prescribed algorithms: biosemiotics applications in genomic systems.

The fields of molecular biology and computer science have cooperated over recent years to create a synergy between the cybernetic and biosemiotic relationship found in cellular genomics to that of information and language found in computational systems. Biological information frequently manifests its "meaning" through instruction or actual production of formal bio-function. Such information is called prescriptive information (PI). PI programs organize and execute a prescribed set of choices. Closer examination of this term in cellular systems has led to a dichotomy in its definition suggesting both prescribed data and prescribed algorithms are constituents of PI. This paper looks at this dichotomy as expressed in both the genetic code and in the central dogma of protein synthesis. An example of a genetic algorithm is modeled after the ribosome, and an examination of the protein synthesis process is used to differentiate PI data from PI algorithms.

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来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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