比较书面和分子符号系统的复杂性
Julia Esposito1, Jyotika Kakar2, Tasneem Khokhar3
1Blue Marble Space Institute of Science, Seattle, WA, USA.
Bio Systems
|August 18, 2024
概括
符号系统,如遗传代码和语言,优化符号的复杂性功能. 这项研究揭示了对整个生命中高效的符号集复杂性的普遍选择压力,这表明分布是关键,而不是个别符号的复杂性.
科学领域:
- 生物语义学是生物语义学.
- 信息理论 信息理论
- 语言学的语言学.
- 生物化学 生物化学
背景情况:
- 符号系统 (SS) 是生命的组成部分,符号的复杂性影响功能优化.
- 了解SS如何样本潜伏符号空间对于生物化学和语言学等领域至关重要.
- 现有的研究缺乏对各种生物模拟系统中符号复杂性的定量比较.
研究的目的:
- 量化探索和比较两个不同的生物模拟系统的图形复杂性:遗传编码氨基酸 (GEAA) 和书面语言.
- 研究分子/图形复杂性和这些系统中的符号集分布之间的关系.
- 识别可能支配最佳符号集复杂性的通用选择压力.
主要方法:
- 对GEAA和书面语言的图形复杂性的定量分析.
- 符号复杂性分布相对于它们各自的隐藏符号空间的比较.
- 分子和图形复杂度指标之间的相关性分析.
主要成果:
- 分子和图形复杂度的测量对GEAA和书面语言都具有很高的相关性.
- 符号集不表现出最小或最大的复杂性,而是属于客观定义的分布.
- 基因编码的氨基酸与它们的潜在空间相比,其复杂性显著较低.
结论:
- 与符号生成和明确化效率相关的选择压力解释了观察到的复杂性分布.
- 这些压力可能是普遍的,为比较SSs提供了可量化的指标.
- 最佳的符号集复杂性分布,而不是单个符号复杂性,可能是整个宇宙中生命的更重要的生物标志物.
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